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Samanta R, Harmalkar A, Prathima P, Gray JJ. Advancing membrane-associated protein docking with improved sampling and scoring in Rosetta. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.09.602802. [PMID: 39026849 PMCID: PMC11257521 DOI: 10.1101/2024.07.09.602802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
The oligomerization of protein macromolecules on cell membranes plays a fundamental role in regulating cellular function. From modulating signal transduction to directing immune response, membrane proteins (MPs) play a crucial role in biological processes and are often the target of many pharmaceutical drugs. Despite their biological relevance, the challenges in experimental determination have hampered the structural availability of membrane proteins and their complexes. Computational docking provides a promising alternative to model membrane protein complex structures. Here, we present Rosetta-MPDock, a flexible transmembrane (TM) protein docking protocol that captures binding-induced conformational changes. Rosetta-MPDock samples large conformational ensembles of flexible monomers and docks them within an implicit membrane environment. We benchmarked this method on 29 TM-protein complexes of variable backbone flexibility. These complexes are classified based on the root-mean-square deviation between the unbound and bound states (RMSDUB) as: rigid (RMSDUB <1.2 Å), moderately-flexible (RMSDUB ∈ [1.2, 2.2) Å), and flexible targets (RMSDUB > 2.2 Å). In a local docking scenario, i.e. with membrane protein partners starting ≈10 Å apart embedded in the membrane in their unbound conformations, Rosetta-MPDock successfully predicts the correct interface (success defined as achieving 3 near-native structures in the 5 top-ranked models) for 67% moderately flexible targets and 60% of the highly flexible targets, a substantial improvement from the existing membrane protein docking methods. Further, by integrating AlphaFold2-multimer for structure determination and using Rosetta-MPDock for docking and refinement, we demonstrate improved success rates over the benchmark targets from 64% to 73%. Rosetta-MPDock advances the capabilities for membrane protein complex structure prediction and modeling to tackle key biological questions and elucidate functional mechanisms in the membrane environment. The benchmark set and the code is available for public use at github.com/Graylab/MPDock.
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Affiliation(s)
- Rituparna Samanta
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
- Current affiliation: University of South Florida, Tampa, FL, USA
| | - Ameya Harmalkar
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
- Current affiliation: Generate Biomedicines Inc., Cambridge, MA, USA
| | - Priyamvada Prathima
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
- Current affiliation: Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Jeffrey J. Gray
- Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA
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2
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Duarte T, Omage FB, Rieder GS, Rocha JBT, Dalla Corte CL. Investigating SARS-CoV-2 virus-host interactions and mRNA expression: Insights using three models of D. melanogaster. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167324. [PMID: 38925484 DOI: 10.1016/j.bbadis.2024.167324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 04/22/2024] [Accepted: 06/19/2024] [Indexed: 06/28/2024]
Abstract
Responsible for COVID-19, SARS-CoV-2 is a coronavirus in which contagious variants continue to appear. Therefore, some population groups have demonstrated greater susceptibility to contagion and disease progression. For these reasons, several researchers have been studying the SARS-CoV-2/human interactome to understand the pathophysiology of COVID-19 and develop new pharmacological strategies. D. melanogaster is a versatile animal model with approximately 90 % human protein orthology related to SARS-CoV-2/human interactome and is widely used in metabolic studies. In this context, our work assessed the potential interaction between human proteins (ZNF10, NUP88, BCL2L1, UBC9, and RBX1) and their orthologous proteins in D. melanogaster (gl, Nup88, Buffy, ubc9, and Rbx1a) with proteins from SARS-CoV-2 (nsp3, nsp9, E, ORF7a, N, and ORF10) using computational approaches. Our results demonstrated that all the proteins have the potential to interact, and we compared the binding sites between humans and fruit flies. The stability and consistency in the structure of the gl_nsp3 complex, specifically, could be crucial for its specific biological functions. Lastly, to enhance the understanding of the influence of host factors on coronavirus infection, we also analyse the mRNA expression of the five genes (mbo, gl, lwr, Buffy, and Roc1a) responsible for encoding the fruit fly proteins. Briefly, we demonstrated that those genes were differentially regulated according to diets, sex, and age. Two groups showed higher positive gene regulation than others: females in the HSD group and males in the aging group, which could imply a higher virus-host susceptibility. Overall, while preliminary, our work contributes to the understanding of host defense mechanisms and potentially identifies candidate proteins and genes for in vivo viral studies against SARS-CoV-2.
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Affiliation(s)
- Tâmie Duarte
- Laboratory of Experimental Biochemistry and Toxicology, Department of Biochemistry and Molecular Biology, Center of Natural and Exact Sciences, Federal University of Santa Maria, 1000 Roraima Avenue, Santa Maria, RS 97105-900, Brazil; Department of Biochemistry and Molecular Biology, Federal University of Santa Maria, 1000 Roraima Avenue, Santa Maria, RS 97105-900, Brazil
| | - Folorunsho Bright Omage
- Biological Chemistry Laboratory, Department of Organic Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), Campinas, SP, Brazil; Computational Biology Research Group, Embrapa Agricultural Informatics, Campinas, SP, Brazil
| | - Guilherme Schmitt Rieder
- Department of Biochemistry and Molecular Biology, Federal University of Santa Maria, 1000 Roraima Avenue, Santa Maria, RS 97105-900, Brazil
| | - João B T Rocha
- Department of Biochemistry and Molecular Biology, Federal University of Santa Maria, 1000 Roraima Avenue, Santa Maria, RS 97105-900, Brazil
| | - Cristiane Lenz Dalla Corte
- Laboratory of Experimental Biochemistry and Toxicology, Department of Biochemistry and Molecular Biology, Center of Natural and Exact Sciences, Federal University of Santa Maria, 1000 Roraima Avenue, Santa Maria, RS 97105-900, Brazil; Department of Biochemistry and Molecular Biology, Federal University of Santa Maria, 1000 Roraima Avenue, Santa Maria, RS 97105-900, Brazil.
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3
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Honorato RV, Trellet ME, Jiménez-García B, Schaarschmidt JJ, Giulini M, Reys V, Koukos PI, Rodrigues JPGLM, Karaca E, van Zundert GCP, Roel-Touris J, van Noort CW, Jandová Z, Melquiond ASJ, Bonvin AMJJ. The HADDOCK2.4 web server for integrative modeling of biomolecular complexes. Nat Protoc 2024:10.1038/s41596-024-01011-0. [PMID: 38886530 DOI: 10.1038/s41596-024-01011-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 04/11/2024] [Indexed: 06/20/2024]
Abstract
Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server's various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody-antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types.
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Affiliation(s)
- Rodrigo V Honorato
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Mikael E Trellet
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Fluigent, Le Kremlin-Bicêtre, France
| | - Brian Jiménez-García
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Zymvol Biomodeling SL, Barcelona, Spain
| | - Jörg J Schaarschmidt
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Karlsruhe Institute of Technology (KIT), Institute of Nanotechnology, Eggenstein-Leopoldshafen, Germany
| | - Marco Giulini
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Victor Reys
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Panagiotis I Koukos
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - João P G L M Rodrigues
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Schrödinger Inc., New York, NY, USA
| | - Ezgi Karaca
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Izmir Biomedicine and Genome Center, Izimir, Turkey
| | - Gydo C P van Zundert
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Schrödinger Inc., New York, NY, USA
| | - Jorge Roel-Touris
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Protein Design and Modeling Lab, Department of Structural Biology, Molecular Biology Institute of Barcelona (IBMB-CSIC), Barcelona, Spain
| | - Charlotte W van Noort
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Zuzana Jandová
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Boehringer Ingelheim International GmbH, Vienna, Austria
| | - Adrien S J Melquiond
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
- Utrecht Medical Center, Utrecht, the Netherlands
| | - Alexandre M J J Bonvin
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands.
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4
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Jiang X, Yang L, Chen G, Feng X, Liu Y, Gao Q, Mai M, Chen CYC, Ye S, Yang Z. Discovery of Kinetin in inhibiting colorectal cancer progression via enhancing PSMB1-mediated RAB34 degradation. Cancer Lett 2024; 584:216600. [PMID: 38159835 DOI: 10.1016/j.canlet.2023.216600] [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: 09/19/2023] [Revised: 11/29/2023] [Accepted: 12/12/2023] [Indexed: 01/03/2024]
Abstract
Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Understanding the underlying mechanism driving CRC progression and identifying potential therapeutic drug targets are of utmost urgency. We previously utilized LC-MS-based proteomic profiling to identify proteins associated with postoperative progression in stage II/III CRC. Here, we revealed that proteasome subunit beta type-1 (PSMB1) is an independent predictor for postoperative progression in stage II/III CRC. Mechanistically, PSMB1 binds directly to onco-protein RAB34 and promotes its proteasome-dependent degradation, potentially leading to the inactivation of the MEK/ERK signaling pathway and inhibition of CRC progression. To further identify potential anticancer drugs, we screened a library of 2509 FDA-approved drugs using computer-aided drug design (CADD) and identified Kinetin as a potentiating agent for PSMB1. Functional assays confirmed that Kinetin enhanced the interaction between PSMB1 and RAB34, hence facilitated the degradation of RAB34 protein and decreased the MEK/ERK phosphorylation. Kinetin suppresses CRC progression in patient-derived xenograft (PDX) and liver metastasis models. Conclusively, our study identifies PSMB1 as a potential biomarker and therapeutic target for CRC, and Kinetin as an anticancer drug by enhancing proteasome-dependent onco-protein degradation.
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Affiliation(s)
- Xuefei Jiang
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Lanlan Yang
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Guanxing Chen
- Artificial Intelligence Medical Research Center, School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
| | - Xingzhi Feng
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Yiting Liu
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Qianling Gao
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Mingru Mai
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Calvin Yu-Chian Chen
- Department of AI for Science, School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, Guangdong, 518055, China
| | - Shubiao Ye
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, 510655, China
| | - Zihuan Yang
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China; Department of Clinical Laboratory, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510655, China.
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5
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Zerze GH. Optimizing the Martini 3 Force Field Reveals the Effects of the Intricate Balance between Protein-Water Interaction Strength and Salt Concentration on Biomolecular Condensate Formation. J Chem Theory Comput 2024; 20:1646-1655. [PMID: 37043540 DOI: 10.1021/acs.jctc.2c01273] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Condensation/dissolution has become a widely acknowledged biological macromolecular assembly phenomenon in subcellular compartmentalization. The MARTINI force field offers a coarse-grained protein model with a resolution that preserves molecular details with an explicit (CG) solvent. Despite its relatively higher resolution, it can still achieve condensate formation in a reasonable computing time with explicit solvent and ionic species. Therefore, it is highly desirable to tune this force field to be able to reproduce the experimentally observed properties of the condensate formation. In this work, we studied the condensate formation of the low-sequence complexity domain of fused in sarcoma protein using a MARTINI 3 force field by systematically modifying (increasing) the protein-water interaction strength and varying the salt concentration. We found that the condensate formation is sensitive both to the protein-water interaction strength and the presence of salt. While the unmodified MARTINI force field yields a complete collapse of proteins into one dense phase (i.e., no dilute phase), we reported a range of modified protein-water interaction strength that is capable of capturing the experimentally found transfer free energy between dense and dilute phases. We also found that the condensates lose their spherical shape upon the addition of salt, especially when the protein-water interactions are weak. Interchain amino acid contact map analysis showed one explanation for this observation: the protein-protein contact fraction reduces as salt is added to systems (when the protein-water interactions are weak), consistent with electrostatic screening effects. This reduction might be responsible for the condensates becoming nonspherical upon the addition of salt by reducing the need for minimizing the interfacial area. However, as the protein-water interactions become stronger to the extent that makes the transfer free energy agree well with experimentally observed transfer free energy, we found an increase in the protein-protein contact fraction upon the addition of salt, consistent with the salting-out effects. Therefore, we concluded that there is an intricate balance between screening effects and salting-out effects upon the addition of salt and this balance is highly sensitive to the strength of protein-water interactions.
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Affiliation(s)
- Gül H Zerze
- William A. Brookshire Department of Chemical and Biomolecular Engineering, University of Houston, Houston, Texas 77204, United States
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6
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Wolpe AG, Luse MA, Baryiames C, Schug WJ, Wolpe JB, Johnstone SR, Dunaway LS, Juśkiewicz ZJ, Loeb SA, Askew Page HR, Chen YL, Sabapathy V, Pavelec CM, Wakefield B, Cifuentes-Pagano E, Artamonov MV, Somlyo AV, Straub AC, Sharma R, Beier F, Barrett EJ, Leitinger N, Pagano PJ, Sonkusare SK, Redemann S, Columbus L, Penuela S, Isakson BE. Pannexin-3 stabilizes the transcription factor Bcl6 in a channel-independent manner to protect against vascular oxidative stress. Sci Signal 2024; 17:eadg2622. [PMID: 38289985 DOI: 10.1126/scisignal.adg2622] [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: 12/12/2022] [Accepted: 01/05/2024] [Indexed: 02/01/2024]
Abstract
Targeted degradation regulates the activity of the transcriptional repressor Bcl6 and its ability to suppress oxidative stress and inflammation. Here, we report that abundance of endothelial Bcl6 is determined by its interaction with Golgi-localized pannexin 3 (Panx3) and that Bcl6 transcriptional activity protects against vascular oxidative stress. Consistent with data from obese, hypertensive humans, mice with an endothelial cell-specific deficiency in Panx3 had spontaneous systemic hypertension without obvious changes in channel function, as assessed by Ca2+ handling, ATP amounts, or Golgi luminal pH. Panx3 bound to Bcl6, and its absence reduced Bcl6 protein abundance, suggesting that the interaction with Panx3 stabilized Bcl6 by preventing its degradation. Panx3 deficiency was associated with increased expression of the gene encoding the H2O2-producing enzyme Nox4, which is normally repressed by Bcl6, resulting in H2O2-induced oxidative damage in the vasculature. Catalase rescued impaired vasodilation in mice lacking endothelial Panx3. Administration of a newly developed peptide to inhibit the Panx3-Bcl6 interaction recapitulated the increase in Nox4 expression and in blood pressure seen in mice with endothelial Panx3 deficiency. Panx3-Bcl6-Nox4 dysregulation occurred in obesity-related hypertension, but not when hypertension was induced in the absence of obesity. Our findings provide insight into a channel-independent role of Panx3 wherein its interaction with Bcl6 determines vascular oxidative state, particularly under the adverse conditions of obesity.
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Affiliation(s)
- Abigail G Wolpe
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Melissa A Luse
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | | | - Wyatt J Schug
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | - Jacob B Wolpe
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Scott R Johnstone
- Fralin Biomedical Research Institute at Virginia Tech Carilion School of Medicine, Center for Vascular and Heart Research, Roanoke, VA 24016, USA
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24060, USA
| | - Luke S Dunaway
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Zuzanna J Juśkiewicz
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Skylar A Loeb
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | - Henry R Askew Page
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Yen-Lin Chen
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Vikram Sabapathy
- Center for Immunity, Inflammation, and Regenerative Medicine (CIIR), University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Caitlin M Pavelec
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Brent Wakefield
- Department of Anatomy and Cell Biology, University of Western Ontario, London, ON N6A 5C1, Canada
| | - Eugenia Cifuentes-Pagano
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Mykhaylo V Artamonov
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Avril V Somlyo
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Adam C Straub
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Rahul Sharma
- Center for Immunity, Inflammation, and Regenerative Medicine (CIIR), University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Frank Beier
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON N6A 5C1, Canada
| | - Eugene J Barrett
- Department of Medicine, Division of Endocrinology and Metabolism, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | - Norbert Leitinger
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
| | - Patrick J Pagano
- Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Swapnil K Sonkusare
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | - Stefanie Redemann
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
- Center for Membrane and Cell Physiology, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
| | - Linda Columbus
- Department of Chemistry, University of Virginia, Charlottesville, VA 22904, USA
| | - Silvia Penuela
- Department of Anatomy and Cell Biology, University of Western Ontario, London, ON N6A 5C1, Canada
- Department of Oncology (Division of Experimental Oncology), Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON N6A 5W9, Canada
| | - Brant E Isakson
- Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22908, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia School of Medicine, Charlottesville, VA 22903, USA
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7
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Pereira GP, Jiménez-García B, Pellarin R, Launay G, Wu S, Martin J, Souza PCT. Rational Prediction of PROTAC-Compatible Protein-Protein Interfaces by Molecular Docking. J Chem Inf Model 2023; 63:6823-6833. [PMID: 37877240 DOI: 10.1021/acs.jcim.3c01154] [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: 10/26/2023]
Abstract
Proteolysis targeting chimeras (PROTACs) are heterobifunctional ligands that mediate the interaction between a protein target and an E3 ligase, resulting in a ternary complex, whose interaction with the ubiquitination machinery leads to target degradation. This technology is emerging as an exciting new avenue for therapeutic development, with several PROTACs currently undergoing clinical trials targeting cancer. Here, we describe a general and computationally efficient methodology combining restraint-based docking, energy-based rescoring, and a filter based on the minimal solvent-accessible surface distance to produce PROTAC-compatible PPIs suitable for when there is no a priori known PROTAC ligand. In a benchmark employing a manually curated data set of 13 ternary complex crystals, we achieved an accuracy of 92% when starting from bound structures and 77% when starting from unbound structures, respectively. Our method only requires that the ligand-bound structures of the monomeric forms of the E3 ligase and target proteins be given to run, making it general, accurate, and highly efficient, with the ability to impact early-stage PROTAC-based drug design campaigns where no structural information about the ternary complex structure is available.
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Affiliation(s)
- Gilberto P Pereira
- Molecular Microbiology and Structural Biochemistry, CNRS UMR 5086 and Université Claude Bernard Lyon 1, 7 Passage du Vercors, 69007 Lyon, France
- Laboratory of Biology and Modeling of the Cell, École Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5239 and Inserm U1293, 46 Allée d'Italie, 69007 Lyon, France
| | | | - Riccardo Pellarin
- Molecular Microbiology and Structural Biochemistry, CNRS UMR 5086 and Université Claude Bernard Lyon 1, 7 Passage du Vercors, 69007 Lyon, France
- Laboratory of Biology and Modeling of the Cell, École Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5239 and Inserm U1293, 46 Allée d'Italie, 69007 Lyon, France
| | - Guillaume Launay
- Molecular Microbiology and Structural Biochemistry, CNRS UMR 5086 and Université Claude Bernard Lyon 1, 7 Passage du Vercors, 69007 Lyon, France
- Laboratory of Biology and Modeling of the Cell, École Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5239 and Inserm U1293, 46 Allée d'Italie, 69007 Lyon, France
| | - Sangwook Wu
- PharmCADD, Busan 48792, Republic of Korea
- Department of Physics, Pukyong National University, Busan 48513, Republic of Korea
| | - Juliette Martin
- Molecular Microbiology and Structural Biochemistry, CNRS UMR 5086 and Université Claude Bernard Lyon 1, 7 Passage du Vercors, 69007 Lyon, France
- Laboratory of Biology and Modeling of the Cell, École Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5239 and Inserm U1293, 46 Allée d'Italie, 69007 Lyon, France
| | - Paulo C T Souza
- Molecular Microbiology and Structural Biochemistry, CNRS UMR 5086 and Université Claude Bernard Lyon 1, 7 Passage du Vercors, 69007 Lyon, France
- Laboratory of Biology and Modeling of the Cell, École Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, CNRS UMR 5239 and Inserm U1293, 46 Allée d'Italie, 69007 Lyon, France
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8
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Jiménez-García B, Roel-Touris J, Barradas-Bautista D. The LightDock Server: Artificial Intelligence-powered modeling of macromolecular interactions. Nucleic Acids Res 2023:7151343. [PMID: 37140054 DOI: 10.1093/nar/gkad327] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/05/2023] [Accepted: 04/17/2023] [Indexed: 05/05/2023] Open
Abstract
Computational docking is an instrumental method of the structural biology toolbox. Specifically, integrative modeling software, such as LightDock, arise as complementary and synergetic methods to experimental structural biology techniques. Ubiquitousness and accessibility are fundamental features to promote ease of use and to improve user experience. With this goal in mind, we have developed the LightDock Server, a web server for the integrative modeling of macromolecular interactions, along with several dedicated usage modes. The server builds upon the LightDock macromolecular docking framework, which has proved useful for modeling medium-to-high flexible complexes, antibody-antigen interactions, or membrane-associated protein assemblies. We believe that this free-to-use resource will be a valuable addition to the structural biology community and can be accessed online at: https://server.lightdock.org/.
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Affiliation(s)
| | - Jorge Roel-Touris
- Protein Design and Modeling Lab, Department of Structural Biology, Molecular Biology Institute of Barcelona (IBMB-CSIC), Baldiri Reixac 15, 08028Barcelona, Spain
| | - Didier Barradas-Bautista
- Kaust Visualization Lab, Core lab Division, King Abdullah University of Science and Technology (KAUST), 23955-6900, Thuwal, Saudi Arabia
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9
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Overduin M, Kervin TA, Klarenbach Z, Adra TRC, Bhat RK. Comprehensive classification of proteins based on structures that engage lipids by COMPOSEL. Biophys Chem 2023; 295:106971. [PMID: 36801589 DOI: 10.1016/j.bpc.2023.106971] [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: 12/24/2022] [Accepted: 02/05/2023] [Indexed: 02/11/2023]
Abstract
Structures can now be predicted for any protein using programs like AlphaFold and Rosetta, which rely on a foundation of experimentally determined structures of architecturally diverse proteins. The accuracy of such artificial intelligence and machine learning (AI/ML) approaches benefits from the specification of restraints which assist in navigating the universe of folds to converge on models most representative of a given protein's physiological structure. This is especially pertinent for membrane proteins, with structures and functions that depend on their presence in lipid bilayers. Structures of proteins in their membrane environments could conceivably be predicted from AI/ML approaches with user-specificized parameters that describe each element of the architecture of a membrane protein accompanied by its lipid environment. We propose the Classification Of Membrane Proteins based On Structures Engaging Lipids (COMPOSEL), which builds on existing nomenclature types for monotopic, bitopic, polytopic and peripheral membrane proteins as well as lipids. Functional and regulatory elements are also defined in the scripts, as shown with membrane fusing synaptotagmins, multidomain PDZD8 and Protrudin proteins that recognize phosphoinositide (PI) lipids, the intrinsically disordered MARCKS protein, caveolins, the β barrel assembly machine (BAM), an adhesion G-protein coupled receptor (aGPCR) and two lipid modifying enzymes - diacylglycerol kinase DGKε and fatty aldehyde dehydrogenase FALDH. This demonstrates how COMPOSEL communicates lipid interactivity as well as signaling mechanisms and binding of metabolites, drug molecules, polypeptides or nucleic acids to describe the operations of any protein. Moreover COMPOSEL can be scaled to express how genomes encode membrane structures and how our organs are infiltrated by pathogens such as SARS-CoV-2.
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Affiliation(s)
- Michael Overduin
- Department of Biochemistry, University of Alberta, Edmonton, AB, Canada.
| | - Troy A Kervin
- Department of Biochemistry, University of Alberta, Edmonton, AB, Canada
| | | | - Trixie Rae C Adra
- Department of Biochemistry, University of Alberta, Edmonton, AB, Canada
| | - Rakesh K Bhat
- Department of Biochemistry, University of Alberta, Edmonton, AB, Canada
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10
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Wang Y, Zhang Z, Liu X, Chen N, Zhao Y, Wang C. Molecular dynamic simulations identifying the mechanism of holoenzyme formation by O-GlcNAc transferase and active p38α. Phys Chem Chem Phys 2023; 25:8090-8102. [PMID: 36876722 DOI: 10.1039/d2cp05968a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
O-N-Acetylglucosamine transferase (OGT) can catalyze the O-GlcNAc modification of thousands of proteins. The holoenzyme formation of OGT and adaptor protein is the precondition for further recognition and glycosylation of the target protein, while the corresponding mechanism is still open. Here, static and dynamic schemes based on statistics can successfully screen the feasible identifying, approaching, and binding mechanism of OGT and its typical adaptor protein p38α. The most favorable interface, energy contribution of hotspots, and conformational changes of fragments were discovered. The hydrogen bond interactions were verified as the main driving force for the whole process. The distinct characteristic of active and inactive p38α is explored and demonstrates that the phosphorylated tyrosine and threonine will form strong ion-pair interactions with Lys714, playing a key role in the dynamic identification stage. Multiple method combinations from different points of view may be helpful for exploring other systems of the protein-protein interactions.
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Affiliation(s)
- Yu Wang
- The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, 475004, China.
| | - Zhiyang Zhang
- The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, 475004, China.
| | - Xiaoyuan Liu
- The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, 475004, China.
| | - Nianhang Chen
- School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China
| | - Yuan Zhao
- The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, 475004, China.
| | - Chaojie Wang
- The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, 475004, China.
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11
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Chitosan and HPMCAS double-coating as protective systems for alginate microparticles loaded with Ctx(Ile 21)-Ha antimicrobial peptide to prevent intestinal infections. Biomaterials 2023; 293:121978. [PMID: 36580719 DOI: 10.1016/j.biomaterials.2022.121978] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 11/03/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
The incorrect use of conventional drugs for both prevention and control of intestinal infections has contributed to a significant spread of bacterial resistance. In this way, studies that promote their replacement are a priority. In the last decade, the use of antimicrobial peptides (AMP), especially Ctx(Ile21)-Ha AMP, has gained strength, demonstrating efficient antimicrobial activity (AA) against pathogens, including multidrug-resistant bacteria. However, gastrointestinal degradation does not allow its direct oral application. In this research, double-coating systems using alginate microparticles loaded with Ctx(Ile21)-Ha peptide were designed, and in vitro release assays simulating the gastrointestinal tract were evaluated. Also, the AA against Salmonella spp. and Escherichia coli was examined. The results showed the physicochemical stability of Ctx(Ile21)-Ha peptide in the system and its potent antimicrobial activity. In addition, the combination of HPMCAS and chitosan as a gastric protection system can be promising for peptide carriers or other low pH-sensitive molecules, adequately released in the intestine. In conclusion, the coated systems employed in this study can improve the formulation of new foods or biopharmaceutical products for specific application against intestinal pathogens in animal production or, possibly, in the near future, in human health.
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12
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Pedersen GB, Blaschek L, Frandsen KEH, Noack LC, Persson S. Cellulose synthesis in land plants. MOLECULAR PLANT 2023; 16:206-231. [PMID: 36564945 DOI: 10.1016/j.molp.2022.12.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 06/17/2023]
Abstract
All plant cells are surrounded by a cell wall that provides cohesion, protection, and a means of directional growth to plants. Cellulose microfibrils contribute the main biomechanical scaffold for most of these walls. The biosynthesis of cellulose, which typically is the most prominent constituent of the cell wall and therefore Earth's most abundant biopolymer, is finely attuned to developmental and environmental cues. Our understanding of the machinery that catalyzes and regulates cellulose biosynthesis has substantially improved due to recent technological advances in, for example, structural biology and microscopy. Here, we provide a comprehensive overview of the structure, function, and regulation of the cellulose synthesis machinery and its regulatory interactors. We aim to highlight important knowledge gaps in the field, and outline emerging approaches that promise a means to close those gaps.
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Affiliation(s)
- Gustav B Pedersen
- Copenhagen Plant Science Center (CPSC), Department of Plant & Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark
| | - Leonard Blaschek
- Copenhagen Plant Science Center (CPSC), Department of Plant & Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark
| | - Kristian E H Frandsen
- Copenhagen Plant Science Center (CPSC), Department of Plant & Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark
| | - Lise C Noack
- Copenhagen Plant Science Center (CPSC), Department of Plant & Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark
| | - Staffan Persson
- Copenhagen Plant Science Center (CPSC), Department of Plant & Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871, Frederiksberg C, Denmark; Joint International Research Laboratory of Metabolic & Developmental Sciences, State Key Laboratory of Hybrid Rice, SJTU-University of Adelaide Joint Centre for Agriculture and Health, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
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13
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Souza FR, Moura PG, Costa RKM, Silva RS, Pimentel AS. Absolute binding free energies of mucroporin and its analog mucroporin-M1 with the heptad repeat 1 domain and RNA-dependent RNA polymerase of SARS-CoV-2. J Biomol Struct Dyn 2022:1-12. [PMID: 35993479 DOI: 10.1080/07391102.2022.2114014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The peptide Mucroporin and its analog Mucroporin-M1 were studied using the molecular docking and molecular dynamics simulation of their complexation with two protein targets, the Heptad Repeat 1 (HR1) domain and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. The molecular docking of the peptide-protein complexes was performed using the glowworm swarm optimization algorithm. The lowest energy poses were submitted to molecular dynamics simulation. Then, the binding free energies of Mucroporin and its analog Mucroporin-M1 with these two protein targets were calculated using the Multistate Bennett Acceptance Ratio (MBAR) method. It was verified that the peptides/HR1 domain complex showed stability in the interaction site determined by molecular docking. It was also found that Mucroporin-M1 has a much higher affinity than Mucroporin to the HR1 protein target. The peptides showed similar stability and affinity at the NTP binding site in the RdRp protein. Additional experimental studies are needed to confirm the antiviral activity of Mucroporin-M1 and a possible mechanism of action against SARS-CoV-2. However, here we indicate that Mucroporin-M1 may have potential antiviral activity against the HR1 domain with the possibility for further peptide optimization.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Felipe Rodrigues Souza
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Paloma Guimarães Moura
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | | | - Rudielson Santos Silva
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - André Silva Pimentel
- Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
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14
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The Nucleoside Adenosine Inhibits Intracellular Microvascular α2C-Adrenoceptor Surface Trafficking. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2022.133637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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15
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Wang X, Sun Y, Wang Q, Liu F, Yang W, Sui X, Yang J, Zhang M, Wang S, Xiao Z, Luo Y, Wang Y, Zhu T. Potential Common Mechanisms of Cytotoxicity Induced by Amide Herbicides via TRPA1 Channel Activation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19137985. [PMID: 35805655 PMCID: PMC9266004 DOI: 10.3390/ijerph19137985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 11/16/2022]
Abstract
The “Multi-Threat Medical Countermeasure (MTMC)” strategy was proposed to develop a single drug with therapeutic efficacy against multiple pathologies or broad-spectrum protection against various toxins with common biochemical signals, molecular mediators, or cellular processes. This study demonstrated that cytotoxicity, expression of transient receptor potential cation channel subfamily A member 1 (TRPA1) mRNA, and intracellular calcium influx were increased in A549 cells exposed to amide herbicides (AHs), in which the order of cytotoxicity was metolachlor > acetochlor > propisochlor > alachlor > butachlor > propanil > pretilachlor, based on IC50 values of 430, 524, 564, 565, 619, 831, and 2333 μM, respectively. Inhibition/knockout of TRPA1 efficiently protected against cytotoxicity, decreased TRPA1 mRNA expression, and reduced calcium influx. The results suggested that the TRPA1 channel could be a key common target for AHs poisoning. The order of TRPA1 affinity for AHs was propanil > pretilachlor > metolachlor > (propiso/ala/aceto/butachlor), based on KD values of 16.2, 309, and 364 μM, respectively. The common molecular mechanisms of TRPA1-AHs interactions were clarified, including toxicity-effector groups (benzene ring, nitrogen/oxygen-containing functional groups, halogen) and residues involved in interactions (Lys787, Leu982). This work provides valuable information for the development of TRPA1 as a promising therapeutic target for broad-spectrum antitoxins.
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Affiliation(s)
- Xiaoning Wang
- Institute of Process Equipment and Environmental Engineering, School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China;
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Yangyang Sun
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Qian Wang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Fengying Liu
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Weijie Yang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Xin Sui
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Jun Yang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Minmin Zhang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Shuai Wang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Zhenyu Xiao
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Yuan Luo
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
- Correspondence: (Y.L.); (T.Z.); Tel.: +86-10-66930602 (Y.L.); +86-13940281581 (T.Z.)
| | - Yongan Wang
- State Key Laboratory of Toxicology and Medical Countermeasures, Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China; (Y.S.); (Q.W.); (F.L.); (W.Y.); (X.S.); (J.Y.); (M.Z.); (S.W.); (Z.X.); (Y.W.)
| | - Tong Zhu
- Institute of Process Equipment and Environmental Engineering, School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China;
- Correspondence: (Y.L.); (T.Z.); Tel.: +86-10-66930602 (Y.L.); +86-13940281581 (T.Z.)
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16
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Marrink SJ, Monticelli L, Melo MN, Alessandri R, Tieleman DP, Souza PCT. Two decades of Martini: Better beads, broader scope. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1620] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Siewert J. Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute & Zernike Institute for Advanced Materials University of Groningen Groningen The Netherlands
| | - Luca Monticelli
- Molecular Microbiology and Structural Biochemistry (MMSB ‐ UMR 5086) CNRS & University of Lyon Lyon France
| | - Manuel N. Melo
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa Oeiras Portugal
| | - Riccardo Alessandri
- Pritzker School of Molecular Engineering University of Chicago Chicago Illinois USA
| | - D. Peter Tieleman
- Centre for Molecular Simulation and Department of Biological Sciences University of Calgary Alberta Canada
| | - Paulo C. T. Souza
- Molecular Microbiology and Structural Biochemistry (MMSB ‐ UMR 5086) CNRS & University of Lyon Lyon France
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17
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Neijenhuis T, van Keulen SC, Bonvin AMJJ. Interface refinement of low- to medium-resolution Cryo-EM complexes using HADDOCK2.4. Structure 2022; 30:476-484.e3. [PMID: 35216656 DOI: 10.1016/j.str.2022.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 11/25/2021] [Accepted: 01/28/2022] [Indexed: 10/19/2022]
Abstract
A wide range of cellular processes requires the formation of multimeric protein complexes. The rise of cryo-electron microscopy (cryo-EM) has enabled the structural characterization of these protein assemblies. The density maps produced can, however, still suffer from limited resolution, impeding the process of resolving structures at atomic resolution. In order to solve this issue, monomers can be fitted into low- to medium-resolution maps. Unfortunately, the models produced frequently contain atomic clashes at the protein-protein interfaces (PPIs), as intermolecular interactions are typically not considered during monomer fitting. Here, we present a refinement approach based on HADDOCK2.4 to remove intermolecular clashes and optimize PPIs. A dataset of 14 cryo-EM complexes was used to test eight protocols. The best-performing protocol, consisting of a semi-flexible simulated annealing refinement with centroid restraints on the monomers, was able to decrease intermolecular atomic clashes by 98% without significantly deteriorating the quality of the cryo-EM density fit.
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Affiliation(s)
- Tim Neijenhuis
- Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Science for Life, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH, Utrecht, the Netherlands
| | - Siri C van Keulen
- Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Science for Life, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH, Utrecht, the Netherlands
| | - Alexandre M J J Bonvin
- Computational Structural Biology Group, Bijvoet Center for Biomolecular Research, Science for Life, Faculty of Science - Chemistry, Utrecht University, Padualaan 8, 3584 CH, Utrecht, the Netherlands.
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18
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Dependence of Protein Structure on Environment: FOD Model Applied to Membrane Proteins. MEMBRANES 2021; 12:membranes12010050. [PMID: 35054576 PMCID: PMC8778870 DOI: 10.3390/membranes12010050] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/13/2021] [Accepted: 12/28/2021] [Indexed: 11/17/2022]
Abstract
The natural environment of proteins is the polar aquatic environment and the hydrophobic (amphipathic) environment of the membrane. The fuzzy oil drop model (FOD) used to characterize water-soluble proteins, as well as its modified version FOD-M, enables a mathematical description of the presence and influence of diverse environments on protein structure. The present work characterized the structures of membrane proteins, including those that act as channels, and a water-soluble protein for contrast. The purpose of the analysis was to verify the possibility that an external force field can be used in the simulation of the protein-folding process, taking into account the diverse nature of the environment that guarantees a structure showing biological activity.
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19
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Abstract
The biological significance of proteins attracted the scientific community in exploring their characteristics. The studies shed light on the interaction patterns and functions of proteins in a living body. Due to their practical difficulties, reliable experimental techniques pave the way for introducing computational methods in the interaction prediction. Automated methods reduced the difficulties but could not yet replace experimental studies as the field is still evolving. Interaction prediction problem being critical needs highly accurate results, but none of the existing methods could offer reliable performance that can parallel with experimental results yet. This article aims to assess the existing computational docking algorithms, their challenges, and future scope. Blind docking techniques are quite helpful when no information other than the individual structures are available. As more and more complex structures are being added to different databases, information-driven approaches can be a good alternative. Artificial intelligence, ruling over the major fields, is expected to take over this domain very shortly.
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20
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Fu T, Li F, Zhang Y, Yin J, Qiu W, Li X, Liu X, Xin W, Wang C, Yu L, Gao J, Zheng Q, Zeng S, Zhu F. VARIDT 2.0: structural variability of drug transporter. Nucleic Acids Res 2021; 50:D1417-D1431. [PMID: 34747471 PMCID: PMC8728241 DOI: 10.1093/nar/gkab1013] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/08/2021] [Accepted: 11/04/2021] [Indexed: 12/20/2022] Open
Abstract
The structural variability data of drug transporter (DT) are key for research on precision medicine and rational drug use. However, these valuable data are not sufficiently covered by the available databases. In this study, a major update of VARIDT (a database previously constructed to provide DTs' variability data) was thus described. First, the experimentally resolved structures of all DTs reported in the original VARIDT were discovered from PubMed and Protein Data Bank. Second, the structural variability data of each DT were collected by literature review, which included: (a) mutation-induced spatial variations in folded state, (b) difference among DT structures of human and model organisms, (c) outward/inward-facing DT conformations and (d) xenobiotics-driven alterations in the 3D complexes. Third, for those DTs without experimentally resolved structural variabilities, homology modeling was further applied as well-established protocol to enrich such valuable data. As a result, 145 mutation-induced spatial variations of 42 DTs, 1622 inter-species structures originating from 292 DTs, 118 outward/inward-facing conformations belonging to 59 DTs, and 822 xenobiotics-regulated structures in complex with 57 DTs were updated to VARIDT (https://idrblab.org/varidt/ and http://varidt.idrblab.net/). All in all, the newly collected structural variabilities will be indispensable for explaining drug sensitivity/selectivity, bridging preclinical research with clinical trial, revealing the mechanism underlying drug-drug interaction, and so on.
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Affiliation(s)
- Tingting Fu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.,Institute of Theoretical Chemistry, College of Chemistry, Jilin University, Changchun 130023, China
| | - Fengcheng Li
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yang Zhang
- Department of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China
| | - Jiayi Yin
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Wenqi Qiu
- Department of Surgery, HKU-SZH & Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Xuedong Li
- Department of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China
| | - Xingang Liu
- Department of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China
| | - Wenwen Xin
- Department of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China
| | - Chengzhao Wang
- Department of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China
| | - Lushan Yu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jianqing Gao
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.,Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
| | - Qingchuan Zheng
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, Changchun 130023, China
| | - Su Zeng
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.,Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
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21
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van Noort CW, Honorato RV, Bonvin AMJJ. Information-driven modeling of biomolecular complexes. Curr Opin Struct Biol 2021; 70:70-77. [PMID: 34139639 DOI: 10.1016/j.sbi.2021.05.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 05/10/2021] [Indexed: 11/15/2022]
Abstract
Proteins play crucial roles in every cellular process by interacting with each other, nucleic acids, metabolites, and other molecules. The resulting assemblies can be very large and intricate and pose challenges to experimental methods. In the current era of integrative modeling, it is often only by a combination of various experimental techniques and computations that three-dimensional models of those molecular machines can be obtained. Among the various computational approaches available, molecular docking is often the method of choice when it comes to predicting three-dimensional structures of complexes. Docking can generate particularly accurate models when taking into account the available information on the complex of interest. We review here the use of experimental and bioinformatics data in protein-protein docking, describing recent software developments and highlighting applications for the modeling of antibody-antigen complexes and membrane protein complexes, and the use of evolutionary and shape information.
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Affiliation(s)
- Charlotte W van Noort
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Department of Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584CH, Netherlands
| | - Rodrigo V Honorato
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Department of Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584CH, Netherlands
| | - Alexandre M J J Bonvin
- Bijvoet Centre for Biomolecular Research, Faculty of Science, Department of Chemistry, Utrecht University, Padualaan 8, Utrecht, 3584CH, Netherlands.
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22
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Prévost C, Sacquin-Mora S. Moving pictures: Reassessing docking experiments with a dynamic view of protein interfaces. Proteins 2021; 89:1315-1323. [PMID: 34038009 DOI: 10.1002/prot.26152] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/22/2021] [Accepted: 05/19/2021] [Indexed: 11/06/2022]
Abstract
The modeling of protein assemblies at the atomic level remains a central issue in structural biology, as protein interactions play a key role in numerous cellular processes. This problem is traditionally addressed using docking tools, where the quality of the models is based on their similarity to a single reference experimental structure. However, using a static reference does not take into account the dynamic quality of the protein interface. Here, we used all-atom classical Molecular Dynamics simulations to investigate the stability of the reference interface for three complexes that previously served as targets in the CAPRI competition. For each one of these targets, we also ran MD simulations for ten models that are distributed over the High, Medium and Acceptable accuracy categories. To assess the quality of these models from a dynamic perspective, we set up new criteria which take into account the stability of the reference experimental protein interface. We show that, when the protein interfaces are allowed to evolve along time, the original ranking based on the static CAPRI criteria no longer holds as over 50% of the docking models undergo a category change (which can be either toward a better or a lower accuracy group) when reassessing their quality using dynamic information.
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Affiliation(s)
- Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, Paris, France.,Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, Paris, France.,Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France
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23
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Abstract
Transmembrane proteins act as an intermediary for a broad range of biological process. Making up 20% to 30% of the proteome, their ubiquitous nature has resulted in them comprising 50% of all targets in drug design. Despite their importance, they make up only 4% of all structures in the PDB database, primarily owing to difficulties associated with isolating and characterizing them. Membrane protein docking algorithms could help to fill this knowledge gap, yet only few exist. Moreover, these existing methods achieve success rates lower than the current best soluble proteins docking software. We present and test a pipeline using our software, JabberDock, to dock membrane proteins. JabberDock docks shapes representative of membrane protein structure and dynamics in their biphasic environment. We verify JabberDock's ability to yield accurate predictions by applying it to a benchmark of 20 transmembrane dimers, returning a success rate of 75.0%. This makes our software very competitive among available membrane protein-protein docking tools.
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Affiliation(s)
- Lucas S P Rudden
- Department of Physics, Durham University, South Road, DH1 3LE Durham, United Kingdom
| | - Matteo T Degiacomi
- Department of Physics, Durham University, South Road, DH1 3LE Durham, United Kingdom
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