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Guicherd M, Ben Khaled M, Guéroult M, Nomme J, Dalibey M, Grimaud F, Alvarez P, Kamionka E, Gavalda S, Noël M, Vuillemin M, Amillastre E, Labourdette D, Cioci G, Tournier V, Kitpreechavanich V, Dubois P, André I, Duquesne S, Marty A. An engineered enzyme embedded into PLA to make self-biodegradable plastic. Nature 2024:10.1038/s41586-024-07709-1. [PMID: 39020178 DOI: 10.1038/s41586-024-07709-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 06/12/2024] [Indexed: 07/19/2024]
Abstract
Plastic production reached 400 million tons in 2022 (ref. 1), with packaging and single-use plastics accounting for a substantial amount of this2. The resulting waste ends up in landfills, incineration or the environment, contributing to environmental pollution3. Shifting to biodegradable and compostable plastics is increasingly being considered as an efficient waste-management alternative4. Although polylactide (PLA) is the most widely used biosourced polymer5, its biodegradation rate under home-compost and soil conditions remains low6-8. Here we present a PLA-based plastic in which an optimized enzyme is embedded to ensure rapid biodegradation and compostability at room temperature, using a scalable industrial process. First, an 80-fold activity enhancement was achieved through structure-based rational engineering of a new hyperthermostable PLA hydrolase. Second, the enzyme was uniformly dispersed within the PLA matrix by means of a masterbatch-based melt extrusion process. The liquid enzyme formulation was incorporated in polycaprolactone, a low-melting-temperature polymer, through melt extrusion at 70 °C, forming an 'enzymated' polycaprolactone masterbatch. Masterbatch pellets were integrated into PLA by melt extrusion at 160 °C, producing an enzymated PLA film (0.02% w/w enzyme) that fully disintegrated under home-compost conditions within 20-24 weeks, meeting home-composting standards. The mechanical and degradation properties of the enzymated film were compatible with industrial packaging applications, and they remained intact during long-term storage. This innovative material not only opens new avenues for composters and biomethane production but also provides a feasible industrial solution for PLA degradation.
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Affiliation(s)
- M Guicherd
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
- Carbios, Clermont-Ferrand, France
| | - M Ben Khaled
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - M Guéroult
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
- Carbios, Clermont-Ferrand, France
| | - J Nomme
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | | | | | - P Alvarez
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - E Kamionka
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - S Gavalda
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
- Carbios, Clermont-Ferrand, France
| | - M Noël
- Carbiolice, Clermont-Ferrand, France
| | - M Vuillemin
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - E Amillastre
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - D Labourdette
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - G Cioci
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | | | - V Kitpreechavanich
- Department of Microbiology, Faculty of Science, Kasetsart University, Bangkok, Thailand
| | - P Dubois
- Center of Innovation and Research in Materials & Polymers, University of Mons, Mons, Belgium
| | - I André
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France.
| | - S Duquesne
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France
| | - A Marty
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France.
- Carbios, Clermont-Ferrand, France.
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2
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Xu G, Luo Z, Yan Y, Wang Q, Ma J. OPUS-Rota5: A highly accurate protein side-chain modeling method with 3D-Unet and RotaFormer. Structure 2024; 32:1001-1010.e2. [PMID: 38657613 DOI: 10.1016/j.str.2024.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 02/06/2024] [Accepted: 03/28/2024] [Indexed: 04/26/2024]
Abstract
Accurate protein side-chain modeling is crucial for protein folding and design. This is particularly true for molecular docking as ligands primarily interact with side chains. In this study, we introduce a two-stage side-chain modeling approach called OPUS-Rota5. It leverages a modified 3D-Unet to capture the local environmental features, including ligand information of each residue, and then employs the RotaFormer module to aggregate various types of features. Evaluation on three test sets, including recently released targets from CAMEO and CASP15, shows that OPUS-Rota5 significantly outperforms some other leading side-chain modeling methods. We also employ OPUS-Rota5 to refine the side chains of 25 G protein-coupled receptor targets predicted by AlphaFold2 and achieve a significantly improved success rate in a subsequent "back" docking of their natural ligands. Therefore, OPUS-Rota5 is a useful and effective tool for molecular docking, particularly for targets with relatively accurate predicted backbones but not side chains such as high-homology targets.
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Affiliation(s)
- Gang Xu
- Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, China; Shanghai AI Laboratory, Shanghai 200030, China
| | - Zhenwei Luo
- Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, China; Shanghai AI Laboratory, Shanghai 200030, China
| | - Yaming Yan
- Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, China
| | - Qinghua Wang
- Center for Biomolecular Innovation, Harcam Biomedicines, Shanghai 200131, China
| | - Jianpeng Ma
- Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200433, China; Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201210, China; Shanghai AI Laboratory, Shanghai 200030, China.
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3
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Raisinghani N, Alshahrani M, Gupta G, Verkhivker G. Atomistic Prediction of Structures, Conformational Ensembles and Binding Energetics for the SARS-CoV-2 Spike JN.1, KP.2 and KP.3 Variants Using AlphaFold2 and Molecular Dynamics Simulations: Mutational Profiling and Binding Free Energy Analysis Reveal Epistatic Hotspots of the ACE2 Affinity and Immune Escape. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.09.602810. [PMID: 39026832 PMCID: PMC11257589 DOI: 10.1101/2024.07.09.602810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
The most recent wave of SARS-CoV-2 Omicron variants descending from BA.2 and BA.2.86 exhibited improved viral growth and fitness due to convergent evolution of functional hotspots. These hotspots operate in tandem to optimize both receptor binding for effective infection and immune evasion efficiency, thereby maintaining overall viral fitness. The lack of molecular details on structure, dynamics and binding energetics of the latest FLiRT and FLuQE variants with the ACE2 receptor and antibodies provides a considerable challenge that is explored in this study. We combined AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested that the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that enable to protect and restore ACE2 binding affinity while conferring beneficial immune escape. To examine immune escape mechanisms, we performed structure-based mutational profiling of the spike protein binding with several classes of antibodies that displayed impaired neutralization against BA.2.86, JN.1, KP.2 and KP.3. The results confirmed the experimental data that JN.1, KP.2 and KP.3 harboring the L455S and F456L mutations can significantly impair the neutralizing activity of class-1 monoclonal antibodies, while the epistatic effects mediated by F456L can facilitate the subsequent convergence of Q493E changes to rescue ACE2 binding. Structural and energetic analysis provided a rationale to the experimental results showing that BD55-5840 and BD55-5514 antibodies that bind to different binding epitopes can retain neutralizing efficacy against all examined variants BA.2.86, JN.1, KP.2 and KP.3. The results support the notion that evolution of Omicron variants may favor emergence of lineages with beneficial combinations of mutations involving mediators of epistatic couplings that control balance of high ACE2 affinity and immune evasion.
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Hong N, Jiang D, Wang Z, Sun H, Luo H, Bao L, Song M, Kang Y, Hou T. TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides. J Chem Inf Model 2024; 64:5016-5027. [PMID: 38920330 DOI: 10.1021/acs.jcim.4c00678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
The intricate interaction between major histocompatibility complexes (MHCs) and antigen peptides with diverse amino acid sequences plays a pivotal role in immune responses and T cell activity. In recent years, deep learning (DL)-based models have emerged as promising tools for accelerating antigen peptide screening. However, most of these models solely rely on one-dimensional amino acid sequences, overlooking crucial information required for the three-dimensional (3-D) space binding process. In this study, we propose TransfIGN, a structure-based DL model that is inspired by our previously developed framework, Interaction Graph Network (IGN), and incorporates sequence information from transformers to predict the interactions between HLA-A*02:01 and antigen peptides. Our model, trained on a comprehensive data set containing 61,816 sequences with 9051 binding affinity labels and 56,848 eluted ligand labels, achieves an area under the curve (AUC) of 0.893 on the binary data set, better than state-of-the-art sequence-based models trained on larger data sets such as NetMHCpan4.1, ANN, and TransPHLA. Furthermore, when evaluated on the IEDB weekly benchmark data sets, our predictions (AUC = 0.816) are better than those of the recommended methods like the IEDB consensus (AUC = 0.795). Notably, the interaction weight matrices generated by our method highlight the strong interactions at specific positions within peptides, emphasizing the model's ability to provide physical interpretability. This capability to unveil binding mechanisms through intricate structural features holds promise for new immunotherapeutic avenues.
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Affiliation(s)
- Nanqi Hong
- College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang 310027, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Dejun Jiang
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Zhe Wang
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Huiyong Sun
- Department of Medicinal Chemistry, China Pharmaceutical University, Nanjing, Jiangsu 210009, China
| | - Hao Luo
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Lingjie Bao
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Mingli Song
- College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Yu Kang
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Tingjun Hou
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang 310058, China
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5
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Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. Exploring conformational landscapes and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variant complexes with the ACE2 receptor using AlphaFold2-based structural ensembles and molecular dynamics simulations. Phys Chem Chem Phys 2024; 26:17720-17744. [PMID: 38869513 DOI: 10.1039/d4cp01372g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles evolution and binding mechanisms of convergent evolution for the SARS-CoV-2 spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamics (MD) simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and MD simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and MD simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.
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Affiliation(s)
- Nishank Raisinghani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA.
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA.
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA.
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, 75275, USA
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas, 75275, USA
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA.
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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6
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Kellogg GE. Three-Dimensional Interaction Homology: Deconstructing Residue-Residue and Residue-Lipid Interactions in Membrane Proteins. Molecules 2024; 29:2838. [PMID: 38930903 PMCID: PMC11207109 DOI: 10.3390/molecules29122838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 06/09/2024] [Accepted: 06/10/2024] [Indexed: 06/28/2024] Open
Abstract
A method is described to deconstruct the network of hydropathic interactions within and between a protein's sidechain and its environment into residue-based three-dimensional maps. These maps encode favorable and unfavorable hydrophobic and polar interactions, in terms of spatial positions for optimal interactions, relative interaction strength, as well as character. In addition, these maps are backbone angle-dependent. After map calculation and clustering, a finite number of unique residue sidechain interaction maps exist for each backbone conformation, with the number related to the residue's size and interaction complexity. Structures for soluble proteins (~749,000 residues) and membrane proteins (~387,000 residues) were analyzed, with the latter group being subdivided into three subsets related to the residue's position in the membrane protein: soluble domain, core-facing transmembrane domain, and lipid-facing transmembrane domain. This work suggests that maps representing residue types and their backbone conformation can be reassembled to optimize the medium-to-high resolution details of a protein structure. In particular, the information encoded in maps constructed from the lipid-facing transmembrane residues appears to paint a clear picture of the protein-lipid interactions that are difficult to obtain experimentally.
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Affiliation(s)
- Glen E Kellogg
- Department of Medicinal Chemistry, Virginia Commonwealth University, Richmond, VA 23298-0540, USA
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7
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McFarlane NR, Gui J, Oláh J, Harvey JN. Gaseous inhibition of the transsulfuration pathway by cystathionine β-synthase. Phys Chem Chem Phys 2024; 26:16579-16588. [PMID: 38832404 DOI: 10.1039/d4cp01321b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
The transsulfuration pathway plays a key role in mammals for maintaining the balance between cysteine and homocysteine, whose concentrations are critical in several biochemical processes. Human cystathionine β-synthase is a heme-containing, pyridoxal 5'-phosphate (PLP)-dependent enzyme found in this pathway. The heme group does not participate directly in catalysis, but has a regulatory function, whereby CO or NO binding inhibits the PLP-dependent reactions. In this study, we explore the detailed structural changes responsible for inhibition using quantum chemical calculations to validate the experimentally observed bonding patterns associated with heme CO and NO binding and molecular dynamics simulations to explore the medium-range structural changes triggered by gas binding and propagating to the PLP active site, which is more than 20 Å distant from the heme group. Our results support a previously proposed mechanical signaling model, whereby the cysteine decoordination associated with gas ligand binding leads to breaking of a hydrogen bond with an arginine residue on a neighbouring helix. In turn, this leads to a shift in position of the helix, and hence also of the PLP cofactor, ultimately disrupting a key hydrogen bond that stabilizes the PLP in its catalytically active form.
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Affiliation(s)
- Neil R McFarlane
- Department of Chemistry, KU Leuven, Celestijnenlaan 200f-box 2404, B-3001 Leuven, Belgium.
| | - Jiangli Gui
- Department of Chemistry, KU Leuven, Celestijnenlaan 200f-box 2404, B-3001 Leuven, Belgium.
| | - Julianna Oláh
- Department of Inorganic and Analytical Chemistry Budapest University of Technology and Economics H-1111 Budapest, Műegyeten rakpart 3, Hungary.
| | - Jeremy N Harvey
- Department of Chemistry, KU Leuven, Celestijnenlaan 200f-box 2404, B-3001 Leuven, Belgium.
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8
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Hale WD, Montaño Romero A, Gonzalez CU, Jayaraman V, Lau AY, Huganir RL, Twomey EC. Allosteric competition and inhibition in AMPA receptors. Nat Struct Mol Biol 2024:10.1038/s41594-024-01328-0. [PMID: 38834914 DOI: 10.1038/s41594-024-01328-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/03/2024] [Indexed: 06/06/2024]
Abstract
Excitatory neurotransmission is principally mediated by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-subtype ionotropic glutamate receptors (AMPARs). Negative allosteric modulators are therapeutic candidates that inhibit AMPAR activation and can compete with positive modulators to control AMPAR function through unresolved mechanisms. Here we show that allosteric inhibition pushes AMPARs into a distinct state that prevents both activation and positive allosteric modulation. We used cryo-electron microscopy to capture AMPARs bound to glutamate, while a negative allosteric modulator, GYKI-52466, and positive allosteric modulator, cyclothiazide, compete for control of the AMPARs. GYKI-52466 binds in the ion channel collar and inhibits AMPARs by decoupling the ligand-binding domains from the ion channel. The rearrangement of the ligand-binding domains ruptures the cyclothiazide site, preventing positive modulation. Our data provide a framework for understanding allostery of AMPARs and for rational design of therapeutics targeting AMPARs in neurological diseases.
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Affiliation(s)
- W Dylan Hale
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alejandra Montaño Romero
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Cuauhtemoc U Gonzalez
- Center for Membrane Biology, Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX, USA
- The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Vasanthi Jayaraman
- Center for Membrane Biology, Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Albert Y Lau
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Richard L Huganir
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Edward C Twomey
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- The Beckman Center for Cryo-EM at Johns Hopkins, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Diana Helis Henry Medical Research Foundation, New Orleans, LA, USA.
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9
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Randolph NZ, Kuhlman B. Invariant point message passing for protein side chain packing. Proteins 2024. [PMID: 38790143 DOI: 10.1002/prot.26705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/19/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
Protein side chain packing (PSCP) is a fundamental problem in the field of protein engineering, as high-confidence and low-energy conformations of amino acid side chains are crucial for understanding (and designing) protein folding, protein-protein interactions, and protein-ligand interactions. Traditional PSCP methods (such as the Rosetta Packer) often rely on a library of discrete side chain conformations, or rotamers, and a forcefield to guide the structure to low-energy conformations. Recently, deep learning (DL) based methods (such as DLPacker, AttnPacker, and DiffPack) have demonstrated state-of-the-art predictions and speed in the PSCP task. Building off the success of geometric graph neural networks for protein modeling, we present the Protein Invariant Point Packer (PIPPack) which effectively processes local structural and sequence information to produce realistic, idealized side chain coordinates usingχ $$ \chi $$ -angle distribution predictions and geometry-aware invariant point message passing (IPMP). On a test set of ∼1400 high-quality protein chains, PIPPack is highly competitive with other state-of-the-art PSCP methods in rotamer recovery and per-residue RMSD but is significantly faster.
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Affiliation(s)
- Nicholas Z Randolph
- Department of Bioinformatics and Computational Biology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Brian Kuhlman
- Department of Bioinformatics and Computational Biology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
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10
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Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. AlphaFold2 Predictions of Conformational Ensembles and Atomistic Simulations of the SARS-CoV-2 Spike XBB Lineages Reveal Epistatic Couplings between Convergent Mutational Hotspots that Control ACE2 Affinity. J Phys Chem B 2024; 128:4696-4715. [PMID: 38696745 DOI: 10.1021/acs.jpcb.4c01341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2024]
Abstract
In this study, we combined AlphaFold-based atomistic structural modeling, microsecond molecular simulations, mutational profiling, and network analysis to characterize binding mechanisms of the SARS-CoV-2 spike protein with the host receptor ACE2 for a series of Omicron XBB variants including XBB.1.5, XBB.1.5+L455F, XBB.1.5+F456L, and XBB.1.5+L455F+F456L. AlphaFold-based structural and dynamic modeling of SARS-CoV-2 Spike XBB lineages can accurately predict the experimental structures and characterize conformational ensembles of the spike protein complexes with the ACE2. Microsecond molecular dynamics simulations identified important differences in the conformational landscapes and equilibrium ensembles of the XBB variants, suggesting that combining AlphaFold predictions of multiple conformations with molecular dynamics simulations can provide a complementary approach for the characterization of functional protein states and binding mechanisms. Using the ensemble-based mutational profiling of protein residues and physics-based rigorous calculations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of the Q493 hotspot in the synchronization of epistatic couplings between L455F and F456L mutations, providing a quantitative insight into the energetic determinants underlying binding differences between XBB lineages. We also proposed a network-based perturbation approach for mutational profiling of allosteric communications and uncovered the important relationships between allosteric centers mediating long-range communication and binding hotspots of epistatic couplings. The results of this study support a mechanism in which the binding mechanisms of the XBB variants may be determined by epistatic effects between convergent evolutionary hotspots that control ACE2 binding.
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Affiliation(s)
- Nishank Raisinghani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas 75275, United States
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas 75275, United States
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States
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11
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Bibert S, Quinodoz M, Perriot S, Krebs FS, Jan M, Malta RC, Collinet E, Canales M, Mathias A, Faignart N, Roulet-Perez E, Meylan P, Brouillet R, Opota O, Lozano-Calderon L, Fellmann F, Guex N, Zoete V, Asner S, Rivolta C, Du Pasquier R, Bochud PY. Herpes simplex encephalitis due to a mutation in an E3 ubiquitin ligase. Nat Commun 2024; 15:3969. [PMID: 38730242 PMCID: PMC11087577 DOI: 10.1038/s41467-024-48287-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 04/26/2024] [Indexed: 05/12/2024] Open
Abstract
Encephalitis is a rare and potentially fatal manifestation of herpes simplex type 1 infection. Following genome-wide genetic analyses, we identified a previously uncharacterized and very rare heterozygous variant in the E3 ubiquitin ligase WWP2, in a 14-month-old girl with herpes simplex encephalitis. The p.R841H variant (NM_007014.4:c.2522G > A) impaired TLR3 mediated signaling in inducible pluripotent stem cells-derived neural precursor cells and neurons; cells bearing this mutation were also more susceptible to HSV-1 infection compared to control cells. The p.R841H variant increased TRIF ubiquitination in vitro. Antiviral immunity was rescued following the correction of p.R841H by CRISPR-Cas9 technology. Moreover, the introduction of p.R841H in wild type cells reduced such immunity, suggesting that this mutation is linked to the observed phenotypes.
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Affiliation(s)
- Stéphanie Bibert
- Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Mathieu Quinodoz
- Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland
- Department of Ophthalmology, University of Basel, Basel, Switzerland
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Sylvain Perriot
- Department of Clinical Neurosciences, Laboratory of Neuroimmunology, Neuroscience Research Centre, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Fanny S Krebs
- Department of Oncology UNIL-CHUV, Computer-Aided Molecular Engineering, University of Lausanne, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, Lausanne, Switzerland
| | - Maxime Jan
- Bioinformatics Competence Center, University of Lausanne, Lausanne, Switzerland
| | - Rita C Malta
- Pediatric Infectious Diseases and Vaccinology Unit, Woman-Mother-Child Department, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Emilie Collinet
- Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Mathieu Canales
- Department of Clinical Neurosciences, Laboratory of Neuroimmunology, Neuroscience Research Centre, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Amandine Mathias
- Department of Clinical Neurosciences, Laboratory of Neuroimmunology, Neuroscience Research Centre, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Nicole Faignart
- Department of Pediatrics, Child Neurology Unit, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Eliane Roulet-Perez
- Department of Pediatrics, Child Neurology Unit, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pascal Meylan
- Institute of Microbiology, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - René Brouillet
- Institute of Microbiology, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Onya Opota
- Institute of Microbiology, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Leyder Lozano-Calderon
- Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Nicolas Guex
- Bioinformatics Competence Center, University of Lausanne, Lausanne, Switzerland
| | - Vincent Zoete
- Department of Oncology UNIL-CHUV, Computer-Aided Molecular Engineering, University of Lausanne, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, Lausanne, Switzerland
- Molecular Modelling Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sandra Asner
- Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland
- Pediatric Infectious Diseases and Vaccinology Unit, Woman-Mother-Child Department, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Carlo Rivolta
- Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland
- Department of Ophthalmology, University of Basel, Basel, Switzerland
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Renaud Du Pasquier
- Department of Clinical Neurosciences, Laboratory of Neuroimmunology, Neuroscience Research Centre, University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Clinical Neurosciences, Service of Neurology, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pierre-Yves Bochud
- Infectious Diseases Service, Department of Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland.
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12
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Juliá-Palacios N, Olivella M, Sigatullina Bondarenko M, Ibáñez-Micó S, Muñoz-Cabello B, Alonso-Luengo O, Soto-Insuga V, García-Navas D, Cuesta-Herraiz L, Andreo-Lillo P, Aguilera-Albesa S, Hedrera-Fernández A, González Alguacil E, Sánchez-Carpintero R, Martín Del Valle F, Jiménez González E, Cean Cabrera L, Medina-Rivera I, Perez-Ordoñez M, Colomé R, Lopez L, Engracia Cazorla M, Fornaguera M, Ormazabal A, Alonso-Colmenero I, Illescas KS, Balsells-Mejía S, Mari-Vico R, Duffo Viñas M, Cappuccio G, Terrone G, Romano R, Manti F, Mastrangelo M, Alfonsi C, de Siqueira Barros B, Nizon M, Gjerulfsen CE, Muro VL, Karall D, Zeiner F, Masnada S, Peterlongo I, Oyarzábal A, Santos-Gómez A, Altafaj X, García-Cazorla Á. L-serine treatment in patients with GRIN-related encephalopathy: a phase 2A, non-randomized study. Brain 2024; 147:1653-1666. [PMID: 38380699 DOI: 10.1093/brain/awae041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/20/2023] [Accepted: 01/21/2024] [Indexed: 02/22/2024] Open
Abstract
GRIN-related disorders are rare developmental encephalopathies with variable manifestations and limited therapeutic options. Here, we present the first non-randomized, open-label, single-arm trial (NCT04646447) designed to evaluate the tolerability and efficacy of L-serine in children with GRIN genetic variants leading to loss-of-function. In this phase 2A trial, patients aged 2-18 years with GRIN loss-of-function pathogenic variants received L-serine for 52 weeks. Primary end points included safety and efficacy by measuring changes in the Vineland Adaptive Behavior Scales, Bayley Scales, age-appropriate Wechsler Scales, Gross Motor Function-88, Sleep Disturbance Scale for Children, Pediatric Quality of Life Inventory, Child Behavior Checklist and the Caregiver-Teacher Report Form following 12 months of treatment. Secondary outcomes included seizure frequency and intensity reduction and EEG improvement. Assessments were performed 3 months and 1 day before starting treatment and 1, 3, 6 and 12 months after beginning the supplement. Twenty-four participants were enrolled (13 males/11 females, mean age 9.8 years, SD 4.8), 23 of whom completed the study. Patients had GRIN2B, GRIN1 and GRIN2A variants (12, 6 and 5 cases, respectively). Their clinical phenotypes showed 91% had intellectual disability (61% severe), 83% had behavioural problems, 78% had movement disorders and 58% had epilepsy. Based on the Vineland Adaptive Behavior Composite standard scores, nine children were classified as mildly impaired (cut-off score > 55), whereas 14 were assigned to the clinically severe group. An improvement was detected in the Daily Living Skills domain (P = 0035) from the Vineland Scales within the mild group. Expressive (P = 0.005), Personal (P = 0.003), Community (P = 0.009), Interpersonal (P = 0.005) and Fine Motor (P = 0.031) subdomains improved for the whole cohort, although improvement was mostly found in the mild group. The Growth Scale Values in the Cognitive subdomain of the Bayley-III Scale showed a significant improvement in the severe group (P = 0.016), with a mean increase of 21.6 points. L-serine treatment was associated with significant improvement in the median Gross Motor Function-88 total score (P = 0.002) and the mean Pediatric Quality of Life total score (P = 0.00068), regardless of severity. L-serine normalized the EEG pattern in five children and the frequency of seizures in one clinically affected child. One patient discontinued treatment due to irritability and insomnia. The trial provides evidence that L-serine is a safe treatment for children with GRIN loss-of-function variants, having the potential to improve adaptive behaviour, motor function and quality of life, with a better response to the treatment in mild phenotypes.
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Affiliation(s)
- Natalia Juliá-Palacios
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | - Mireia Olivella
- Bioinformatics and Bioimaging Group. Faculty of Science, Technology and Engineering, University of Vic-Central University of Catalonia, 08500 Vic, Spain
- Institute for Research and Innovation in Life and Health Sciences (IRIS-CC), University of Vic-Central University of Catalonia, 08500 Vic, Spain
| | - Mariya Sigatullina Bondarenko
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | | | - Beatriz Muñoz-Cabello
- Department of Pediatrics, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain
| | - Olga Alonso-Luengo
- Department of Pediatrics, Hospital Universitario Virgen del Rocío, 41013 Sevilla, Spain
| | | | - Deyanira García-Navas
- Department of Pediatric Neurology, Complejo Hospitalario Universitario de Cáceres, 10003 Cáceres, Spain
| | | | - Patricia Andreo-Lillo
- Neuropediatric Unit, Pediatric Department, University Hospital of Sant Joan d'Alacant, 03550 Sant Joan d'Alacant, Spain
| | - Sergio Aguilera-Albesa
- Paediatric Neurology Unit, Department of Pediatrics, Hospital Universitario de Navarra, 31008, Pamplona, Spain
| | - Antonio Hedrera-Fernández
- Child Neurology Unit, Pediatrics Department, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain
| | | | | | | | | | | | - Ines Medina-Rivera
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | - Marta Perez-Ordoñez
- Child and Adolescent Mental Health Area, Psychiatry and Psychology, Hospital Sant Joan de Déu, 08950 Barcelona, Spain
| | - Roser Colomé
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | - Laura Lopez
- Department of Rehabilitation, Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain
| | - María Engracia Cazorla
- Department of Rehabilitation, Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain
| | - Montserrat Fornaguera
- Department of Rehabilitation, Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain
| | - Aida Ormazabal
- Department of Clinical Biochemistry, Hospital Sant Joan de Déu, 08950 Barcelona, Spain
- European Reference Network for Hereditary Metabolic Diseases (MetabERN), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid 28029, Spain
| | - Itziar Alonso-Colmenero
- Pediatric Neurology Department, Hospital Sant Joan de Déu, Full Member of ERN EpiCare, Barcelona University, 08950 Barcelona, Spain
| | - Katia Sofía Illescas
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | - Sol Balsells-Mejía
- Department of Research Promotion and Management. Statistical Support, Hospital Sant Joan de Déu (HSJD), 08950 Barcelona, Spain
| | - Rosanna Mari-Vico
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | - Maria Duffo Viñas
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
- Child and Adolescent Mental Health Area, Psychiatry and Psychology, Hospital Sant Joan de Déu, 08950 Barcelona, Spain
| | - Gerarda Cappuccio
- Department of Translational Medical Sciences, Università degli Studi di Napoli 'Federico II', 80125 Naples, Italy
- Telethon Institute of Genetics and Medicine, Department of Pediatrics, Pozzuoli, 80131 Naples, Italy
| | - Gaetano Terrone
- Department of Translational Medical Sciences, Università degli Studi di Napoli 'Federico II', 80125 Naples, Italy
| | - Roberta Romano
- Department of Translational Medical Sciences, Università degli Studi di Napoli 'Federico II', 80125 Naples, Italy
| | - Filippo Manti
- Department of Human Neuroscience, University of Rome La Sapienza, 00185 Roma, Lazio, Italy
| | - Mario Mastrangelo
- Department of Women and Child Health and Uroginecological Sciences, Sapienza University of Rome, 00185 Rome, Italy
- Child Neurology and Psychiatry Unit, Department of Neuroscience/Mental Health, Azienda Ospedaliero-Universitaria Policlinico Umberto I, 00161 Rome, Italy
| | - Chiara Alfonsi
- Department of Human Neuroscience, University of Rome La Sapienza, 00185 Roma, Lazio, Italy
| | - Bruna de Siqueira Barros
- Núcleo de Estudos da Saúde do Adolescente, Programa de Pós-Graduação em Ciências Médicas, Universidade do Estado do Rio de Janeiro, Faculdade de Ciência Médicas, 56066 Rio de Janeiro, RJ, Brazil
| | - Mathilde Nizon
- Service de Génétique Médicale, CHU Nantes, 44093 Nantes, France
| | | | - Valeria L Muro
- Pediatric Neurology Unit, Hospital Britanico Buenos Aires, C1280AEB Buenos Aires, Argentina
| | - Daniela Karall
- Clinic for Paediatrics, Division of Inherited Metabolic Disorders, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Fiona Zeiner
- Clinic for Paediatrics, Division of Inherited Metabolic Disorders, Medical University of Innsbruck, 6020 Innsbruck, Austria
| | - Silvia Masnada
- Department of Child Neurology, V. Buzzi Children's Hospital, 20125 Milan, Italy
| | - Irene Peterlongo
- Department of Child Neurology, V. Buzzi Children's Hospital, 20125 Milan, Italy
| | - Alfonso Oyarzábal
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
| | - Ana Santos-Gómez
- Department of Biomedicine, School of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, 08036 Barcelona, Spain
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, 08036 Barcelona, Spain
| | - Xavier Altafaj
- Department of Biomedicine, School of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, 08036 Barcelona, Spain
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), University of Barcelona, 08036 Barcelona, Spain
| | - Ángeles García-Cazorla
- Neurometabolic Unit and Synaptic Metabolism Lab, Department of Neurology, Hospital Sant Joan de Déu-IRSJD, CIBERER and MetabERN, 08950 Barcelona, Spain
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13
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Pu Z, Cao J, Wu W, Song Z, Yang L, Wu J, Yu H. Reconstructing dynamics correlation network to simultaneously improve activity and stability of 2,3-butanediol dehydrogenase by design of distal interchain disulfide bonds. Int J Biol Macromol 2024; 267:131415. [PMID: 38582485 DOI: 10.1016/j.ijbiomac.2024.131415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 04/03/2024] [Accepted: 04/03/2024] [Indexed: 04/08/2024]
Abstract
The complete enzyme catalytic cycle includes substrate binding, chemical reaction and product release, in which different dynamic conformations are adopted. Due to the complex relationship among enzyme activity, stability and dynamics, the directed evolution of enzymes for improved activity or stability commonly leads to a trade-off in stability or activity. It hence remains a challenge to engineer an enzyme to have both enhanced activity and stability. Here, we have attempted to reconstruct the dynamics correlation network involved with active center to improve both activity and stability of a 2,3-butanediol dehydrogenase (2,3-BDH) by introducing inter-chain disulfide bonds. A computational strategy was first applied to evaluate the effect of introducing inter-chain disulfide bond on activity and stability of three 2,3-BDHs, and the N258C mutation of 2,3-BDH from Corynebacterium glutamicum (CgBDH) was proved to be effective in improving both activity and stability. In the results, CgBDH-N258C showed a different unfolding curve from the wild type, with two melting temperatures (Tm) of 68.3 °C and 50.8 °C, 19.7 °C and 2 °C higher than 48.6 °C of the wild type. Its half-life was also improved by 14.8-fold compared to the wild type. Catalytic efficiency (kcat/Km) of the mutant was increased by 7.9-fold toward native substrate diacetyl and 8.8-fold toward non-native substrate 2,5-hexanedione compared to the wild type. Molecular dynamics simulations revealed that an interaction network formed by Cys258, Arg162, Ala144 and the catalytic residues was reconstructed in the mutant and the dynamics change caused by the disulfide bond could be propagated through the interactions network. This improved the enzyme stability and activity by decreasing the flexibility and locking more "reactive" pose, respectively. Further construction of mutations including A144G showing a 44-fold improvement in catalytic efficiency toward meso-2,3-BD confirmed the role of modifying dynamics correlation network in tunning enzyme activity and selectivity. This study provided important insights into the relationship among dynamics, enzyme catalysis and stability, and will be useful in the designing new enzymes with co-evolution of stability, activity and selectivity.
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Affiliation(s)
- Zhongji Pu
- Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Hangzhou, Zhejiang 311200, China; Xianghu Laboratory, Hangzhou 311231, China
| | - Jiawen Cao
- Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Wenhui Wu
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Hangzhou, Zhejiang 311200, China
| | - Zhongdi Song
- Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Interdisciplinary Research Academy, Zhejiang Shuren University, Hangzhou 310015, China
| | - Lirong Yang
- Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Hangzhou, Zhejiang 311200, China
| | - Jianping Wu
- Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Hangzhou, Zhejiang 311200, China
| | - Haoran Yu
- Institute of Bioengineering, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Centre, Hangzhou, Zhejiang 311200, China.
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14
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Gupta G, Verkhivker G. Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking. Int J Mol Sci 2024; 25:4955. [PMID: 38732174 PMCID: PMC11084335 DOI: 10.3390/ijms25094955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/24/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.
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Affiliation(s)
- Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA;
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA;
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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15
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Lian Y, Bodian D, Shehu A. Elucidating the Role of Wildtype and Variant FGFR2 Structural Dynamics in (Dys)Function and Disorder. Int J Mol Sci 2024; 25:4523. [PMID: 38674107 PMCID: PMC11050683 DOI: 10.3390/ijms25084523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
The fibroblast growth factor receptor 2 (FGFR2) gene is one of the most extensively studied genes with many known mutations implicated in several human disorders, including oncogenic ones. Most FGFR2 disease-associated gene mutations are missense mutations that result in constitutive activation of the FGFR2 protein and downstream molecular pathways. Many tertiary structures of the FGFR2 kinase domain are publicly available in the wildtype and mutated forms and in the inactive and activated state of the receptor. The current literature suggests a molecular brake inhibiting the ATP-binding A loop from adopting the activated state. Mutations relieve this brake, triggering allosteric changes between active and inactive states. However, the existing analysis relies on static structures and fails to account for the intrinsic structural dynamics. In this study, we utilize experimentally resolved structures of the FGFR2 tyrosine kinase domain and machine learning to capture the intrinsic structural dynamics, correlate it with functional regions and disease types, and enrich it with predicted structures of variants with currently no experimentally resolved structures. Our findings demonstrate the value of machine learning-enabled characterizations of structure dynamics in revealing the impact of mutations on (dys)function and disorder in FGFR2.
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Affiliation(s)
- Yiyang Lian
- School of Systems Biology, George Mason University, Manassas, VA 20110, USA;
| | - Dale Bodian
- Diamond Age Data Science, Boston, MA 02143, USA;
| | - Amarda Shehu
- School of Systems Biology, George Mason University, Manassas, VA 20110, USA;
- Department of Computer Science, George Mason University, Fairfax, VA 22030, USA
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16
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Raisinghani N, Alshahrani M, Gupta G, Verkhivker G. Ensemble-Based Mutational Profiling and Network Analysis of the SARS-CoV-2 Spike Omicron XBB Lineages for Interactions with the ACE2 Receptor and Antibodies: Cooperation of Binding Hotspots in Mediating Epistatic Couplings Underlies Binding Mechanism and Immune Escape. Int J Mol Sci 2024; 25:4281. [PMID: 38673865 PMCID: PMC11049863 DOI: 10.3390/ijms25084281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 04/09/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
In this study, we performed a computational study of binding mechanisms for the SARS-CoV-2 spike Omicron XBB lineages with the host cell receptor ACE2 and a panel of diverse class one antibodies. The central objective of this investigation was to examine the molecular factors underlying epistatic couplings among convergent evolution hotspots that enable optimal balancing of ACE2 binding and antibody evasion for Omicron variants BA.1, BA2, BA.3, BA.4/BA.5, BQ.1.1, XBB.1, XBB.1.5, and XBB.1.5 + L455F/F456L. By combining evolutionary analysis, molecular dynamics simulations, and ensemble-based mutational scanning of spike protein residues in complexes with ACE2, we identified structural stability and binding affinity hotspots that are consistent with the results of biochemical studies. In agreement with the results of deep mutational scanning experiments, our quantitative analysis correctly reproduced strong and variant-specific epistatic effects in the XBB.1.5 and BA.2 variants. It was shown that Y453W and F456L mutations can enhance ACE2 binding when coupled with Q493 in XBB.1.5, while these mutations become destabilized when coupled with the R493 position in the BA.2 variant. The results provided a molecular rationale of the epistatic mechanism in Omicron variants, showing a central role of the Q493/R493 hotspot in modulating epistatic couplings between convergent mutational sites L455F and F456L in XBB lineages. The results of mutational scanning and binding analysis of the Omicron XBB spike variants with ACE2 receptors and a panel of class one antibodies provide a quantitative rationale for the experimental evidence that epistatic interactions of the physically proximal binding hotspots Y501, R498, Q493, L455F, and F456L can determine strong ACE2 binding, while convergent mutational sites F456L and F486P are instrumental in mediating broad antibody resistance. The study supports a mechanism in which the impact on ACE2 binding affinity is mediated through a small group of universal binding hotspots, while the effect of immune evasion could be more variant-dependent and modulated by convergent mutational sites in the conformationally adaptable spike regions.
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Affiliation(s)
- Nishank Raisinghani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (N.R.); (M.A.); (G.G.)
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (N.R.); (M.A.); (G.G.)
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (N.R.); (M.A.); (G.G.)
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (N.R.); (M.A.); (G.G.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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17
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Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587850. [PMID: 38617283 PMCID: PMC11014522 DOI: 10.1101/2024.04.02.587850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles and binding mechanisms of convergent evolution for the SARS-CoV-2 Spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron Spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamic simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron Spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and molecular dynamics simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and molecular dynamics simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.
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18
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Parvathy J, Yazhini A, Srinivasan N, Sowdhamini R. Interfacial residues in protein-protein complexes are in the eyes of the beholder. Proteins 2024; 92:509-528. [PMID: 37982321 DOI: 10.1002/prot.26628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 10/14/2023] [Accepted: 10/17/2023] [Indexed: 11/21/2023]
Abstract
Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.
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Affiliation(s)
- Jayadevan Parvathy
- Interdisciplinary Mathematical Sciences Initiative (IMI), Indian Institute of Science, Bangalore, India
- Molecular Biophysics Unit (MBU), Indian Institute of Science, Bangalore, India
| | | | | | - Ramanathan Sowdhamini
- Molecular Biophysics Unit (MBU), Indian Institute of Science, Bangalore, India
- National Center for Biological Sciences (NCBS), Bangalore, India
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19
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Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles, and Binding Energetics of the SARS-CoV-2 Omicron BA.2.86 Spike Protein with ACE2 Host Receptor and Antibodies: Compensatory Functional Effects of Binding Hotspots in Modulating Mechanisms of Receptor Binding and Immune Escape. J Chem Inf Model 2024; 64:1657-1681. [PMID: 38373700 DOI: 10.1021/acs.jcim.3c01857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
The latest wave of SARS-CoV-2 Omicron variants displayed a growth advantage and increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with atomistic simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both the structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that the AlphaFold2-predicted structural ensemble of the BA.2.86 spike protein complex with ACE2 can accurately capture the main conformational states of the Omicron variant. Complementary to AlphaFold2 structural predictions, microsecond molecular dynamics simulations reveal the details of the conformational landscape and produced equilibrium ensembles of the BA.2.86 structures that are used to perform mutational scanning of spike residues and characterize structural stability and binding energy hotspots. The ensemble-based mutational profiling of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 revealed a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 convergent mutational hotspots R403K, F486P, and R493Q. To examine the immune evasion properties of BA.2.86 in atomistic detail, we performed structure-based mutational profiling of the spike protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against the BA.2.86 variant. The results revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have evolved to outcompete other Omicron subvariants by improving immune evasion while preserving binding affinity with ACE2 via through a compensatory effect of R493Q and F486P convergent mutational hotspots. This study demonstrated that an integrative approach combining AlphaFold2 predictions with complementary atomistic molecular dynamics simulations and robust ensemble-based mutational profiling of spike residues can enable accurate and comprehensive characterization of structure, dynamics, and binding mechanisms of newly emerging Omicron variants.
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Affiliation(s)
- Nishank Raisinghani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States of America
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States of America
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States of America
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas 75275, United States of America
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas 75275, United States of America
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, United States of America
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, California 92618, United States of America
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20
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Chennakesavalu S, Rotskoff GM. Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers. J Phys Chem B 2024; 128:2114-2123. [PMID: 38394363 DOI: 10.1021/acs.jpcb.3c08195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2024]
Abstract
Excitement at the prospect of using data-driven generative models to sample configurational ensembles of biomolecular systems stems from the extraordinary success of these models on a diverse set of high-dimensional sampling tasks. Unlike image generation or even the closely related problem of protein structure prediction, there are currently no data sources with sufficient breadth to parametrize generative models for conformational ensembles. To enable discovery, a fundamentally different approach to building generative models is required: models should be able to propose rare, albeit physical, conformations that may not arise in even the largest data sets. Here we introduce a modular strategy to generate conformations based on "backmapping" from a fixed protein backbone that (1) maintains conformational diversity of the side chains and (2) couples the side-chain fluctuations using global information about the protein conformation. Our model combines simple statistical models of side-chain conformations based on rotamer libraries with the now ubiquitous transformer architecture to sample with atomistic accuracy. Together, these ingredients provide a strategy for rapid data acquisition and hence a crucial ingredient for scalable physical simulation with generative neural networks.
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Affiliation(s)
| | - Grant M Rotskoff
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California 94305, United States
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21
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Esteban-Hofer L, Emmanouilidis L, Yulikov M, Allain FHT, Jeschke G. Ensemble structure of the N-terminal domain (1-267) of FUS in a biomolecular condensate. Biophys J 2024; 123:538-554. [PMID: 38279531 PMCID: PMC10938082 DOI: 10.1016/j.bpj.2024.01.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 11/06/2023] [Accepted: 01/22/2024] [Indexed: 01/28/2024] Open
Abstract
Solutions of some proteins phase separate into a condensed state of high protein concentration and a dispersed state of low concentration. Such behavior is observed in living cells for a number of RNA-binding proteins that feature intrinsically disordered domains. It is relevant for cell function via the formation of membraneless organelles and transcriptional condensates. On a basic level, the process can be studied in vitro on protein domains that are necessary and sufficient for liquid-liquid phase separation (LLPS). We have performed distance distribution measurements by electron paramagnetic resonance for 13 sections in an N-terminal domain (NTD) construct of the protein fused in sarcoma (FUS), consisting of the QGSY-rich domain and the RGG1 domain, in the denatured, dispersed, and condensed state. Using 10 distance distribution restraints for ensemble modeling and three such restraints for model validation, we have found that FUS NTD behaves as a random-coil polymer under good-solvent conditions in both the dispersed and condensed state. Conformation distribution in the biomolecular condensate is virtually indistinguishable from the one in an unrestrained ensemble, with the latter one being based on only residue-specific Ramachandran angle distributions. Over its whole length, FUS NTD is slightly more compact in the condensed than in the dispersed state, which is in line with the theory for random coils in good solvent proposed by de Gennes, Daoud, and Jannink. The estimated concentration in the condensate exceeds the overlap concentration resulting from this theory. The QGSY-rich domain is slightly more extended, slightly more hydrated, and has slightly higher propensity for LLPS than the RGG1 domain. Our results support previous suggestions that LLPS of FUS is driven by multiple transient nonspecific hydrogen bonding and π-sp2 interactions.
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Affiliation(s)
- Laura Esteban-Hofer
- ETH Zurich, Department of Chemistry and Applied Biosciences, Zurich, Switzerland
| | | | - Maxim Yulikov
- ETH Zurich, Department of Chemistry and Applied Biosciences, Zurich, Switzerland
| | | | - Gunnar Jeschke
- ETH Zurich, Department of Chemistry and Applied Biosciences, Zurich, Switzerland.
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22
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Shah SM, Demidova EV, Ringenbach S, Faezov B, Andrake M, Gandhi A, Mur P, Viana-Errasti J, Xiu J, Swensen J, Valle L, Dunbrack RL, Hall MJ, Arora S. Exploring Co-occurring POLE Exonuclease and Non-exonuclease Domain Mutations and Their Impact on Tumor Mutagenicity. CANCER RESEARCH COMMUNICATIONS 2024; 4:213-225. [PMID: 38282550 PMCID: PMC10812383 DOI: 10.1158/2767-9764.crc-23-0312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/05/2023] [Accepted: 01/02/2024] [Indexed: 01/13/2024]
Abstract
POLE driver mutations in the exonuclease domain (ExoD driver) are prevalent in several cancers, including colorectal cancer and endometrial cancer, leading to dramatically ultra-high tumor mutation burden (TMB). To understand whether POLE mutations that are not classified as drivers (POLE Variant) contribute to mutagenesis, we assessed TMB in 447 POLE-mutated colorectal cancers, endometrial cancers, and ovarian cancers classified as TMB-high ≥10 mutations/Mb (mut/Mb) or TMB-low <10 mut/Mb. TMB was significantly highest in tumors with "POLE ExoD driver plus POLE Variant" (colorectal cancer and endometrial cancer, P < 0.001; ovarian cancer, P < 0.05). TMB increased with additional POLE variants (P < 0.001), but plateaued at 2, suggesting an association between the presence of these variants and TMB. Integrated analysis of AlphaFold2 POLE models and quantitative stability estimates predicted the impact of multiple POLE variants on POLE functionality. The prevalence of immunogenic neoepitopes was notably higher in the "POLE ExoD driver plus POLE Variant" tumors. Overall, this study reveals a novel correlation between POLE variants in POLE ExoD-driven tumors, and ultra-high TMB. Currently, only select pathogenic ExoD mutations with a reliable association with ultra-high TMB inform clinical practice. Thus, these findings are hypothesis-generating, require functional validation, and could potentially inform tumor classification, treatment responses, and clinical outcomes. SIGNIFICANCE Somatic POLE ExoD driver mutations cause proofreading deficiency that induces high TMB. This study suggests a novel modifier role for POLE variants in POLE ExoD-driven tumors, associated with ultra-high TMB. These data, in addition to future functional studies, may inform tumor classification, therapeutic response, and patient outcomes.
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Affiliation(s)
- Shreya M. Shah
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania
- Science Scholars Program, Temple University, Philadelphia, Pennsylvania
| | - Elena V. Demidova
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania
- Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russian Federation
| | - Salena Ringenbach
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania
- Lewis Katz School of Medicine, Temple University, Bethlehem, Pennsylvania
| | - Bulat Faezov
- Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russian Federation
- Program in Cancer Signaling and Microenvironment, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Mark Andrake
- Program in Cancer Signaling and Microenvironment, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Arjun Gandhi
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania
- University College Dublin School of Medicine and Medical Science, Dublin, Ireland
| | - Pilar Mur
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
| | - Julen Viana-Errasti
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
| | | | | | - Laura Valle
- Hereditary Cancer Program, Catalan Institute of Oncology, IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
| | - Roland L. Dunbrack
- Program in Cancer Signaling and Microenvironment, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Michael J. Hall
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania
| | - Sanjeevani Arora
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania
- Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania
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23
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Hanna G, Khanna T, Islam SA, David A, Sternberg MJE. Missense3D-TM: Predicting the Effect of Missense Variants in Helical Transmembrane Protein Regions Using 3D Protein Structures. J Mol Biol 2024; 436:168374. [PMID: 38182301 DOI: 10.1016/j.jmb.2023.168374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 10/29/2023] [Accepted: 11/20/2023] [Indexed: 01/07/2024]
Abstract
Variant effect predictors assess if a substitution is pathogenic or benign. Most predictors, including those that are structure-based, are designed for globular proteins in aqueous environments and do not consider that the variant residue is located within the membrane. We report Missense3D-TM that provides a structure-based assessment of the impact of a missense variant located within a membrane. On a dataset of 2,078 pathogenic and 1,060 benign variants, spanning 711 proteins from 706 structures, Missense3D-TM achieved an accuracy of 66%, Mathews correlation coefficient of 0.37, sensitivity of 58% and specificity of 81%. Missense3D-TM performed similarly to mCSM-membrane: accuracy 66% vs 61% (p = 0.02) on an unbalanced test set and 70% vs 67% (p = 0.20) on a balanced test set. The Missense3D-TM website provides an analysis of the structural effects of the variant along with its predicted position within the membrane. The web server is available at http://missense3d.bc.ic.ac.uk/.
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Affiliation(s)
- Gordon Hanna
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
| | - Tarun Khanna
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
| | - Suhail A Islam
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
| | - Alessia David
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK.
| | - Michael J E Sternberg
- Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London SW7 2AZ, UK
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24
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Jin H, Liu D, Ni Y, Wang H, Long D. Quantitative Ensemble Interpretation of Membrane Paramagnetic Relaxation Enhancement (mPRE) for Studying Membrane-Associated Intrinsically Disordered Proteins. J Am Chem Soc 2024; 146:791-800. [PMID: 38146836 DOI: 10.1021/jacs.3c10847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
An understanding of the functional role played by a membrane-associated intrinsically disordered protein (IDP) requires characterization of its heterogeneous conformations as well as its poses relative to the membranes, which is of great interest but technically challenging. Here, we explore the membrane paramagnetic relaxation enhancement (mPRE) for constructing ensembles of IDPs that dynamically associate with membrane mimetics incorporating spin-labeled lipids. To accurately interpret the mPRE Γ2 rates, both the dynamics of IDPs and spin probe molecules are taken into account, with the latter described by a weighted three-dimensional (3D) grid model built based on all-atom simulations. The IDP internal conformations, orientations, and immersion depths in lipid bilayers are comprehensively optimized in the Γ2-based ensemble modeling. Our approach is tested and validated on the example of POPG bicelle-bound disordered cytoplasmic domain of CD3ε (CD3εCD), a component of the T-cell receptor (TCR) complex. The mPRE-derived CD3εCD ensemble provides new insights into the IDP-membrane fuzzy association, in particular for the tyrosine-based signaling motif that plays a critical role in TCR signaling. The comparative analysis of the ensembles for wild-type CD3εCD and mutants that mimic the mono- and dual-phosphorylation effects suggests a delicate membrane regulatory mechanism for activation and inhibition of the TCR activity.
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Affiliation(s)
- Hong Jin
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Dan Liu
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Yu Ni
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Hui Wang
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
| | - Dong Long
- MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, University of Science and Technology of China, Hefei 230027, China
- Department of Chemistry, University of Science and Technology of China, Hefei 230026, China
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25
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Gürkan B, Poelman H, Pereverzeva L, Kruijswijk D, de Vos AF, Groenen AG, Nollet EE, Wichapong K, Lutgens E, van der Poll T, Du J, Wiersinga WJ, Nicolaes GAF, van ‘t Veer C. The IRAK-M death domain: a tale of three surfaces. Front Mol Biosci 2024; 10:1265455. [PMID: 38268724 PMCID: PMC10806146 DOI: 10.3389/fmolb.2023.1265455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 12/29/2023] [Indexed: 01/26/2024] Open
Abstract
The anti-inflammatory interleukin-1 receptor associated kinase-M (IRAK-M) is a negative regulator of MyD88/IRAK-4/IRAK-1 signaling. However, IRAK-M has also been reported to activate NF-κB through the MyD88/IRAK-4/IRAK-M myddosome in a MEKK-3 dependent manner. Here we provide support that IRAK-M uses three surfaces of its Death Domain (DD) to activate NF-κB downstream of MyD88/IRAK-4/IRAK-M. Surface 1, with central residue Trp74, binds to MyD88/IRAK-4. Surface 2, with central Lys60, associates with other IRAK-M DDs to form an IRAK-M homotetramer under the MyD88/IRAK-4 scaffold. Surface 3; with central residue Arg97 is located on the opposite side of Trp74 in the IRAK-M DD tetramer, lacks any interaction points with the MyD88/IRAK-4 complex. Although the IRAK-M DD residue Arg97 is not directly involved in the association with MyD88/IRAK-4, Arg97 was responsible for 50% of the NF-κB activation though the MyD88/IRAK-4/IRAK-M myddosome. Arg97 was also found to be pivotal for IRAK-M's interaction with IRAK-1, and important for IRAK-M's interaction with TRAF6. Residue Arg97 was responsible for 50% of the NF-κB generated by MyD88/IRAK-4/IRAK-M myddosome in IRAK-1/MEKK3 double knockout cells. By structural modeling we found that the IRAK-M tetramer surface around Arg97 has excellent properties that allow formation of an IRAK-M homo-octamer. This model explains why mutation of Arg97 results in an IRAK-M molecule with increased inhibitory properties: it still binds to myddosome, competing with myddosome IRAK-1 binding, while resulting in less NF-κB formation. The findings further identify the structure-function properties of IRAK-M, which is a potential therapeutic target in inflammatory disease.
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Affiliation(s)
- Berke Gürkan
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Hessel Poelman
- Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, Netherlands
- Medical Biochemistry, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Liza Pereverzeva
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Danielle Kruijswijk
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Alex F. de Vos
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Anouk G. Groenen
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Edgar E. Nollet
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Kanin Wichapong
- Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, Netherlands
| | - Esther Lutgens
- Medical Biochemistry, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Tom van der Poll
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Division of Infectious Diseases, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Jiangfeng Du
- School of Life Sciences, Zhengzhou University, Zhengzhou, China
| | - W. Joost Wiersinga
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Division of Infectious Diseases, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Gerry A. F. Nicolaes
- Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, Netherlands
- Medical Biochemistry, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
| | - Cornelis van ‘t Veer
- Center of Experimental and Molecular Medicine, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
- Amsterdam Infection and Immunity Institute, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands
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26
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Nishimura M, Fujii T, Tanaka H, Maehara K, Morishima K, Shimizu M, Kobayashi Y, Nozawa K, Takizawa Y, Sugiyama M, Ohkawa Y, Kurumizaka H. Genome-wide mapping and cryo-EM structural analyses of the overlapping tri-nucleosome composed of hexasome-hexasome-octasome moieties. Commun Biol 2024; 7:61. [PMID: 38191828 PMCID: PMC10774305 DOI: 10.1038/s42003-023-05694-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 12/11/2023] [Indexed: 01/10/2024] Open
Abstract
The nucleosome is a fundamental unit of chromatin in which about 150 base pairs of DNA are wrapped around a histone octamer. The overlapping di-nucleosome has been proposed as a product of chromatin remodeling around the transcription start site, and previously found as a chromatin unit, in which about 250 base pairs of DNA continuously bind to the histone core composed of a hexamer and an octamer. In the present study, our genome-wide analysis of human cells suggests another higher nucleosome stacking structure, the overlapping tri-nucleosome, which wraps about 300-350 base-pairs of DNA in the region downstream of certain transcription start sites of actively transcribed genes. We determine the cryo-electron microscopy (cryo-EM) structure of the overlapping tri-nucleosome, in which three subnucleosome moieties, hexasome, hexasome, and octasome, are associated by short connecting DNA segments. Small angle X-ray scattering and coarse-grained molecular dynamics simulation analyses reveal that the cryo-EM structure of the overlapping tri-nucleosome may reflect its structure in solution. Our findings suggest that nucleosome stacking structures composed of hexasome and octasome moieties may be formed by nucleosome remodeling factors around transcription start sites for gene regulation.
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Affiliation(s)
- Masahiro Nishimura
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan
- Epigenetics and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, 111 TW, Alexander Drive, Research Triangle Park, NC, 27707, USA
| | - Takeru Fujii
- Division of Transcriptomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi, Fukuoka, 812-0054, Japan
| | - Hiroki Tanaka
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan
- Department of Structural Virology, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan
| | - Kazumitsu Maehara
- Division of Transcriptomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi, Fukuoka, 812-0054, Japan
| | - Ken Morishima
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Masahiro Shimizu
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Yuki Kobayashi
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan
| | - Kayo Nozawa
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan
- School of Life Science and Technology, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa, 226-8501, Japan
| | - Yoshimasa Takizawa
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan
| | - Masaaki Sugiyama
- Institute for Integrated Radiation and Nuclear Science, Kyoto University, Kumatori, Sennan-gun, Osaka, 590-0494, Japan
| | - Yasuyuki Ohkawa
- Division of Transcriptomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi, Fukuoka, 812-0054, Japan.
| | - Hitoshi Kurumizaka
- Laboratory of Chromatin Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-0032, Japan.
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27
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Parisi G, Piacentini R, Incocciati A, Bonamore A, Macone A, Rupert J, Zacco E, Miotto M, Milanetti E, Tartaglia GG, Ruocco G, Boffi A, Di Rienzo L. Design of protein-binding peptides with controlled binding affinity: the case of SARS-CoV-2 receptor binding domain and angiotensin-converting enzyme 2 derived peptides. Front Mol Biosci 2024; 10:1332359. [PMID: 38250735 PMCID: PMC10797010 DOI: 10.3389/fmolb.2023.1332359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024] Open
Abstract
The development of methods able to modulate the binding affinity between proteins and peptides is of paramount biotechnological interest in view of a vast range of applications that imply designed polypeptides capable to impair or favour Protein-Protein Interactions. Here, we applied a peptide design algorithm based on shape complementarity optimization and electrostatic compatibility and provided the first experimental in vitro proof of the efficacy of the design algorithm. Focusing on the interaction between the SARS-CoV-2 Spike Receptor-Binding Domain (RBD) and the human angiotensin-converting enzyme 2 (ACE2) receptor, we extracted a 23-residues long peptide that structurally mimics the major interacting portion of the ACE2 receptor and designed in silico five mutants of such a peptide with a modulated affinity. Remarkably, experimental KD measurements, conducted using biolayer interferometry, matched the in silico predictions. Moreover, we investigated the molecular determinants that govern the variation in binding affinity through molecular dynamics simulation, by identifying the mechanisms driving the different values of binding affinity at a single residue level. Finally, the peptide sequence with the highest affinity, in comparison with the wild type peptide, was expressed as a fusion protein with human H ferritin (HFt) 24-mer. Solution measurements performed on the latter constructs confirmed that peptides still exhibited the expected trend, thereby enhancing their efficacy in RBD binding. Altogether, these results indicate the high potentiality of this general method in developing potent high-affinity vectors for hindering/enhancing protein-protein associations.
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Affiliation(s)
- Giacomo Parisi
- Department of Basic and Applied Sciences for Engineering (SBAI), Università“Sapienza”, Roma, Italy
| | - Roberta Piacentini
- Department of Biochemical Sciences “Alessandro Rossi Fanelli”, Università“Sapienza”, Roma, Italy
| | - Alessio Incocciati
- Department of Biochemical Sciences “Alessandro Rossi Fanelli”, Università“Sapienza”, Roma, Italy
| | - Alessandra Bonamore
- Department of Biochemical Sciences “Alessandro Rossi Fanelli”, Università“Sapienza”, Roma, Italy
| | - Alberto Macone
- Department of Biochemical Sciences “Alessandro Rossi Fanelli”, Università“Sapienza”, Roma, Italy
| | - Jakob Rupert
- Department of Biology and Biotechnologies “Charles Darwin”, Università“Sapienza”, Roma, Italy
- Centre for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova, Italy
| | - Elsa Zacco
- Centre for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova, Italy
| | - Mattia Miotto
- Center for Life Nano and Neuro Science, Istituto Italiano di Tecnologia (IIT), Roma, Italy
| | - Edoardo Milanetti
- Center for Life Nano and Neuro Science, Istituto Italiano di Tecnologia (IIT), Roma, Italy
- Department of Physics, Università“Sapienza”, Roma, Italy
| | - Gian Gaetano Tartaglia
- Department of Biology and Biotechnologies “Charles Darwin”, Università“Sapienza”, Roma, Italy
- Centre for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova, Italy
| | - Giancarlo Ruocco
- Center for Life Nano and Neuro Science, Istituto Italiano di Tecnologia (IIT), Roma, Italy
- Department of Physics, Università“Sapienza”, Roma, Italy
| | - Alberto Boffi
- Department of Biochemical Sciences “Alessandro Rossi Fanelli”, Università“Sapienza”, Roma, Italy
| | - Lorenzo Di Rienzo
- Center for Life Nano and Neuro Science, Istituto Italiano di Tecnologia (IIT), Roma, Italy
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28
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Draizen EJ, Readey J, Mura C, Bourne PE. Prop3D: A flexible, Python-based platform for machine learning with protein structural properties and biophysical data. BMC Bioinformatics 2024; 25:11. [PMID: 38177985 PMCID: PMC10768222 DOI: 10.1186/s12859-023-05586-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 11/27/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Machine learning (ML) has a rich history in structural bioinformatics, and modern approaches, such as deep learning, are revolutionizing our knowledge of the subtle relationships between biomolecular sequence, structure, function, dynamics and evolution. As with any advance that rests upon statistical learning approaches, the recent progress in biomolecular sciences is enabled by the availability of vast volumes of sufficiently-variable data. To be useful, such data must be well-structured, machine-readable, intelligible and manipulable. These and related requirements pose challenges that become especially acute at the computational scales typical in ML. Furthermore, in structural bioinformatics such data generally relate to protein three-dimensional (3D) structures, which are inherently more complex than sequence-based data. A significant and recurring challenge concerns the creation of large, high-quality, openly-accessible datasets that can be used for specific training and benchmarking tasks in ML pipelines for predictive modeling projects, along with reproducible splits for training and testing. RESULTS Here, we report 'Prop3D', a platform that allows for the creation, sharing and extensible reuse of libraries of protein domains, featurized with biophysical and evolutionary properties that can range from detailed, atomically-resolved physicochemical quantities (e.g., electrostatics) to coarser, residue-level features (e.g., phylogenetic conservation). As a community resource, we also supply a 'Prop3D-20sf' protein dataset, obtained by applying our approach to CATH . We have developed and deployed the Prop3D framework, both in the cloud and on local HPC resources, to systematically and reproducibly create comprehensive datasets via the Highly Scalable Data Service ( HSDS ). Our datasets are freely accessible via a public HSDS instance, or they can be used with accompanying Python wrappers for popular ML frameworks. CONCLUSION Prop3D and its associated Prop3D-20sf dataset can be of broad utility in at least three ways. Firstly, the Prop3D workflow code can be customized and deployed on various cloud-based compute platforms, with scalability achieved largely by saving the results to distributed HDF5 files via HSDS . Secondly, the linked Prop3D-20sf dataset provides a hand-crafted, already-featurized dataset of protein domains for 20 highly-populated CATH families; importantly, provision of this pre-computed resource can aid the more efficient development (and reproducible deployment) of ML pipelines. Thirdly, Prop3D-20sf's construction explicitly takes into account (in creating datasets and data-splits) the enigma of 'data leakage', stemming from the evolutionary relationships between proteins.
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Affiliation(s)
- Eli J Draizen
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
- School of Data Science, University of Virginia, Charlottesville, VA, USA.
| | | | - Cameron Mura
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
- School of Data Science, University of Virginia, Charlottesville, VA, USA.
| | - Philip E Bourne
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- School of Data Science, University of Virginia, Charlottesville, VA, USA
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29
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Pang YT, Yang L, Gumbart JC. From simple to complex: Reconstructing all-atom structures from coarse-grained models using cg2all. Structure 2024; 32:5-7. [PMID: 38181727 DOI: 10.1016/j.str.2023.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 12/08/2023] [Accepted: 12/08/2023] [Indexed: 01/07/2024]
Abstract
In this issue of Structure, Heo and Feig present cg2all, a novel deep-learning model capable of efficiently predicting all-atom protein structures from coarse-grained (CG) representations. The model maintains high accuracy, even when the CG model is simplified to a single bead per residue, and has a number of promising applications.
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Affiliation(s)
- Yui Tik Pang
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Lixinhao Yang
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - James C Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA; School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA.
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30
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Heo L, Feig M. One bead per residue can describe all-atom protein structures. Structure 2024; 32:97-111.e6. [PMID: 38000367 PMCID: PMC10872525 DOI: 10.1016/j.str.2023.10.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/16/2023] [Accepted: 10/30/2023] [Indexed: 11/26/2023]
Abstract
Atomistic resolution is the standard for high-resolution biomolecular structures, but experimental structural data are often at lower resolution. Coarse-grained models are also used extensively in computational studies to reach biologically relevant spatial and temporal scales. This study explores the use of advanced machine learning networks for reconstructing atomistic models from reduced representations. The main finding is that a single bead per amino acid residue allows construction of accurate and stereochemically realistic all-atom structures with minimal loss of information. This suggests that lower resolution representations of proteins may be sufficient for many applications when combined with a machine learning framework that encodes knowledge from known structures. Practical applications include the rapid addition of atomistic detail to low-resolution structures from experiment or computational coarse-grained models. The application of rapid, deterministic all-atom reconstruction within multi-scale frameworks is further demonstrated with a rapid protocol for the generation of accurate models from cryo-EM densities close to experimental structures.
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Affiliation(s)
- Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
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31
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Lebedenko OO, Salikov VA, Izmailov SA, Podkorytov IS, Skrynnikov NR. Using NMR diffusion data to validate MD models of disordered proteins: Test case of N-terminal tail of histone H4. Biophys J 2024; 123:80-100. [PMID: 37990496 PMCID: PMC10808029 DOI: 10.1016/j.bpj.2023.11.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/28/2023] [Accepted: 11/17/2023] [Indexed: 11/23/2023] Open
Abstract
MD simulations can provide uniquely detailed models of intrinsically disordered proteins (IDPs). However, these models need careful experimental validation. The coefficient of translational diffusion Dtr, measurable by pulsed field gradient NMR, offers a potentially useful piece of experimental information related to the compactness of the IDP's conformational ensemble. Here, we investigate, both experimentally and via the MD modeling, the translational diffusion of a 25-residue N-terminal fragment from histone H4 (N-H4). We found that the predicted values of Dtr, as obtained from mean-square displacement of the peptide in the MD simulations, are largely determined by the viscosity of the MD water (which has been reinvestigated as a part of our study). Beyond that, our analysis of the diffusion data indicates that MD simulations of N-H4 in the TIP4P-Ew water give rise to an overly compact conformational ensemble for this peptide. In contrast, TIP4P-D and OPC simulations produce the ensembles that are consistent with the experimental Dtr result. These observations are supported by the analyses of the 15N spin relaxation rates. We also tested a number of empirical methods to predict Dtr based on IDP's coordinates extracted from the MD snapshots. In particular, we show that the popular approach involving the program HYDROPRO can produce misleading results. This happens because HYDROPRO is not intended to predict the diffusion properties of highly flexible biopolymers such as IDPs. Likewise, recent empirical schemes that exploit the relationship between the small-angle x-ray scattering-informed conformational ensembles of IDPs and the respective experimental Dtr values also prove to be problematic. In this sense, the first-principle calculations of Dtr from the MD simulations, such as demonstrated in this work, should provide a useful benchmark for future efforts in this area.
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Affiliation(s)
- Olga O Lebedenko
- Laboratory of Biomolecular NMR, St. Petersburg State University, St. Petersburg, Russia
| | - Vladislav A Salikov
- Laboratory of Biomolecular NMR, St. Petersburg State University, St. Petersburg, Russia
| | - Sergei A Izmailov
- Laboratory of Biomolecular NMR, St. Petersburg State University, St. Petersburg, Russia
| | - Ivan S Podkorytov
- Laboratory of Biomolecular NMR, St. Petersburg State University, St. Petersburg, Russia
| | - Nikolai R Skrynnikov
- Laboratory of Biomolecular NMR, St. Petersburg State University, St. Petersburg, Russia; Department of Chemistry, Purdue University, West Lafayette, Indiana.
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32
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Krupa MA, Krupa P. Free-Docking and Template-Based Docking: Physics Versus Knowledge-Based Docking. Methods Mol Biol 2024; 2780:27-41. [PMID: 38987462 DOI: 10.1007/978-1-0716-3985-6_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
Docking methods can be used to predict the orientations of two or more molecules with respect of each other using a plethora of various algorithms, which can be based on the physics of interactions or can use information from databases and templates. The usability of these approaches depends on the type and size of the molecules, whose relative orientation will be estimated. The two most important limitations are (i) the computational cost of the prediction and (ii) the availability of the structural information for similar complexes. In general, if there is enough information about similar systems, knowledge-based and template-based methods can significantly reduce the computational cost while providing high accuracy of the prediction. However, if the information about the system topology and interactions between its partners is scarce, physics-based methods are more reliable or even the only choice. In this chapter, knowledge-, template-, and physics-based methods will be compared and briefly discussed providing examples of their usability with a special emphasis on physics-based protein-protein, protein-peptide, and protein-fullerene docking in the UNRES coarse-grained model.
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Affiliation(s)
- Magdalena A Krupa
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
| | - Paweł Krupa
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland.
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33
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Okuma H, Saijo-Hamano Y, Yamada H, Sherif AA, Hashizaki E, Sakai N, Kato T, Imasaki T, Kikkawa S, Nitta E, Sasai M, Abe T, Sugihara F, Maniwa Y, Kosako H, Takei K, Standley DM, Yamamoto M, Nitta R. Structural basis of Irgb6 inactivation by Toxoplasma gondii through the phosphorylation of switch I. Genes Cells 2024; 29:17-38. [PMID: 37984375 DOI: 10.1111/gtc.13080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/12/2023] [Accepted: 10/29/2023] [Indexed: 11/22/2023]
Abstract
Irgb6 is a priming immune-related GTPase (IRG) that counteracts Toxoplasma gondii. It is known to be recruited to the low virulent type II T. gondii parasitophorous vacuole (PV), initiating cell-autonomous immunity. However, the molecular mechanism by which immunity-related GTPases become inactivated after the parasite infection remains obscure. Here, we found that Thr95 of Irgb6 is prominently phosphorylated in response to low virulent type II T. gondii infection. We observed that a phosphomimetic T95D mutation in Irgb6 impaired its localization to the PV and exhibited reduced GTPase activity in vitro. Structural analysis unveiled an atypical conformation of nucleotide-free Irgb6-T95D, resulting from a conformational change in the G-domain that allosterically modified the PV membrane-binding interface. In silico docking corroborated the disruption of the physiological membrane binding site. These findings provide novel insights into a T. gondii-induced allosteric inactivation mechanism of Irgb6.
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Affiliation(s)
- Hiromichi Okuma
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Yumiko Saijo-Hamano
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Hiroshi Yamada
- Department of Neuroscience, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Aalaa Alrahman Sherif
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka, Japan
- Laboratory of Systems Immunology, WPI Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Emi Hashizaki
- Laboratory of Immunoparasitology, Osaka University, Osaka, Japan
- Department of Immunoparasitology, Research Institute for Microbial Diseases, Osaka, Japan
| | | | - Takaaki Kato
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Tsuyoshi Imasaki
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Satoshi Kikkawa
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Eriko Nitta
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Miwa Sasai
- Laboratory of Immunoparasitology, Osaka University, Osaka, Japan
- Department of Immunoparasitology, Research Institute for Microbial Diseases, Osaka, Japan
| | - Tadashi Abe
- Department of Neuroscience, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Fuminori Sugihara
- Core Instrumentation Facility, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Yoshimasa Maniwa
- Division of Thoracic Surgery, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Hidetaka Kosako
- Division of Cell Signaling, Fujii Memorial Institute of Medical Sciences, Tokushima University, Tokushima, Japan
| | - Kohji Takei
- Department of Neuroscience, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Daron M Standley
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka, Japan
- Laboratory of Systems Immunology, WPI Immunology Frontier Research Center, Osaka University, Osaka, Japan
| | - Masahiro Yamamoto
- Laboratory of Immunoparasitology, Osaka University, Osaka, Japan
- Department of Immunoparasitology, Research Institute for Microbial Diseases, Osaka, Japan
| | - Ryo Nitta
- Division of Structural Medicine and Anatomy, Department of Physiology and Cell Biology, Kobe University Graduate School of Medicine, Kobe, Japan
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34
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Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.11.571185. [PMID: 38168257 PMCID: PMC10760024 DOI: 10.1101/2023.12.11.571185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
In this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.
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35
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Simpkin AJ, Mesdaghi S, Sánchez Rodríguez F, Elliott L, Murphy DL, Kryshtafovych A, Keegan RM, Rigden DJ. Tertiary structure assessment at CASP15. Proteins 2023; 91:1616-1635. [PMID: 37746927 PMCID: PMC10792517 DOI: 10.1002/prot.26593] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 08/25/2023] [Accepted: 09/07/2023] [Indexed: 09/26/2023]
Abstract
The results of tertiary structure assessment at CASP15 are reported. For the first time, recognizing the outstanding performance of AlphaFold 2 (AF2) at CASP14, all single-chain predictions were assessed together, irrespective of whether a template was available. At CASP15, there was no single stand-out group, with most of the best-scoring groups-led by PEZYFoldings, UM-TBM, and Yang Server-employing AF2 in one way or another. Many top groups paid special attention to generating deep Multiple Sequence Alignments (MSAs) and testing variant MSAs, thereby allowing them to successfully address some of the hardest targets. Such difficult targets, as well as lacking templates, were typically proteins with few homologues. Local divergence between prediction and target correlated with localization at crystal lattice or chain interfaces, and with regions exhibiting high B-factor factors in crystal structure targets, and should not necessarily be considered as representing error in the prediction. However, analysis of exposed and buried side chain accuracy showed room for improvement even in the latter. Nevertheless, a majority of groups produced high-quality predictions for most targets, which are valuable for experimental structure determination, functional analysis, and many other tasks across biology. These include those applying methods similar to those used to generate major resources such as the AlphaFold Protein Structure Database and the ESM Metagenomic atlas: the confidence estimates of the former were also notably accurate.
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Affiliation(s)
- Adam J. Simpkin
- Department of Biochemistry, Cell and Systems BiologyInstitute of Structural, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
| | - Shahram Mesdaghi
- Department of Biochemistry, Cell and Systems BiologyInstitute of Structural, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
- Computational Biology Facility, MerseyBio, University of LiverpoolLiverpoolUK
| | - Filomeno Sánchez Rodríguez
- Department of Biochemistry, Cell and Systems BiologyInstitute of Structural, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
- Life Science, Diamond Light Source, Harwell Science and Innovation CampusOxfordshireUK
- Department of Chemistry, York Structural Biology LaboratoryUniversity of YorkYorkUK
| | - Luc Elliott
- Department of Biochemistry, Cell and Systems BiologyInstitute of Structural, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
| | - David L. Murphy
- Department of Biochemistry, Cell and Systems BiologyInstitute of Structural, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
| | | | - Ronan M. Keegan
- UKRI‐STFC, Rutherford Appleton Laboratory, Research Complex at HarwellDidcotUK
| | - Daniel J. Rigden
- Department of Biochemistry, Cell and Systems BiologyInstitute of Structural, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
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36
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Zielinski M, Peralta Reyes FS, Gremer L, Schemmert S, Frieg B, Schäfer LU, Willuweit A, Donner L, Elvers M, Nilsson LNG, Syvänen S, Sehlin D, Ingelsson M, Willbold D, Schröder GF. Cryo-EM of Aβ fibrils from mouse models find tg-APP ArcSwe fibrils resemble those found in patients with sporadic Alzheimer's disease. Nat Neurosci 2023; 26:2073-2080. [PMID: 37973869 PMCID: PMC10689242 DOI: 10.1038/s41593-023-01484-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 10/06/2023] [Indexed: 11/19/2023]
Abstract
The use of transgenic mice displaying amyloid-β (Aβ) brain pathology has been essential for the preclinical assessment of new treatment strategies for Alzheimer's disease. However, the properties of Aβ in such mice have not been systematically compared to Aβ in the brains of patients with Alzheimer's disease. Here, we determined the structures of nine ex vivo Aβ fibrils from six different mouse models by cryogenic-electron microscopy. We found novel Aβ fibril structures in the APP/PS1, ARTE10 and tg-SwDI models, whereas the human type II filament fold was found in the ARTE10, tg-APPSwe and APP23 models. The tg-APPArcSwe mice showed an Aβ fibril whose structure resembles the human type I filament found in patients with sporadic Alzheimer's disease. A detailed assessment of the Aβ fibril structure is key to the selection of adequate mouse models for the preclinical development of novel plaque-targeting therapeutics and positron emission tomography imaging tracers in Alzheimer's disease.
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Affiliation(s)
- Mara Zielinski
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany
- JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, Jülich, Germany
| | | | - Lothar Gremer
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany.
- JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, Jülich, Germany.
- Institut für Physikalische Biologie, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Sarah Schemmert
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany
| | - Benedikt Frieg
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany
- JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, Jülich, Germany
| | - Luisa U Schäfer
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany
- JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, Jülich, Germany
- Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Antje Willuweit
- Institute of Neuroscience and Medicine, Medical Imaging Physics (INM-4), Forschungszentrum Jülich, Jülich, Germany
| | - Lili Donner
- Department of Vascular and Endovascular Surgery, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Margitta Elvers
- Department of Vascular and Endovascular Surgery, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Lars N G Nilsson
- Department of Pharmacology, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Stina Syvänen
- Department of Public Health and Caring Sciences, Molecular Geriatrics, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden
| | - Dag Sehlin
- Department of Public Health and Caring Sciences, Molecular Geriatrics, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Molecular Geriatrics, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden
- Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
- Tanz Centre for Research in Neurodegenerative Diseases, Departments of Medicine and Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Dieter Willbold
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany.
- JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, Jülich, Germany.
- Institut für Physikalische Biologie, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Gunnar F Schröder
- Institute of Biological Information Processing, Structural Biochemistry (IBI-7), Forschungszentrum Jülich, Jülich, Germany.
- JuStruct, Jülich Center for Structural Biology, Forschungszentrum Jülich, Jülich, Germany.
- Physics Department, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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37
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Caillot M, Miloudi H, Taly A, Profitós-Pelejà N, Santos JC, Ribeiro ML, Maitre E, Saule S, Roué G, Jardin F, Sola B. Exportin 1-mediated nuclear/cytoplasmic trafficking controls drug sensitivity of classical Hodgkin's lymphoma. Mol Oncol 2023; 17:2546-2564. [PMID: 36727672 PMCID: PMC10701774 DOI: 10.1002/1878-0261.13386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 12/22/2022] [Accepted: 02/01/2023] [Indexed: 02/03/2023] Open
Abstract
Exportin 1 (XPO1) is the main nuclear export receptor that controls the subcellular trafficking and the functions of major regulatory proteins. XPO1 is overexpressed in various cancers and small inhibitors of nuclear export (SINEs) have been developed to inhibit XPO1. In primary mediastinal B-cell lymphoma (PMBL) and classical Hodgkin's lymphoma (cHL), the XPO1 gene may be mutated on one nucleotide and encodes the mutant XPO1E571K . To understand the impact of mutation on protein function, we studied the response of PMBL and cHL cells to selinexor, a SINE, and ibrutinib, an inhibitor of Bruton tyrosine kinase. XPO1 mutation renders lymphoma cells more sensitive to selinexor due to a faster degradation of mutant XPO1 compared to the wild-type. We further showed that a mistrafficking of p65 (RELA) and p52 (NFκB2) transcription factors between the nuclear and cytoplasmic compartments accounts for the response toward ibrutinib. XPO1 mutation may be envisaged as a biomarker of the response of PMBL and cHL cells and other B-cell hemopathies to SINEs and drugs that target even indirectly the NFκB signaling pathway.
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Affiliation(s)
| | | | - Antoine Taly
- Laboratoire de Biochimie Théorique, CNRS, Université de Paris, Paris, France
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Nuria Profitós-Pelejà
- Lymphoma Translational Group, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - Juliana C Santos
- Lymphoma Translational Group, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - Marcelo L Ribeiro
- Lymphoma Translational Group, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - Elsa Maitre
- Normandie Univ, INSERM, Unicaen, Caen, France
- Laboratoire d'hématologie, CHU Côte de Nacre, Caen, France
| | - Simon Saule
- Institut Curie, PSL Research University, CNRS, INSERM, Orsay, France
- Université Paris-Sud, Université Paris-Saclay, CNRS, INSERM, Orsay, France
| | - Gaël Roué
- Lymphoma Translational Group, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - Fabrice Jardin
- Normandie Univ, INSERM, Unirouen, Rouen, France
- Service d'hématologie, Centre de lutte contre le cancer Henri Becquerel, Rouen, France
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38
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Twizerimana AP, Becker D, Zhu S, Luedde T, Gohlke H, Münk C. The cyclophilin A-binding loop of the capsid regulates the human TRIM5α sensitivity of nonpandemic HIV-1. Proc Natl Acad Sci U S A 2023; 120:e2306374120. [PMID: 37983491 PMCID: PMC10691330 DOI: 10.1073/pnas.2306374120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 09/26/2023] [Indexed: 11/22/2023] Open
Abstract
The rather few cases of humans infected by HIV-1 N, O, or P raise the question of their incomplete adaptation to humans. We hypothesized that early postentry restrictions may be relevant for the impaired spread of these HIVs. One of the best-characterized species-specific restriction factors is TRIM5α. HIV-1 M can escape human (hu) TRIM5α restriction by binding cyclophilin A (CYPA, also known as PPIA, peptidylprolyl isomerase A) to the so-called CYPA-binding loop of its capsid protein. How non-M HIV-1s interact with huTRIM5α is ill-defined. By testing full-length reporter viruses (Δ env) of HIV-1 N, O, P, and SIVgor (simian IV of gorillas), we found that in contrast to HIV-1 M, the nonpandemic HIVs and SIVgor showed restriction by huTRIM5α. Work to identify capsid residues that mediate susceptibility to huTRIM5α revealed that residue 88 in the capsid CYPA-binding loop was important for such differences. There, HIV-1 M uses alanine to resist, while non-M HIV-1s have either valine or methionine, which avail them for huTRIM5α. Capsid residue 88 determines the sensitivity to TRIM5α in an unknown way. Molecular simulations indicated that capsid residue 88 can affect trans-to-cis isomerization patterns on the capsids of the viruses we tested. These differential CYPA usages by pandemic and nonpandemic HIV-1 suggest that the enzymatic activity of CYPA on the viral core might be important for its protective function against huTRIM5α.
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Affiliation(s)
- Augustin P. Twizerimana
- Clinic of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf40225, Germany
| | - Daniel Becker
- Institute for Pharmaceutical and Medicinal Chemistry, Heinrich Heine University Düsseldorf, Düsseldorf40225, Germany
| | - Shenglin Zhu
- Clinic of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf40225, Germany
| | - Tom Luedde
- Clinic of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf40225, Germany
| | - Holger Gohlke
- Institute for Pharmaceutical and Medicinal Chemistry, Heinrich Heine University Düsseldorf, Düsseldorf40225, Germany
- Institute of Bio- and Geosciences (IBG-4: Bioinformatics), Forschungszentrum Jülich GmbH, Jülich52425, Germany
| | - Carsten Münk
- Clinic of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf40225, Germany
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39
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Hale WD, Romero AM, Gonzalez CU, Jayaraman V, Lau AY, Huganir RL, Twomey EC. Allosteric Competition and Inhibition in AMPA Receptors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.28.569057. [PMID: 38076818 PMCID: PMC10705377 DOI: 10.1101/2023.11.28.569057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Excitatory neurotransmission is principally mediated by AMPA-subtype ionotropic glutamate receptors (AMPARs). Dysregulation of AMPARs is the cause of many neurological disorders and how therapeutic candidates such as negative allosteric modulators inhibit AMPARs is unclear. Here, we show that non-competitive inhibition desensitizes AMPARs to activation and prevents positive allosteric modulation. We dissected the noncompetitive inhibition mechanism of action by capturing AMPARs bound to glutamate and the prototypical negative allosteric modulator, GYKI-52466, with cryo-electron microscopy. Noncompetitive inhibition by GYKI-52466, which binds in the transmembrane collar region surrounding the ion channel, negatively modulates AMPARs by decoupling glutamate binding in the ligand binding domain from the ion channel. Furthermore, during allosteric competition between negative and positive modulators, negative allosteric modulation by GKYI-52466 outcompetes positive allosteric modulators to control AMPAR function. Our data provide a new framework for understanding allostery of AMPARs and foundations for rational design of therapeutics targeting AMPARs in neurological diseases.
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Affiliation(s)
- W. Dylan Hale
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Alejandra Montaño Romero
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Cuauhtemoc U. Gonzalez
- Center for Membrane Biology, Department of Biochemistry and Molecular Biology, University of Texas Health Science Center at Houston, TX, USA
- The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Vasanthi Jayaraman
- Center for Membrane Biology, Department of Biochemistry and Molecular Biology, University of Texas Health Science Center at Houston, TX, USA
| | - Albert Y. Lau
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Richard L. Huganir
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Edward C. Twomey
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD USA
- The Beckman Center for Cryo-EM at Johns Hopkins, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Diana Helis Henry Medical Research Foundation, New Orleans, LA USA
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40
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Visani GM, Galvin W, Pun MN, Nourmohammad A. H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing. ARXIV 2023:arXiv:2311.09312v2. [PMID: 38013891 PMCID: PMC10680869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Accurately modeling protein 3D structure is essential for the design of functional proteins. An important sub-task of structure modeling is protein side-chain packing: predicting the conformation of side-chains (rotamers) given the protein's backbone structure and amino-acid sequence. Conventional approaches for this task rely on expensive sampling procedures over hand-crafted energy functions and rotamer libraries. Recently, several deep learning methods have been developed to tackle the problem in a data-driven way, albeit with vastly different formulations (from image-to-image translation to directly predicting atomic coordinates). Here, we frame the problem as a joint regression over the side-chains' true degrees of freedom: the dihedral χ angles. We carefully study possible objective functions for this task, while accounting for the underlying symmetries of the task. We propose Holographic Packer (H-Packer), a novel two-stage algorithm for side-chain packing built on top of two light-weight rotationally equivariant neural networks. We evaluate our method on CASP13 and CASP14 targets. H-Packer is computationally efficient and shows favorable performance against conventional physics-based algorithms and is competitive against alternative deep learning solutions.
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Affiliation(s)
- Gian Marco Visani
- Paul G. Allen School of Computer Science and Engineering, University of Washington
| | - William Galvin
- Paul G. Allen School of Computer Science and Engineering, University of Washington
| | | | - Armita Nourmohammad
- Paul G. Allen School of Computer Science and Engineering, University of Washington
- Department of Physics, University of Washington
- Department of Applied Mathematics, University of Washington
- Fred Hutch Cancer Research Center, Seattle, WA
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41
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Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. Accurate Characterization of Conformational Ensembles and Binding Mechanisms of the SARS-CoV-2 Omicron BA.2 and BA.2.86 Spike Protein with the Host Receptor and Distinct Classes of Antibodies Using AlphaFold2-Augmented Integrative Computational Modeling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.18.567697. [PMID: 38045395 PMCID: PMC10690158 DOI: 10.1101/2023.11.18.567697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The latest wave SARS-CoV-2 Omicron variants displayed a growth advantage and the increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with all-atom MD simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that AlphaFold2-predicted conformational ensemble of the BA.2.86 spike protein complex can accurately capture the main dynamics signatures obtained from microscond molecular dynamics simulations. The ensemble-based dynamic mutational scanning of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 dissected the role of the BA.2 and BA.2.86 backgrounds in modulating binding free energy changes revealing a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 mutational sites R403K, F486P and R493Q. To examine immune evasion properties of BA.2.86 in atomistic detail, we performed large scale structure-based mutational profiling of the S protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against BA.2.86 variant. The results quantified specific function of the BA.2.86 mutations to ensure broad resistance against different classes of RBD antibodies. This study revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have primarily evolved to improve immune escape while modulating binding affinity with ACE2 through cooperative effect of R403K, F486P and R493Q mutations. The study supports a hypothesis that the impact of the increased ACE2 binding affinity on viral fitness is more universal and is mediated through cross-talk between convergent mutational hotspots, while the effect of immune evasion could be more variant-dependent.
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42
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Carrington G, Hau A, Kosta S, Dugdale HF, Muntoni F, D’Amico A, Van den Bergh P, Romero NB, Malfatti E, Vilchez JJ, Oldfors A, Pajusalu S, Õunap K, Giralt-Pujol M, Zanoteli E, Campbell KS, Iwamoto H, Peckham M, Ochala J. Human skeletal myopathy myosin mutations disrupt myosin head sequestration. JCI Insight 2023; 8:e172322. [PMID: 37788100 PMCID: PMC10721271 DOI: 10.1172/jci.insight.172322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/20/2023] [Indexed: 10/05/2023] Open
Abstract
Myosin heavy chains encoded by MYH7 and MYH2 are abundant in human skeletal muscle and important for muscle contraction. However, it is unclear how mutations in these genes disrupt myosin structure and function leading to skeletal muscle myopathies termed myosinopathies. Here, we used multiple approaches to analyze the effects of common MYH7 and MYH2 mutations in the light meromyosin (LMM) region of myosin. Analyses of expressed and purified MYH7 and MYH2 LMM mutant proteins combined with in silico modeling showed that myosin coiled coil structure and packing of filaments in vitro are commonly disrupted. Using muscle biopsies from patients and fluorescent ATP analog chase protocols to estimate the proportion of myosin heads that were super-relaxed, together with x-ray diffraction measurements to estimate myosin head order, we found that basal myosin ATP consumption was increased and the myosin super-relaxed state was decreased in vivo. In addition, myofiber mechanics experiments to investigate contractile function showed that myofiber contractility was not affected. These findings indicate that the structural remodeling associated with LMM mutations induces a pathogenic state in which formation of shutdown heads is impaired, thus increasing myosin head ATP demand in the filaments, rather than affecting contractility. These key findings will help design future therapies for myosinopathies.
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Affiliation(s)
- Glenn Carrington
- The Astbury Centre for Structural and Molecular Biology and
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Abbi Hau
- Centre of Human and Applied Physiological Sciences and
- Randall Centre for Cell and Molecular Biophysics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King’s College London, United Kingdom
| | - Sarah Kosta
- Department of Physiology, University of Kentucky, Lexington, Kentucky, USA
| | - Hannah F. Dugdale
- Centre of Human and Applied Physiological Sciences and
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom
| | - Francesco Muntoni
- UCL Great Ormond Street Institute of Child Health, London, United Kingdom
- NIHR Biomedical Research Centre at Great Ormond Street Hospital, Great Ormond Street, London, United Kingdom
| | - Adele D’Amico
- Department of Neurosciences, Unit of Neuromuscular and Neurodegenerative Disorders, IRCCS Bambino Gesù Children’s Hospital, Rome, Italy
| | - Peter Van den Bergh
- Neuromuscular Reference Center, Neurology Department, University Hospital Saint-Luc, Brussels, Belgium
| | - Norma B. Romero
- Neuromuscular Morphology Unit, Institute of Myology, Myology Research Centre INSERM, Sorbonne University, Hôpital Pitié-Salpêtrière, Paris, France
| | - Edoardo Malfatti
- APHP, Centre de Référence de Pathologie Neuromusculaire Nord-Est-Ile-de-France, Henri Mondor Hospital, Inserm U955, Creteil, France
- U1179 UVSQ-INSERM Handicap Neuromuscular: Physiology, Biotherapy and Applied Pharmacology, UFR Simone Veil-Santé, Université Versailles Saint Quentin en Yvelines, Paris-Saclay, France
| | - Juan Jesus Vilchez
- Neuromuscular and Ataxias Research Group, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) Spain, Valencia, Spain
| | - Anders Oldfors
- Department of Laboratory Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Sander Pajusalu
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Katrin Õunap
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Marta Giralt-Pujol
- The Astbury Centre for Structural and Molecular Biology and
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Edmar Zanoteli
- Universidade de São Paulo, Hospital das Clínicas, Faculty of Medicine, Department of Neurology, São Paulo SP, Brazil
- Universidade Federal de São Paulo, Escola Paulista de Medicina, Department of Neurology, São Paulo SP, Brazil
| | - Kenneth S. Campbell
- Department of Physiology, University of Kentucky, Lexington, Kentucky, USA
- Division of Cardiovascular Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Hiroyuki Iwamoto
- SPring-8, Japan Synchrotron Radiation Research Institute, Hyogo, Japan
| | - Michelle Peckham
- The Astbury Centre for Structural and Molecular Biology and
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, United Kingdom
| | - Julien Ochala
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
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43
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Ning S, Sun M, Dong X, Li A, Zeng C, Liu M, Gong Z, Zhao Y. Dynamic geometry design of cyclic peptide architectures for RNA structure. Phys Chem Chem Phys 2023; 25:27967-27980. [PMID: 37768078 DOI: 10.1039/d3cp03384h] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Designing inhibitors for RNA is still challenging due to the bottleneck of maintaining the binding interaction of inhibitor-RNA accompanied by subtle RNA flexibility. Thus, the current approach usually needs to screen thousands of candidate inhibitors for binding. Here, we propose a dynamic geometry design approach to enrich the hits with only a tiny pool of designed geometrically compatible scaffold candidates. First, our method uses graph-based tree decomposition to explore the complementarity rigid binding cyclic peptide and design the amino acid side chain length and charge to fit the RNA pocket. Then, we perform an energy-based dynamical network algorithm to optimize the inhibitor-RNA hydrogen bonds. Dynamic geometry-guided design yields successful inhibitors with low micromolar binding affinity scaffolds and experimentally competes with the natural RNA chaperone. The results indicate that the dynamic geometry method yields higher efficiency and accuracy than traditional methods. The strategy could be further optimized to design the length and chirality by adopting nonstandard amino acids and facilitating RNA engineering for biological or medical applications.
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Affiliation(s)
- Shangbo Ning
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China.
| | - Min Sun
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences, Wuhan, Hubei 430071, China.
| | - Xu Dong
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences, Wuhan, Hubei 430071, China.
| | - Anbang Li
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China.
| | - Chen Zeng
- Department of Physics, The George Washington University, Washington, DC 20052, USA
| | - Maili Liu
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences, Wuhan, Hubei 430071, China.
| | - Zhou Gong
- State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences, Wuhan, Hubei 430071, China.
| | - Yunjie Zhao
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China.
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44
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Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. Comparative Analysis of Conformational Dynamics and Systematic Characterization of Cryptic Pockets in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 Spike Complexes with the ACE2 Host Receptor: Confluence of Binding and Structural Plasticity in Mediating Networks of Conserved Allosteric Sites. Viruses 2023; 15:2073. [PMID: 37896850 PMCID: PMC10612107 DOI: 10.3390/v15102073] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/04/2023] [Accepted: 10/06/2023] [Indexed: 10/29/2023] Open
Abstract
In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full-length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results are significant for understanding the functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.
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Affiliation(s)
- Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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45
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Verkhivker G, Alshahrani M, Gupta G. Exploring Conformational Landscapes and Cryptic Binding Pockets in Distinct Functional States of the SARS-CoV-2 Omicron BA.1 and BA.2 Trimers: Mutation-Induced Modulation of Protein Dynamics and Network-Guided Prediction of Variant-Specific Allosteric Binding Sites. Viruses 2023; 15:2009. [PMID: 37896786 PMCID: PMC10610873 DOI: 10.3390/v15102009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/23/2023] [Accepted: 09/26/2023] [Indexed: 10/29/2023] Open
Abstract
A significant body of experimental structures of SARS-CoV-2 spike trimers for the BA.1 and BA.2 variants revealed a considerable plasticity of the spike protein and the emergence of druggable binding pockets. Understanding the interplay of conformational dynamics changes induced by the Omicron variants and the identification of cryptic dynamic binding pockets in the S protein is of paramount importance as exploring broad-spectrum antiviral agents to combat the emerging variants is imperative. In the current study, we explore conformational landscapes and characterize the universe of binding pockets in multiple open and closed functional spike states of the BA.1 and BA.2 Omicron variants. By using a combination of atomistic simulations, a dynamics network analysis, and an allostery-guided network screening of binding pockets in the conformational ensembles of the BA.1 and BA.2 spike conformations, we identified all experimentally known allosteric sites and discovered significant variant-specific differences in the distribution of binding sites in the BA.1 and BA.2 trimers. This study provided a structural characterization of the predicted cryptic pockets and captured the experimentally known allosteric sites, revealing the critical role of conformational plasticity in modulating the distribution and cross-talk between functional binding sites. We found that mutational and dynamic changes in the BA.1 variant can induce the remodeling and stabilization of a known druggable pocket in the N-terminal domain, while this pocket is drastically altered and may no longer be available for ligand binding in the BA.2 variant. Our results predicted the experimentally known allosteric site in the receptor-binding domain that remains stable and ranks as the most favorable site in the conformational ensembles of the BA.2 variant but could become fragmented and less probable in BA.1 conformations. We also uncovered several cryptic pockets formed at the inter-domain and inter-protomer interface, including functional regions of the S2 subunit and stem helix region, which are consistent with the known role of pocket residues in modulating conformational transitions and antibody recognition. The results of this study are particularly significant for understanding the dynamic and network features of the universe of available binding pockets in spike proteins, as well as the effects of the Omicron-variant-specific modulation of preferential druggable pockets. The exploration of predicted druggable sites can present a new and previously underappreciated opportunity for therapeutic interventions for Omicron variants through the conformation-selective and variant-specific targeting of functional sites involved in allosteric changes.
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Affiliation(s)
- Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
| | - Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
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46
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Martins C, Diharce J, Nadaradjane AA, de Brevern AG. Evaluation of the Potential Impact of In Silico Humanization on V HH Dynamics. Int J Mol Sci 2023; 24:14586. [PMID: 37834033 PMCID: PMC10572902 DOI: 10.3390/ijms241914586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/14/2023] [Accepted: 09/16/2023] [Indexed: 10/15/2023] Open
Abstract
Camelids have the peculiarity of having classical antibodies composed of heavy and light chains as well as single-chain antibodies. They have lost their light chains and one heavy-chain domain. This evolutionary feature means that their terminal heavy-chain domain, VH, called VHH here, has no partner and forms an independent domain. The VHH is small and easy to express alone; it retains thermodynamic and interaction properties. Consequently, VHHs have garnered significant interest from both biotechnological and pharmaceutical perspectives. However, due to their origin in camelids, they cannot be used directly on humans. A humanization step is needed before a possible use. However, changes, even in the constant parts of the antibodies, can lead to a loss of quality. A dedicated tool, Llamanade, has recently been made available to the scientific community. In a previous paper, we already showed the different types of VHH dynamics. Here, we have selected a representative VHH and tested two humanization hypotheses to accurately assess the potential impact of these changes. This example shows that despite the non-negligible change (1/10th of residues) brought about by humanization, the effect is not drastic, and the humanized VHH retains conformational properties quite similar to those of the camelid VHH.
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Affiliation(s)
- Carla Martins
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB, F-75014 Paris, France; (C.M.); (J.D.)
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB, F-97715 Saint Denis Messag, France
| | - Julien Diharce
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB, F-75014 Paris, France; (C.M.); (J.D.)
| | - Aravindan Arun Nadaradjane
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB, F-97715 Saint Denis Messag, France
| | - Alexandre G. de Brevern
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB, F-75014 Paris, France; (C.M.); (J.D.)
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB, F-97715 Saint Denis Messag, France
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47
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Vishwanath S, Carnell GW, Ferrari M, Asbach B, Billmeier M, George C, Sans MS, Nadesalingam A, Huang CQ, Paloniemi M, Stewart H, Chan A, Wells DA, Neckermann P, Peterhoff D, Einhauser S, Cantoni D, Neto MM, Jordan I, Sandig V, Tonks P, Temperton N, Frost S, Sohr K, Ballesteros MTL, Arbabi F, Geiger J, Dohmen C, Plank C, Kinsley R, Wagner R, Heeney JL. A computationally designed antigen eliciting broad humoral responses against SARS-CoV-2 and related sarbecoviruses. Nat Biomed Eng 2023:10.1038/s41551-023-01094-2. [PMID: 37749309 DOI: 10.1038/s41551-023-01094-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 08/23/2023] [Indexed: 09/27/2023]
Abstract
The threat of spillovers of coronaviruses associated with the severe acute respiratory syndrome (SARS) from animals to humans necessitates vaccines that offer broader protection from sarbecoviruses. By leveraging a viral-genome-informed computational method for selecting immune-optimized and structurally engineered antigens, here we show that a single antigen based on the receptor binding domain of the spike protein of sarbecoviruses elicits broad humoral responses against SARS-CoV-1, SARS-CoV-2, WIV16 and RaTG13 in mice, rabbits and guinea pigs. When administered as a DNA immunogen or by a vector based on a modified vaccinia virus Ankara, the optimized antigen induced vaccine protection from the Delta variant of SARS-CoV-2 in mice genetically engineered to express angiotensin-converting enzyme 2 and primed by a viral-vector vaccine (AZD1222) against SARS-CoV-2. A vaccine formulation incorporating mRNA coding for the optimized antigen further validated its broad immunogenicity. Vaccines that elicit broad immune responses across subgroups of coronaviruses may counteract the threat of zoonotic spillovers of betacoronaviruses.
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Affiliation(s)
- Sneha Vishwanath
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - George William Carnell
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | | | - Benedikt Asbach
- Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany
| | - Martina Billmeier
- Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany
| | - Charlotte George
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Maria Suau Sans
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Angalee Nadesalingam
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Chloe Qingzhou Huang
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Minna Paloniemi
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Hazel Stewart
- Department of Pathology, University of Cambridge, Cambridge, UK
| | - Andrew Chan
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | | | - Patrick Neckermann
- Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany
| | - David Peterhoff
- Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Regensburg, Germany
| | - Sebastian Einhauser
- Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany
| | - Diego Cantoni
- Viral Pseudotype Unit, Medway School of Pharmacy, The Universities of Kent and Greenwich at Medway, Chatham, UK
| | - Martin Mayora Neto
- Viral Pseudotype Unit, Medway School of Pharmacy, The Universities of Kent and Greenwich at Medway, Chatham, UK
| | | | | | - Paul Tonks
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Nigel Temperton
- Viral Pseudotype Unit, Medway School of Pharmacy, The Universities of Kent and Greenwich at Medway, Chatham, UK
| | - Simon Frost
- DIOSynVax Ltd, University of Cambridge, Cambridge, UK
- London School of Hygiene and Tropical Medicine, London, UK
- Microsoft Health Futures, Redmond, WA, USA
| | | | | | | | | | | | | | - Rebecca Kinsley
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
- DIOSynVax Ltd, University of Cambridge, Cambridge, UK
| | - Ralf Wagner
- DIOSynVax Ltd, University of Cambridge, Cambridge, UK
- Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Regensburg, Germany
| | - Jonathan Luke Heeney
- Lab of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK.
- DIOSynVax Ltd, University of Cambridge, Cambridge, UK.
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48
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Gaudreault F, Corbeil CR, Sulea T. Enhanced antibody-antigen structure prediction from molecular docking using AlphaFold2. Sci Rep 2023; 13:15107. [PMID: 37704686 PMCID: PMC10499836 DOI: 10.1038/s41598-023-42090-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 09/05/2023] [Indexed: 09/15/2023] Open
Abstract
Predicting the structure of antibody-antigen complexes has tremendous value in biomedical research but unfortunately suffers from a poor performance in real-life applications. AlphaFold2 (AF2) has provided renewed hope for improvements in the field of protein-protein docking but has shown limited success against antibody-antigen complexes due to the lack of co-evolutionary constraints. In this study, we used physics-based protein docking methods for building decoy sets consisting of low-energy docking solutions that were either geometrically close to the native structure (positives) or not (negatives). The docking models were then fed into AF2 to assess their confidence with a novel composite score based on normalized pLDDT and pTMscore metrics after AF2 structural refinement. We show benefits of the AF2 composite score for rescoring docking poses both in terms of (1) classification of positives/negatives and of (2) success rates with particular emphasis on early enrichment. Docking models of at least medium quality present in the decoy set, but not necessarily highly ranked by docking methods, benefitted most from AF2 rescoring by experiencing large advances towards the top of the reranked list of models. These improvements, obtained without any calibration or novel methodologies, led to a notable level of performance in antibody-antigen unbound docking that was never achieved previously.
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Affiliation(s)
- Francis Gaudreault
- Human Health Therapeutics Research Centre, National Research Council Canada, 6100 Royalmount Avenue, Montreal, QC, H4P 2R2, Canada
| | - Christopher R Corbeil
- Human Health Therapeutics Research Centre, National Research Council Canada, 6100 Royalmount Avenue, Montreal, QC, H4P 2R2, Canada
| | - Traian Sulea
- Human Health Therapeutics Research Centre, National Research Council Canada, 6100 Royalmount Avenue, Montreal, QC, H4P 2R2, Canada.
- Institute of Parasitology, McGill University, 21111 Lakeshore Road, Sainte-Anne-de-Bellevue, QC, H9X 3V9, Canada.
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49
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Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. Examining Functional Linkages Between Conformational Dynamics, Protein Stability and Evolution of Cryptic Binding Pockets in the SARS-CoV-2 Omicron Spike Complexes with the ACE2 Host Receptor: Recombinant Omicron Variants Mediate Variability of Conserved Allosteric Sites and Binding Epitopes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.557205. [PMID: 37745525 PMCID: PMC10515794 DOI: 10.1101/2023.09.11.557205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results of are significant for understanding functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.
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50
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Shao Q, Jiang Y, Yang ZJ. EnzyHTP Computational Directed Evolution with Adaptive Resource Allocation. J Chem Inf Model 2023; 63:5650-5659. [PMID: 37611241 PMCID: PMC11211066 DOI: 10.1021/acs.jcim.3c00618] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
Directed evolution facilitates enzyme engineering via iterative rounds of mutagenesis. Despite the wide applications of high-throughput screening, building "smart libraries" to effectively identify beneficial variants remains a major challenge in the community. Here, we developed a new computational directed evolution protocol based on EnzyHTP, a software that we have previously reported to automate enzyme modeling. To enhance the throughput efficiency, we implemented an adaptive resource allocation strategy that dynamically allocates different types of computing resources (e.g., GPU/CPU) based on the specific need of an enzyme modeling subtask in the workflow. We implemented the strategy as a Python library and tested the library using fluoroacetate dehalogenase as a model enzyme. The results show that compared to fixed resource allocation where both CPU and GPU are on-call for use during the entire workflow, applying adaptive resource allocation can save 87% CPU hours and 14% GPU hours. Furthermore, we constructed a computational directed evolution protocol under the framework of adaptive resource allocation. The workflow was tested against two rounds of mutational screening in the directed evolution experiments of Kemp eliminase (KE07) with a total of 184 mutants. Using folding stability and electrostatic stabilization energy as computational readout, we identified all four experimentally observed target variants. Enabled by the workflow, the entire computation task (i.e., 18.4 μs MD and 18,400 QM single-point calculations) completes in 3 days of wall-clock time using ∼30 GPUs and ∼1000 CPUs.
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Affiliation(s)
- Qianzhen Shao
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Yaoyukun Jiang
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Zhongyue J. Yang
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
- Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37235, United States
- Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37235, United States
- Data Science Institute, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, Tennessee 37235, United States
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