1
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Marques S, Kouba P, Legrand A, Sedlar J, Disson L, Planas-Iglesias J, Sanusi Z, Kunka A, Damborsky J, Pajdla T, Prokop Z, Mazurenko S, Sivic J, Bednar D. CoVAMPnet: Comparative Markov State Analysis for Studying Effects of Drug Candidates on Disordered Biomolecules. JACS AU 2024; 4:2228-2245. [PMID: 38938816 PMCID: PMC11200249 DOI: 10.1021/jacsau.4c00182] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/24/2024] [Accepted: 05/13/2024] [Indexed: 06/29/2024]
Abstract
Computational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here, we developed a comparative Markov state analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered Aβ42 peptide involved in Alzheimer's disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of Aβ42 by interacting nonspecifically with charged residues. SPA impacted Aβ42 more than TMP, protecting α-helices and suppressing the formation of aggregation-prone β-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on Aβ42 and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target biomolecules other than Aβ peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules.
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Affiliation(s)
- Sérgio
M. Marques
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Petr Kouba
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- Czech
Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, Dejvice, Praha 6 160 00, Czech Republic
- Faculty
of Electrical Engineering, Czech Technical
University in Prague, Technicka 2, Dejvice, Praha 6 166 27, Czech Republic
| | - Anthony Legrand
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Jiri Sedlar
- Czech
Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, Dejvice, Praha 6 160 00, Czech Republic
| | - Lucas Disson
- Czech
Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, Dejvice, Praha 6 160 00, Czech Republic
| | - Joan Planas-Iglesias
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Zainab Sanusi
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Antonin Kunka
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Jiri Damborsky
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Tomas Pajdla
- Czech
Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, Dejvice, Praha 6 160 00, Czech Republic
| | - Zbynek Prokop
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Stanislav Mazurenko
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
| | - Josef Sivic
- Czech
Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Jugoslavskych partyzanu 1580/3, Dejvice, Praha 6 160 00, Czech Republic
| | - David Bednar
- Loschmidt
Laboratories, Department of Experimental Biology and RECETOX, Faculty
of Science, Masaryk University, Kamenice 5, Brno 625 00, Czech Republic
- International
Clinical Research Center, St. Anne’s
University Hospital Brno, Pekarska 53, Brno 656
91, Czech Republic
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2
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Kombo DC, LaMarche MJ, Konkankit CC, Rackovsky S. Application of artificial intelligence and machine learning techniques to the analysis of dynamic protein sequences. Proteins 2024. [PMID: 38808365 DOI: 10.1002/prot.26704] [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: 02/23/2024] [Revised: 05/07/2024] [Accepted: 05/13/2024] [Indexed: 05/30/2024]
Abstract
We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed previously, which encodes the intrinsic dynamic properties of the naturally occurring amino acids. We Fourier analyze the resulting sequences. It is demonstrated that classification models built using several different supervised learning methods are able to successfully distinguish folded from intrinsically disordered proteins from sequence alone. It is further shown that the most important sequence property for this discrimination is the sequence mobility, which is the sequence averaged value of the residue-specific average alpha carbon B factor. This is in agreement with previous work, in which we have demonstrated the central role played by the sequence mobility in protein dynamic bioinformatics and biophysics. This finding opens a path to the application of dynamic bioinformatics, in combination with machine learning algorithms, to a range of significant biomedical problems.
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Affiliation(s)
- David C Kombo
- Department of Medicinal Chemistry, Integrated Drug Discovery, Cambridge, Massachusetts, USA
| | - Matthew J LaMarche
- Department of Medicinal Chemistry, Integrated Drug Discovery, Cambridge, Massachusetts, USA
| | - Chilaluck C Konkankit
- Department of Chemistry and Chemical Biology, Baker Laboratory, Cornell University, Ithaca, New York, USA
| | - S Rackovsky
- Department of Chemistry and Chemical Biology, Baker Laboratory, Cornell University, Ithaca, New York, USA
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3
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Brooks CL, MacKerell AD, Post CB, Nilsson L. Biomolecular dynamics in the 21st century. Biochim Biophys Acta Gen Subj 2024; 1868:130534. [PMID: 38065235 PMCID: PMC10842176 DOI: 10.1016/j.bbagen.2023.130534] [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: 09/26/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 01/03/2024]
Abstract
The relevance of motions in biological macromolecules has been clear since the early structural analyses of proteins by X-ray crystallography. Computer simulations have been applied to provide a deeper understanding of the dynamics of biological macromolecules since 1976, and are now a standard tool in many labs working on the structure and function of biomolecules. In this mini-review we highlight some areas of current interest and active development for simulations, in particular all-atom molecular dynamics simulations.
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Affiliation(s)
- Charles L Brooks
- University of Michigan, Department of Chemistry, Ann Arbor, MI 48109, USA.
| | | | - Carol B Post
- Purdue University, Department of Medicinal Chemistry and Molecular Pharmacology, West Lafayette, IN 47907-2091, USA.
| | - Lennart Nilsson
- Karolinska Institutet, Department of Biosciences and Nutrition, SE-14183 Huddinge, Sweden.
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4
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Saikia B, Baruah A. Recent advances in de novo computational design and redesign of intrinsically disordered proteins and intrinsically disordered protein regions. Arch Biochem Biophys 2024; 752:109857. [PMID: 38097100 DOI: 10.1016/j.abb.2023.109857] [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: 10/06/2023] [Revised: 12/10/2023] [Accepted: 12/10/2023] [Indexed: 12/17/2023]
Abstract
In the early 2000s, the concept of "unstructured biology" has emerged to be an important field in protein science by generating various new research directions. Many novel strategies and methods have been developed that are focused on effectively identifying/predicting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs), identifying their potential functions, disorder based drug design etc. Due to the range of functions of IDPs/IDPRs and their involvement in various debilitating diseases they are of contemporary interest to the scientific community. Recent researches are focused on designing/redesigning specific IDPs/IDPRs de novo. These de novo design/redesigns of IDPs/IDPRs are carried out by altering compositional biases and specific sequence patterning parameters. The main focus of these researches is to influence specific molecular functions, phase behavior, cellular phenotypes etc. In this review, we first provide the differences of natively folded and natively unfolded or IDPs with respect to their potential energy landscapes. Here, we provide current understandings on the different computational design strategies and methods that have been utilized in de novo design and redesigns of IDPs and IDPRs. Finally, we conclude the review by discussing the challenges that have been faced during the computational design/design attempts of IDPs/IDPRs.
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Affiliation(s)
- Bondeepa Saikia
- Department of Chemistry, Dibrugarh University, Dibrugarh, 786004, Assam, India
| | - Anupaul Baruah
- Department of Chemistry, Dibrugarh University, Dibrugarh, 786004, Assam, India.
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5
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Zhang P, Yang W. Toward a general neural network force field for protein simulations: Refining the intramolecular interaction in protein. J Chem Phys 2023; 159:024118. [PMID: 37431910 PMCID: PMC10481389 DOI: 10.1063/5.0142280] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 06/22/2023] [Indexed: 07/12/2023] Open
Abstract
Molecular dynamics (MD) is an extremely powerful, highly effective, and widely used approach to understanding the nature of chemical processes in atomic details for proteins. The accuracy of results from MD simulations is highly dependent on force fields. Currently, molecular mechanical (MM) force fields are mainly utilized in MD simulations because of their low computational cost. Quantum mechanical (QM) calculation has high accuracy, but it is exceedingly time consuming for protein simulations. Machine learning (ML) provides the capability for generating accurate potential at the QM level without increasing much computational effort for specific systems that can be studied at the QM level. However, the construction of general machine learned force fields, needed for broad applications and large and complex systems, is still challenging. Here, general and transferable neural network (NN) force fields based on CHARMM force fields, named CHARMM-NN, are constructed for proteins by training NN models on 27 fragments partitioned from the residue-based systematic molecular fragmentation (rSMF) method. The NN for each fragment is based on atom types and uses new input features that are similar to MM inputs, including bonds, angles, dihedrals, and non-bonded terms, which enhance the compatibility of CHARMM-NN to MM MD and enable the implementation of CHARMM-NN force fields in different MD programs. While the main part of the energy of the protein is based on rSMF and NN, the nonbonded interactions between the fragments and with water are taken from the CHARMM force field through mechanical embedding. The validations of the method for dipeptides on geometric data, relative potential energies, and structural reorganization energies demonstrate that the CHARMM-NN local minima on the potential energy surface are very accurate approximations to QM, showing the success of CHARMM-NN for bonded interactions. However, the MD simulations on peptides and proteins indicate that more accurate methods to represent protein-water interactions in fragments and non-bonded interactions between fragments should be considered in the future improvement of CHARMM-NN, which can increase the accuracy of approximation beyond the current mechanical embedding QM/MM level.
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Affiliation(s)
- Pan Zhang
- Department of Chemistry, Duke University, Durham, North Carolina 27708, USA
| | - Weitao Yang
- Department of Chemistry, Duke University, Durham, North Carolina 27708, USA
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6
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Coppa C, Bazzoli A, Barkhordari M, Contini A. Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models. J Chem Inf Model 2023; 63:3030-3042. [PMID: 37163419 DOI: 10.1021/acs.jcim.3c00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Accelerated molecular dynamics (aMD) protocols were assessed on predicting the secondary structure of eight peptides, of which two are helical, three are β-hairpins, and three are disordered. Protocols consisted of combinations of three force fields (ff99SB, ff14SB, ff19SB) and two explicit solvation models (TIP3P and OPC), and were evaluated in two independent aMD simulations, one starting from an extended conformation, the other starting from a misfolded conformation. The results of these analyses indicate that all three combinations performed well on helical peptides. As for β-hairpins, ff19SB performed well with both solvation methods, with a slight preference for the TIP3P solvation model, even though performance was dependent on both peptide sequence and initial conformation. The ff19SB/OPC combination had the best performance on intrinsically disordered peptides. In general, ff14SB/TIP3P suffered the strongest helical bias.
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Affiliation(s)
- Crescenzo Coppa
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Andrea Bazzoli
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Maral Barkhordari
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Alessandro Contini
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
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7
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Li T, Hendrix E, He Y. Simple and Effective Conformational Sampling Strategy for Intrinsically Disordered Proteins Using the UNRES Web Server. J Phys Chem B 2023; 127:2177-2186. [PMID: 36827446 DOI: 10.1021/acs.jpcb.2c08945] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Intrinsically disordered proteins (IDPs) contain more charged amino acids than folded proteins, resulting in a lack of hydrophobic core(s) and a tendency to adopt rapidly interconverting structures rather than well-defined structures. The structural heterogeneity of IDPs, encoded by the amino acid sequence, is closely related to their unique roles in biological pathways, which require them to interact with different binding partners. Recently, Robustelli and co-workers have demonstrated that a balanced all-atom force field can be used to sample heterogeneous structures of disordered proteins ( Proc. Natl. Acad. Sci. U.S.A. 2018, 115, E4758-E4766). However, such a solution requires extensive computational resources, such as Anton supercomputers. Here, we propose a simple and effective solution to sample the conformational space of IDPs using a publicly available web server, namely, the UNited-RESidue (UNRES) web server. Our proposed solution requires no investment in computational resources and no prior knowledge of UNRES. UNRES Replica Exchange Molecular Dynamics (REMD) simulations were carried out on a set of eight disordered proteins at temperatures spanning from 270 to 430 K. Utilizing the latest UNRES force field designed for structured proteins, with proper selections of temperatures, we were able to produce comparable results to all-atom force fields as reported in work done by Robustelli and co-workers. In addition, NMR observables and the radius of gyration calculated from UNRES ensembles were directly compared with the experimental data to further evaluate the accuracy of the UNRES model at all temperatures. Our results suggest that carrying out the UNRES simulations at optimal temperatures using the UNRES web server can be a good alternative to sample heterogeneous structures of IDPs.
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Affiliation(s)
- Tongtong Li
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Emily Hendrix
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Yi He
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States.,Translational Informatics Division, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87131, United States
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8
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Conformational ensemble of the NSP1 CTD in SARS-CoV-2: Perspectives from the free energy landscape. Biophys J 2023:S0006-3495(23)00102-9. [PMID: 36793215 PMCID: PMC9928668 DOI: 10.1016/j.bpj.2023.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/13/2023] [Accepted: 02/10/2023] [Indexed: 02/17/2023] Open
Abstract
The nonstructural protein-1 (NSP1) of the severe acute respiratory syndrome-associated coronavirus 2 plays a crucial role in the translational shutdown and immune evasion inside host cells. Despite its known intrinsic disorder, the C-terminal domain (CTD) of NSP1 has been reported to form a double α-helical structure and block the 40S-ribosomal channel for mRNA translation. Experimental studies indicate that NSP1 CTD functions independently from the globular N-terminal region separated with a long linker domain, underscoring the necessity of exploring the standalone conformational ensemble. In this contribution, we utilize exascale computing resources to yield unbiased molecular dynamics simulation of NSP1 CTD in all-atom resolution starting from multiple initial seed structures. A data-driven approach elicits collective variables (CVs) that are significantly superior to conventional descriptors in capturing the conformational heterogeneity. The free energy landscape as a function of the CV space is estimated using the modified expectation maximized molecular dynamics. Originally developed by us for small peptides, here, we establish the efficacy of expectation maximized molecular dynamics in conjunction with data-driven CV space for a more complex and relevant biomolecular system. The results reveal the existence of two disordered metastable populations in the free energy landscape that are separated from the conformation resembling ribosomal subunit bound state by high kinetic barriers. Chemical shift correlation and secondary structure analysis capture significant differences among key structures of the ensemble. Altogether, these insights can underpin drug development studies and mutational experiments that help induce population shifts to alter translational blocking and understand its molecular basis in further detail.
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9
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Sun B, Kekenes-Huskey PM. Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling. Q Rev Biophys 2023; 56:e2. [PMID: 36628457 PMCID: PMC11070111 DOI: 10.1017/s003358352300001x] [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] [Indexed: 01/12/2023]
Abstract
The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.
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Affiliation(s)
- Bin Sun
- Research Center for Pharmacoinformatics (The State-Province Key Laboratories of Biomedicine-Pharmaceutics of China), Department of Medicinal Chemistry and Natural Medicine Chemistry, College of Pharmacy, Harbin Medical University, Harbin 150081, China
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10
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Bhattacharya S, Zhang M, Hu W, Qi T, Heisterkamp N. Targeting disordered-structured domain interactions in Galectin-3 based on NMR and enhanced MD. Biophys J 2022; 121:4342-4357. [PMID: 36209362 PMCID: PMC9703043 DOI: 10.1016/j.bpj.2022.10.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 05/18/2022] [Accepted: 10/06/2022] [Indexed: 12/14/2022] Open
Abstract
Intrinsically disordered regions (IDRs) are common and important functional domains in many proteins. However, IDRs are difficult to target for drug development due to the lack of defined structures that would facilitate the identification of possible drug-binding pockets. Galectin-3 is a carbohydrate-binding protein of which overexpression has been implicated in a wide variety of disorders, including cancer and inflammation. Apart from its carbohydrate-recognition/binding domain (CRD), Galectin-3 also contains a functionally important disordered N-terminal domain (NTD) that contacts the C-terminal domain (CTD) and could be a target for drug development. To overcome challenges involved in inhibitor design due to lack of structure and the highly dynamic nature of the NTD, we used a protocol combining nuclear magnetic resonance data from recombinant Galectin-3 with accelerated molecular dynamics (MD) simulations. This approach identified a pocket in the CTD with which the NTD makes frequent contact. In accordance with this model, mutation of residues L131 and L203 in this pocket caused loss of Galectin-3 agglutination ability, signifying the functional relevance of the cavity. In silico screening was used to design candidate inhibitory peptides targeting the newly discovered cavity, and experimental testing of only three of these yielded one peptide that inhibits the agglutination promoted by wild-type Galectin-3. NMR experiments further confirmed that this peptide indeed binds to a cavity in the CTD, not within the actual CRD. Our results show that it is possible to apply a combination of MD simulations and NMR experiments to precisely predict the binding interface of a disordered domain with a structured domain, and furthermore use this predicted interface for designing inhibitors. This procedure can potentially be extended to many other targets in which similar IDR interactions play a vital functional role.
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Affiliation(s)
- Supriyo Bhattacharya
- Integrative Genomics Core, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Mingfeng Zhang
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, California
| | - Weidong Hu
- Department of Molecular Imaging and Therapy, Beckman Research Institute of City of Hope, Duarte, California
| | - Tong Qi
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, California
| | - Nora Heisterkamp
- Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, California.
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11
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Chaves-Arquero B, Martínez-Lumbreras S, Sibille N, Camero S, Bernadó P, Jiménez MÁ, Zorrilla S, Pérez-Cañadillas JM. eIF4G1 N-terminal intrinsically disordered domain is a multi-docking station for RNA, Pab1, Pub1, and self-assembly. Front Mol Biosci 2022; 9:986121. [PMID: 36213119 PMCID: PMC9537944 DOI: 10.3389/fmolb.2022.986121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Yeast eIF4G1 interacts with RNA binding proteins (RBPs) like Pab1 and Pub1 affecting its function in translation initiation and stress granules formation. We present an NMR and SAXS study of the N-terminal intrinsically disordered region of eIF4G1 (residues 1-249) and its interactions with Pub1, Pab1 and RNA. The conformational ensemble of eIF4G11-249 shows an α-helix within the BOX3 conserved element and a dynamic network of fuzzy π-π and π-cation interactions involving arginine and aromatic residues. The Pab1 RRM2 domain interacts with eIF4G1 BOX3, the canonical interaction site, but also with BOX2, a conserved element of unknown function to date. The RNA1 region interacts with RNA through a new RNA interaction motif and with the Pub1 RRM3 domain. This later also interacts with eIF4G1 BOX1 modulating its intrinsic self-assembly properties. The description of the biomolecular interactions involving eIF4G1 to the residue detail increases our knowledge about biological processes involving this key translation initiation factor.
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Affiliation(s)
- Belén Chaves-Arquero
- Department of Biological Physical Chemistry, Institute of Physical-Chemistry “Rocasolano”, CSIC, Madrid, Spain
| | - Santiago Martínez-Lumbreras
- Department of Biological Physical Chemistry, Institute of Physical-Chemistry “Rocasolano”, CSIC, Madrid, Spain
| | - Nathalie Sibille
- Centre de Biochimie Structurale (CBS), CNRS, INSERM, Univ. Montpellier, Montpellier, France
| | - Sergio Camero
- Department of Biological Physical Chemistry, Institute of Physical-Chemistry “Rocasolano”, CSIC, Madrid, Spain
| | - Pau Bernadó
- Centre de Biochimie Structurale (CBS), CNRS, INSERM, Univ. Montpellier, Montpellier, France
| | - M. Ángeles Jiménez
- Department of Biological Physical Chemistry, Institute of Physical-Chemistry “Rocasolano”, CSIC, Madrid, Spain
| | - Silvia Zorrilla
- Department of Cellular and Molecular Biology, Biological Research Center, CSIC, Madrid, Spain
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12
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Teixeira JMC, Liu ZH, Namini A, Li J, Vernon RM, Krzeminski M, Shamandy AA, Zhang O, Haghighatlari M, Yu L, Head-Gordon T, Forman-Kay JD. IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States. J Phys Chem A 2022; 126:5985-6003. [PMID: 36030416 PMCID: PMC9465686 DOI: 10.1021/acs.jpca.2c03726] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
The power of structural information for informing biological
mechanisms
is clear for stable folded macromolecules, but similar structure–function
insight is more difficult to obtain for highly dynamic systems such
as intrinsically disordered proteins (IDPs) which must be described
as structural ensembles. Here, we present IDPConformerGenerator, a
flexible, modular open-source software platform for generating large
and diverse ensembles of disordered protein states that builds conformers
that obey geometric, steric, and other physical restraints on the
input sequence. IDPConformerGenerator samples backbone phi (φ),
psi (ψ), and omega (ω) torsion angles of relevant sequence
fragments from loops and secondary structure elements extracted from
folded protein structures in the RCSB Protein Data Bank and builds
side chains from robust Monte Carlo algorithms using expanded rotamer
libraries. IDPConformerGenerator has many user-defined options enabling
variable fractional sampling of secondary structures, supports Bayesian
models for assessing the agreement of IDP ensembles for consistency
with experimental data, and introduces a machine learning approach
to transform between internal and Cartesian coordinates with reduced
error. IDPConformerGenerator will facilitate the characterization
of disordered proteins to ultimately provide structural insights into
these states that have key biological functions.
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Affiliation(s)
- João M. C. Teixeira
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Zi Hao Liu
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Ashley Namini
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | | | - Robert M. Vernon
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Mickaël Krzeminski
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Alaa A. Shamandy
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario M5S 2E4, Canada
| | | | | | | | | | - Julie D. Forman-Kay
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
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13
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Veríssimo GC, Serafim MSM, Kronenberger T, Ferreira RS, Honorio KM, Maltarollo VG. Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern. Expert Opin Drug Discov 2022; 17:929-947. [PMID: 35983695 DOI: 10.1080/17460441.2022.2114451] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed. AREAS COVERED One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future. EXPERT OPINION Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.
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Affiliation(s)
- Gabriel C Veríssimo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Mateus Sá M Serafim
- Departamento de Microbiologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Thales Kronenberger
- Department of Medical Oncology and Pneumology, Internal Medicine VIII, University Hospital of Tübingen, Tübingen, Germany.,School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Rafaela S Ferreira
- Departamento de Bioquímica e Imunologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
| | - Kathia M Honorio
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo (USP), São Paulo, Brazil.,Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (UFABC), Santo André, Brazil
| | - Vinícius G Maltarollo
- Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
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14
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Hsueh SCC, Aina A, Roman AY, Cashman NR, Peng X, Plotkin SS. Optimizing Epitope Conformational Ensembles Using α-Synuclein Cyclic Peptide "Glycindel" Scaffolds: A Customized Immunogen Method for Generating Oligomer-Selective Antibodies for Parkinson's Disease. ACS Chem Neurosci 2022; 13:2261-2280. [PMID: 35840132 DOI: 10.1021/acschemneuro.1c00567] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Effectively presenting epitopes on immunogens, in order to raise conformationally selective antibodies through active immunization, is a central problem in treating protein misfolding diseases, particularly neurodegenerative diseases such as Alzheimer's disease or Parkinson's disease. We seek to selectively target conformations enriched in toxic, oligomeric propagating species while sparing the healthy forms of the protein that are often more abundant. To this end, we computationally modeled scaffolded epitopes in cyclic peptides by inserting/deleting a variable number of flanking glycines ("glycindels") to best mimic a misfolding-specific conformation of an epitope of α-synuclein enriched in the oligomer ensemble, as characterized by a region most readily disordered and solvent-exposed in a stressed, partially denatured protofibril. We screen and rank the cyclic peptide scaffolds of α-synuclein in silico based on their ensemble overlap properties with the fibril, oligomer-model and isolated monomer ensembles. We present experimental data of seeded aggregation that support nucleation rates consistent with computationally predicted cyclic peptide conformational similarity. We also introduce a method for screening against structured off-pathway targets in the human proteome by selecting scaffolds with minimal conformational similarity between their epitope and the same solvent-exposed primary sequence in structured human proteins. Different cyclic peptide scaffolds with variable numbers of glycines are predicted computationally to have markedly different conformational ensembles. Ensemble comparison and overlap were quantified by the Jensen-Shannon divergence and a new measure introduced here, the embedding depth, which determines the extent to which a given ensemble is subsumed by another ensemble and which may be a more useful measure in developing immunogens that confer conformational selectivity to an antibody.
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Affiliation(s)
- Shawn C C Hsueh
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Adekunle Aina
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Andrei Yu Roman
- Djavad Mowafaghian Centre for Brain Health, The University of British Columbia, Vancouver, BC V6T 2B5, Canada
| | - Neil R Cashman
- Djavad Mowafaghian Centre for Brain Health, The University of British Columbia, Vancouver, BC V6T 2B5, Canada
| | - Xubiao Peng
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC V6T 1Z1, Canada
| | - Steven S Plotkin
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC V6T 1Z1, Canada.,Genome Science and Technology Program, The University of British Columbia, Vancouver, BC V6T 1Z1, Canada
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15
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Doll SG, Meshkin H, Bryer AJ, Li F, Ko YH, Lokareddy RK, Gillilan RE, Gupta K, Perilla JR, Cingolani G. Recognition of the TDP-43 nuclear localization signal by importin α1/β. Cell Rep 2022; 39:111007. [PMID: 35767952 PMCID: PMC9290431 DOI: 10.1016/j.celrep.2022.111007] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 03/31/2022] [Accepted: 06/06/2022] [Indexed: 11/27/2022] Open
Abstract
Cytoplasmic mislocalization of the TAR-DNA binding protein of 43 kDa (TDP-43) leads to large, insoluble aggregates that are a hallmark of amyotrophic lateral sclerosis and frontotemporal dementia. Here, we study how importin α1/β recognizes TDP-43 bipartite nuclear localization signal (NLS). We find that the NLS makes extensive contacts with importin α1, especially at the minor NLS-binding site. NLS binding results in steric clashes with the C terminus of importin α1 that disrupts the TDP-43 N-terminal domain (NTD) dimerization interface. A putative phosphorylation site in the proximity of TDP-43 R83 at the minor NLS site destabilizes binding to importins by reducing the NLS backbone dynamics. Based on these data, we explain the pathogenic role of several post-translational modifications and mutations in the proximity of TDP-43 minor NLS site that are linked to disease and shed light on the chaperone activity of importin α1/β.
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Affiliation(s)
- Steven G Doll
- Department of Biochemistry and Molecular Biology, Thomas Jefferson University, 1020 Locust St., Philadelphia, PA 19107, USA
| | - Hamed Meshkin
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, USA
| | - Alexander J Bryer
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, USA
| | - Fenglin Li
- Department of Biochemistry and Molecular Biology, Thomas Jefferson University, 1020 Locust St., Philadelphia, PA 19107, USA
| | - Ying-Hui Ko
- Department of Biochemistry and Molecular Biology, Thomas Jefferson University, 1020 Locust St., Philadelphia, PA 19107, USA
| | - Ravi K Lokareddy
- Department of Biochemistry and Molecular Biology, Thomas Jefferson University, 1020 Locust St., Philadelphia, PA 19107, USA
| | - Richard E Gillilan
- Macromolecular Diffraction Facility, Cornell High Energy Synchrotron Source (MacCHESS), Cornell University, 161 Synchrotron Drive, Ithaca, NY 14853, USA
| | - Kushol Gupta
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Juan R Perilla
- Department of Chemistry and Biochemistry, University of Delaware, Newark, DE 19716, USA
| | - Gino Cingolani
- Department of Biochemistry and Molecular Biology, Thomas Jefferson University, 1020 Locust St., Philadelphia, PA 19107, USA.
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16
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Sora V, Papaleo E. Structural Details of BH3 Motifs and BH3-Mediated Interactions: an Updated Perspective. Front Mol Biosci 2022; 9:864874. [PMID: 35685242 PMCID: PMC9171138 DOI: 10.3389/fmolb.2022.864874] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 04/13/2022] [Indexed: 11/18/2022] Open
Abstract
Apoptosis is a mechanism of programmed cell death crucial in organism development, maintenance of tissue homeostasis, and several pathogenic processes. The B cell lymphoma 2 (BCL2) protein family lies at the core of the apoptotic process, and the delicate balance between its pro- and anti-apoptotic members ultimately decides the cell fate. BCL2 proteins can bind with each other and several other biological partners through the BCL2 homology domain 3 (BH3), which has been also classified as a possible Short Linear Motif and whose distinctive features remain elusive even after decades of studies. Here, we aim to provide an updated overview of the structural features characterizing BH3s and BH3-mediated interactions (with a focus on human proteins), elaborating on the plasticity of BCL2 proteins and the motif properties. We also discussed the implication of these findings for the discovery of interactors of the BH3-binding groove of BCL2 proteins and the design of mimetics for therapeutic purposes.
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Affiliation(s)
- Valentina Sora
- Cancer Structural Biology, Danish Cancer Society Research Center, Copenhagen, Denmark
- Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Elena Papaleo
- Cancer Structural Biology, Danish Cancer Society Research Center, Copenhagen, Denmark
- Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, Kongens Lyngby, Denmark
- *Correspondence: Elena Papaleo, ,
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17
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Lebold KM, Best RB. Tuning Formation of Protein-DNA Coacervates by Sequence and Environment. J Phys Chem B 2022; 126:2407-2419. [PMID: 35317553 DOI: 10.1021/acs.jpcb.2c00424] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The high concentration of nucleic acids and positively charged proteins in the cell nucleus provides many possibilities for complex coacervation. We consider a prototypical mixture of nucleic acids together with the polycationic C-terminus of histone H1 (CH1). Using a minimal coarse-grained model that captures the shape, flexibility, and charge distributions of the molecules, we find that coacervates are readily formed at physiological ionic strengths, in agreement with experiment, with a progressive increase in local ordering at low ionic strength. Variation of the positions of charged residues in the protein tunes phase separation: for well-mixed or only moderately blocky distributions of charge, there is a modest increase of local ordering with increasing blockiness that is also associated with an increased propensity to phase separate. This ordering is also associated with a slowdown of rotational and translational diffusion in the dense phase. However, for more extreme blockiness (and consequently higher local charge density), we see a qualitative change in the condensed phase to become a segregated structure with a dramatically increased ordering of the DNA. Naturally occurring proteins with these sequence properties, such as protamines in sperm cells, are found to be associated with very dense packing of nucleic acids.
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Affiliation(s)
- Kathryn M Lebold
- Laboratory of Chemical Physics, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Robert B Best
- Laboratory of Chemical Physics, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, United States
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18
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Pei H, Guo W, Peng Y, Xiong H, Chen Y. Targeting key proteins involved in transcriptional regulation for cancer therapy: Current strategies and future prospective. Med Res Rev 2022; 42:1607-1660. [PMID: 35312190 DOI: 10.1002/med.21886] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 02/10/2022] [Accepted: 02/22/2022] [Indexed: 12/14/2022]
Abstract
The key proteins involved in transcriptional regulation play convergent roles in cellular homeostasis, and their dysfunction mediates aberrant gene expressions that underline the hallmarks of tumorigenesis. As tumor progression is dependent on such abnormal regulation of transcription, it is important to discover novel chemical entities as antitumor drugs that target key tumor-associated proteins involved in transcriptional regulation. Despite most key proteins (especially transcription factors) involved in transcriptional regulation are historically recognized as undruggable targets, multiple targeting approaches at diverse levels of transcriptional regulation, such as epigenetic intervention, inhibition of DNA-binding of transcriptional factors, and inhibition of the protein-protein interactions (PPIs), have been established in preclinically or clinically studies. In addition, several new approaches have recently been described, such as targeting proteasomal degradation and eliciting synthetic lethality. This review will emphasize on accentuating these developing therapeutic approaches and provide a thorough conspectus of the drug development to target key proteins involved in transcriptional regulation and their impact on future oncotherapy.
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Affiliation(s)
- Haixiang Pei
- Institute for Advanced Study, Shenzhen University and Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, China.,Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China
| | - Weikai Guo
- Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China.,Joint National Laboratory for Antibody Drug Engineering, School of Basic Medical Science, Henan University, Kaifeng, China
| | - Yangrui Peng
- Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China
| | - Hai Xiong
- Institute for Advanced Study, Shenzhen University and Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, China
| | - Yihua Chen
- Shanghai Key Laboratory of Regulatory Biology, The Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China
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19
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Kulkarni P, Leite VBP, Roy S, Bhattacharyya S, Mohanty A, Achuthan S, Singh D, Appadurai R, Rangarajan G, Weninger K, Orban J, Srivastava A, Jolly MK, Onuchic JN, Uversky VN, Salgia R. Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma. BIOPHYSICS REVIEWS 2022; 3:011306. [PMID: 38505224 PMCID: PMC10903413 DOI: 10.1063/5.0080512] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/17/2022] [Indexed: 03/21/2024]
Abstract
Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.
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Affiliation(s)
- Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Vitor B. P. Leite
- Departamento de Física, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista (UNESP), São José do Rio Preto, São Paulo 15054-000, Brazil
| | - Susmita Roy
- Department of Chemical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
| | - Supriyo Bhattacharyya
- Translational Bioinformatics, Center for Informatics, Department of Computational and Quantitative Medicine, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Atish Mohanty
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Srisairam Achuthan
- Center for Informatics, Division of Research Informatics, City of Hope National Medical Center, Duarte, California 91010, USA
| | - Divyoj Singh
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Rajeswari Appadurai
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
| | - Govindan Rangarajan
- Department of Mathematics, Indian Institute of Science, Bangalore 560012, India
| | - Keith Weninger
- Department of Physics, North Carolina State University, Raleigh, North Carolina 27695, USA
| | | | - Anand Srivastava
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, India
| | - Mohit Kumar Jolly
- Center for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Jose N. Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005-1892, USA
| | | | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, California 91010, USA
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20
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Röder K, Wales DJ. The Energy Landscape Perspective: Encoding Structure and Function for Biomolecules. Front Mol Biosci 2022; 9:820792. [PMID: 35155579 PMCID: PMC8829389 DOI: 10.3389/fmolb.2022.820792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 01/07/2022] [Indexed: 12/02/2022] Open
Abstract
The energy landscape perspective is outlined with particular reference to biomolecules that perform multiple functions. We associate these multifunctional molecules with multifunnel energy landscapes, illustrated by some selected examples, where understanding the organisation of the landscape has provided new insight into function. Conformational selection and induced fit may provide alternative routes to realisation of multifunctionality, exploiting the possibility of environmental control and distinct binding modes.
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Affiliation(s)
| | - David J. Wales
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
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21
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Montepietra D, Cecconi C, Brancolini G. Combining enhanced sampling and deep learning dimensionality reduction for the study of the heat shock protein B8 and its pathological mutant K141E. RSC Adv 2022; 12:31996-32011. [PMID: 36380940 PMCID: PMC9641792 DOI: 10.1039/d2ra04913a] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 10/28/2022] [Indexed: 11/11/2022] Open
Abstract
The biological functions of proteins closely depend on their conformational dynamics. This aspect is especially relevant for intrinsically disordered proteins (IDP) for which structural ensembles often offer more useful representations than individual conformations. Here we employ extensive enhanced sampling temperature replica-exchange atomistic simulations (TREMD) and deep learning dimensionality reduction to study the conformational ensembles of the human heat shock protein B8 and its pathological mutant K141E, for which no experimental 3D structures are available. First, we combined homology modelling with TREMD to generate high-dimensional data sets of 3D structures. Then, we employed a recently developed machine learning based post-processing algorithm, EncoderMap, to project the large conformational data sets into meaningful two-dimensional maps that helped us interpret the data and extract the most significant conformations adopted by both proteins during TREMD. These studies provide the first 3D structural characterization of HSPB8 and reveal the effects of the pathogenic K141E mutation on its conformational ensembles. In particular, this missense mutation appears to increase the compactness of the protein and its structural variability, at the same time rearranging the hydrophobic patches exposed on the protein surface. These results offer the possibility of rationalizing the pathogenic effects of the K141E mutation in terms of conformational changes. The study provides the first 3D structural characterization of HSPB8 and its K141E mutant: extensive TREMD are combined with a deep learning algorithm to rationalize the disordered ensemble of structures adopted by each variant.![]()
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Affiliation(s)
- Daniele Montepietra
- Department of Physics, Computer Science and Mathematics, University of Modena and Reggio Emilia, Via Campi 213/A, 41100 Modena, Italy
- Istituto Nanoscienze – CNR-NANO, Center S3, Via G. Campi 213/A, 41100 Modena, Italy
| | - Ciro Cecconi
- Department of Physics, Computer Science and Mathematics, University of Modena and Reggio Emilia, Via Campi 213/A, 41100 Modena, Italy
- Istituto Nanoscienze – CNR-NANO, Center S3, Via G. Campi 213/A, 41100 Modena, Italy
| | - Giorgia Brancolini
- Istituto Nanoscienze – CNR-NANO, Center S3, Via G. Campi 213/A, 41100 Modena, Italy
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22
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Conformational dynamics promotes disordered regions from function-dispensable to essential in evolved site-specific DNA recombinases. Comput Struct Biotechnol J 2022; 20:989-1001. [PMID: 35242289 PMCID: PMC8860914 DOI: 10.1016/j.csbj.2022.01.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 01/11/2022] [Accepted: 01/11/2022] [Indexed: 12/11/2022] Open
Abstract
New functional regions emerging in evolution of DNA site-specific recombinase tails. Transient structural nucleation promotes function-dispensable regions to essential. Molecular dynamics reveals conformational diversity and its functional implications. Evolved disordered molecular mechanisms of N-term tails for protein stability. Structural disorder-based link between protein evolution, stability and function.
Protein intrinsically disordered regions (IDRs) play pivotal roles in molecular recognition and regulatory processes through structural disorder-to-order transitions. To understand and exploit the distinctive functional implications of IDRs and to unravel the underlying molecular mechanisms, structural disorder-to-function relationships need to be deciphered. The DNA site-specific recombinase system Cre/loxP represents an attractive model to investigate functional molecular mechanisms of IDRs. Cre contains a functionally dispensable disordered N-terminal tail, which becomes indispensable in the evolved Tre/loxLTR recombinase system. The difficulty to experimentally obtain structural information about this tail has so far precluded any mechanistic study on its involvement in DNA recombination. Here, we use in vitro and in silico evolution data, conformational dynamics, AI-based folding simulations, thermodynamic stability calculations, mutagenesis and DNA recombination assays to investigate how evolution and the dynamic behavior of this IDR may determine distinct functional properties. Our studies suggest that partial conformational order in the N-terminal tail of Tre recombinase and its packing to a conserved hydrophobic surface on the protein provide thermodynamic stability. Based on our results, we propose a link between protein stability and function, offering new plausible atom-detailed mechanistic insights into disorder-function relationships. Our work highlights the potential of N-terminal tails to be exploited for regulation of the activity of Cre-like tyrosine-type SSRs, which merits future investigations and could be of relevance in future rational engineering for their use in biotechnology and genomic medicine.
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23
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Behkamal B, Naghibzadeh M, Saberi MR, Tehranizadeh ZA, Pagnani A, Al Nasr K. Three-Dimensional Graph Matching to Identify Secondary Structure Correspondence of Medium-Resolution Cryo-EM Density Maps. Biomolecules 2021; 11:1773. [PMID: 34944417 PMCID: PMC8698881 DOI: 10.3390/biom11121773] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/18/2021] [Accepted: 11/20/2021] [Indexed: 01/15/2023] Open
Abstract
Cryo-electron microscopy (cryo-EM) is a structural technique that has played a significant role in protein structure determination in recent years. Compared to the traditional methods of X-ray crystallography and NMR spectroscopy, cryo-EM is capable of producing images of much larger protein complexes. However, cryo-EM reconstructions are limited to medium-resolution (~4-10 Å) for some cases. At this resolution range, a cryo-EM density map can hardly be used to directly determine the structure of proteins at atomic level resolutions, or even at their amino acid residue backbones. At such a resolution, only the position and orientation of secondary structure elements (SSEs) such as α-helices and β-sheets are observable. Consequently, finding the mapping of the secondary structures of the modeled structure (SSEs-A) to the cryo-EM map (SSEs-C) is one of the primary concerns in cryo-EM modeling. To address this issue, this study proposes a novel automatic computational method to identify SSEs correspondence in three-dimensional (3D) space. Initially, through a modeling of the target sequence with the aid of extracting highly reliable features from a generated 3D model and map, the SSEs matching problem is formulated as a 3D vector matching problem. Afterward, the 3D vector matching problem is transformed into a 3D graph matching problem. Finally, a similarity-based voting algorithm combined with the principle of least conflict (PLC) concept is developed to obtain the SSEs correspondence. To evaluate the accuracy of the method, a testing set of 25 experimental and simulated maps with a maximum of 65 SSEs is selected. Comparative studies are also conducted to demonstrate the superiority of the proposed method over some state-of-the-art techniques. The results demonstrate that the method is efficient, robust, and works well in the presence of errors in the predicted secondary structures of the cryo-EM images.
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Affiliation(s)
- Bahareh Behkamal
- Department of Computer Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran;
| | - Mahmoud Naghibzadeh
- Department of Computer Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran;
| | - Mohammad Reza Saberi
- Medicinal Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad 9177899191, Iran; (M.R.S.); (Z.A.T.)
- Bioinformatics Research Group, Mashhad University of Medical Sciences, Mashhad 9177899191, Iran
| | - Zeinab Amiri Tehranizadeh
- Medicinal Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad 9177899191, Iran; (M.R.S.); (Z.A.T.)
| | - Andrea Pagnani
- Politecnico di Torino, Corso Duca degli Abruzzi 24, I-10129 Torino, Italy;
- Italian Institute for Genomic Medicine, IRCCS Candiolo, SP-142, I-10060 Candiolo, Italy
- INFN, Sezione di Torino, I-10125 Torino, Italy
| | - Kamal Al Nasr
- Department of Computer Science, Tennessee State University, Nashville, TN 37209, USA
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Gong X, Zhang Y, Chen J. Advanced Sampling Methods for Multiscale Simulation of Disordered Proteins and Dynamic Interactions. Biomolecules 2021; 11:1416. [PMID: 34680048 PMCID: PMC8533332 DOI: 10.3390/biom11101416] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/22/2021] [Accepted: 09/24/2021] [Indexed: 11/16/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) are highly prevalent and play important roles in biology and human diseases. It is now also recognized that many IDPs remain dynamic even in specific complexes and functional assemblies. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for a mechanistic understanding of IDPs in biology, diseases, and therapeutics. Here, we provide an in-depth review of recent advances in the multi-scale simulation of disordered protein states, with a particular emphasis on the development and application of advanced sampling techniques for studying IDPs. These techniques are critical for adequate sampling of the manifold functionally relevant conformational spaces of IDPs. Together with dramatically improved protein force fields, these advanced simulation approaches have achieved substantial success and demonstrated significant promise towards the quantitative and predictive modeling of IDPs and their dynamic interactions. We will also discuss important challenges remaining in the atomistic simulation of larger systems and how various coarse-grained approaches may help to bridge the remaining gaps in the accessible time- and length-scales of IDP simulations.
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Affiliation(s)
- Xiping Gong
- Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA; (X.G.); (Y.Z.)
| | - Yumeng Zhang
- Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA; (X.G.); (Y.Z.)
| | - Jianhan Chen
- Department of Chemistry, University of Massachusetts Amherst, Amherst, MA 01003, USA; (X.G.); (Y.Z.)
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA 01003, USA
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25
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Chen J, Zaer S, Drori P, Zamel J, Joron K, Kalisman N, Lerner E, Dokholyan NV. The structural heterogeneity of α-synuclein is governed by several distinct subpopulations with interconversion times slower than milliseconds. Structure 2021; 29:1048-1064.e6. [PMID: 34015255 PMCID: PMC8419013 DOI: 10.1016/j.str.2021.05.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/12/2021] [Accepted: 04/30/2021] [Indexed: 11/22/2022]
Abstract
α-Synuclein plays an important role in synaptic functions by interacting with synaptic vesicle membrane, while its oligomers and fibrils are associated with several neurodegenerative diseases. The specific monomer structures that promote its membrane binding and self-association remain elusive due to its transient nature as an intrinsically disordered protein. Here, we use inter-dye distance distributions from bulk time-resolved Förster resonance energy transfer as restraints in discrete molecular dynamics simulations to map the conformational space of the α-synuclein monomer. We further confirm the generated conformational ensemble in orthogonal experiments utilizing far-UV circular dichroism and cross-linking mass spectrometry. Single-molecule protein-induced fluorescence enhancement measurements show that within this conformational ensemble, some of the conformations of α-synuclein are surprisingly stable, exhibiting conformational transitions slower than milliseconds. Our comprehensive analysis of the conformational ensemble reveals essential structural properties and potential conformations that promote its various functions in membrane interaction or oligomer and fibril formation.
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Affiliation(s)
- Jiaxing Chen
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA 17033, USA
| | - Sofia Zaer
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Paz Drori
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Joanna Zamel
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Khalil Joron
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Nir Kalisman
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Eitan Lerner
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Faculty of Mathematics & Science, The Edmond J. Safra Campus, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel; The Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA 17033, USA; Department of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA 17033, USA; Departments of Chemistry and Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA.
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26
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Clerc I, Sagar A, Barducci A, Sibille N, Bernadó P, Cortés J. The diversity of molecular interactions involving intrinsically disordered proteins: A molecular modeling perspective. Comput Struct Biotechnol J 2021; 19:3817-3828. [PMID: 34285781 PMCID: PMC8273358 DOI: 10.1016/j.csbj.2021.06.031] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/17/2021] [Accepted: 06/21/2021] [Indexed: 01/15/2023] Open
Abstract
Intrinsically Disordered Proteins and Regions (IDPs/IDRs) are key components of a multitude of biological processes. Conformational malleability enables IDPs/IDRs to perform very specialized functions that cannot be accomplished by globular proteins. The functional role for most of these proteins is related to the recognition of other biomolecules to regulate biological processes or as a part of signaling pathways. Depending on the extent of disorder, the number of interacting sites and the type of partner, very different architectures for the resulting assemblies are possible. More recently, molecular condensates with liquid-like properties composed of multiple copies of IDPs and nucleic acids have been proven to regulate key processes in eukaryotic cells. The structural and kinetic details of disordered biomolecular complexes are difficult to unveil experimentally due to their inherent conformational heterogeneity. Computational approaches, alone or in combination with experimental data, have emerged as unavoidable tools to understand the functional mechanisms of this elusive type of assemblies. The level of description used, all-atom or coarse-grained, strongly depends on the size of the molecular systems and on the timescale of the investigated mechanism. In this mini-review, we describe the most relevant architectures found for molecular interactions involving IDPs/IDRs and the computational strategies applied for their investigation.
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Affiliation(s)
- Ilinka Clerc
- LAAS-CNRS, Université de Toulouse, CNRS, Toulouse, France
| | - Amin Sagar
- Centre de Biochimie Structurale, INSERM, CNRS, Université de Montpellier, France
| | - Alessandro Barducci
- Centre de Biochimie Structurale, INSERM, CNRS, Université de Montpellier, France
| | - Nathalie Sibille
- Centre de Biochimie Structurale, INSERM, CNRS, Université de Montpellier, France
| | - Pau Bernadó
- Centre de Biochimie Structurale, INSERM, CNRS, Université de Montpellier, France
| | - Juan Cortés
- LAAS-CNRS, Université de Toulouse, CNRS, Toulouse, France
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Spoel D, Zhang J, Zhang H. Quantitative predictions from molecular simulations using explicit or implicit interactions. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1560] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- David Spoel
- Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology Uppsala University Uppsala Sweden
| | - Jin Zhang
- Department of Chemistry Southern University of Science and Technology Shenzhen China
| | - Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering University of Science and Technology Beijing Beijing China
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Molecular Dynamics Simulations of Human FOXO3 Reveal Intrinsically Disordered Regions Spread Spatially by Intramolecular Electrostatic Repulsion. Biomolecules 2021; 11:biom11060856. [PMID: 34201262 PMCID: PMC8228108 DOI: 10.3390/biom11060856] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/01/2021] [Accepted: 06/03/2021] [Indexed: 12/17/2022] Open
Abstract
The human transcription factor FOXO3 (a member of the 'forkhead' family of transcription factors) controls a variety of cellular functions that make it a highly relevant target for intervention in anti-cancer and anti-aging therapies. FOXO3 is a mostly intrinsically disordered protein (IDP). Absence of knowledge of its structural properties outside the DNA-binding domain constitutes a considerable obstacle to a better understanding of structure/function relationships. Here, I present extensive molecular dynamics (MD) simulation data based on implicit solvation models of the entire FOXO3/DNA complex, and accelerated MD simulations under explicit solvent conditions of a central region of particular structural interest (FOXO3120-530). A new graphical tool for studying and visualizing the structural diversity of IDPs, the Local Compaction Plot (LCP), is introduced. The simulations confirm the highly disordered nature of FOXO3 and distinguish various degrees of folding propensity. Unexpectedly, two 'linker' regions immediately adjacent to the DNA-binding domain are present in a highly extended conformation. This extended conformation is not due to their amino acid composition, but rather is caused by electrostatic repulsion of the domains connected by the linkers. FOXO3 is thus an IDP present in an unusually extended conformation to facilitate interaction with molecular interaction partners.
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Mu J, Liu H, Zhang J, Luo R, Chen HF. Recent Force Field Strategies for Intrinsically Disordered Proteins. J Chem Inf Model 2021; 61:1037-1047. [PMID: 33591749 PMCID: PMC8256680 DOI: 10.1021/acs.jcim.0c01175] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.
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Affiliation(s)
- Junxi Mu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hao Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, School of Medicine, Shanghai Jiao Tong University, Shanghai 20025, China
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical and Molecular Engineering, Materials Science and Engineering, and Biomedical Engineering, University of California, Irvine, California 92697-3900, United States
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
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Structure-based peptide design targeting intrinsically disordered proteins: Novel histone H4 and H2A peptidic inhibitors. Comput Struct Biotechnol J 2021; 19:934-948. [PMID: 33598107 PMCID: PMC7856395 DOI: 10.1016/j.csbj.2021.01.026] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/17/2021] [Accepted: 01/18/2021] [Indexed: 12/12/2022] Open
Abstract
Intrinsically disordered proteins/protein regions (IDPs/IDPRs) are emerging drug targets. Lack of fast methods hinders the discovery of inhibitors for IDPs/ IDPRs. Fast and inexpensive structure-based approaches have been developed. The developed methods were applied to succesfully design inhibitors targeting the disordered tail of histone H4 and H2A. The presented methods can be widely used to identify inhibitors for other IDPs/IDPRs.
A growing body of research has demonstrated that targeting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) is feasible and represents a new trending strategy in drug discovery. However, the number of inhibitors targeting IDPs/IDPRs is increasing slowly due to limitations of the methods that can be used to accelerate the discovery process. We have applied structure-based methods to successfully develop the first peptidic inhibitor (HIPe - Histone Inhibitory Peptide) that targets histone H4 that are released from NETs (Neutrophil Extracellular Traps). HIPe binds stably to the disordered N-terminal tail of histone H4, thereby preventing histone H4-induced cell death. Recently, by utilisation of the same state-of-the-art approaches, we have developed a novel peptidic inhibitor (CHIP - Cyclical Histone H2A Interference Peptide) that binds to NET-resident histone H2A, which results in a blockade of monocyte adhesion and consequently reduction in atheroprogression. Here, we present comprehensive details on the computational methods utilised to design and develop HIPe and CHIP. We have exploited protein–protein complexes as starting structures for rational peptide design and then applied binding free energy methods to predict and prioritise binding strength of the designed peptides with histone H4 and H2A. By doing this way, we have modelled only around 20 peptides and from these were able to select 4–5 peptides, from a total of more than a trillion candidate peptides, for functional characterisation in different experiments. The developed computational protocols are generic and can be widely used to design and develop novel inhibitors for other disordered proteins.
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Key Words
- ARDS, acute respiratory distress syndrome
- BFE, binding free energy
- BRCA-1, breast cancer type1 susceptibility protein
- CCL5, chemokine ligand 5
- CHIP, cyclical histone H2A interference peptide
- Computer-aided molecular design (CAMD)
- DC, decomposition
- Disordered proteins
- H2A, histone H2A
- H2B, histone H2B
- H3, histone H3
- H4, histone H4
- HIPe, histone inhibitory peptide
- HNP1, human neutrophil peptide 1
- Histones
- IDPRs, intrinsically disordered protein regions
- IDPs, intrinsically disordered proteins
- MD, molecular dynamics
- MM/GBSA, molecular mechanics/generalised born surface area
- NETs, neutrophil extracellular traps
- Neutrophil extracellular traps (NETs)
- PDB, protein data bank
- PPIs, protein-protein interactions
- PTP1B, protein tyrosine phosphatase 1B
- Peptides
- Protein-protein interactions (PPIs)
- SMCs, smooth muscle cells
- aMD, accelerated molecular dynamics
- p53, tumor protein 53
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Jagannathan NS, Hogue CWV, Tucker-Kellogg L. Computational modeling suggests binding-induced expansion of Epsin disordered regions upon association with AP2. PLoS Comput Biol 2021; 17:e1008474. [PMID: 33406091 PMCID: PMC7787433 DOI: 10.1371/journal.pcbi.1008474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 10/27/2020] [Indexed: 11/22/2022] Open
Abstract
Intrinsically disordered regions (IDRs) are prevalent in the eukaryotic proteome. Common functional roles of IDRs include forming flexible linkers or undergoing allosteric folding-upon-binding. Recent studies have suggested an additional functional role for IDRs: generating steric pressure on the plasma membrane during endocytosis, via molecular crowding. However, in order to accomplish useful functions, such crowding needs to be regulated in space (e.g., endocytic hotspots) and time (e.g., during vesicle formation). In this work, we explore binding-induced regulation of IDR steric volume. We simulate the IDRs of two proteins from Clathrin-mediated endocytosis (CME) to see if their conformational spaces are regulated via binding-induced expansion. Using Monte-Carlo computational modeling of excluded volumes, we generate large conformational ensembles (3 million) for the IDRs of Epsin and Eps15 and dock the conformers to the alpha subunit of Adaptor Protein 2 (AP2α), their CME binding partner. Our results show that as more molecules of AP2α are bound, the Epsin-derived ensemble shows a significant increase in global dimensions, measured as the radius of Gyration (RG) and the end-to-end distance (EED). Unlike Epsin, Eps15-derived conformers that permit AP2α binding at one motif were found to be more likely to accommodate binding of AP2α at other motifs, suggesting a tendency toward co-accessibility of binding motifs. Co-accessibility was not observed for any pair of binding motifs in Epsin. Thus, we speculate that the disordered regions of Epsin and Eps15 perform different roles during CME, with accessibility in Eps15 allowing it to act as a recruiter of AP2α molecules, while binding-induced expansion of the Epsin disordered region could impose steric pressure and remodel the plasma membrane during vesicle formation. Protein functions were originally believed to arise from ordered protein structures. This dogma was later challenged by the identification of intrinsically disordered proteins that lack specific structure. The functional roles of such proteins usually fell in two categories–exploiting the disorder for flexibility (like floppy connector), or imposing order upon binding to an external partner. In this study we explore the possibility of an alternative mechanism that harnesses disorder for function through regulated molecular crowding. Specifically, we use modeling to study two proteins involved in reshaping the cell membrane, Epsin and Eps15. We ask if they undergo binding-induced expansion, where binding of an external partner AP2 causes not a transition toward order, but rather an energetically favorable increase in propensity to occupy larger volumes. Our results show that Epsin tends to occupy a larger volume when bound to AP2, consistent with increased molecular crowding, which could help reshape the cell membrane. Such regulation of disorder via binding (without folding) opens hitherto unexplored avenues that cells might employ to harness disorder.
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Affiliation(s)
- N. Suhas Jagannathan
- Cancer & Stem Cell Biology, and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore
- Singapore-MIT Alliance, Computation and Systems Biology Program, National University of Singapore, Singapore
| | - Christopher W. V. Hogue
- Singapore-MIT Alliance, Computation and Systems Biology Program, National University of Singapore, Singapore
- Mechanobiology Institute, National University of Singapore, Singapore
| | - Lisa Tucker-Kellogg
- Cancer & Stem Cell Biology, and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore
- Singapore-MIT Alliance, Computation and Systems Biology Program, National University of Singapore, Singapore
- * E-mail:
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Fatafta H, Samantray S, Sayyed-Ahmad A, Coskuner-Weber O, Strodel B. Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2021; 183:135-185. [PMID: 34656328 DOI: 10.1016/bs.pmbts.2021.06.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/26/2023]
Abstract
Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.
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Affiliation(s)
- Hebah Fatafta
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Forschungszentrum Jülich, Jülich, Germany
| | - Suman Samantray
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Forschungszentrum Jülich, Jülich, Germany; AICES Graduate School, RWTH Aachen University, Aachen, Germany
| | | | - Orkid Coskuner-Weber
- Molecular Biotechnology, Turkish-German University, Sahinkaya Caddesi, Istanbul, Turkey
| | - Birgit Strodel
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Forschungszentrum Jülich, Jülich, Germany; Institute of Theoretical and Computational Chemistry, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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Abstract
Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.
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Development of Charge-Augmented Three-Point Water Model (CAIPi3P) for Accurate Simulations of Intrinsically Disordered Proteins. Int J Mol Sci 2020; 21:ijms21176166. [PMID: 32859072 PMCID: PMC7504337 DOI: 10.3390/ijms21176166] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 08/17/2020] [Accepted: 08/21/2020] [Indexed: 01/15/2023] Open
Abstract
Intrinsically disordered proteins (IDPs) are molecules without a fixed tertiary structure, exerting crucial roles in cellular signalling, growth and molecular recognition events. Due to their high plasticity, IDPs are very challenging in experimental and computational structural studies. To provide detailed atomic insight in IDPs' dynamics governing their functional mechanisms, all-atom molecular dynamics (MD) simulations are widely employed. However, the current generalist force fields and solvent models are unable to generate satisfactory ensembles for IDPs when compared to existing experimental data. In this work, we present a new solvation model, denoted as the Charge-Augmented Three-Point Water Model for Intrinsically Disordered Proteins (CAIPi3P). CAIPi3P has been generated by performing a systematic scan of atomic partial charges assigned to the widely popular molecular scaffold of the three-point TIP3P water model. We found that explicit solvent MD simulations employing CAIPi3P solvation considerably improved the small-angle X-ray scattering (SAXS) scattering profiles for three different IDPs. Not surprisingly, this improvement was further enhanced by using CAIPi3P water in combination with the protein force field parametrized for IDPs. We also demonstrated the applicability of CAIPi3P to molecular systems containing structured as well as intrinsically disordered regions/domains. Our results highlight the crucial importance of solvent effects for generating molecular ensembles of IDPs which reproduce the experimental data available. Hence, we conclude that our newly developed CAIPi3P solvation model is a valuable tool for molecular simulations of intrinsically disordered proteins and assessing their molecular dynamics.
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35
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Probing Surfaces in Dynamic Protein Interactions. J Mol Biol 2020; 432:2949-2972. [DOI: 10.1016/j.jmb.2020.02.032] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Revised: 02/22/2020] [Accepted: 02/24/2020] [Indexed: 01/09/2023]
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36
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Kumari A, Somvanshi P, Grover A. Ameliorating amyloid aggregation through osmolytes as a probable therapeutic molecule against Alzheimer's disease and type 2 diabetes. RSC Adv 2020; 10:12166-12182. [PMID: 35497581 PMCID: PMC9050657 DOI: 10.1039/d0ra00429d] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 02/16/2020] [Indexed: 01/31/2023] Open
Abstract
Large numbers of neurological and metabolic disorders occurring in humans are induced by the aberrant growth of aggregated or misfolded proteins.
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Affiliation(s)
- Anchala Kumari
- Department of Biotechnology
- Teri School of Advanced Studies
- New Delhi-110070
- India
- School of Biotechnology
| | - Pallavi Somvanshi
- Department of Biotechnology
- Teri School of Advanced Studies
- New Delhi-110070
- India
| | - Abhinav Grover
- School of Biotechnology
- Jawaharlal Nehru University
- New Delhi-110067
- India
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Demerdash O, Shrestha UR, Petridis L, Smith JC, Mitchell JC, Ramanathan A. Using Small-Angle Scattering Data and Parametric Machine Learning to Optimize Force Field Parameters for Intrinsically Disordered Proteins. Front Mol Biosci 2019; 6:64. [PMID: 31475155 PMCID: PMC6705226 DOI: 10.3389/fmolb.2019.00064] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 07/16/2019] [Indexed: 12/26/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered regions (IDRs) play important roles in many aspects of normal cell physiology, such as signal transduction and transcription, as well as pathological states, including Alzheimer's, Parkinson's, and Huntington's disease. Unlike their globular counterparts that are defined by a few structures and free energy minima, IDP/IDR comprise a large ensemble of rapidly interconverting structures and a corresponding free energy landscape characterized by multiple minima. This aspect has precluded the use of structural biological techniques, such as X-ray crystallography and nuclear magnetic resonance (NMR) for resolving their structures. Instead, low-resolution techniques, such as small-angle X-ray or neutron scattering (SAXS/SANS), have become a mainstay in characterizing coarse features of the ensemble of structures. These are typically complemented with NMR data if possible or computational techniques, such as atomistic molecular dynamics, to further resolve the underlying ensemble of structures. However, over the past 10–15 years, it has become evident that the classical, pairwise-additive force fields that have enjoyed a high degree of success for globular proteins have been somewhat limited in modeling IDP/IDR structures that agree with experiment. There has thus been a significant effort to rehabilitate these models to obtain better agreement with experiment, typically done by optimizing parameters in a piecewise fashion. In this work, we take a different approach by optimizing a set of force field parameters simultaneously, using machine learning to adapt force field parameters to experimental SAXS scattering profiles. We demonstrate our approach in modeling three biologically IDP ensembles based on experimental SAXS profiles and show that our optimization approach significantly improve force field parameters that generate ensembles in better agreement with experiment.
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Affiliation(s)
- Omar Demerdash
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge, TN, United States
| | - Utsab R Shrestha
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge, TN, United States
| | - Loukas Petridis
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge, TN, United States
| | - Jeremy C Smith
- University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge, TN, United States.,Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, United States
| | - Julie C Mitchell
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge, TN, United States
| | - Arvind Ramanathan
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,Data Science and Learning Division, Argonne National Laboratory, Lemont, IL, United States
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Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications. Int J Mol Sci 2019; 20:ijms20153774. [PMID: 31375023 PMCID: PMC6696403 DOI: 10.3390/ijms20153774] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/28/2019] [Accepted: 07/30/2019] [Indexed: 12/23/2022] Open
Abstract
Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.
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Schramm A, Bignon C, Brocca S, Grandori R, Santambrogio C, Longhi S. An arsenal of methods for the experimental characterization of intrinsically disordered proteins - How to choose and combine them? Arch Biochem Biophys 2019; 676:108055. [PMID: 31356778 DOI: 10.1016/j.abb.2019.07.020] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 07/16/2019] [Accepted: 07/24/2019] [Indexed: 12/12/2022]
Abstract
In this review, we detail the most common experimental approaches to assess and characterize protein intrinsic structural disorder, with the notable exception of NMR and EPR spectroscopy, two ideally suited approaches that will be described in depth in two other reviews within this special issue. We discuss the advantages, the limitations, as well as the caveats of the various methods. We also describe less common and more demanding approaches that enable achieving further insights into the conformational properties of IDPs. Finally, we present recent developments that have enabled assessment of structural disorder in living cells, and discuss the currently available methods to model IDPs as conformational ensembles.
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Affiliation(s)
- Antoine Schramm
- CNRS and Aix-Marseille Univ, Laboratoire Architecture et Fonction des Macromolecules Biologiques (AFMB), UMR 7257, Marseille, France
| | - Christophe Bignon
- CNRS and Aix-Marseille Univ, Laboratoire Architecture et Fonction des Macromolecules Biologiques (AFMB), UMR 7257, Marseille, France
| | - Stefania Brocca
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy
| | - Rita Grandori
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy
| | - Carlo Santambrogio
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy
| | - Sonia Longhi
- CNRS and Aix-Marseille Univ, Laboratoire Architecture et Fonction des Macromolecules Biologiques (AFMB), UMR 7257, Marseille, France.
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Intrinsically Disordered Proteins in Chronic Diseases. Biomolecules 2019; 9:biom9040147. [PMID: 30979084 PMCID: PMC6523076 DOI: 10.3390/biom9040147] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 04/03/2019] [Indexed: 12/14/2022] Open
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