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Koehl P, Navaza R, Tekpinar M, Delarue M. MinActionPath2: path generation between different conformations of large macromolecular assemblies by action minimization. Nucleic Acids Res 2024; 52:W256-W263. [PMID: 38783081 PMCID: PMC11223808 DOI: 10.1093/nar/gkae421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/25/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
Recent progress in solving macromolecular structures and assemblies by cryogenic electron microscopy techniques enables sampling of their conformations in different states that are relevant to their biological function. Knowing the transition path between these conformations would provide new avenues for drug discovery. While the experimental study of transition paths is intrinsically difficult, in-silico methods can be used to generate an initial guess for those paths. The Elastic Network Model (ENM), along with a coarse-grained representation (CG) of the structures are among the most popular models to explore such possible paths. Here we propose an update to our software platform MinActionPath that generates non-linear transition paths based on ENM and CG models, using action minimization to solve the equations of motion. The new website enables the study of large structures such as ribosomes or entire virus envelopes. It provides direct visualization of the trajectories along with quantitative analyses of their behaviors at http://dynstr.pasteur.fr/servers/minactionpath/minactionpath2_submission.
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Affiliation(s)
- Patrice Koehl
- Department of Computer Science and Genome Centre, University of California, Davis, CA 95616, USA
| | - Rafael Navaza
- Plateforme de Cristallographie, C2RT, Institut Pasteur, Université Paris Cité, UMR 3528 du CNRS, 75015 Paris, France
| | - Mustafa Tekpinar
- Unité Architecture et Dynamique des Macromolécules Biologiques, Institut Pasteur, Université Paris Cité, UMR 3528 du CNRS, 75015 Paris, France
| | - Marc Delarue
- Unité Architecture et Dynamique des Macromolécules Biologiques, Institut Pasteur, Université Paris Cité, UMR 3528 du CNRS, 75015 Paris, France
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Zaman AB, Inan TT, De Jong K, Shehu A. Adaptive Stochastic Optimization to Improve Protein Conformation Sampling. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:2759-2771. [PMID: 34882562 DOI: 10.1109/tcbb.2021.3134103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
We have long known that characterizing protein structures structure is key to understanding protein function. Computational approaches have largely addressed a narrow formulation of the problem, seeking to compute one native structure from an amino-acid sequence. Now AlphaFold2 is shown to be able to reveal a high-quality native structure for many proteins. However, researchers over the years have argued for broadening our view to account for the multiplicity of native structures. We now know that many protein molecules switch between different structures to regulate interactions with molecular partners in the cell. Elucidating such structures de novo is exceptionally difficult, as it requires exploration of possibly a very large structure space in search of competing, near-optimal structures. Here we report on a novel stochastic optimization method capable of revealing very different structures for a given protein from knowledge of its amino-acid sequence. The method leverages evolutionary search techniques and adapts its exploration of the search space to balance between exploration and exploitation in the presence of a computational budget. In addition to demonstrating the utility of this method for identifying multiple native structures, we additionally provide a benchmark dataset for researchers to continue work on this problem.
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Wong ZC, Ungur L. Deriving the vibronic coupling constants of the cyclopentadienyl radical with density functional theory and G0W0. J Chem Phys 2020; 153:064303. [DOI: 10.1063/5.0014753] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Zi Cheng Wong
- Department of Chemistry, National University of Singapore, Block S8 Level 3, 3 Science Drive 3, 117543, Singapore
| | - Liviu Ungur
- Department of Chemistry, National University of Singapore, Block S8 Level 3, 3 Science Drive 3, 117543, Singapore
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Grudinin S, Laine E, Hoffmann A. Predicting Protein Functional Motions: an Old Recipe with a New Twist. Biophys J 2020; 118:2513-2525. [PMID: 32330413 DOI: 10.1016/j.bpj.2020.03.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 03/09/2020] [Accepted: 03/18/2020] [Indexed: 01/21/2023] Open
Abstract
Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.
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Affiliation(s)
- Sergei Grudinin
- University Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France.
| | - Elodie Laine
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, France
| | - Alexandre Hoffmann
- University Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France
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Matsudaira PT, Verma CS. Editorial. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2019; 143:1-4. [PMID: 30951764 DOI: 10.1016/j.pbiomolbio.2019.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Paul T Matsudaira
- Department of Biological Science, National University of Singapore, 14 Science Drive 4, 117543, Singapore; Centre for BioImaging Sciences, National University of Singapore, 14 Science Drive 4, 117543, Singapore; MechanoBiology Institute, National University of Singapore, 5A Engineering Drive 1, 117411, Singapore.
| | - Chandra S Verma
- Department of Biological Science, National University of Singapore, 14 Science Drive 4, 117543, Singapore; School of Biological Sciences, Nanyang Technological University, 60 Nanyang Dr, 637551, Singapore; Bioinformatics Institute (A*STAR), 30 Biopolis Street, #07-01 Matrix, 138671, Singapore.
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Nguyen MK, Jaillet L, Redon S. Generating conformational transition paths with low potential-energy barriers for proteins. J Comput Aided Mol Des 2018; 32:853-867. [PMID: 30069648 DOI: 10.1007/s10822-018-0137-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 07/19/2018] [Indexed: 10/28/2022]
Abstract
The knowledge of conformational transition paths in proteins can be useful for understanding protein mechanisms. Recently, we have introduced the As-Rigid-As-Possible (ARAP) interpolation method, for generating interpolation paths between two protein conformations. The method was shown to preserve well the rigidity of the initial conformation along the path. However, because the method is totally geometry-based, the generated paths may be inconsistent because the atom interactions are ignored. Therefore, in this article, we would like to introduce a new method to generate conformational transition paths with low potential-energy barriers for proteins. The method is composed of three processing stages. First, ARAP interpolation is used for generating an initial path. Then, the path conformations are enhanced by a clash remover. Finally, Nudged Elastic Band, a path-optimization method, is used to produce a low-energy path. Large energy reductions are found in the paths obtained from the method than in those obtained from the ARAP interpolation method alone. The results also show that ARAP interpolation is a good candidate for generating an initial path because it leads to lower potential-energy paths than two other common methods for path interpolation.
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Affiliation(s)
- Minh Khoa Nguyen
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP (Institute of Engineering Univ. Grenoble Alpes), LJK, 38000, Grenoble, France
| | - Léonard Jaillet
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP (Institute of Engineering Univ. Grenoble Alpes), LJK, 38000, Grenoble, France.
| | - Stéphane Redon
- Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP (Institute of Engineering Univ. Grenoble Alpes), LJK, 38000, Grenoble, France
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Zhai H, Alexandrova AN. Local Fluxionality of Surface-Deposited Cluster Catalysts: The Case of Pt 7 on Al 2O 3. J Phys Chem Lett 2018; 9:1696-1702. [PMID: 29551071 DOI: 10.1021/acs.jpclett.8b00379] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Subnano surface-supported catalytic clusters can be generally characterized by many low-energy isomers accessible at elevated temperatures of catalysis. The most stable isomer may not be the most catalytically active. Additionally, isomers may interconvert across barriers, i.e., exhibit fluxionality, during catalysis. To study the big picture of the cluster fluxional behavior, we model such a process as isomerization graph using bipartite matching algorithm, harmonic transition state theory, and paralleled nudged elastic band method. All the minimal energy paths form a minimum spanning tree (MST) of the original graph. Detailed inspection shows that, at temperatures typical for catalysis, the cluster geometry changes frequently within several regions in the MST, while transition across regions is less likely. As a further confirmation, the structural similarity analysis was additionally performed based on molecular dynamics trajectories. This local fluxionality picture provides a new perspective on understanding finite-temperate catalytic processes.
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Affiliation(s)
- Huanchen Zhai
- Department of Chemistry and Biochemistry , University of California, Los Angeles , Los Angeles , California 90095 , United States
| | - Anastassia N Alexandrova
- Department of Chemistry and Biochemistry , University of California, Los Angeles , Los Angeles , California 90095 , United States
- California NanoSystems Institute , Los Angeles , California 90095 , United States
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Delarue M, Koehl P, Orland H. Ab initio sampling of transition paths by conditioned Langevin dynamics. J Chem Phys 2017; 147:152703. [PMID: 29055326 DOI: 10.1063/1.4985651] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
We propose a novel stochastic method to generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time tf under a given potential U(x). These paths are sampled with a probability given by the overdamped Langevin dynamics. We show that these paths can be exactly generated by a local stochastic partial differential equation. This equation cannot be solved in general but we present several approximations that are valid either in the low temperature regime or in the presence of barrier crossing. We show that this method warrants the generation of statistically independent transition paths. It is computationally very efficient. We illustrate the method first on two simple potentials, the two-dimensional Mueller potential and the Mexican hat potential, and then on the multi-dimensional problem of conformational transitions in proteins using the "Mixed Elastic Network Model" as a benchmark.
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Affiliation(s)
- Marc Delarue
- Unité de Dynamique Structurale des Macromolécules, UMR 3528 du CNRS, Institut Pasteur, 75015 Paris, France
| | - Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis, California 95616, USA
| | - Henri Orland
- Institut de Physique Théorique, CEA, URA 2306 du CNRS, F-91191 Gif-sur-Yvette, France and Beijing Computational Science Research Center, Building 9, East Zone, ZPark II, No.10 East Xibeiwang Road, Haidian District, Beijing 100193, China
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Koehl P. Minimum action principle and shape dynamics. J R Soc Interface 2017; 14:rsif.2017.0031. [PMID: 28515327 DOI: 10.1098/rsif.2017.0031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 04/24/2017] [Indexed: 01/02/2023] Open
Abstract
In this paper, we propose a new method for computing a distance between two shapes embedded in three-dimensional space. Instead of comparing directly the geometric properties of the two shapes, we measure the cost of deforming one of the two shapes into the other. The deformation is computed as the geodesic between the two shapes in the space of shapes. The geodesic is found as a minimizer of the Onsager-Machlup action, based on an elastic energy for shapes that we define. Its length is set to be the integral of the action along that path; it defines an intrinsic quasi-metric on the space of shapes. We illustrate applications of our method to geometric morphometrics using three datasets representing bones and teeth of primates. Experiments on these datasets show that the variational quasi-metric we have introduced performs remarkably well both in shape recognition and in identifying evolutionary patterns, with success rates similar to, and in some cases better than, those obtained by expert observers.
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Affiliation(s)
- Patrice Koehl
- Department of Computer Science and Genome Center, University of California, Davis, CA 95616, USA
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Koehl P, Poitevin F, Navaza R, Delarue M. The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems. J Chem Theory Comput 2017; 13:1424-1438. [PMID: 28170254 DOI: 10.1021/acs.jctc.6b01136] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.
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Affiliation(s)
- Patrice Koehl
- Department of Computer Sciences and Genome Center, University of California, Davis , Davis, California 95616, United States
| | - Frédéric Poitevin
- Department of Structural Biology, Stanford University , Stanford, California 94305, United States.,Stanford PULSE Institute, SLAC National Accelerator Laboratory, Standford University , Menlo Park, California 94025, United States
| | - Rafael Navaza
- Platform of Crystallogenesis and Crystallography, CiTech, Institut Pasteur , 75015 Paris, France
| | - Marc Delarue
- Unité de Dynamique Structurale des Macromolécules, UMR 3528 du CNRS, Institut Pasteur , 75015 Paris, France
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