1
|
Kornev AP, Weng JH, Maillard RA, Taylor SS. Gauging Dynamics-driven Allostery Using a New Computational Tool: A CAP Case Study. J Mol Biol 2024; 436:168395. [PMID: 38097109 PMCID: PMC10851786 DOI: 10.1016/j.jmb.2023.168395] [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: 09/06/2023] [Revised: 11/22/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023]
Abstract
In this study, we utilize Protein Residue Networks (PRNs), constructed using Local Spatial Pattern (LSP) alignment, to explore the dynamic behavior of Catabolite Activator Protein (CAP) upon the sequential binding of cAMP. We employed the Degree Centrality of these PRNs to investigate protein dynamics on a sub-nanosecond time scale, hypothesizing that it would reflect changes in CAP's entropy related to its thermal motions. We show that the binding of the first cAMP led to an increase in stability in the Cyclic-Nucleotide Binding Domain A (CNBD-A) and destabilization in CNBD-B, agreeing with previous reports explaining the negative cooperativity of cAMP binding in terms of an entropy-driven allostery. LSP-based PRNs also allow for the study of Betweenness Centrality, another graph-theoretical characteristic of PRNs, providing insights into global residue connectivity within CAP. Using this approach, we were able to correctly identify amino acids that were shown to be critical in mediating allosteric interactions in CAP. The agreement between our studies and previous experimental reports validates our method, particularly with respect to the reliability of Degree Centrality as a proxy for entropy related to protein thermal dynamics. Because LSP-based PRNs can be easily extended to include dynamics of small organic molecules, polynucleotides, or other allosteric proteins, the methods presented here mark a significant advancement in the field, positioning them as vital tools for a fast, cost-effective, and accurate analysis of entropy-driven allostery and identification of allosteric hotspots.
Collapse
Affiliation(s)
- Alexandr P Kornev
- Departmen of Pharmacology, University of California San Diego, La Jolla, CA 92093, USA.
| | - Jui-Hung Weng
- Departmen of Pharmacology, University of California San Diego, La Jolla, CA 92093, USA
| | - Rodrigo A Maillard
- Department of Chemistry, Georgetown University, Washington, DC 20007, USA
| | - Susan S Taylor
- Departmen of Pharmacology, University of California San Diego, La Jolla, CA 92093, USA; Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093, USA
| |
Collapse
|
2
|
Ersoy A, Altintel B, Livnat Levanon N, Ben-Tal N, Haliloglu T, Lewinson O. Computational analysis of long-range allosteric communications in CFTR. eLife 2023; 12:RP88659. [PMID: 38109179 PMCID: PMC10727502 DOI: 10.7554/elife.88659] [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] [Indexed: 12/19/2023] Open
Abstract
Malfunction of the CFTR protein results in cystic fibrosis, one of the most common hereditary diseases. CFTR functions as an anion channel, the gating of which is controlled by long-range allosteric communications. Allostery also has direct bearings on CF treatment: the most effective CFTR drugs modulate its activity allosterically. Herein, we integrated Gaussian network model, transfer entropy, and anisotropic normal mode-Langevin dynamics and investigated the allosteric communications network of CFTR. The results are in remarkable agreement with experimental observations and mutational analysis and provide extensive novel insight. We identified residues that serve as pivotal allosteric sources and transducers, many of which correspond to disease-causing mutations. We find that in the ATP-free form, dynamic fluctuations of the residues that comprise the ATP-binding sites facilitate the initial binding of the nucleotide. Subsequent binding of ATP then brings to the fore and focuses on dynamic fluctuations that were present in a latent and diffuse form in the absence of ATP. We demonstrate that drugs that potentiate CFTR's conductance do so not by directly acting on the gating residues, but rather by mimicking the allosteric signal sent by the ATP-binding sites. We have also uncovered a previously undiscovered allosteric 'hotspot' located proximal to the docking site of the phosphorylated regulatory (R) domain, thereby establishing a molecular foundation for its phosphorylation-dependent excitatory role. This study unveils the molecular underpinnings of allosteric connectivity within CFTR and highlights a novel allosteric 'hotspot' that could serve as a promising target for the development of novel therapeutic interventions.
Collapse
Affiliation(s)
- Ayca Ersoy
- Department of Chemical Engineering, Bogazici UniversityIstanbulTurkey
- Polymer Research Center, Bogazici UniversityIstanbulTurkey
| | - Bengi Altintel
- Department of Chemical Engineering, Bogazici UniversityIstanbulTurkey
- Polymer Research Center, Bogazici UniversityIstanbulTurkey
| | - Nurit Livnat Levanon
- Department of Molecular Microbiology, Bruce and Ruth Rappaport Faculty of Medicine, Technion-Israel Institute of TechnologyTel AvivIsrael
| | - Nir Ben-Tal
- Department of Biochemistry and Molecular Biology, Faculty of Life Sciences, Tel-Aviv UniversityTel-AvivIsrael
| | - Turkan Haliloglu
- Department of Chemical Engineering, Bogazici UniversityIstanbulTurkey
- Polymer Research Center, Bogazici UniversityIstanbulTurkey
| | - Oded Lewinson
- Department of Molecular Microbiology, Bruce and Ruth Rappaport Faculty of Medicine, Technion-Israel Institute of TechnologyTel AvivIsrael
| |
Collapse
|
3
|
Krieger JM, Sorzano COS, Carazo JM. Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing. Int J Mol Sci 2023; 24:14245. [PMID: 37762547 PMCID: PMC10532346 DOI: 10.3390/ijms241814245] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/10/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.
Collapse
Affiliation(s)
- James M. Krieger
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
| | | | - Jose Maria Carazo
- Biocomputing Unit, National Centre for Biotechnology (CNB CSIC), Campus Universidad Autónoma de Madrid, Darwin 3, Cantoblanco, 28049 Madrid, Spain
| |
Collapse
|
4
|
Gasparini P, Philot EA, Pantaleão SQ, Torres-Bonfim NESM, Kliousoff A, Quiroz RCN, Perahia D, Simões RP, Magro AJ, Scott AL. Unveiling mutation effects on the structural dynamics of the main protease from SARS-CoV-2 with hybrid simulation methods. J Mol Graph Model 2023; 121:108443. [PMID: 36870228 PMCID: PMC9945984 DOI: 10.1016/j.jmgm.2023.108443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 02/15/2023] [Accepted: 02/21/2023] [Indexed: 02/25/2023]
Abstract
The main protease of SARS-CoV-2 (called Mpro or 3CLpro) is essential for processing polyproteins encoded by viral RNA. Several Mpro mutations were found in SARS-CoV-2 variants, which are related to higher transmissibility, pathogenicity, and resistance to neutralization antibodies. Macromolecules adopt several favored conformations in solution depending on their structure and shape, determining their dynamics and function. In this study, we used a hybrid simulation method to generate intermediate structures along the six lowest frequency normal modes and sample the conformational space and characterize the structural dynamics and global motions of WT SARS-CoV-2 Mpro and 48 mutations, including mutations found in P.1, B.1.1.7, B.1.351, B.1.525 and B.1.429+B.1.427 variants. We tried to contribute to the elucidation of the effects of mutation in the structural dynamics of SARS-CoV-2 Mpro. A machine learning analysis was performed following the investigation regarding the influence of the K90R, P99L, P108S, and N151D mutations on the dimeric interface assembling of the SARS-CoV-2 Mpro. The parameters allowed the selection of potential structurally stable dimers, which demonstrated that some single surface aa substitutions not located at the dimeric interface (K90R, P99L, P108S, and N151D) are able to induce significant quaternary changes. Furthermore, our results demonstrated, by a Quantum Mechanics method, the influence of SARS-CoV-2 Mpro mutations on the catalytic mechanism, confirming that only one of the chains of the WT and mutant SARS-CoV-2 Mpros are prone to cleave substrates. Finally, it was also possible to identify the aa residue F140 as an important factor related to the increasing enzymatic reactivity of a significant number of SARS-CoV-2 Mpro conformations generated by the normal modes-based simulations.
Collapse
Affiliation(s)
- P Gasparini
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil
| | - E A Philot
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil
| | - S Q Pantaleão
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil
| | - N E S M Torres-Bonfim
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil
| | - A Kliousoff
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil
| | - R C N Quiroz
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil
| | - D Perahia
- École Normale Supérieure Paris-Saclay, LBPA, Scaly, France
| | - R P Simões
- Department of Bioprocesses and Biotechnology, School of Agriculture (FCA), Unesp, Botucatu, São Paulo, Brazil
| | - A J Magro
- Department of Bioprocesses and Biotechnology, School of Agriculture (FCA), Unesp, Botucatu, São Paulo, Brazil; Institute of Biotechnology (IBTEC), Unesp, Botucatu, São Paulo, Brazil
| | - A L Scott
- Computational Biology and Biophysics Laboratory, Federal University of ABC - UFABC, Santo André, São Paulo, Brazil.
| |
Collapse
|
5
|
Banerjee A, Saha S, Tvedt NC, Yang LW, Bahar I. Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods. Curr Opin Struct Biol 2023; 78:102517. [PMID: 36587424 PMCID: PMC10038760 DOI: 10.1016/j.sbi.2022.102517] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/19/2022] [Accepted: 11/22/2022] [Indexed: 12/31/2022]
Abstract
Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in, if not determine, viable mechanisms of biological function. In recent years, machine learning frameworks have proven uniquely useful in structural biology, and recent studies further provide evidence to the utility and/or necessity of considering intrinsic dynamics for increasing their predictive ability. Efficient quantification of dynamics-based attributes by recently developed physics-based theories and models such as elastic network models provides a unique opportunity to generate data on dynamics for training ML models towards inferring mechanisms of protein function, assessing pathogenicity, or estimating binding affinities.
Collapse
Affiliation(s)
- Anupam Banerjee
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA
| | - Satyaki Saha
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA
| | - Nathan C Tvedt
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA; Computational and Applied Mathematics and Statistics, The College of William and Mary, Williamsburg, VA 23185, USA
| | - Lee-Wei Yang
- Institute of Bioinformatics and Structural Biology, and PhD Program in Biomedical Artificial Intelligence, National Tsing Hua University, Hsinchu 300044, Taiwan; Physics Division, National Center for Theoretical Sciences, Taipei 106319, Taiwan
| | - Ivet Bahar
- Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh PA 15261, USA.
| |
Collapse
|
6
|
Costa MGS, Batista PR, Gomes A, Bastos LS, Louet M, Floquet N, Bisch PM, Perahia D. MDexciteR: Enhanced Sampling Molecular Dynamics by Excited Normal Modes or Principal Components Obtained from Experiments. J Chem Theory Comput 2023; 19:412-425. [PMID: 36622950 DOI: 10.1021/acs.jctc.2c00599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Molecular dynamics with excited normal modes (MDeNM) is an enhanced sampling method for exploring conformational changes in proteins with minimal biases. The excitation corresponds to injecting kinetic energy along normal modes describing intrinsic collective motions. Herein, we developed a new automated open-source implementation, MDexciteR (https://github.com/mcosta27/MDexciteR), enabling the integration of MDeNM with two commonly used simulation programs with GPU support. Second, we generalized the method to include the excitation of principal components calculated from experimental ensembles. Finally, we evaluated whether the use of coarse-grained normal modes calculated with elastic network representations preserved the performance and accuracy of the method. The advantages and limitations of these new approaches are discussed based on results obtained for three different protein test cases: two globular and a protein/membrane system.
Collapse
Affiliation(s)
- Mauricio G S Costa
- Programa de Computação Científica, Vice-Presidência de Educação Informação e Comunicação, Fundação Oswaldo Cruz, Av. Brasil 4365, Residência Oficial, Manguinhos, 21040-900Rio de Janeiro, Brasil
- Laboratoire de Biologie et de Pharmacologie Appliquée (LBPA), UMR 8113, CNRS, École Normale Supérieure Paris-Saclay, 4 Avenue des Sciences, 91190Gif-sur-Yvette, France
| | - Paulo R Batista
- Programa de Computação Científica, Vice-Presidência de Educação Informação e Comunicação, Fundação Oswaldo Cruz, Av. Brasil 4365, Residência Oficial, Manguinhos, 21040-900Rio de Janeiro, Brasil
| | - Antoniel Gomes
- Laboratório de Física Biológica, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro21941-902, Brasil
| | - Leonardo S Bastos
- Programa de Computação Científica, Vice-Presidência de Educação Informação e Comunicação, Fundação Oswaldo Cruz, Av. Brasil 4365, Residência Oficial, Manguinhos, 21040-900Rio de Janeiro, Brasil
| | - Maxime Louet
- Institut des Biomolecules Max Mousseron, UMR5247, CNRS, Université De Montpellier, ENSCM, 1919 Route de Mende, Montpellier, Cedex 0534095, France
| | - Nicolas Floquet
- Institut des Biomolecules Max Mousseron, UMR5247, CNRS, Université De Montpellier, ENSCM, 1919 Route de Mende, Montpellier, Cedex 0534095, France
| | - Paulo M Bisch
- Laboratório de Física Biológica, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro21941-902, Brasil
| | - David Perahia
- Laboratoire de Biologie et de Pharmacologie Appliquée (LBPA), UMR 8113, CNRS, École Normale Supérieure Paris-Saclay, 4 Avenue des Sciences, 91190Gif-sur-Yvette, France
| |
Collapse
|
7
|
Quiroz RCN, Philot EA, General IJ, Perahia D, Scott AL. Effect of phosphorylation on the structural dynamics, thermal stability of human dopamine transporter: A simulation study using normal modes, molecular dynamics and Markov State Model. J Mol Graph Model 2023; 118:108359. [PMID: 36279761 DOI: 10.1016/j.jmgm.2022.108359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/04/2022] [Accepted: 10/06/2022] [Indexed: 11/06/2022]
Abstract
The Human Dopamine Transporter (hDAT) plays an essential role in modulating the Influx/Efflux of dopamine, and it is involved in the mechanism of certain neurodegenerative diseases such as Parkinson's disease. Several studies have reported important states for Dopamine transport: outward-facing open state (OFo), the outward-facing closed state (OFc), the holo-occluded state closed (holo), and the inward-facing open state (IFo). Furthermore, experimental assays have shown that different phosphorylation conditions in hDAT can affect the rate of dopamine absorption. We present a protocol using hybrid simulation methods to study the conformational dynamics and stability of states of hDAT under different phosphorylation sites. With this protocol, we explored the conformational space of hDAT, identified the states, and evaluated the free energy differences and the transition probabilities between them in each of the phosphorylation cases. We also presented the conformational changes and correlated them with those described in the literature. There is a thesis/hypothesis that the phosphorylation condition corresponding to NP-333 system (where all sites Ser/Thr from residue 2 to 62 and 254 to 613 are phosphorylated, except residue 333) would decrease the rate of dopamine transport from the extracellular medium to the intracellular medium by hDAT as previously described in the literature by Lin et al., 2003. Our results corroborated this thesis/hypothesis and the data reported. It is probably due to the affectation/changes/alteration of the conformational dynamics of this system that makes the intermediate states more likely and makes it difficult to initial states associated with the uptake of dopamine in the extracellular medium, corroborating the experimental results. Furthermore, our results showed that just single phosphorylation/dephosphorylation could alter intrinsic protein motions affecting the sampling of one or more states necessary for dopamine transport. In this sense, the modification of phosphorylation influences protein movements and conformational preferences, affecting the stability of states and the transition between them and, therefore, the transport.
Collapse
Affiliation(s)
- R C N Quiroz
- Biossistemas, Universidade Federal do ABC, CCNH, Santo André, Brazil; Centro de Matemática, Computação e Cognição. Laboratório de Biofísica e Biologia Computacional. Universidade Federal do ABC, Santo André, São Paulo, Brazil
| | - E A Philot
- Centro de Matemática, Computação e Cognição. Laboratório de Biofísica e Biologia Computacional. Universidade Federal do ABC, Santo André, São Paulo, Brazil
| | - I J General
- School of Science and Technology, Universidad Nacional de San Martin, ICIFI and CONICET, 25 de Mayo y Francia, San Martín, 1650, Buenos Aires, Argentina
| | - D Perahia
- Laboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, UMR 8113, CNRS, 4 avenue des Sciences, 91190 Gif-sur-Yvette, France
| | - A L Scott
- UFABC - Universidade Federal Do ABC, Centro de Matemática, Computação e Cognição, Laboratório de Biofísica e Biologia Computacional, Brazil.
| |
Collapse
|
8
|
Dasgupta B, Tiwari SP. Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics. Biophys Rev 2022; 14:1379-1392. [PMID: 36659985 PMCID: PMC9842844 DOI: 10.1007/s12551-022-01026-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/27/2022] [Indexed: 12/23/2022] Open
Abstract
The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.
Collapse
Affiliation(s)
- Bhaskar Dasgupta
- Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-Ku, Tokyo, 153-8904 Japan
| | - Sandhya P. Tiwari
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima City, 1-3-1 Kagamiyama, Hiroshima, 739-8526 Japan
- Present Address: Institute of Protein Research, Osaka University, 3-2 Yamadaoka, Suita-Shi, Osaka, 565-0871 Japan
| |
Collapse
|
9
|
Docking-based long timescale simulation of cell-size protein systems at atomic resolution. Proc Natl Acad Sci U S A 2022; 119:e2210249119. [PMID: 36191203 PMCID: PMC9565162 DOI: 10.1073/pnas.2210249119] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Advances in computational modeling have led to an increasing focus on larger biomolecular systems, up to the level of a cell. Protein interactions are a central component of cellular processes. Techniques for modeling protein interactions have been divided between two fields: protein docking (predicting the static structures of protein complexes) and molecular simulation (modeling the dynamics of protein association, for relatively short simulation times at atomic resolution). Our study combined the two approaches to reach very long simulation times. The study makes the model more adequate to the real cells, to explore cellular processes at atomic resolution to better understand molecular mechanisms of life, and to use this knowledge to improve our ability to treat diseases. Computational methodologies are increasingly addressing modeling of the whole cell at the molecular level. Proteins and their interactions are the key component of cellular processes. Techniques for modeling protein interactions, thus far, have included protein docking and molecular simulation. The latter approaches account for the dynamics of the interactions but are relatively slow, if carried out at all-atom resolution, or are significantly coarse grained. Protein docking algorithms are far more efficient in sampling spatial coordinates. However, they do not account for the kinetics of the association (i.e., they do not involve the time coordinate). Our proof-of-concept study bridges the two modeling approaches, developing an approach that can reach unprecedented simulation timescales at all-atom resolution. The global intermolecular energy landscape of a large system of proteins was mapped by the pairwise fast Fourier transform docking and sampled in space and time by Monte Carlo simulations. The simulation protocol was parametrized on existing data and validated on a number of observations from experiments and molecular dynamics simulations. The simulation protocol performed consistently across very different systems of proteins at different protein concentrations. It recapitulated data on the previously observed protein diffusion rates and aggregation. The speed of calculation allows reaching second-long trajectories of protein systems that approach the size of the cells, at atomic resolution.
Collapse
|
10
|
Krieger JM, Sorzano COS, Carazo JM, Bahar I. Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0. ACTA CRYSTALLOGRAPHICA SECTION D STRUCTURAL BIOLOGY 2022; 78:399-409. [PMID: 35362464 PMCID: PMC8972803 DOI: 10.1107/s2059798322001966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 02/18/2022] [Indexed: 11/24/2022]
Abstract
New computational biophysics pipelines for analysing the global dynamics of structural ensembles and large, dynamic complexes resolved by cryoEM are reviewed. Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.
Collapse
|
11
|
Naullage PM, Haghighatlari M, Namini A, Teixeira JMC, Li J, Zhang O, Gradinaru CC, Forman-Kay JD, Head-Gordon T. Protein Dynamics to Define and Refine Disordered Protein Ensembles. J Phys Chem B 2022; 126:1885-1894. [PMID: 35213160 PMCID: PMC10122607 DOI: 10.1021/acs.jpcb.1c10925] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Intrinsically disordered proteins and unfolded proteins have fluctuating conformational ensembles that are fundamental to their biological function and impact protein folding, stability, and misfolding. Despite the importance of protein dynamics and conformational sampling, time-dependent data types are not fully exploited when defining and refining disordered protein ensembles. Here we introduce a computational framework using an elastic network model and normal-mode displacements to generate a dynamic disordered ensemble consistent with NMR-derived dynamics parameters, including transverse R2 relaxation rates and Lipari-Szabo order parameters (S2 values). We illustrate our approach using the unfolded state of the drkN SH3 domain to show that the dynamical ensembles give better agreement than a static ensemble for a wide range of experimental validation data including NMR chemical shifts, J-couplings, nuclear Overhauser effects, paramagnetic relaxation enhancements, residual dipolar couplings, hydrodynamic radii, single-molecule fluorescence Förster resonance energy transfer, and small-angle X-ray scattering.
Collapse
Affiliation(s)
- Pavithra M Naullage
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Mojtaba Haghighatlari
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Ashley Namini
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - João M C Teixeira
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Jie Li
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Oufan Zhang
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Claudiu C Gradinaru
- Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, 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
| | - Teresa Head-Gordon
- Pitzer Center for Theoretical Chemistry, University of California, Berkeley, California 94720, United States
- Department of Chemistry, University of California, Berkeley, California 94720, United States
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States
- Department of Bioengineering, University of California, Berkeley, California 94720, United States
| |
Collapse
|
12
|
Kaynak BT, Krieger JM, Dudas B, Dahmani ZL, Costa MGS, Balog E, Scott AL, Doruker P, Perahia D, Bahar I. Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods. Front Mol Biosci 2022; 9:832847. [PMID: 35187088 PMCID: PMC8855042 DOI: 10.3389/fmolb.2022.832847] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/12/2022] [Indexed: 12/17/2022] Open
Abstract
Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.
Collapse
Affiliation(s)
- Burak T. Kaynak
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - James M. Krieger
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Balint Dudas
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Laboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, Gif-sur-Yvette, France
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary
| | - Zakaria L. Dahmani
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mauricio G. S. Costa
- Programa de Computação Científica, Vice-Presiden̂cia de Educação, Informação e Comunicação, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Erika Balog
- Department of Biophysics and Radiation Biology, Semmelweis University, Budapest, Hungary
| | - Ana Ligia Scott
- Laboratory of Bioinformatics and Computational Biology, Center of Mathematics, Computation and Cognition, Federal University of ABC-UFABC, Santo André, Brazil
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Ivet Bahar, ; David Perahia, ; Pemra Doruker,
| | - David Perahia
- Laboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, Gif-sur-Yvette, France
- *Correspondence: Ivet Bahar, ; David Perahia, ; Pemra Doruker,
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Ivet Bahar, ; David Perahia, ; Pemra Doruker,
| |
Collapse
|
13
|
Sanejouand YH. Normal-mode driven exploration of protein domain motions. J Comput Chem 2021; 42:2250-2257. [PMID: 34599620 DOI: 10.1002/jcc.26755] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/02/2021] [Accepted: 09/05/2021] [Indexed: 12/27/2022]
Abstract
Domain motions involved in the function of proteins can often be well described as a combination of motions along a handfull of low-frequency modes, that is, with the values of a few normal coordinates. This means that, when the functional motion of a protein is unknown, it should prove possible to predict it, since it amounts to guess a few values. However, without the help of additional experimental data, using normal coordinates for generating accurate conformers far away from the initial one is not so straightforward. To do so, a new approach is proposed: instead of building conformers directly with the values of a subset of normal coordinates, they are built in two steps, the conformer built with normal coordinates being just used for defining a set of distance constraints, the final conformer being built so as to match them. Note that this approach amounts to transform the problem of generating accurate protein conformers using normal coordinates into a better known one: the distance-geometry problem, which is herein solved with the help of the ROSETTA software. In the present study, this approach allowed to rebuild accurately six large amplitude conformational changes, using at most six low-frequency normal coordinates. As a consequence of the low-dimensionality of the corresponding subspace, random exploration also proved enough for generating low-energy conformers close to the known end-point of the conformational change of the LAO binding protein, lysozyme T4 and adenylate kinase.
Collapse
|
14
|
Herreros D, Lederman RR, Krieger J, Jiménez-Moreno A, Martínez M, Myška D, Strelak D, Filipovic J, Bahar I, Carazo JM, Sanchez COS. Approximating deformation fields for the analysis of continuous heterogeneity of biological macromolecules by 3D Zernike polynomials. IUCRJ 2021; 8:992-1005. [PMID: 34804551 PMCID: PMC8562670 DOI: 10.1107/s2052252521008903] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 08/25/2021] [Indexed: 05/04/2023]
Abstract
Structural biology has evolved greatly due to the advances introduced in fields like electron microscopy. This image-capturing technique, combined with improved algorithms and current data processing software, allows the recovery of different conformational states of a macromolecule, opening new possibilities for the study of its flexibility and dynamic events. However, the ensemble analysis of these different conformations, and in particular their placement into a common variable space in which the differences and similarities can be easily recognized, is not an easy matter. To simplify the analysis of continuous heterogeneity data, this work proposes a new automatic algorithm that relies on a mathematical basis defined over the sphere to estimate the deformation fields describing conformational transitions among different structures. Thanks to the approximation of these deformation fields, it is possible to describe the forces acting on the molecules due to the presence of different motions. It is also possible to represent and compare several structures in a low-dimensional mapping, which summarizes the structural characteristics of different states. All these analyses are integrated into a common framework, providing the user with the ability to combine them seamlessly. In addition, this new approach is a significant step forward compared with principal component analysis and normal mode analysis of cryo-electron microscopy maps, avoiding the need to select components or modes and producing localized analysis.
Collapse
Affiliation(s)
- David Herreros
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin 3, Cantoblanco, Madrid 28049, Spain
| | - Roy R. Lederman
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, Pennsylvania, USA
| | - Amaya Jiménez-Moreno
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin 3, Cantoblanco, Madrid 28049, Spain
| | - Marta Martínez
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin 3, Cantoblanco, Madrid 28049, Spain
| | - David Myška
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - David Strelak
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin 3, Cantoblanco, Madrid 28049, Spain
- Faculty of Informatics, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - Jiri Filipovic
- Institute of Computer Science, Masaryk University, Botanická 68a, 60200 Brno, Czech Republic
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, Pennsylvania, USA
| | - Jose Maria Carazo
- Centro Nacional de Biotecnologia-CSIC, C/ Darwin 3, Cantoblanco, Madrid 28049, Spain
| | | |
Collapse
|
15
|
Kaynak BT, Zhang S, Bahar I, Doruker P. ClustENMD: Efficient sampling of biomolecular conformational space at atomic resolution. Bioinformatics 2021; 37:3956-3958. [PMID: 34240100 PMCID: PMC8570821 DOI: 10.1093/bioinformatics/btab496] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/08/2021] [Accepted: 07/02/2021] [Indexed: 11/30/2022] Open
Abstract
Summary Efficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe a new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model for deformations along global modes, followed by clustering and short molecular dynamics simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace. Availability and implementation ClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Burak T Kaynak
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| |
Collapse
|
16
|
He XL, Du LF, Zhang J, Liang Y, Wu YD, Su JG, Li QM. The functional motions and related key residues behind the uncoating of coxsackievirus A16. Proteins 2021; 89:1365-1375. [PMID: 34085313 DOI: 10.1002/prot.26157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 05/09/2021] [Accepted: 06/01/2021] [Indexed: 11/05/2022]
Abstract
The coxsackievirus A16 (CVA16) is a highly contagious virus that causes the hand, foot, and mouth disease, which seriously threatens the health of children. At present, there are still no available antiviral drugs or effective treatments against the infection of CVA16, and thus it is of great significance to develop anti-CVA16 vaccines. However, the intrinsic uncoating property of the capsid may destroy the neutralizing epitopes and influence its immunogenicity, which hinders the vaccine developments. In the present work, the functional-quantity-based elastic network model analysis method developed by our group was extended to combine with group theory to investigate the uncoating motions of the CVA16 capsid, and then the functionally key residues controlling the uncoating motions were identified by our functional-quantity-based perturbation method. Several motion modes encoded in the topological structure of the capsid were revealed to be responsible for the uncoating of CVA16 particle. These modes predominantly contribute to the fluctuation of the gyration radius of the capsid. Then, by using the perturbation method, four clusters of key sites involved in the uncoating motions were identified, whose perturbations induce significant changes in the fluctuation of the gyration radius. These key residues are mainly located at the 2-fold channels, the quasi 3-fold channels, the bottom of the canyons, and the inter-subunit interfaces around the 3-fold axes. Our studies are helpful for better understanding the uncoating mechanism of the CVA16 capsid and provide potential target sites to prevent the uncoating motions, which is valuable for the vaccine design against CVA16.
Collapse
Affiliation(s)
- Xing Long He
- Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao, China
| | - Li Fang Du
- The Sixth Laboratory, National Vaccine and Serum Institute, Beijing, China
| | - Jing Zhang
- The Sixth Laboratory, National Vaccine and Serum Institute, Beijing, China
| | - Yu Liang
- The Sixth Laboratory, National Vaccine and Serum Institute, Beijing, China
| | - Yi Dong Wu
- Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao, China
| | - Ji Guo Su
- Key Laboratory for Microstructural Material Physics of Hebei Province, School of Science, Yanshan University, Qinhuangdao, China.,The Sixth Laboratory, National Vaccine and Serum Institute, Beijing, China
| | - Qi Ming Li
- The Sixth Laboratory, National Vaccine and Serum Institute, Beijing, China
| |
Collapse
|
17
|
Revealing the activation mechanism of autoinhibited RalF by integrated simulation and experimental approaches. Sci Rep 2021; 11:10059. [PMID: 33980916 PMCID: PMC8115643 DOI: 10.1038/s41598-021-89169-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 04/19/2021] [Indexed: 12/11/2022] Open
Abstract
RalF is an Arf GEF from Legionella pneumophilia, the bacterium that causes severe pneumonia. In its crystal structure, RalF is in the autoinhibited form. A large-scale domain motion is expected to lift the autoinhibition, the mechanism of which is still unknown. Since RalF is activated in the presence of the membrane, its active structure and the structure of the RalF-Arf1 complex could not have been determined experimentally. On the simulation side, it has been proven that classical Molecular Dynamics (MD) alone is not efficient enough to map motions of such amplitude and determine the active conformation of RalF. In this article, using Molecular Dynamics with excited Normal Modes (MDeNM) combined with previous experimental findings we were able to determine the active RalF structure and the structure of the RalF-Arf1 complex in the presence of the membrane, bridging the gap between experiments and simulation.
Collapse
|
18
|
Singh N, Villoutreix BO. Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: Lessons from the pandemic and preparing for future health crises. Comput Struct Biotechnol J 2021; 19:2537-2548. [PMID: 33936562 PMCID: PMC8074526 DOI: 10.1016/j.csbj.2021.04.059] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/22/2021] [Accepted: 04/24/2021] [Indexed: 12/11/2022] Open
Abstract
There is an urgent need to identify new therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients. This pandemic has thus spurred intensive research in most scientific areas and in a short period of time, several vaccines have been developed. But, while the race to find vaccines for COVID-19 has dominated the headlines, other types of therapeutic agents are being developed. In this mini-review, we report several databases and online tools that could assist the discovery of anti-SARS-CoV-2 small chemical compounds and peptides. We then give examples of studies that combined in silico and in vitro screening, either for drug repositioning purposes or to search for novel bioactive compounds. Finally, we question the overall lack of discussion and plan observed in academic research in many countries during this crisis and suggest that there is room for improvement.
Collapse
Affiliation(s)
- Natesh Singh
- Université de Paris, Inserm UMR 1141 NeuroDiderot, Robert-Debré Hospital, 75019 Paris, France
| | - Bruno O. Villoutreix
- Université de Paris, Inserm UMR 1141 NeuroDiderot, Robert-Debré Hospital, 75019 Paris, France
| |
Collapse
|
19
|
Hu G, Doruker P, Li H, Demet Akten E. Editorial: Understanding Protein Dynamics, Binding and Allostery for Drug Design. Front Mol Biosci 2021; 8:681364. [PMID: 33968997 PMCID: PMC8097160 DOI: 10.3389/fmolb.2021.681364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 03/25/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou, China
| | - Pemra Doruker
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Hongchun Li
- Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ebru Demet Akten
- Department of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey
| |
Collapse
|
20
|
Zhang Y, Krieger J, Mikulska-Ruminska K, Kaynak B, Sorzano COS, Carazo JM, Xing J, Bahar I. State-dependent sequential allostery exhibited by chaperonin TRiC/CCT revealed by network analysis of Cryo-EM maps. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2021; 160:104-120. [PMID: 32866476 PMCID: PMC7914283 DOI: 10.1016/j.pbiomolbio.2020.08.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 06/25/2020] [Accepted: 08/16/2020] [Indexed: 12/17/2022]
Abstract
The eukaryotic chaperonin TRiC/CCT plays a major role in assisting the folding of many proteins through an ATP-driven allosteric cycle. Recent structures elucidated by cryo-electron microscopy provide a broad view of the conformations visited at various stages of the chaperonin cycle, including a sequential activation of its subunits in response to nucleotide binding. But we lack a thorough mechanistic understanding of the structure-based dynamics and communication properties that underlie the TRiC/CCT machinery. In this study, we present a computational methodology based on elastic network models adapted to cryo-EM density maps to gain a deeper understanding of the structure-encoded allosteric dynamics of this hexadecameric machine. We have analysed several structures of the chaperonin resolved in different states toward mapping its conformational landscape. Our study indicates that the overall architecture intrinsically favours cooperative movements that comply with the structural variabilities observed in experiments. Furthermore, the individual subunits CCT1-CCT8 exhibit state-dependent sequential events at different states of the allosteric cycle. For example, in the ATP-bound state, subunits CCT5 and CCT4 selectively initiate the lid closure motions favoured by the overall architecture; whereas in the apo form of the heteromer, the subunit CCT7 exhibits the highest predisposition to structural change. The changes then propagate through parallel fluxes of allosteric signals to neighbours on both rings. The predicted state-dependent mechanisms of sequential activation provide new insights into TRiC/CCT intra- and inter-ring signal transduction events.
Collapse
Affiliation(s)
- Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - James Krieger
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Karolina Mikulska-Ruminska
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Burak Kaynak
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | | | - José-María Carazo
- Centro Nacional de Biotecnología (CSIC), Darwin, 3, 28049, Madrid, Spain
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA
| | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, PA, 15261, USA.
| |
Collapse
|
21
|
Halder A, Anto A, Subramanyan V, Bhattacharyya M, Vishveshwara S, Vishveshwara S. Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case. Front Mol Biosci 2020; 7:596945. [PMID: 33392257 PMCID: PMC7775578 DOI: 10.3389/fmolb.2020.596945] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/04/2020] [Indexed: 02/04/2023] Open
Abstract
Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.
Collapse
Affiliation(s)
- Anushka Halder
- Department of Pharmacology, Yale University, New Haven, CT, United States
| | - Arinnia Anto
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India
| | - Varsha Subramanyan
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | | | - Smitha Vishveshwara
- Department of Physics, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | | |
Collapse
|