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Falkner S, Coretti A, Dellago C. Enhanced Sampling of Configuration and Path Space in a Generalized Ensemble by Shooting Point Exchange. PHYSICAL REVIEW LETTERS 2024; 132:128001. [PMID: 38579233 DOI: 10.1103/physrevlett.132.128001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 12/15/2023] [Accepted: 02/09/2024] [Indexed: 04/07/2024]
Abstract
The computer simulation of many molecular processes is complicated by long timescales caused by rare transitions between long-lived states. Here, we propose a new approach to simulate such rare events, which combines transition path sampling with enhanced exploration of configuration space. The method relies on exchange moves between configuration and trajectory space, carried out based on a generalized ensemble. This scheme substantially enhances the efficiency of the transition path sampling simulations, particularly for systems with multiple transition channels, and yields information on thermodynamics, kinetics and reaction coordinates of molecular processes without distorting their dynamics. The method is illustrated using the isomerization of proline in the KPTP tetrapeptide.
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Naleem N, Abreu CRA, Warmuz K, Tong M, Kirmizialtin S, Tuckerman ME. An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions. J Chem Phys 2023; 159:034102. [PMID: 37458344 DOI: 10.1063/5.0147597] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/23/2023] [Indexed: 07/20/2023] Open
Abstract
Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the "feature importance" approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.
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Affiliation(s)
- Nawavi Naleem
- Chemistry Program, Science Division, New York University, Abu Dhabi, UAE
| | - Charlles R A Abreu
- Chemical Engineering Department, Escola de Química, Universidade Federal do Rio de Janeiro, 21941-909 Rio de Janeiro, RJ, Brazil
| | - Krzysztof Warmuz
- Computer Science Program, Science Division, New York University, Abu Dhabi, UAE
| | - Muchen Tong
- Department of Chemistry, New York University (NYU), New York, New York 10003, USA
| | - Serdal Kirmizialtin
- Chemistry Program, Science Division, New York University, Abu Dhabi, UAE
- Department of Chemistry, New York University (NYU), New York, New York 10003, USA
- Center for Smart Engineering Materials, New York University, Abu Dhabi, UAE
| | - Mark E Tuckerman
- Department of Chemistry, New York University (NYU), New York, New York 10003, USA
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, 3663 Zhongshan Rd. North, Shanghai 200062, China
- Simons Center for Computational Physical Chemistry at New York University, New York, New York 10003, USA
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Magrino T, Huet L, Saitta AM, Pietrucci F. Critical Assessment of Data-Driven versus Heuristic Reaction Coordinates in Solution Chemistry. J Phys Chem A 2022; 126:8887-8900. [DOI: 10.1021/acs.jpca.2c07640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Théo Magrino
- Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, Sorbonne Université, Muséum National d’Histoire Naturelle, CNRS UMR 7590, Paris 75005, France
| | - Léon Huet
- Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, Sorbonne Université, Muséum National d’Histoire Naturelle, CNRS UMR 7590, Paris 75005, France
| | - A. Marco Saitta
- Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, Sorbonne Université, Muséum National d’Histoire Naturelle, CNRS UMR 7590, Paris 75005, France
| | - Fabio Pietrucci
- Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, Sorbonne Université, Muséum National d’Histoire Naturelle, CNRS UMR 7590, Paris 75005, France
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Alkorta I, Elguero J. The SN2 reaction and its relationship with the Walden inversion, the Finkelstein and Menshutkin reactions together with theoretical calculations for the Finkelstein reaction. Struct Chem 2021. [DOI: 10.1007/s11224-021-01805-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
AbstractThis communication gives an overview of the relationships between four reactions that although related were not always perceived as such: SN2, Walden, Finkelstein, and Menshutkin. Binary interactions (SN2 & Walden, SN2 & Menshutkin, SN2 & Finkelstein, Walden & Menshutkin, Walden & Finkelstein, Menshutkin & Finkelstein) were reported. Carbon, silicon, nitrogen, and phosphorus as central atoms and fluorides, chlorides, bromides, and iodides as lateral atoms were considered. Theoretical calculations provide Gibbs free energies that were analyzed with linear models to obtain the halide contributions. The M06-2x DFT computational method and the 6-311++G(d,p) basis set have been used for all atoms except for iodine where the effective core potential def2-TZVP basis set was used. Concerning the central atom pairs, carbon/silicon vs. nitrogen/phosphorus, we reported here for the first time that the effect of valence expansion was known for Si but not for P. Concerning the lateral halogen atoms, some empirical models including the interaction between F and I as entering and leaving groups explain the Gibbs free energies.
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Bolhuis PG, Swenson DWH. Transition Path Sampling as Markov Chain Monte Carlo of Trajectories: Recent Algorithms, Software, Applications, and Future Outlook. ADVANCED THEORY AND SIMULATIONS 2021. [DOI: 10.1002/adts.202000237] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Peter G. Bolhuis
- Amsterdam Center for Multiscale Modeling van 't Hoff Institute for Molecular Sciences University of Amsterdam PO Box 94157 1090 GD Amsterdam The Netherlands
| | - David W. H. Swenson
- Centre Blaise Pascal Ecole Normale Superieure 46, allée d'Italie 69364 Lyon Cedex 07 France
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Silveira RL, Knott BC, Pereira CS, Crowley MF, Skaf MS, Beckham GT. Transition Path Sampling Study of the Feruloyl Esterase Mechanism. J Phys Chem B 2021; 125:2018-2030. [PMID: 33616402 DOI: 10.1021/acs.jpcb.0c09725] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Serine hydrolases cleave peptide and ester bonds and are ubiquitous in nature, with applications in biotechnology, in materials, and as drug targets. The serine hydrolase two-step mechanism employs a serine-histidine-aspartate/glutamate catalytic triad, where the histidine residue acts as a base to activate poor nucleophiles (a serine residue or a water molecule) and as an acid to allow the dissociation of poor leaving groups. This mechanism has been the subject of debate regarding how histidine shuttles the proton from the nucleophile to the leaving group. To elucidate the reaction mechanism of serine hydrolases, we employ quantum mechanics/molecular mechanics-based transition path sampling to obtain the reaction coordinate using the Aspergillus niger feruloyl esterase A (AnFaeA) as a model enzyme. The optimal reaction coordinates include terms involving nucleophilic attack on the carbonyl carbon and proton transfer to, and dissociation of, the leaving group. During the reaction, the histidine residue undergoes a reorientation on the time scale of hundreds of femtoseconds that supports the "moving histidine" mechanism, thus calling into question the "ring flip" mechanism. We find a concerted mechanism, where the transition state coincides with the tetrahedral intermediate with the histidine residue pointed between the nucleophile and the leaving group. Moreover, motions of the catalytic aspartate toward the histidine occur concertedly with proton abstraction by the catalytic histidine and help stabilize the transition state, thus partially explaining how serine hydrolases enable poor nucleophiles to attack the substrate carbonyl carbon. Rate calculations indicate that the second step (deacylation) is rate-determining, with a calculated rate constant of 66 s-1. Overall, these results reveal the pivotal role of active-site dynamics in the catalytic mechanism of AnFaeA, which is likely similar in other serine hydrolases.
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Affiliation(s)
- Rodrigo L Silveira
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States.,Institute of Chemistry and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, Sao Paulo 13084-862, Brazil.,Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, RJ 21941-909, Brazil
| | - Brandon C Knott
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
| | - Caroline S Pereira
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States.,Institute of Chemistry and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, Sao Paulo 13084-862, Brazil
| | - Michael F Crowley
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
| | - Munir S Skaf
- Institute of Chemistry and Center for Computing in Engineering and Sciences, University of Campinas, Campinas, Sao Paulo 13084-862, Brazil
| | - Gregg T Beckham
- Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
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Levintov L, Paul S, Vashisth H. Reaction Coordinate and Thermodynamics of Base Flipping in RNA. J Chem Theory Comput 2021; 17:1914-1921. [PMID: 33594886 DOI: 10.1021/acs.jctc.0c01199] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Base flipping is a key biophysical event involved in recognition of various ligands by ribonucleic acid (RNA) molecules. However, the mechanism of base flipping in RNA remains poorly understood, in part due to the lack of atomistic details on complex rearrangements in neighboring bases. In this work, we applied transition path sampling (TPS) methods to study base flipping in a double-stranded RNA (dsRNA) molecule that is known to interact with RNA-editing enzymes through this mechanism. We obtained an ensemble of 1000 transition trajectories to describe the base-flipping process. We used the likelihood maximization method to determine the refined reaction coordinate (RC) consisting of two collective variables (CVs), a distance and a dihedral angle between nucleotides that form stacking interactions with the flipping base. The free energy profile projected along the refined RC revealed three minima, two corresponding to the initial and final states and one for a metastable state. We suggest that the metastable state likely represents a wobbled conformation of nucleobases observed in NMR studies that is often characterized as the flipped state. The analyses of reactive trajectories further revealed that the base flipping is coupled to a global conformational change in a stem-loop of dsRNA.
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Affiliation(s)
- Lev Levintov
- Department of Chemical Engineering, University of New Hampshire, Durham 03824, New Hampshire, United States
| | - Sanjib Paul
- Department of Chemistry, New York University, New York 10003, New York, United States
| | - Harish Vashisth
- Department of Chemical Engineering, University of New Hampshire, Durham 03824, New Hampshire, United States
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