1
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Yan X, Qu C, Li Q, Zhu L, Tong HH, Liu H, Ouyang Q, Yao X. Multiscale calculations reveal new insights into the reaction mechanism between KRAS G12C and α, β-unsaturated carbonyl of covalent inhibitors. Comput Struct Biotechnol J 2024; 23:1408-1417. [PMID: 38616962 PMCID: PMC11015740 DOI: 10.1016/j.csbj.2024.03.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 03/29/2024] [Accepted: 03/29/2024] [Indexed: 04/16/2024] Open
Abstract
Utilizing α,β-unsaturated carbonyl group as Michael acceptors to react with thiols represents a successful strategy for developing KRASG12C inhibitors. Despite this, the precise reaction mechanism between KRASG12C and covalent inhibitors remains a subject of debate, primarily due to the absence of an appropriate residue capable of deprotonating the cysteine thiol as a base. To uncover this reaction mechanism, we first discussed the chemical reaction mechanism in solvent conditions via density functional theory (DFT) calculation. Based on this, we then proposed and validated the enzymatic reaction mechanism by employing quantum mechanics/molecular mechanics (QM/MM) calculation. Our QM/MM analysis suggests that, in biological conditions, proton transfer and nucleophilic addition may proceed through a concerted process to form an enolate intermediate, bypassing the need for a base catalyst. This proposed mechanism differs from previous findings. Following the formation of the enolate intermediate, solvent-assisted tautomerization results in the final product. Our calculations indicate that solvent-assisted tautomerization is the rate-limiting step in the catalytic cycle under biological conditions. On the basis of this reaction mechanism, the calculated kinact/ki for two inhibitors is consistent well with the experimental results. Our findings provide new insights into the reaction mechanism between the cysteine of KRASG12C and the covalent inhibitors and may provide valuable information for designing effective covalent inhibitors targeting KRASG12C and other similar targets.
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Affiliation(s)
- Xiao Yan
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
| | - Chuanhua Qu
- College of Pharmacy, National & Local Joint Engineering Research Center of Targeted and Innovative Therapeutics, Chongqing Key Laboratory of Kinase Modulators as Innovative Medicine, Chongqing University of Arts and Sciences, Chongqing 402160, China
| | - Qin Li
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
| | - Lei Zhu
- College of Pharmacy, Third Military Medical University, Shapingba, Chongqing 400038, China
| | - Henry H.Y. Tong
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
| | - Huanxiang Liu
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
| | - Qin Ouyang
- College of Pharmacy, Third Military Medical University, Shapingba, Chongqing 400038, China
| | - Xiaojun Yao
- Faculty of Applied Sciences, Macao Polytechnic University, Macao Special Administrative Region of China
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2
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Solov’yov AV, Verkhovtsev AV, Mason NJ, Amos RA, Bald I, Baldacchino G, Dromey B, Falk M, Fedor J, Gerhards L, Hausmann M, Hildenbrand G, Hrabovský M, Kadlec S, Kočišek J, Lépine F, Ming S, Nisbet A, Ricketts K, Sala L, Schlathölter T, Wheatley AEH, Solov’yov IA. Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment. Chem Rev 2024; 124:8014-8129. [PMID: 38842266 PMCID: PMC11240271 DOI: 10.1021/acs.chemrev.3c00902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 05/02/2024] [Accepted: 05/10/2024] [Indexed: 06/07/2024]
Abstract
This roadmap reviews the new, highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The Review highlights several recent advances in the field and provides a roadmap for the development of the field over the next decade. Condensed matter systems exposed to radiation can be inorganic, organic, or biological, finite or infinite, composed of different molecular species or materials, exist in different phases, and operate under different thermodynamic conditions. Many of the key phenomena related to the behavior of irradiated systems are very similar and can be understood based on the same fundamental theoretical principles and computational approaches. The multiscale nature of such phenomena requires the quantitative description of the radiation-induced effects occurring at different spatial and temporal scales, ranging from the atomic to the macroscopic, and the interlinks between such descriptions. The multiscale nature of the effects and the similarity of their manifestation in systems of different origins necessarily bring together different disciplines, such as physics, chemistry, biology, materials science, nanoscience, and biomedical research, demonstrating the numerous interlinks and commonalities between them. This research field is highly relevant to many novel and emerging technologies and medical applications.
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Affiliation(s)
| | | | - Nigel J. Mason
- School
of Physics and Astronomy, University of
Kent, Canterbury CT2 7NH, United
Kingdom
| | - Richard A. Amos
- Department
of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, U.K.
| | - Ilko Bald
- Institute
of Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany
| | - Gérard Baldacchino
- Université
Paris-Saclay, CEA, LIDYL, 91191 Gif-sur-Yvette, France
- CY Cergy Paris Université,
CEA, LIDYL, 91191 Gif-sur-Yvette, France
| | - Brendan Dromey
- Centre
for Light Matter Interactions, School of Mathematics and Physics, Queen’s University Belfast, Belfast BT7 1NN, United Kingdom
| | - Martin Falk
- Institute
of Biophysics of the Czech Academy of Sciences, Královopolská 135, 61200 Brno, Czech Republic
- Kirchhoff-Institute
for Physics, Heidelberg University, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany
| | - Juraj Fedor
- J.
Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Dolejškova 3, 18223 Prague, Czech Republic
| | - Luca Gerhards
- Institute
of Physics, Carl von Ossietzky University, Carl-von-Ossietzky-Str. 9-11, 26129 Oldenburg, Germany
| | - Michael Hausmann
- Kirchhoff-Institute
for Physics, Heidelberg University, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany
| | - Georg Hildenbrand
- Kirchhoff-Institute
for Physics, Heidelberg University, Im Neuenheimer Feld 227, 69120 Heidelberg, Germany
- Faculty
of Engineering, University of Applied Sciences
Aschaffenburg, Würzburger
Str. 45, 63743 Aschaffenburg, Germany
| | | | - Stanislav Kadlec
- Eaton European
Innovation Center, Bořivojova
2380, 25263 Roztoky, Czech Republic
| | - Jaroslav Kočišek
- J.
Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Dolejškova 3, 18223 Prague, Czech Republic
| | - Franck Lépine
- Université
Claude Bernard Lyon 1, CNRS, Institut Lumière
Matière, F-69622, Villeurbanne, France
| | - Siyi Ming
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield
Road, Cambridge CB2 1EW, United Kingdom
| | - Andrew Nisbet
- Department
of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, U.K.
| | - Kate Ricketts
- Department
of Targeted Intervention, University College
London, Gower Street, London WC1E 6BT, United Kingdom
| | - Leo Sala
- J.
Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Dolejškova 3, 18223 Prague, Czech Republic
| | - Thomas Schlathölter
- Zernike
Institute for Advanced Materials, University
of Groningen, Nijenborgh
4, 9747 AG Groningen, The Netherlands
- University
College Groningen, University of Groningen, Hoendiepskade 23/24, 9718 BG Groningen, The Netherlands
| | - Andrew E. H. Wheatley
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield
Road, Cambridge CB2 1EW, United Kingdom
| | - Ilia A. Solov’yov
- Institute
of Physics, Carl von Ossietzky University, Carl-von-Ossietzky-Str. 9-11, 26129 Oldenburg, Germany
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3
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Pöverlein MC, Hulm A, Dietschreit JCB, Kussmann J, Ochsenfeld C, Kaila VRI. QM/MM Free Energy Calculations of Long-Range Biological Protonation Dynamics by Adaptive and Focused Sampling. J Chem Theory Comput 2024; 20:5751-5762. [PMID: 38718352 DOI: 10.1021/acs.jctc.4c00199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Water-mediated proton transfer reactions are central for catalytic processes in a wide range of biochemical systems, ranging from biological energy conversion to chemical transformations in the metabolism. Yet, the accurate computational treatment of such complex biochemical reactions is highly challenging and requires the application of multiscale methods, in particular hybrid quantum/classical (QM/MM) approaches combined with free energy simulations. Here, we combine the unique exploration power of new advanced sampling methods with density functional theory (DFT)-based QM/MM free energy methods for multiscale simulations of long-range protonation dynamics in biological systems. In this regard, we show that combining multiple walkers/well-tempered metadynamics with an extended system adaptive biasing force method (MWE) provides a powerful approach for exploration of water-mediated proton transfer reactions in complex biochemical systems. We compare and combine the MWE method also with QM/MM umbrella sampling and explore the sampling of the free energy landscape with both geometric (linear combination of proton transfer distances) and physical (center of excess charge) reaction coordinates and show how these affect the convergence of the potential of mean force (PMF) and the activation free energy. We find that the QM/MM-MWE method can efficiently explore both direct and water-mediated proton transfer pathways together with forward and reverse hole transfer mechanisms in the highly complex proton channel of respiratory Complex I, while the QM/MM-US approach shows a systematic convergence of selected long-range proton transfer pathways. In this regard, we show that the PMF along multiple proton transfer pathways is recovered by combining the strengths of both approaches in a QM/MM-MWE/focused US (FUS) scheme and reveals new mechanistic insight into the proton transfer principles of Complex I. Our findings provide a promising basis for the quantitative multiscale simulations of long-range proton transfer reactions in biological systems.
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Affiliation(s)
- Maximilian C Pöverlein
- Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden
| | - Andreas Hulm
- Chair of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), 81377 Munich, Germany
| | - Johannes C B Dietschreit
- Chair of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), 81377 Munich, Germany
- Department of Material Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Jörg Kussmann
- Chair of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), 81377 Munich, Germany
| | - Christian Ochsenfeld
- Chair of Theoretical Chemistry, Department of Chemistry, University of Munich (LMU), 81377 Munich, Germany
- Max Planck Institute for Solid State Research, D-70569 Stuttgart, Germany
| | - Ville R I Kaila
- Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden
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4
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Mansour B, Gauld JW. Computational Insights into Amide Bond Formation Catalyzed by the Condensation Domain of Nonribosomal Peptide Synthetases. ACS OMEGA 2024; 9:28556-28563. [PMID: 38973878 PMCID: PMC11223147 DOI: 10.1021/acsomega.4c02531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 06/10/2024] [Accepted: 06/12/2024] [Indexed: 07/09/2024]
Abstract
Nonribosomal peptide synthetases (NRPSs) are important enzymes that synthesize an array of nongenetically encoded peptides. The latter have diverse physicochemical properties and roles. NRPSs are modular enzymes in which, for example, the condensation (C-) domain catalyzes the formation of amide bonds. The NRPS tyrocidine synthetase from Brevibacillus brevis is responsible for synthesizing the cyclic-peptide antibiotic tyrocidine. The first step is formation of an amide bond between a proline and phenylalanine which is catalyzed by a C-domain. In this study, a multiscale computational approach (molecular dynamics and QM/MM) has been used to investigate substrate binding and catalytic mechanism of the C-domain of tyrocidine synthetase. Overall, the mechanism is found to proceed through three exergonic steps in which an active site Histidine, His222, acts as a base and acid. First, His222 acts as a base to facilitate nucleophilic attack of the prolyl nitrogen at the phenylalanyl's carbonyl carbon. This is also the rate-limiting step with a free energy barrier of 38.8 kJ mol-1. The second step is collapse of the resulting tetrahedral intermediate with cleavage of the S-C bond between the phenylalanyl and its Ppant arm, along with formation of the above amide bond. Meanwhile, the now protonated His222 imidazole has rotated toward the newly formed thiolate of the Ppant arm. In the final step, His222 acts as an acid, protonating the thiolate and regenerating a neutral His222. The overall mechanism is found to be exergonic with the final product complex being 46.3 kJ mol-1 lower in energy than the initial reactant complex.
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Affiliation(s)
- Basel Mansour
- Department of Chemistry and
Biochemistry, University of Windsor, Windsor, Ontario N9B 3P4, Canada
| | - James W. Gauld
- Department of Chemistry and
Biochemistry, University of Windsor, Windsor, Ontario N9B 3P4, Canada
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5
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Jung J, Yagi K, Tan C, Oshima H, Mori T, Yu I, Matsunaga Y, Kobayashi C, Ito S, Ugarte La Torre D, Sugita Y. GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models. J Phys Chem B 2024; 128:6028-6048. [PMID: 38876465 PMCID: PMC11215777 DOI: 10.1021/acs.jpcb.4c02096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 06/16/2024]
Abstract
GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.
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Affiliation(s)
- Jaewoon Jung
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Cheng Tan
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Hiraku Oshima
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
- Graduate
School of Life Science, University of Hyogo, Harima Science Park City, Hyogo 678-1297, Japan
| | - Takaharu Mori
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department
of Chemistry, Tokyo University of Science, Shinjuku-ku, Tokyo 162-8601, Japan
| | - Isseki Yu
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Department
of Bioinformatics, Maebashi Institute of
Technology, Maebashi, Gunma 371-0816, Japan
| | - Yasuhiro Matsunaga
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Graduate
School of Science and Engineering, Saitama
University, Saitama 338-8570, Japan
| | - Chigusa Kobayashi
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Shingo Ito
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
| | - Diego Ugarte La Torre
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Computational
Biophysics Research Team, RIKEN Center for
Computational Science, Kobe, Hyogo 650-0047, Japan
- Theoretical
Molecular Science Laboratory, RIKEN Cluster
for Pioneering Research, Wako, Saitama 351-0198, Japan
- Laboratory
for Biomolecular Function Simulation, RIKEN
Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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6
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Lei YK, Yagi K, Sugita Y. Learning QM/MM potential using equivariant multiscale model. J Chem Phys 2024; 160:214109. [PMID: 38828815 DOI: 10.1063/5.0205123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Accepted: 05/09/2024] [Indexed: 06/05/2024] Open
Abstract
The machine learning (ML) method emerges as an efficient and precise surrogate model for high-level electronic structure theory. Its application has been limited to closed chemical systems without considering external potentials from the surrounding environment. To address this limitation and incorporate the influence of external potentials, polarization effects, and long-range interactions between a chemical system and its environment, the first two terms of the Taylor expansion of an electrostatic operator have been used as extra input to the existing ML model to represent the electrostatic environments. However, high-order electrostatic interaction is often essential to account for external potentials from the environment. The existing models based only on invariant features cannot capture significant distribution patterns of the external potentials. Here, we propose a novel ML model that includes high-order terms of the Taylor expansion of an electrostatic operator and uses an equivariant model, which can generate a high-order tensor covariant with rotations as a base model. Therefore, we can use the multipole-expansion equation to derive a useful representation by accounting for polarization and intermolecular interaction. Moreover, to deal with long-range interactions, we follow the same strategy adopted to derive long-range interactions between a target system and its environment media. Our model achieves higher prediction accuracy and transferability among various environment media with these modifications.
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Affiliation(s)
- Yao-Kun Lei
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198, Japan
- Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
- RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), Wako, Saitama 351-0198, Japan
- Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
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7
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Cournia Z, Chipot C. Applications of Free-Energy Calculations to Biomolecular Processes. A Collection. J Phys Chem B 2024; 128:3299-3301. [PMID: 38600851 DOI: 10.1021/acs.jpcb.4c01283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Affiliation(s)
- Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
| | - Christophe Chipot
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n◦7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy Cedex, France
- Department of Biochemistry and Molecular Biology, The University of Chicago, 929 East 57th Street W225, Chicago, Illinois 60637, United States
- Theoretical and Computational Biophysics Group, Beckman Institute, and Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
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8
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Cournia Z, Chipot C. Applications of Free-Energy Calculations to Biomolecular Processes. A Collection. J Chem Inf Model 2024; 64:2129-2131. [PMID: 38587007 DOI: 10.1021/acs.jcim.4c00349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Affiliation(s)
- Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
| | - Christophe Chipot
- Laboratoire International Associé Centre National de la Recherche Scientifique et University of Illinois at Urbana-Champaign, Unité Mixte de Recherche n◦7019, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy Cedex, France
- Department of Biochemistry and Molecular Biology, The University of Chicago, 929 East 57th Street W225, Chicago, Illinois 60637, United States
- Theoretical and Computational Biophysics Group, Beckman Institute, and Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
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9
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Nam K, Shao Y, Major DT, Wolf-Watz M. Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development. ACS OMEGA 2024; 9:7393-7412. [PMID: 38405524 PMCID: PMC10883025 DOI: 10.1021/acsomega.3c09084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/15/2024] [Accepted: 01/19/2024] [Indexed: 02/27/2024]
Abstract
Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey the field of computational enzymology, highlighting key principles governing enzyme mechanisms and discussing ongoing challenges and promising advances. Over the years, computer simulations have become indispensable in the study of enzyme mechanisms, with the integration of experimental and computational exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies have demonstrated the power of computer simulations in characterizing reaction pathways, transition states, substrate selectivity, product distribution, and dynamic conformational changes for various enzymes. Nevertheless, significant challenges remain in investigating the mechanisms of complex multistep reactions, large-scale conformational changes, and allosteric regulation. Beyond mechanistic studies, computational enzyme modeling has emerged as an essential tool for computer-aided enzyme design and the rational discovery of covalent drugs for targeted therapies. Overall, enzyme design/engineering and covalent drug development can greatly benefit from our understanding of the detailed mechanisms of enzymes, such as protein dynamics, entropy contributions, and allostery, as revealed by computational studies. Such a convergence of different research approaches is expected to continue, creating synergies in enzyme research. This review, by outlining the ever-expanding field of enzyme research, aims to provide guidance for future research directions and facilitate new developments in this important and evolving field.
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Affiliation(s)
- Kwangho Nam
- Department
of Chemistry and Biochemistry, University
of Texas at Arlington, Arlington, Texas 76019, United States
| | - Yihan Shao
- Department
of Chemistry and Biochemistry, University
of Oklahoma, Norman, Oklahoma 73019-5251, United States
| | - Dan T. Major
- Department
of Chemistry and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 52900, Israel
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10
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Shao Q, Xiong M, Li J, Hu H, Su H, Xu Y. Unraveling the catalytic mechanism of SARS-CoV-2 papain-like protease with allosteric modulation of C270 mutation using multiscale computational approaches. Chem Sci 2023; 14:4681-4696. [PMID: 37181765 PMCID: PMC10171076 DOI: 10.1039/d3sc00166k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 04/10/2023] [Indexed: 05/16/2023] Open
Abstract
Papain-like protease (PLpro) is a promising therapeutic target against SARS-CoV-2, but its restricted S1/S2 subsites pose an obstacle in developing active site-directed inhibitors. We have recently identified C270 as a novel covalent allosteric site for SARS-CoV-2 PLpro inhibitors. Here we present a theoretical investigation of the proteolysis reaction catalyzed by the wild-type SARS-CoV-2 PLpro as well as the C270R mutant. Enhanced sampling MD simulations were first performed to explore the influence of C270R mutation on the protease dynamics, and sampled thermodynamically favorable conformations were then submitted to MM/PBSA and QM/MM MD simulations for thorough characterization of the protease-substrate binding and covalent reactions. The disclosed proteolysis mechanism of PLpro, as characterized by the occurrence of proton transfer from the catalytic C111 to H272 prior to the substrate binding and with deacylation being the rate-determining step of the whole proteolysis process, is not completely identical to that of the 3C-like protease, another key cysteine protease of coronaviruses. The C270R mutation alters the structural dynamics of the BL2 loop that indirectly impairs the catalytic function of H272 and reduces the binding of the substrate with the protease, ultimately showing an inhibitory effect on PLpro. Together, these results provide a comprehensive understanding at the atomic level of the key aspects of SARS-CoV-2 PLpro proteolysis, including the catalytic activity allosterically regulated by C270 modification, which is crucial to the follow-up inhibitor design and development.
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Affiliation(s)
- Qiang Shao
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences Shanghai 201203 China
- University of Chinese Academy of Sciences Beijing 100049 China
| | - Muya Xiong
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences Shanghai 201203 China
- University of Chinese Academy of Sciences Beijing 100049 China
| | - Jiameng Li
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine Nanjing 210023 China
| | - Hangchen Hu
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences Hangzhou 310024 China
| | - Haixia Su
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences Shanghai 201203 China
| | - Yechun Xu
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences Shanghai 201203 China
- University of Chinese Academy of Sciences Beijing 100049 China
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine Nanjing 210023 China
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences Hangzhou 310024 China
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11
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Kubař T, Elstner M, Cui Q. Hybrid Quantum Mechanical/Molecular Mechanical Methods For Studying Energy Transduction in Biomolecular Machines. Annu Rev Biophys 2023; 52:525-551. [PMID: 36791746 PMCID: PMC10810093 DOI: 10.1146/annurev-biophys-111622-091140] [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: 02/17/2023]
Abstract
Hybrid quantum mechanical/molecular mechanical (QM/MM) methods have become indispensable tools for the study of biomolecules. In this article, we briefly review the basic methodological details of QM/MM approaches and discuss their applications to various energy transduction problems in biomolecular machines, such as long-range proton transports, fast electron transfers, and mechanochemical coupling. We highlight the particular importance for these applications of balancing computational efficiency and accuracy. Using several recent examples, we illustrate the value and limitations of QM/MM methodologies for both ground and excited states, as well as strategies for calibrating them in specific applications. We conclude with brief comments on several areas that can benefit from further efforts to make QM/MM analyses more quantitative and applicable to increasingly complex biological problems.
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Affiliation(s)
- T Kubař
- Institute of Physical Chemistry, Karlsruhe Institute of Technology, Karlsruhe, Germany;
| | - M Elstner
- Institute of Physical Chemistry, Karlsruhe Institute of Technology, Karlsruhe, Germany;
- Institute of Biological Interfaces (IBG-2), Karlsruhe Institute of Technology, Karlsruhe, Germany;
| | - Q Cui
- Department of Chemistry, Boston University, Boston, Massachusetts, USA;
- Department of Physics, Boston University, Boston, Massachusetts, USA
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
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12
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Ito S, Yagi K, Sugita Y. Allosteric regulation of β-reaction stage I in tryptophan synthase upon the α-ligand binding. J Chem Phys 2023; 158:115101. [PMID: 36948822 DOI: 10.1063/5.0134117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
Tryptophan synthase (TRPS) is a bifunctional enzyme consisting of α- and β-subunits that catalyzes the last two steps of L-tryptophan (L-Trp) biosynthesis. The first stage of the reaction at the β-subunit is called β-reaction stage I, which converts the β-ligand from an internal aldimine [E(Ain)] to an α-aminoacrylate [E(A-A)] intermediate. The activity is known to increase 3-10-fold upon the binding of 3-indole-D-glycerol-3'-phosphate (IGP) at the α-subunit. The effect of α-ligand binding on β-reaction stage I at the distal β-active site is not well understood despite the abundant structural information available for TRPS. Here, we investigate the β-reaction stage I by carrying out minimum-energy pathway searches based on a hybrid quantum mechanics/molecular mechanics (QM/MM) model. The free-energy differences along the pathway are also examined using QM/MM umbrella sampling simulations with QM calculations at the B3LYP-D3/aug-cc-pVDZ level of theory. Our simulations suggest that the sidechain orientation of βD305 near the β-ligand likely plays an essential role in the allosteric regulation: a hydrogen bond is formed between βD305 and the β-ligand in the absence of the α-ligand, prohibiting a smooth rotation of the hydroxyl group in the quinonoid intermediate, whereas the dihedral angle rotates smoothly after the hydrogen bond is switched from βD305-β-ligand to βD305-βR141. This switch could occur upon the IGP-binding at the α-subunit, as evidenced by the existing TRPS crystal structures.
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Affiliation(s)
- Shingo Ito
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
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13
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Kaur R, Nikkel DJ, Aboelnga MM, Wetmore SD. The Impact of DFT Functional, Cluster Model Size, and Implicit Solvation on the Structural Description of Single-Metal-Mediated DNA Phosphodiester Bond Cleavage: The Case Study of APE1. J Phys Chem B 2022; 126:10672-10683. [PMID: 36485014 DOI: 10.1021/acs.jpcb.2c06756] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Phosphodiester bond hydrolysis in nucleic acids is a ubiquitous reaction that can be facilitated by enzymes called nucleases, which often use metal ions to achieve catalytic function. While a two-metal-mediated pathway has been well established for many enzymes, there is growing support that some enzymes require only one metal for the catalytic step. Using human apurinic/apyrimidinic endonuclease (APE1) as a prototypical example and cluster models, this study clarifies the impact of DFT functional, cluster model size, and implicit solvation on single-metal-mediated phosphodiester bond cleavage and provides insight into how to efficiently model this chemistry. Initially, a model containing 69 atoms built from a high-resolution X-ray crystal structure is used to explore the reaction pathway mapped by a range of DFT functionals and basis sets, which provides support for the use of standard functionals (M06-2X and B3LYP-D3) to study this reaction. Subsequently, systematically increasing the model size to 185 atoms by including additional amino acids and altering residue truncation points highlights that small models containing only a few amino acids or β carbon truncation points introduce model strains and lead to incorrect metal coordination. Indeed, a model that contains all key residues (general base and acid, residues that stabilize the substrate, and amino acids that maintain the metal coordination) is required for an accurate structural depiction of the one-metal-mediated phosphodiester bond hydrolysis by APE1, which results in 185 atoms. The additional inclusion of the broader enzyme environment through continuum solvation models has negligible effects. The insights gained in the present work can be used to direct future computational studies of other one-metal-dependent nucleases to provide a greater understanding of how nature achieves this difficult chemistry.
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Affiliation(s)
- Rajwinder Kaur
- Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive West, Lethbridge, Alberta T1K 3M4, Canada
| | - Dylan J Nikkel
- Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive West, Lethbridge, Alberta T1K 3M4, Canada
| | - Mohamed M Aboelnga
- Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive West, Lethbridge, Alberta T1K 3M4, Canada.,Chemistry Department, Faculty of Science, Damietta University, New Damietta 34517, Egypt
| | - Stacey D Wetmore
- Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive West, Lethbridge, Alberta T1K 3M4, Canada
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14
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Matsunaga Y, Kamiya M, Oshima H, Jung J, Ito S, Sugita Y. Use of multistate Bennett acceptance ratio method for free-energy calculations from enhanced sampling and free-energy perturbation. Biophys Rev 2022; 14:1503-1512. [PMID: 36659993 PMCID: PMC9842838 DOI: 10.1007/s12551-022-01030-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 12/01/2022] [Indexed: 12/15/2022] Open
Abstract
Multistate Bennett acceptance ratio (MBAR) works as a method to analyze molecular dynamics (MD) simulation data after the simulations have been finished. It is widely used to estimate free-energy changes between different states and averaged properties at the states of interest. MBAR allows us to treat a wide range of states from those at different temperature/pressure to those with different model parameters. Due to the broad applicability, the MBAR equations are rather difficult to apply for free-energy calculations using different types of MD simulations including enhanced conformational sampling methods and free-energy perturbation. In this review, we first summarize the basic theory of the MBAR equations and categorize the representative usages into the following four: (i) perturbation, (ii) scaling, (iii) accumulation, and (iv) full potential energy. For each, we explain how to prepare input data using MD simulation trajectories for solving the MBAR equations. MBAR is also useful to estimate reliable free-energy differences using MD trajectories based on a semi-empirical quantum mechanics/molecular mechanics (QM/MM) model and ab initio QM/MM energy calculations on the MD snapshots. We also explain how to use the MBAR software in the GENESIS package, which we call mbar_analysis, for the four representative cases. The proposed estimations of free-energy changes and thermodynamic averages are effective and useful for various biomolecular systems.
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Affiliation(s)
- Yasuhiro Matsunaga
- grid.263023.60000 0001 0703 3735Graduate School of Science and Engineering, Saitama University, Saitama, Saitama 338-8570 Japan
| | - Motoshi Kamiya
- grid.467196.b0000 0001 2285 6123Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585 Japan
| | - Hiraku Oshima
- grid.508743.dLaboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan
| | - Jaewoon Jung
- grid.474693.bComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047 Japan
| | - Shingo Ito
- grid.7597.c0000000094465255Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198 Japan
| | - Yuji Sugita
- grid.508743.dLaboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan ,grid.474693.bComputational Biophysics Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047 Japan ,grid.7597.c0000000094465255Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Wako, Saitama 351-0198 Japan
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15
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Kulshrestha A, Punnathanam SN, Ayappa KG. Finite temperature string method with umbrella sampling using path collective variables: application to secondary structure change in a protein. SOFT MATTER 2022; 18:7593-7603. [PMID: 36165347 DOI: 10.1039/d2sm00888b] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The transition of an α-helix to a β-sheet in proteins is among the most complex conformational changes seen in biomolecular systems. Due to long time scales involved in the transition, it is challenging to study such protein conformational changes using direct molecular dynamics simulations. This limitation is typically overcome using an indirect approach wherein one computes the free energy landscape associated with the transition. Computation of free energy landscapes, however, requires a suitable set of collective variables that describe the transition. In this work, we demonstrate the use of path collective variables [D. Branduardi, F. L. Gervasio and M. Parrinello, J. Chem. Phys., 2007, 126, 054103] and combine it with the finite temperature string (FTS) method [E. Weinan, W. Ren and E. Vanden-Eijnden, J. Phys. Chem. B, 2005, 109, 6688-6693] to determine the molecular mechanisms involved during the structural transition of the mini G-protein from an α-helix to a β-hairpin. The transition from the α-helix proceeds via unfolding of the terminal residues, giving rise to a β-turn unfolded intermediate to eventually form the β-hairpin. Our proposed algorithm uses umbrella sampling simulations to simulate images along the string and the weighted histogram analysis to compute the free energy along the computed transition path. This work demonstrates that the string method in combination with path collective variables can be exploited to study complex protein conformational changes such as a complete change in the secondary structure.
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Affiliation(s)
- Avijeet Kulshrestha
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, 560012, India.
| | - Sudeep N Punnathanam
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, 560012, India.
| | - K Ganapathy Ayappa
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, 560012, India.
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16
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Sato K, Sasaki R, Matsuda R, Nakagawa M, Ekimoto T, Yamane T, Ikeguchi M, Tabata KV, Noji H, Kinbara K. Correction to "Supramolecular Mechanosensitive Potassium Channel Formed by Fluorinated Amphiphilic Cyclophane". J Am Chem Soc 2022; 144:13983-13984. [PMID: 35861320 DOI: 10.1021/jacs.2c07339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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17
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Talluri S. Engineering and Design of Programmable Genome Editors. J Phys Chem B 2022; 126:5140-5150. [PMID: 35819243 DOI: 10.1021/acs.jpcb.2c03761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Programmable genome editors are enzymes that can be targeted to a specific location in the genome for making site-specific alterations or deletions. The engineering, design, and development of sequence-specific editors has resulted in a dramatic increase in the precision of editing for nucleotide sequences. These editors can target specific locations in a genome, in vivo. The genome editors are being deployed for the development of genetically modified organisms for agriculture and industry, and for gene therapy of inherited human genetic disorders, cancer, and immunotherapy. Experimental and computational studies of structure, binding, activity, dynamics, and folding, reviewed here, have provided valuable insights that have the potential for increasing the functional efficiency of these gene/genome editors. Biochemical and biophysical studies of the specificities of natural and engineered genome editors reveal that increased binding affinity can be detrimental because of the increase of off-target effects and that the engineering and design of genome editors with higher specificity may require modulation and control of the conformational dynamics.
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Affiliation(s)
- Sekhar Talluri
- Department of Biotechnology, GITAM, Visakhapatnam, India 530045
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18
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Manathunga M, Götz AW, Merz KM. Computer-aided drug design, quantum-mechanical methods for biological problems. Curr Opin Struct Biol 2022; 75:102417. [PMID: 35779437 DOI: 10.1016/j.sbi.2022.102417] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/14/2022] [Accepted: 05/16/2022] [Indexed: 11/28/2022]
Abstract
Quantum chemistry enables to study systems with chemical accuracy (<1 kcal/mol from experiment) but is restricted to a handful of atoms due to its computational expense. This has led to ongoing interest to optimize and simplify these methods while retaining accuracy. Implementing quantum mechanical (QM) methods on modern hardware such as multiple-GPUs is one example of how the field is optimizing performance. Multiscale approaches like the so-called QM/molecular mechanical method are gaining popularity in drug discovery because they focus the application of QM methods on the region of choice (e.g., the binding site), while using efficient MM models to represent less relevant areas. The creation of simplified QM methods is another example, including the use of machine learning to create ultra-fast and accurate QM models. Herein, we summarize recent advancements in the development of optimized QM methods that enhance our ability to use these methods in computer aided drug discovery.
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Affiliation(s)
- Madushanka Manathunga
- Department of Chemistry and Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, United States. https://twitter.com/@MaduManathunga
| | - Andreas W Götz
- San Diego Supercomputer Center, University of California San Diego, La Jolla, CA 92093, United States. https://twitter.com/@awgoetz
| | - Kenneth M Merz
- Department of Chemistry and Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, United States.
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19
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Song Z, Trozzi F, Tian H, Yin C, Tao P. Mechanistic Insights into Enzyme Catalysis from Explaining Machine-Learned Quantum Mechanical and Molecular Mechanical Minimum Energy Pathways. ACS PHYSICAL CHEMISTRY AU 2022; 2:316-330. [PMID: 35936506 PMCID: PMC9344433 DOI: 10.1021/acsphyschemau.2c00005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
With the increasing popularity of machine learning (ML) applications, the demand for explainable artificial intelligence techniques to explain ML models developed for computational chemistry has also emerged. In this study, we present the development of the Boltzmann-weighted cumulative integrated gradients (BCIG) approach for effective explanation of mechanistic insights into ML models trained on high-level quantum mechanical and molecular mechanical (QM/MM) minimum energy pathways. Using the acylation reactions of the Toho-1 β-lactamase and two antibiotics (ampicillin and cefalexin) as the model systems, we show that the BCIG approach could quantitatively attribute the energetic contribution in one system and the relative reactivity of individual steps across different systems to specific chemical processes such as the bond making/breaking and proton transfers. The proposed BCIG contribution attribution method quantifies chemistry-interpretable insights in terms of contributions from each elementary chemical process, which is in agreement with the validating QM/MM calculations and our intuitive mechanistic understandings of the model reactions.
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20
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Ito S, Yagi K, Sugita Y. Computational Analysis on the Allostery of Tryptophan Synthase: Relationship between α/β-Ligand Binding and Distal Domain Closure. J Phys Chem B 2022; 126:3300-3308. [PMID: 35446577 PMCID: PMC9083551 DOI: 10.1021/acs.jpcb.2c01556] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Tryptophan synthase (TRPS) is a bifunctional enzyme consisting of α and β-subunits and catalyzes the last two steps of l-tryptophan (L-Trp) biosynthesis, namely, cleavage of 3-indole-d-glycerol-3'-phosphate (IGP) into indole and glyceraldehyde-3-phosphate (G3P) in the α-subunit, and a pyridoxal phosphate (PLP)-dependent reaction of indole and l-serine (L-Ser) to produce L-Trp in the β-subunit. Importantly, the IGP binding at the α-subunit affects the β-subunit conformation and its ligand-binding affinity, which, in turn, enhances the enzymatic reaction at the α-subunit. The intersubunit communications in TRPS have been investigated extensively for decades because of the fundamental and pharmaceutical importance, while it is still difficult to answer how TRPS allostery is regulated at the atomic detail. Here, we investigate the allosteric regulation of TRPS by all-atom classical molecular dynamics (MD) simulations and analyze the potential of mean-force (PMF) along conformational changes of the α- and β-subunits. The present simulation has revealed a widely opened conformation of the β-subunit, which provides a pathway for L-Ser to enter into the β-active site. The IGP binding closes the α-subunit and induces a wide opening of the β-subunit, thereby enhancing the binding affinity of L-Ser to the β-subunit. Structural analyses have identified critical hydrogen bonds (HBs) at the interface of the two subunits (αG181-βS178, αP57-βR175, etc.) and HBs between the β-subunit (βT110 - βH115) and a complex of PLP and L-Ser (an α-aminoacrylate intermediate). The former HBs regulate the allosteric, β-subunit opening, whereas the latter HBs are essential for closing the β-subunit in a later step. The proposed mechanism for how the interdomain communication in TRPS is realized with ligand bindings is consistent with the previous experimental data, giving a general idea to interpret the allosteric regulations in multidomain proteins.
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Affiliation(s)
- Shingo Ito
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Yuji Sugita
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.,Computational Biophysics Research Team, RIKEN Center for Computational Science, 7-1-26 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.,Laboratory for Biomolecular Function Simulation, RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
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21
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Derat E, Kamerlin SCL. Computational Advances in Protein Engineering and Enzyme Design. J Phys Chem B 2022; 126:2449-2451. [PMID: 35387452 DOI: 10.1021/acs.jpcb.2c01198] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Etienne Derat
- Institut Parisien de Chimie Moléculaire, UMR 8232 CNRS, Sorbonne Université, 75005 Paris, France
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22
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Demapan D, Kussmann J, Ochsenfeld C, Cui Q. Factors That Determine the Variation of Equilibrium and Kinetic Properties of QM/MM Enzyme Simulations: QM Region, Conformation, and Boundary Condition. J Chem Theory Comput 2022; 18:2530-2542. [PMID: 35226489 PMCID: PMC9652774 DOI: 10.1021/acs.jctc.1c00714] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
To analyze the impact of various technical details on the results of quantum mechanical (QM)/molecular mechanical (MM) enzyme simulations, including the QM region size, catechol-O-methyltransferase (COMT) is studied as a model system using an approximate QM/MM method (DFTB3/CHARMM). The results show that key equilibrium and kinetic properties for methyl transfer in COMT exhibit limited variations with respect to the size of the QM region, which ranges from ∼100 to ∼500 atoms in this study. With extensive sampling, local and global structural characteristics of the enzyme are largely conserved across the studied QM regions, while the nature of the transition state (e.g., secondary kinetic isotope effect) and reaction exergonicity are largely maintained. Deviations in the free energy profile with different QM region sizes are similar in magnitude to those observed with changes in other simulation protocols, such as different initial enzyme conformations and boundary conditions. Electronic structural properties, such as the covariance matrix of residual charge fluctuations, appear to exhibit rather long-range correlations, especially when the peptide backbone is included in the QM region; this observation holds when a range-separated DFT approach is used as the QM region, suggesting that delocalization error is unlikely the origin. Overall, the analyses suggest that multiple simulation details determine the results of QM/MM enzyme simulations with comparable contributions.
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Affiliation(s)
- Darren Demapan
- Department of Chemistry, University of Munich (LMU), Butenandtstr. 7 (C), D-81377 Munich, Germany.,Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Jörg Kussmann
- Department of Chemistry, University of Munich (LMU), Butenandtstr. 7 (C), D-81377 Munich, Germany
| | - Christian Ochsenfeld
- Department of Chemistry, University of Munich (LMU), Butenandtstr. 7 (C), D-81377 Munich, Germany
| | - Qiang Cui
- Departments of Chemistry, Physics and Biomedical Engineering, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
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23
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Lorenz-Fonfria VA, Yagi K, Ito S, Kandori H. Retinal Vibrations in Bacteriorhodopsin are Mechanically Harmonic but Electrically Anharmonic: Evidence From Overtone and Combination Bands. Front Mol Biosci 2022; 8:749261. [PMID: 34977154 PMCID: PMC8718751 DOI: 10.3389/fmolb.2021.749261] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/18/2021] [Indexed: 11/28/2022] Open
Abstract
Fundamental vibrations of the chromophore in the membrane protein bacteriorhodopsin (BR), a protonated Schiff base retinal, have been studied for decades, both by resonance Raman and by infrared (IR) difference spectroscopy. Such studies started comparing vibrational changes between the initial BR state (all-trans retinal) and the K intermediate (13-cis retinal), being later extended to the rest of intermediates. They contributed to our understanding of the proton-pumping mechanism of BR by exploiting the sensitivity of fundamental vibrational transitions of the retinal to its conformation. Here, we report on new bands in the 2,500 to 1,800 cm−1 region of the K-BR difference FT-IR spectrum. We show that the bands between 2,500 and 2,300 cm−1 originate from overtone and combination transitions from C-C stretches of the retinal. We assigned bands below 2,300 cm−1 to the combination of retinal C-C stretches with methyl rocks and with hydrogen-out-of-plane vibrations. Remarkably, experimental C-C overtone bands appeared at roughly twice the wavenumber of their fundamentals, with anharmonic mechanical constants ≤3.5 cm−1, and in some cases of ∼1 cm−1. Comparison of combination and fundamental bands indicates that most of the mechanical coupling constants are also very small. Despite the mechanical quasi-harmonicity of the C-C stretches, the area of their overtone bands was only ∼50 to ∼100 times smaller than of their fundamental bands. We concluded that electrical anharmonicity, the second mechanism giving intensity to overtone bands, must be particularly high for the retinal C-C stretches. We corroborated the assignments of negative bands in the K-BR difference FT-IR spectrum by ab initio anharmonic vibrational calculations of all-trans retinal in BR using a quantum-mechanics/molecular mechanics approach, reproducing reasonably well the small experimental anharmonic and coupling mechanical constants. Yet, and in spite accounting for both mechanical and electrical anharmonicities, the intensity of overtone C-C transitions was underestimated by a factor of 4–20, indicating room for improvement in state-of-the-art anharmonic vibrational calculations. The relatively intense overtone and combination bands of the retinal might open the possibility to detect retinal conformational changes too subtle to significantly affect fundamental transitions but leaving a footprint in overtone and combination transitions.
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Affiliation(s)
| | - Kiyoshi Yagi
- Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research, Saitama, Japan
| | - Shota Ito
- Department of Life Science and Applied Chemistry, Nagoya Institute of Technology, Nagoya, Japan
| | - Hideki Kandori
- Department of Life Science and Applied Chemistry, Nagoya Institute of Technology, Nagoya, Japan.,OptoBioTechnology Research Center, Nagoya Institute of Technology, Nagoya, Japan
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24
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Modeling Catalysis in Allosteric Enzymes: Capturing Conformational Consequences. Top Catal 2021; 65:165-186. [DOI: 10.1007/s11244-021-01521-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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25
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Yagi K, Re S, Mori T, Sugita Y. Weight average approaches for predicting dynamical properties of biomolecules. Curr Opin Struct Biol 2021; 72:88-94. [PMID: 34592697 DOI: 10.1016/j.sbi.2021.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 08/21/2021] [Accepted: 08/24/2021] [Indexed: 11/16/2022]
Abstract
Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.
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Affiliation(s)
- Kiyoshi Yagi
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Suyong Re
- RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; Artificial Intelligence Center for Health and Biomedical Research, National Institutes of Biomedical Innovation, Health, and Nutrition 7-6-8, Saito-Asagi, Ibaraki, Osaka, 567-0085, Japan
| | - Takaharu Mori
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Yuji Sugita
- RIKEN Cluster for Pioneering Research, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan; RIKEN Center for Biosystems Dynamics Research, 1-6-5 Minatojima-Minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan; RIKEN Center for Computational Science, 7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo 650-0047, Japan.
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Harder, better, faster, stronger: Large-scale QM and QM/MM for predictive modeling in enzymes and proteins. Curr Opin Struct Biol 2021; 72:9-17. [PMID: 34388673 DOI: 10.1016/j.sbi.2021.07.004] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/25/2021] [Accepted: 07/05/2021] [Indexed: 11/23/2022]
Abstract
Computational prediction of enzyme mechanism and protein function requires accurate physics-based models and suitable sampling. We discuss recent advances in large-scale quantum mechanical (QM) modeling of biochemical systems that have reduced the cost of high-accuracy models. Tradeoffs between sampling and accuracy have motivated modeling with molecular mechanics (MM) in a multiscale QM/MM or iterative approach. Limitations to both conventional density-functional theory and classical MM force fields remain for describing noncovalent interactions in comparison to experiment or wavefunction theory. Because predictions of enzyme action (i.e. electrostatics), free energy barriers, and mechanisms are sensitive to the protocol and embedding method in QM/MM, convergence tests and systematic methods for quantifying QM-level interactions are a needed, active area of development.
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