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Pederson JP, McDaniel JG. PyDFT-QMMM: A modular, extensible software framework for DFT-based QM/MM molecular dynamics. J Chem Phys 2024; 161:034103. [PMID: 39007371 DOI: 10.1063/5.0219851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 06/24/2024] [Indexed: 07/16/2024] Open
Abstract
PyDFT-QMMM is a Python-based package for performing hybrid quantum mechanics/molecular mechanics (QM/MM) simulations at the density functional level of theory. The program is designed to treat short-range and long-range interactions through user-specified combinations of electrostatic and mechanical embedding procedures within periodic simulation domains, providing necessary interfaces to external quantum chemistry and molecular dynamics software. To enable direct embedding of long-range electrostatics in periodic systems, we have derived and implemented force terms for our previously described QM/MM/PME approach [Pederson and McDaniel, J. Chem. Phys. 156, 174105 (2022)]. Communication with external software packages Psi4 and OpenMM is facilitated through Python application programming interfaces (APIs). The core library contains basic utilities for running QM/MM molecular dynamics simulations, and plug-in entry-points are provided for users to implement custom energy/force calculation and integration routines, within an extensible architecture. The user interacts with PyDFT-QMMM primarily through its Python API, allowing for complex workflow development with Python scripting, for example, interfacing with PLUMED for free energy simulations. We provide benchmarks of forces and energy conservation for the QM/MM/PME and alternative QM/MM electrostatic embedding approaches. We further demonstrate a simple example use case for water solute in a water solvent system, for which radial distribution functions are computed from 100 ps QM/MM simulations; in this example, we highlight how the solvation structure is sensitive to different basis-set choices due to under- or over-polarization of the QM water molecule's electron density.
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Affiliation(s)
- John P Pederson
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Jesse G McDaniel
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
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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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Cheng Z, Bi H, Liu S, Chen J, Misquitta AJ, Yu K. Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters. J Chem Theory Comput 2024; 20:5598-5608. [PMID: 38888427 DOI: 10.1021/acs.jctc.4c00337] [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: 06/20/2024]
Abstract
Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This study introduces a comprehensive asymptotic parameter database encompassing atomic multipole moments, polarizabilities, and dispersion coefficients. Leveraging active learning, our database comprehensively represents protein fragments with up to 8 heavy atoms, capturing their conformational diversity with merely 78,000 data points. Additionally, the E(3) neural network (E3NN) is employed to predict the asymptotic parameters directly from the local geometry. The E3NN models demonstrate exceptional accuracy and transferability across all asymptotic parameters, achieving an R2 of 0.999 for both protein fragments and 20 amino acid dipeptide test sets. The long-range electrostatic and dispersion energies can be obtained using the E3NN-predicted parameters, with an error of 0.07 and 0.02 kcal/mol, respectively, when compared to symmetry-adapted perturbation theory (SAPT). Therefore, our force fields demonstrate the capability to accurately describe long-range interactions in proteins, paving the way for next-generation protein force fields.
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Affiliation(s)
- Zheng Cheng
- School of Mathematical Sciences, Peking University, Beijing 100871, China
- AI for Science Institute, Beijing 100084, P. R. China
| | - Hangrui Bi
- School of Mathematical Sciences, Peking University, Beijing 100871, China
- DP Technology, Beijing 100080, P. R. China
| | - Siyuan Liu
- DP Technology, Beijing 100080, P. R. China
| | - Junmin Chen
- Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, Guangdong, P. R. China
- Tsinghua Shenzhen International Graduate School, Shenzhen 518055, Guangdong, P. R. China
| | - Alston J Misquitta
- School of Physics and Astronomy, Queen Mary, University of London, London E1 4NS, U.K
| | - Kuang Yu
- Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, Guangdong, P. R. China
- Tsinghua Shenzhen International Graduate School, Shenzhen 518055, Guangdong, P. R. China
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4
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Gorantla KR, Krishnan A, Waheed SO, Varghese A, DiCastri I, LaRouche C, Paik M, Fields GB, Karabencheva-Christova TG. Novel Insights into the Catalytic Mechanism of Collagenolysis by Zn(II)-Dependent Matrix Metalloproteinase-1. Biochemistry 2024. [PMID: 38963231 DOI: 10.1021/acs.biochem.4c00076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
Collagen hydrolysis, catalyzed by Zn(II)-dependent matrix metalloproteinases (MMPs), is a critical physiological process. Despite previous computational investigations into the catalytic mechanisms of MMP-mediated collagenolysis, a significant knowledge gap in understanding remains regarding the influence of conformational sampling and entropic contributions at physiological temperature on enzymatic collagenolysis. In our comprehensive multilevel computational study, employing quantum mechanics/molecular mechanics (QM/MM) metadynamics (MetD) simulations, we aimed to bridge this gap and provide valuable insights into the catalytic mechanism of MMP-1. Specifically, we compared the full enzyme-substrate complex in solution, clusters in solution, and gas-phase to elucidate insights into MMP-1-catalyzed collagenolysis. Our findings reveal significant differences in the catalytic mechanism when considering thermal effects and the dynamic evolution of the system, contrasting with conventional static potential energy surface QM/MM reaction path studies. Notably, we observed a significant stabilization of the critical tetrahedral intermediate, attributed to contributions from conformational flexibility and entropy. Moreover, we found that protonation of the scissile bond nitrogen occurs via proton transfer from a Zn(II)-coordinated hydroxide rather than from a solvent water molecule. Following C-N bond cleavage, the C-terminus remains coordinated to the catalytic Zn(II), while the N-terminus forms a hydrogen bond with a solvent water molecule. Subsequently, the release of the C-terminus is facilitated by the coordination of a water molecule. Our study underscores the pivotal role of protein conformational dynamics at physiological temperature in stabilizing the transition state of the rate-limiting step and key intermediates, compared to the corresponding reaction in solution. These fundamental insights into the mechanism of collagen degradation provide valuable guidance for the development of MMP-1-specific inhibitors.
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Affiliation(s)
- Koteswara Rao Gorantla
- Department of Chemistry, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Anandhu Krishnan
- Department of Chemistry, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Sodiq O Waheed
- Department of Chemistry, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Ann Varghese
- Department of Chemistry, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Isabella DiCastri
- Department of Chemical Engineering, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Ciara LaRouche
- Department of Chemical Engineering, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Meredith Paik
- Department of Chemistry, Michigan Technological University, Houghton, Michigan 49931, United States
| | - Gregg B Fields
- Department of Chemistry and Biochemistry and I-HEALTH, Florida Atlantic University, Jupiter, Florida 33458, United States
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5
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Wang M, Mei Y, Ryde U. Convergence criteria for single-step free-energy calculations: the relation between the Π bias measure and the sample variance. Chem Sci 2024; 15:8786-8799. [PMID: 38873060 PMCID: PMC11168088 DOI: 10.1039/d4sc00140k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/08/2024] [Indexed: 06/15/2024] Open
Abstract
Free energy calculations play a crucial role in simulating chemical processes, enzymatic reactions, and drug design. However, assessing the reliability and convergence of these calculations remains a challenge. This study focuses on single-step free-energy calculations using thermodynamic perturbation. It explores how the sample distributions influence the estimated results and evaluates the reliability of various convergence criteria, including Kofke's bias measure Π and the standard deviation of the energy difference ΔU, σ ΔU . The findings reveal that for Gaussian distributions, there is a straightforward relationship between Π and σ ΔU , free energies can be accurately approximated using a second-order cumulant expansion, and reliable results are attainable for σ ΔU up to 25 kcal mol-1. However, interpreting non-Gaussian distributions is more complex. If the distribution is skewed towards more positive values than a Gaussian, converging the free energy becomes easier, rendering standard convergence criteria overly stringent. Conversely, distributions that are skewed towards more negative values than a Gaussian present greater challenges in achieving convergence, making standard criteria unreliable. We propose a practical approach to assess the convergence of estimated free energies.
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Affiliation(s)
- Meiting Wang
- School of Medical Engineering & Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang Medical University Xinxiang 453003 China
- Department of Computational Chemistry, Lund University, Chemical Centre P.O. Box 124 SE-221 00 Lund Sweden
| | - Ye Mei
- State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University Shanghai 200241 China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai Shanghai 200062 China
- Collaborative Innovation Center of Extreme Optics, Shanxi University Taiyuan Shanxi 030006 China
| | - Ulf Ryde
- Department of Computational Chemistry, Lund University, Chemical Centre P.O. Box 124 SE-221 00 Lund Sweden
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6
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Mirgaux M, Leherte L, Wouters J. Human indoleamine-2,3-dioxygenase 2 cofactor lability and low substrate affinity explained by homology modeling, molecular dynamics and molecular docking. J Biomol Struct Dyn 2024; 42:4475-4488. [PMID: 37301605 DOI: 10.1080/07391102.2023.2220830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 05/28/2023] [Indexed: 06/12/2023]
Abstract
The human indoleamine-2,3-dioxygenase 2 (hIDO2) protein is growing of interest as it is increasingly implicated in multiple diseases (cancer, autoimmune diseases, COVID-19). However, it is only poorly reported in the literature. Its mode of action remains unknown because it does not seem to catalyze the reaction for which it is attributed: the degradation of the L-Tryptophan into N-formyl-kynurenine. This contrasts with its paralog, the human indoleamine-2,3-dioxygenase 1 (hIDO1), which has been extensively studied in the literature and for which several inhibitors are already in clinical trials. Yet, the recent failure of one of the most advanced hIDO1 inhibitors, the Epacadostat, could be caused by a still unknown interaction between hIDO1 and hIDO2. In order to better understand the mechanism of hIDO2, and in the absence of experimental structural data, a computational study mixing homology modeling, Molecular Dynamics, and molecular docking was conducted. The present article highlights an exacerbated lability of the cofactor as well as an inadequate positioning of the substrate in the active site of hIDO2, which might bring part of an answer to its lack of activity.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Manon Mirgaux
- Department of Chemistry, Laboratoire de Chimie Biologique Structurale (CBS), Namur Institute of Structured Matter (NISM), Namur Research Institute for Life Science (NARILIS), University of Namur (UNamur), Namur, Belgium
| | - Laurence Leherte
- Department of Chemistry, Laboratoire de Chimie Biologique Structurale (CBS), Namur Institute of Structured Matter (NISM), Namur Research Institute for Life Science (NARILIS), University of Namur (UNamur), Namur, Belgium
| | - Johan Wouters
- Department of Chemistry, Laboratoire de Chimie Biologique Structurale (CBS), Namur Institute of Structured Matter (NISM), Namur Research Institute for Life Science (NARILIS), University of Namur (UNamur), Namur, Belgium
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7
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Carrasco-Busturia D, Ippoliti E, Meloni S, Rothlisberger U, Olsen JMH. Multiscale biomolecular simulations in the exascale era. Curr Opin Struct Biol 2024; 86:102821. [PMID: 38688076 DOI: 10.1016/j.sbi.2024.102821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/03/2024] [Accepted: 04/04/2024] [Indexed: 05/02/2024]
Abstract
The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations are crucial for capturing processes beyond the reach of classical MD simulations. The advent of exascale computing offers unprecedented opportunities for scientific exploration, not least within life sciences, where simulations are essential to unravel intricate molecular mechanisms underlying biological processes. However, leveraging the immense computational power of exascale computing requires innovative algorithms and software designs. In this context, we discuss the current status and future prospects of multiscale biomolecular simulations on exascale supercomputers with a focus on QM/MM MD. We highlight our own efforts in developing a versatile and high-performance multiscale simulation framework with the aim of efficient utilization of state-of-the-art supercomputers. We showcase its application in uncovering complex biological mechanisms and its potential for leveraging exascale computing.
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Affiliation(s)
- David Carrasco-Busturia
- DTU Chemistry, Technical University of Denmark (DTU), Kongens Lyngby, DK-2800, Denmark. https://twitter.com/@DavidCdeB
| | - Emiliano Ippoliti
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich, DE-52428, Germany
| | - Simone Meloni
- Dipartimento di Scienze Chimiche, Farmaceutiche ed Agrarie (DOCPAS), Università degli Studi di Ferrara (Unife), Ferrara, I-44121, Italy. https://twitter.com/@smeloni99
| | - Ursula Rothlisberger
- Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, CH-1015, Switzerland. https://twitter.com/@lcbc_epfl
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8
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Capone M, Romanelli M, Castaldo D, Parolin G, Bello A, Gil G, Vanzan M. A Vision for the Future of Multiscale Modeling. ACS PHYSICAL CHEMISTRY AU 2024; 4:202-225. [PMID: 38800726 PMCID: PMC11117712 DOI: 10.1021/acsphyschemau.3c00080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 05/29/2024]
Abstract
The rise of modern computer science enabled physical chemistry to make enormous progresses in understanding and harnessing natural and artificial phenomena. Nevertheless, despite the advances achieved over past decades, computational resources are still insufficient to thoroughly simulate extended systems from first principles. Indeed, countless biological, catalytic and photophysical processes require ab initio treatments to be properly described, but the breadth of length and time scales involved makes it practically unfeasible. A way to address these issues is to couple theories and algorithms working at different scales by dividing the system into domains treated at different levels of approximation, ranging from quantum mechanics to classical molecular dynamics, even including continuum electrodynamics. This approach is known as multiscale modeling and its use over the past 60 years has led to remarkable results. Considering the rapid advances in theory, algorithm design, and computing power, we believe multiscale modeling will massively grow into a dominant research methodology in the forthcoming years. Hereby we describe the main approaches developed within its realm, highlighting their achievements and current drawbacks, eventually proposing a plausible direction for future developments considering also the emergence of new computational techniques such as machine learning and quantum computing. We then discuss how advanced multiscale modeling methods could be exploited to address critical scientific challenges, focusing on the simulation of complex light-harvesting processes, such as natural photosynthesis. While doing so, we suggest a cutting-edge computational paradigm consisting in performing simultaneous multiscale calculations on a system allowing the various domains, treated with appropriate accuracy, to move and extend while they properly interact with each other. Although this vision is very ambitious, we believe the quick development of computer science will lead to both massive improvements and widespread use of these techniques, resulting in enormous progresses in physical chemistry and, eventually, in our society.
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Affiliation(s)
- Matteo Capone
- Department
of Physical and Chemical Sciences, University
of L’Aquila, L’Aquila 67010, Italy
| | - Marco Romanelli
- Department
of Chemical Sciences, University of Padova, Padova 35131, Italy
| | - Davide Castaldo
- Department
of Chemical Sciences, University of Padova, Padova 35131, Italy
| | - Giovanni Parolin
- Department
of Chemical Sciences, University of Padova, Padova 35131, Italy
| | - Alessandro Bello
- Department
of Chemical Sciences, University of Padova, Padova 35131, Italy
- Department
of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Gabriel Gil
- Department
of Chemical Sciences, University of Padova, Padova 35131, Italy
- Instituto
de Cibernética, Matemática y Física (ICIMAF), La Habana 10400, Cuba
| | - Mirko Vanzan
- Department
of Chemical Sciences, University of Padova, Padova 35131, Italy
- Department
of Physics, University of Milano, Milano 20133, Italy
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9
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Pyzer-Knapp EO, Curioni A. Advancing biomolecular simulation through exascale HPC, AI and quantum computing. Curr Opin Struct Biol 2024; 87:102826. [PMID: 38733863 DOI: 10.1016/j.sbi.2024.102826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/11/2024] [Accepted: 04/11/2024] [Indexed: 05/13/2024]
Abstract
Biomolecular simulation can act as both a digital microscope and a crystal ball; offering the potential for a deeper understanding of experimental observations whilst also presenting a forward-looking avenue for the in silico design and evaluation of hitherto unsynthesized compounds. Indeed, as the intricacy of our scientific inquiries has grown, so too has the computational prowess we seek to deploy in our pursuit of answers. As we enter the Exascale era, this mini-review surveys the computational landscape from both the point of view of the development of new and ever more powerful systems, and the simulations that are run on them. Moreover, as we stand on the cusp of a transformative phase in computational biology, this article offers a contemplative glance into the future, speculating on the profound implications of artificial intelligence and quantum computing for large-scale biomolecular simulations.
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10
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Nochebuena J, Liu S, Cisneros GA. Relative cooperativity in neutral and charged molecular clusters using QM/MM calculations. J Chem Phys 2024; 160:134301. [PMID: 38557841 DOI: 10.1063/5.0203020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 03/13/2024] [Indexed: 04/04/2024] Open
Abstract
QM/MM methods have been used to study electronic structure properties and chemical reactivity in complex molecular systems where direct electronic structure calculations are not feasible. In our previous work, we showed that non-polarizable force fields, by design, describe intermolecular interactions through pairwise interactions, overlooking many-body interactions involving three or more particles. In contrast, polarizable force fields account partially for many-body effects through polarization, but still handle van der Waals and permanent electrostatic interactions pairwise. We showed that despite those limitations, polarizable and non-polarizable force fields can reproduce relative cooperativity achieved using density functional theory due to error compensation mechanisms. In this contribution, we assess the performance of QM/MM methods in reproducing these phenomena. Our study highlights the significance of the QM region size and force field choice in QM/MM calculations, emphasizing the importance of parameter validation to obtain accurate interaction energy predictions.
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Affiliation(s)
- Jorge Nochebuena
- Department of Physics, University of Texas at Dallas, Richardson, Texas 75080, USA
| | - Shubin Liu
- Research Computing Center, University of North Carolina, Chapel Hill, North Carolina 27599, USA
- Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - G Andrés Cisneros
- Department of Physics, University of Texas at Dallas, Richardson, Texas 75080, USA
- Department of Chemistry and Biochemistry, University of Texas at Dallas, Richardson, Texas 75080, USA
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11
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Adhikary KK, Verpoort F, Heynderickx PM. Theoretical investigation of nucleophilic substitution reaction of phenyl carbonyl isothiocyanates with pyridines in gas and polar aprotic solvent. Phys Chem Chem Phys 2024; 26:3168-3183. [PMID: 38192244 DOI: 10.1039/d3cp04272c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
This study focuses on the mutual interaction of substituents in the nucleophile and substrate - cross interaction constant, ρXY, in the uncatalyzed aminolysis by substituting pyridine with phenyl carbonyl isothiocyanate. The mechanism was found to be a stepwise process with a rate-limiting breakdown of the -NCS leaving group. This stepwise reaction mechanism considers the cross-interaction constant (CIC) with rate-limiting breakdown of tetrahedral intermediate in gas and solvent phases. The corresponding Hammett coefficients are related to the substituents associated with (1) the nucleophiles (X), ρX (-1.93 to -6.54 for the gas phase and 10.5 to 18.9 in the solvent model), and with (2) the substituents associated with the phenyl ring of the substrate (Y), ρY (0.41-3.48 for the gas phase and 1.83 to -10.70 for the solvent model). It also includes the Brønsted coefficient with X, βX (0.11-1.52 for the gas phase and -2.57 to 3.96 for the solvent model), and CIC values, ρXY (0.69 for the gas phase and 0.87 for the solvent model). In this work, the NBO analysis, reaction potential, reaction electronic flux (REF), dual descriptor, and the structure-energy relationships were considered in interpreting the mechanistic criteria.
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Affiliation(s)
- Keshab Kumar Adhikary
- Center for Environmental and Energy Research (CEER) - Engineering of Materials via Catalysis and Characterization, Ghent University Global Campus, 119-5 Songdomunhwa-Ro, Yeonsu-Gu, Incheon, 406-840, South Korea.
| | - Francis Verpoort
- Laboratory of Organometallics, Catalysis and Ordered Materials, State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan 430070, P. R. China
- National Research Tomsk Polytechnic University, Lenin Avenue 30, 634050 Tomsk, Russian Federation
| | - Philippe M Heynderickx
- Center for Environmental and Energy Research (CEER) - Engineering of Materials via Catalysis and Characterization, Ghent University Global Campus, 119-5 Songdomunhwa-Ro, Yeonsu-Gu, Incheon, 406-840, South Korea.
- Department of Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, Ghent, B-9000, Belgium
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12
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Dangat Y, Freindorf M, Kraka E. Mechanistic Insights into S-Depalmitolyse Activity of Cln5 Protein Linked to Neurodegeneration and Batten Disease: A QM/MM Study. J Am Chem Soc 2024; 146:145-158. [PMID: 38055807 DOI: 10.1021/jacs.3c06397] [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: 12/08/2023]
Abstract
Ceroid lipofuscinosis neuronal protein 5 (Cln5) is encoded by the CLN5 gene. The genetic variants of this gene are associated with the CLN5 form of Batten disease. Recently, the first crystal structure of Cln5 was reported. Cln5 shows cysteine palmitoyl thioesterase S-depalmitoylation activity, which was explored via fluorescent emission spectroscopy utilizing the fluorescent probe DDP-5. In this work, the mechanism of the reaction between Cln5 and DDP-5 was studied computationally by applying a QM/MM methodology at the ωB97X-D/6-31G(d,p):AMBER level. The results of our study clearly demonstrate the critical role of the catalytic triad Cys280-His166-Glu183 in S-depalmitoylation activity. This is evidenced through a comparison of the pathways catalyzed by the Cys280-His166-Glu183 triad and those with only Cys280 involved. The computed reaction barriers are in agreement with the catalytic efficiency. The calculated Gibb's free-energy profile suggests that S-depalmitoylation is a rate-limiting step compared to the preceding S-palmitoylation, with barriers of 26.1 and 25.3 kcal/mol, respectively. The energetics were complemented by monitoring the fluctuations in the electron density distribution through NBO charges and bond strength alterations via local mode stretching force constants during the catalytic pathways. This comprehensive protocol led to a more holistic picture of the reaction mechanism at the atomic level. It forms the foundation for future studies on the effects of gene mutations on both the S-palmitoylation and S-depalmitoylation steps, providing valuable data for the further development of enzyme replacement therapy, which is currently the only FDA-approved therapy for childhood neurodegenerative diseases, including Batten disease.
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Affiliation(s)
- Yuvraj Dangat
- Department of Chemistry, Southern Methodist University, 3215 Daniel Avenue, Dallas, Texas 75275-0314, United States
| | - Marek Freindorf
- Department of Chemistry, Southern Methodist University, 3215 Daniel Avenue, Dallas, Texas 75275-0314, United States
| | - Elfi Kraka
- Department of Chemistry, Southern Methodist University, 3215 Daniel Avenue, Dallas, Texas 75275-0314, United States
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13
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Vijayakumar S, Kumar LL, Borkotoky S, Murali A. The Application of MD Simulation to Lead Identification, Vaccine Design, and Structural Studies in Combat against Leishmaniasis - A Review. Mini Rev Med Chem 2024; 24:1089-1111. [PMID: 37680156 DOI: 10.2174/1389557523666230901105231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/07/2023] [Accepted: 07/14/2023] [Indexed: 09/09/2023]
Abstract
Drug discovery, vaccine design, and protein interaction studies are rapidly moving toward the routine use of molecular dynamics simulations (MDS) and related methods. As a result of MDS, it is possible to gain insights into the dynamics and function of identified drug targets, antibody-antigen interactions, potential vaccine candidates, intrinsically disordered proteins, and essential proteins. The MDS appears to be used in all possible ways in combating diseases such as cancer, however, it has not been well documented as to how effectively it is applied to infectious diseases such as Leishmaniasis. As a result, this review aims to survey the application of MDS in combating leishmaniasis. We have systematically collected articles that illustrate the implementation of MDS in drug discovery, vaccine development, and structural studies related to Leishmaniasis. Of all the articles reviewed, we identified that only a limited number of studies focused on the development of vaccines against Leishmaniasis through MDS. Also, the PCA and FEL studies were not carried out in most of the studies. These two were globally accepted utilities to understand the conformational changes and hence it is recommended that this analysis should be taken up in similar approaches in the future.
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Affiliation(s)
| | | | - Subhomoi Borkotoky
- Department of Biotechnology, Invertis University, Bareilly, Uttar Pradesh, India
| | - Ayaluru Murali
- Department of Bioinformatics, Pondicherry University, Puducherry, India
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14
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Jin Z, Wei Z. Molecular simulation for food protein-ligand interactions: A comprehensive review on principles, current applications, and emerging trends. Compr Rev Food Sci Food Saf 2024; 23:e13280. [PMID: 38284571 DOI: 10.1111/1541-4337.13280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/19/2023] [Accepted: 11/22/2023] [Indexed: 01/30/2024]
Abstract
In recent years, investigations on molecular interaction mechanisms between food proteins and ligands have attracted much interest. The interaction mechanisms can supply much useful information for many fields in the food industry, including nutrient delivery, food processing, auxiliary detection, and others. Molecular simulation has offered extraordinary insights into the interaction mechanisms. It can reflect binding conformation, interaction forces, binding affinity, key residues, and other information that physicochemical experiments cannot reveal in a fast and detailed manner. The simulation results have proven to be consistent with the results of physicochemical experiments. Molecular simulation holds great potential for future applications in the field of food protein-ligand interactions. This review elaborates on the principles of molecular docking and molecular dynamics simulation. Besides, their applications in food protein-ligand interactions are summarized. Furthermore, challenges, perspectives, and trends in molecular simulation of food protein-ligand interactions are proposed. Based on the results of molecular simulation, the mechanisms of interfacial behavior, enzyme-substrate binding, and structural changes during food processing can be reflected, and strategies for hazardous substance detection and food flavor adjustment can be generated. Moreover, molecular simulation can accelerate food development and reduce animal experiments. However, there are still several challenges to applying molecular simulation to food protein-ligand interaction research. The future trends will be a combination of international cooperation and data sharing, quantum mechanics/molecular mechanics, advanced computational techniques, and machine learning, which contribute to promoting food protein-ligand interaction simulation. Overall, the use of molecular simulation to study food protein-ligand interactions has a promising prospect.
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Affiliation(s)
- Zihan Jin
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Zihao Wei
- State Key Laboratory of Marine Food Processing & Safety Control, College of Food Science and Engineering, Ocean University of China, Qingdao, China
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15
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Klem H, Alegre-Requena JV, Paton RS. Catalytic Effects of Active Site Conformational Change in the Allosteric Activation of Imidazole Glycerol Phosphate Synthase. ACS Catal 2023; 13:16249-16257. [PMID: 38125975 PMCID: PMC10729027 DOI: 10.1021/acscatal.3c04176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/10/2023] [Accepted: 11/13/2023] [Indexed: 12/23/2023]
Abstract
Imidazole glycerol phosphate synthase (IGPS) is a class-I glutamine amidotransferase (GAT) that hydrolyzes glutamine. Ammonia is produced and transferred to a second active site, where it reacts with N1-(5'-phosphoribosyl)-formimino-5-aminoimidazole-4-carboxamide ribonucleotide (PrFAR) to form precursors to purine and histidine biosynthesis. Binding of PrFAR over 25 Å away from the active site increases glutaminase efficiency by ∼4500-fold, primarily altering the glutamine turnover number. IGPS has been the focus of many studies on allosteric communication; however, atomic details for how the glutamine hydrolysis rate increases in the presence of PrFAR are lacking. We present a density functional theory study on 237-atom active site cluster models of IGPS based on crystallized structures representing the inactive and allosterically active conformations and investigate the multistep reaction leading to thioester formation and ammonia production. The proposed mechanism is supported by similar, well-studied enzyme mechanisms, and the corresponding energy profile is consistent with steady-state kinetic studies of PrFAR + IGPS. Additional active site models are constructed to examine the relationship between active site structural change and transition-state stabilization via energy decomposition schemes. The results reveal that the inactive IGPS conformation does not provide an adequately formed oxyanion hole structure and that repositioning of the oxyanion strand relative to the substrate is vital for a catalysis-competent oxyanion hole, with or without the hVal51 dihedral flip. These findings are valuable for future endeavors in modeling the IGPS allosteric mechanism by providing insight into the atomistic changes required for rate enhancement that can inform suitable reaction coordinates for subsequent investigations.
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Affiliation(s)
- Heidi Klem
- Department of Chemistry, Colorado State University, Fort Collins, Colorado 80523, United States
| | - Juan V Alegre-Requena
- Dpto.de Química Inorgánica, Instituto de Síntesis Química y Catálisis Homogénea (ISQCH), CSIC, Universidad de Zaragoza, Zaragoza 50009, Spain
| | - Robert S Paton
- Department of Chemistry, Colorado State University, Fort Collins, Colorado 80523, United States
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16
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Zheng M, Li Y, Zhang Q, Wang W. Impacts of QM region sizes and conformation numbers on modelling enzyme reactions: a case study of polyethylene terephthalate hydrolase. Phys Chem Chem Phys 2023; 25:31596-31603. [PMID: 37917137 DOI: 10.1039/d3cp04519f] [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: 11/03/2023]
Abstract
A quantum mechanics/molecular mechanics (QM/MM) approach is a broadly used tool in computational enzymology. Treating the QM region with a high-level DFT method is one of the important branches. Here, taking leaf-branch compost cutinase-catalyzed polyethylene terephthalate depolymerization as an example, the convergence behavior of energy barriers as well as key structural and charge features with respect to the size of the QM region (up to 1000 atoms) is systematically investigated. BP86/6-31G(d)//CHARMM and M06-2X/6-311G(d,p)//CHARMM level of theories were applied for geometry optimizations and single-point energy calculations, respectively. Six independent enzyme conformations for all the four catalytic steps (steps (i)-(iv)) were considered. Most of the twenty-four cases show that at least 500 QM atoms are needed while only two rare cases show that ∼100 QM atoms are sufficient for convergence when only a single conformation was considered. This explains why most previous studies showed that 500 or more QM atoms are required while a few others showed that ∼100 QM atoms are sufficient for DFT/MM calculations. More importantly, average energy barriers and key structural/charge features from six conformations show an accelerated convergence than that in a single conformation. For instance, to reach energy barrier convergence (within 2.0 kcal mol-1) for step (ii), only ∼100 QM atoms are required if six conformations are considered while 500 or more QM atoms are needed with a single conformation. The convergence is accelerated to be more rapid if hundreds and thousands of conformations were considered, which aligns with previous findings that only several dozens of QM atoms are required for convergence with semi-empirical QM/MM MD simulations.
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Affiliation(s)
- Mingna Zheng
- Environment Research Institute, Shandong University, Qingdao, 266237, PR China.
| | - Yanwei Li
- Environment Research Institute, Shandong University, Qingdao, 266237, PR China.
| | - Qingzhu Zhang
- Environment Research Institute, Shandong University, Qingdao, 266237, PR China.
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Qingdao, 266237, PR China.
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17
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Mysovsky AS, Bogdanov AI. Seamless Multilayer─A Novel Total Energy Partition Scheme for Embedded and Hybrid Calculations. J Chem Theory Comput 2023. [PMID: 37973151 DOI: 10.1021/acs.jctc.3c00666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
In this paper, we provide general formulation of a multilayer approach, covering both additive and subtractive quantum mechanics/molecular mechanics (QM/MM) as special cases. After that, we suggest a novel definition of QM/MM total energy based on the consideration of a system divided into three layers. In a simplified form, it is E = E Q M ( 1 + 2 ) - E Q M ( 2 ) + E M M ( 2 + 3 ) , where layers 1, 2, and 3 represent inner QM, outer QM, and classical MM regions, respectively. The novel formulation is also not limited by only QM/MM combination of methods─in fact, any computational methods can be combined in a hybrid calculation. In this paper, we call the new approach seamless multilayer. Test calculations performed for silica and boric oxide show that the new approach requires no QM/MM interface parameterization as well as no or very simple correction terms for boundary atoms. This can greatly facilitate QM/MM studies of covalent inorganic solids. However, test calculations of α-Al2O3 show that for ionic compounds, the new method requires some additional development.
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Affiliation(s)
- Andrey S Mysovsky
- A.P. Vinogradov Institute of Geochemistry SB RAS, 1a Favorsky Street, 664033 Irkutsk, Russia
- Institute of Quantum Physics, Irkutsk National Research Technical University, 83 Lermontov Street, 664074 Irkutsk, Russia
| | - Alexander I Bogdanov
- A.P. Vinogradov Institute of Geochemistry SB RAS, 1a Favorsky Street, 664033 Irkutsk, Russia
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18
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Coimbra JTS, Fernandes PA, Ramos MJ. Deciphering the Catalytic Mechanism of Virginiamycin B Lyase with Multiscale Methods and Molecular Dynamics Simulations. J Chem Inf Model 2023; 63:6354-6365. [PMID: 37791530 DOI: 10.1021/acs.jcim.3c00962] [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: 10/05/2023]
Abstract
Due to the emergence of antibiotic resistance, the need to explore novel antibiotics and/or novel strategies to counter antibiotic resistance is of utmost importance. In this work, we explored the molecular and mechanistic details of the degradation of a streptogramin B antibiotic by virginiamycin B (Vgb) lyase of Staphylococcus aureus using classical molecular dynamics simulations and multiscale quantum mechanics/molecular mechanics methods. Our results were in line with available experimental kinetic information. Although we were able to identify a stepwise mechanism, in the wild-type enzyme, the intermediate is short-lived, showing a small barrier to decay to the product state. The impact of point mutations on the reaction was also assessed, showing not only the importance of active site residues to the reaction catalyzed by Vgb lyase but also of near positive and negative residues surrounding the active site. Using molecular dynamics simulations, we also predicted the most likely protonation state of the 3-hydroxypicolinic moiety of the antibiotic and the impact of mutants on antibiotic binding. All this information will expand our understanding of linearization reactions of cyclic antibiotics, which are crucial for the development of novel strategies that aim to tackle antibiotic resistance.
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Affiliation(s)
- João T S Coimbra
- LAQV, REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
| | - Pedro A Fernandes
- LAQV, REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
| | - Maria J Ramos
- LAQV, REQUIMTE, Departamento de Química e Bioquímica, Faculdade de Ciências Universidade do Porto, Rua do Campo Alegre, s/n, 4169-007 Porto, Portugal
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19
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Zhang F, Zeng T, Wu R. QM/MM Modeling Aided Enzyme Engineering in Natural Products Biosynthesis. J Chem Inf Model 2023; 63:5018-5034. [PMID: 37556841 DOI: 10.1021/acs.jcim.3c00779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
Natural products and their derivatives are widely used across various industries, particularly pharmaceuticals. Modern engineered biosynthesis provides an alternative way of producing and meeting the growing need for diverse natural products. Natural enzymes, on the other hand, often exhibit unsatisfactory catalytic characteristics and necessitate further enzyme engineering modifications. QM/MM, as a powerful and extensively used computational tool in the field of enzyme catalysis, has been increasingly applied in rational enzyme engineering over the past decade. In this review, we summarize recent advances in QM/MM computational investigation on enzyme catalysis and enzyme engineering for natural product biosynthesis. The challenges and perspectives for future QM/MM applications aided enzyme engineering in natural product biosynthesis will also be discussed.
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Affiliation(s)
- Fan Zhang
- Guangdong Provincial Key Laboratory of Translational Cancer Research of Chinese Medicines, Joint International Research Laboratory of Translational Cancer Research of Chinese Medicines, International Institute for Translational Chinese Medicine, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, P. R. China
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, Sun Yat-sen University, Guangzhou 510006, P. R. China
| | - Tao Zeng
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, Sun Yat-sen University, Guangzhou 510006, P. R. China
| | - Ruibo Wu
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, Sun Yat-sen University, Guangzhou 510006, P. R. China
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20
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Abstract
A survey of protein databases indicates that the majority of enzymes exist in oligomeric forms, with about half of those found in the UniProt database being homodimeric. Understanding why many enzymes are in their dimeric form is imperative. Recent developments in experimental and computational techniques have allowed for a deeper comprehension of the cooperative interactions between the subunits of dimeric enzymes. This review aims to succinctly summarize these recent advancements by providing an overview of experimental and theoretical methods, as well as an understanding of cooperativity in substrate binding and the molecular mechanisms of cooperative catalysis within homodimeric enzymes. Focus is set upon the beneficial effects of dimerization and cooperative catalysis. These advancements not only provide essential case studies and theoretical support for comprehending dimeric enzyme catalysis but also serve as a foundation for designing highly efficient catalysts, such as dimeric organic catalysts. Moreover, these developments have significant implications for drug design, as exemplified by Paxlovid, which was designed for the homodimeric main protease of SARS-CoV-2.
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Affiliation(s)
- Ke-Wei Chen
- Lab of Computional Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Tian-Yu Sun
- Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Yun-Dong Wu
- Lab of Computional Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Shenzhen Bay Laboratory, Shenzhen 518132, China
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21
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Baklanov AV, Kiselev VG. The Nature of the Enthalpy-Entropy Compensation and "Exotic" Arrhenius Parameters in the Denaturation Kinetics of Proteins. Int J Mol Sci 2023; 24:10630. [PMID: 37445807 DOI: 10.3390/ijms241310630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/13/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
Protein unfolding is a ubiquitous process responsible for the loss of protein functionality (denaturation), which, in turn, can be accompanied by the death of cells and organisms. The nature of enthalpy-entropy compensation (EEC) in the kinetics of protein unfolding is a subject of debate. In order to investigate the nature of EEC, the "completely loose" transition state (TS) model has been applied to calculate the Arrhenius parameters for the unfolding of polyglycine dimers as a model process. The calculated Arrhenius parameters increase with increasing dimer length and demonstrate enthalpy-entropy compensation. It is shown that EEC results from the linear correlations of enthalpy and entropy of activation with dimer length, which are derived directly from the properties of the transition state. It is shown that EEC in solvated (hydrated, etc.) proteins is a direct consequence of EEC in proteins themselves. The suggested model allows us also to reproduce and explain "exotic" very high values of the pre-exponential factor measured for the proteins unfolding, which are drastically higher than those known for unimolecular reactions of organic molecules. A similar approach can be applied to analyzing the nature of EEC phenomena observed in other areas of chemistry.
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Affiliation(s)
- Alexey V Baklanov
- Institute of Chemical Kinetics and Combustion SB RAS, 3 Institutskaya Street, 630090 Novosibirsk, Russia
| | - Vitaly G Kiselev
- Institute of Chemical Kinetics and Combustion SB RAS, 3 Institutskaya Street, 630090 Novosibirsk, Russia
- Department of Physics, Novosibirsk State University, 1 Pirogova Street, 630090 Novosibirsk, Russia
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22
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Raghavan B, Paulikat M, Ahmad K, Callea L, Rizzi A, Ippoliti E, Mandelli D, Bonati L, De Vivo M, Carloni P. Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations. J Chem Inf Model 2023. [PMID: 37319347 DOI: 10.1021/acs.jcim.3c00557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
The initial phases of drug discovery - in silico drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of ∼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.
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Affiliation(s)
- Bharath Raghavan
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
- Department of Physics, RWTH Aachen University, Aachen 52074, Germany
| | - Mirko Paulikat
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Katya Ahmad
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Lara Callea
- Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - Andrea Rizzi
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
- Atomistic Simulations, Italian Institute of Technology, Genova 16163, Italy
| | - Emiliano Ippoliti
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Davide Mandelli
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Laura Bonati
- Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
| | - Marco De Vivo
- Molecular Modelling and Drug Discovery, Italian Institute of Technology, Genova 16163, Italy
| | - Paolo Carloni
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
- Department of Physics and Universitätsklinikum, RWTH Aachen University, Aachen 52074, Germany
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23
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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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24
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Clemente CM, Capece L, Martí MA. Best Practices on QM/MM Simulations of Biological Systems. J Chem Inf Model 2023; 63:2609-2627. [PMID: 37100031 DOI: 10.1021/acs.jcim.2c01522] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
During the second half of the 20th century, following structural biology hallmark works on DNA and proteins, biochemists shifted their questions from "what does this molecule look like?" to "how does this process work?". Prompted by the theoretical and practical developments in computational chemistry, this led to the emergence of biomolecular simulations and, along with the 2013 Nobel Prize in Chemistry, to the development of hybrid QM/MM methods. QM/MM methods are necessary whenever the problem we want to address involves chemical reactivity and/or a change in the system's electronic structure, with archetypal examples being the studies of an enzyme's reaction mechanism and a metalloprotein's active site. In the last decades QM/MM methods have seen an increasing adoption driven by their incorporation in widely used biomolecular simulation software. However, properly setting up a QM/MM simulation is not an easy task, and several issues need to be properly addressed to obtain meaningful results. In the present work, we describe both the theoretical concepts and practical issues that need to be considered when performing QM/MM simulations. We start with a brief historical perspective on the development of these methods and describe when and why QM/MM methods are mandatory. Then we show how to properly select and analyze the performance of the QM level of theory, the QM system size, and the position and type of the boundaries. We show the relevance of performing prior QM model system (or QM cluster) calculations in a vacuum and how to use the corresponding results to adequately calibrate those derived from QM/MM. We also discuss how to prepare the starting structure and how to select an adequate simulation strategy, including those based on geometry optimizations as well as free energy methods. In particular, we focus on the determination of free energy profiles using multiple steered molecular dynamics (MSMD) combined with Jarzynski's equation. Finally, we describe the results for two illustrative and complementary examples: the reaction performed by chorismate mutase and the study of ligand binding to hemoglobins. Overall, we provide many practical recommendations (or shortcuts) together with important conceptualizations that we hope will encourage more and more researchers to incorporate QM/MM studies into their research projects.
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Affiliation(s)
- Camila M Clemente
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellón 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
| | - Luciana Capece
- Departamento de Química Inorgánica Analítica y Química Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química de los Materiales, Ambiente y Energía (INQUIMAE) CONICET, Pabellòn 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
| | - Marcelo A Martí
- Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (FCEyN-UBA) e Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN) CONICET, Pabellón 2 de Ciudad Universitaria, Ciudad de Buenos Aires C1428EHA, Argentina
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25
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Papaleo E, Tiberti M, Arnaudi M, Pecorari C, Faienza F, Cantwell L, Degn K, Pacello F, Battistoni A, Lambrughi M, Filomeni G. TRAP1 S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins. Cell Death Dis 2023; 14:284. [PMID: 37085483 PMCID: PMC10121659 DOI: 10.1038/s41419-023-05780-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 03/13/2023] [Accepted: 03/27/2023] [Indexed: 04/23/2023]
Abstract
S-nitrosylation is a post-translational modification in which nitric oxide (NO) binds to the thiol group of cysteine, generating an S-nitrosothiol (SNO) adduct. S-nitrosylation has different physiological roles, and its alteration has also been linked to a growing list of pathologies, including cancer. SNO can affect the function and stability of different proteins, such as the mitochondrial chaperone TRAP1. Interestingly, the SNO site (C501) of TRAP1 is in the proximity of another cysteine (C527). This feature suggests that the S-nitrosylated C501 could engage in a disulfide bridge with C527 in TRAP1, resembling the well-known ability of S-nitrosylated cysteines to resolve in disulfide bridge with vicinal cysteines. We used enhanced sampling simulations and in-vitro biochemical assays to address the structural mechanisms induced by TRAP1 S-nitrosylation. We showed that the SNO site induces conformational changes in the proximal cysteine and favors conformations suitable for disulfide bridge formation. We explored 4172 known S-nitrosylated proteins using high-throughput structural analyses. Furthermore, we used a coarse-grained model for 44 protein targets to account for protein flexibility. This resulted in the identification of up to 1248 proximal cysteines, which could sense the redox state of the SNO site, opening new perspectives on the biological effects of redox switches. In addition, we devised two bioinformatic workflows ( https://github.com/ELELAB/SNO_investigation_pipelines ) to identify proximal or vicinal cysteines for a SNO site with accompanying structural annotations. Finally, we analyzed mutations in tumor suppressors or oncogenes in connection with the conformational switch induced by S-nitrosylation. We classified the variants as neutral, stabilizing, or destabilizing for the propensity to be S-nitrosylated and undergo the population-shift mechanism. The methods applied here provide a comprehensive toolkit for future high-throughput studies of new protein candidates, variant classification, and a rich data source for the research community in the NO field.
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Affiliation(s)
- Elena Papaleo
- Cancer Structural Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark.
- Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800, Lyngby, Denmark.
| | - Matteo Tiberti
- Cancer Structural Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
| | - Matteo Arnaudi
- Cancer Structural Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
- Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800, Lyngby, Denmark
| | - Chiara Pecorari
- Redox Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
| | - Fiorella Faienza
- Department of Biology, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Lisa Cantwell
- Cancer Structural Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kristine Degn
- Cancer Systems Biology, Section for Bioinformatics, Department of Health and Technology, Technical University of Denmark, 2800, Lyngby, Denmark
| | - Francesca Pacello
- Department of Biology, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Andrea Battistoni
- Department of Biology, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Matteo Lambrughi
- Cancer Structural Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
| | - Giuseppe Filomeni
- Redox Biology, Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
- Department of Biology, University of Rome Tor Vergata, 00133, Rome, Italy
- Center for Healthy Aging, Copenhagen University, 2200, Copenhagen, Denmark
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26
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Raghavan B, Schackert FK, Levy A, Johnson SK, Ippoliti E, Mandelli D, Olsen JMH, Rothlisberger U, Carloni P. MiMiCPy: An Efficient Toolkit for MiMiC-Based QM/MM Simulations. J Chem Inf Model 2023; 63:1406-1412. [PMID: 36811959 PMCID: PMC10015468 DOI: 10.1021/acs.jcim.2c01620] [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]
Abstract
MiMiC is a highly flexible, extremely scalable multiscale modeling framework. It couples the CPMD (quantum mechanics, QM) and GROMACS (molecular mechanics, MM) codes. The code requires preparing separate input files for the two programs with a selection of the QM region. This can be a tedious procedure prone to human error, especially when dealing with large QM regions. Here, we present MiMiCPy, a user-friendly tool that automatizes the preparation of MiMiC input files. It is written in Python 3 with an object-oriented approach. The main subcommand PrepQM can be used to generate MiMiC inputs directly from the command line or through a PyMOL/VMD plugin for visually selecting the QM region. Many other subcommands are also provided for debugging and fixing MiMiC input files. MiMiCPy is designed with a modular structure that allows seamless extensions to new program formats depending on the requirements of MiMiC.
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Affiliation(s)
- Bharath Raghavan
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany.,Department of Physics, RWTH Aachen University, Aachen 52074, Germany
| | - Florian K Schackert
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany.,Department of Physics, RWTH Aachen University, Aachen 52074, Germany
| | - Andrea Levy
- Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Sophia K Johnson
- Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Emiliano Ippoliti
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Davide Mandelli
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | | | - Ursula Rothlisberger
- Laboratory of Computational Chemistry and Biochemistry, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Paolo Carloni
- Computational Biomedicine, Institute of Advanced Simulations IAS-5/Institute for Neuroscience and Medicine INM-9, Forschungszentrum Jülich GmbH, Jülich 52428, Germany.,Department of Physics, RWTH Aachen University, Aachen 52074, Germany
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27
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Villot C, Lao KU. Electronic structure theory on modeling short-range noncovalent interactions between amino acids. J Chem Phys 2023; 158:094301. [PMID: 36889981 DOI: 10.1063/5.0138032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023] Open
Abstract
While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the "gold standard" coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order Møller-Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, ωB97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the δMP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.
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Affiliation(s)
- Corentin Villot
- Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, USA
| | - Ka Un Lao
- Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, USA
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28
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Fiorentini R, Tarenzi T, Potestio R. Fast, Accurate, and System-Specific Variable-Resolution Modeling of Proteins. J Chem Inf Model 2023; 63:1260-1275. [PMID: 36735551 PMCID: PMC9976289 DOI: 10.1021/acs.jcim.2c01311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Indexed: 02/04/2023]
Abstract
In recent years, a few multiple-resolution modeling strategies have been proposed, in which functionally relevant parts of a biomolecule are described with atomistic resolution, with the remainder of the system being concurrently treated using a coarse-grained model. In most cases, the parametrization of the latter requires lengthy reference all-atom simulations and/or the usage of off-shelf coarse-grained force fields, whose interactions have to be refined to fit the specific system under examination. Here, we overcome these limitations through a novel multiresolution modeling scheme for proteins, dubbed coarse-grained anisotropic network model for variable resolution simulations, or CANVAS. This scheme enables a user-defined modulation of the resolution level throughout the system structure; a fast parametrization of the potential without the necessity of reference simulations; and the straightforward usage of the model on the most commonly used molecular dynamics platforms. The method is presented and validated with two case studies, the enzyme adenylate kinase and the therapeutic antibody pembrolizumab, by comparing the results obtained with the CANVAS model against fully atomistic simulations. The modeling software, implemented in Python, is made freely available for the community on a collaborative github repository.
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Affiliation(s)
- Raffaele Fiorentini
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
| | - Thomas Tarenzi
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
| | - Raffaello Potestio
- Department
of Physics, University of Trento, via Sommarive 14, I-38123 Trento, Italy
- INFN-TIFPA, Trento
Institute for Fundamental Physics and Applications, via Sommarive 14, I-38123 Trento, Italy
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29
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Melo MCR, Bernardi RC. Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike. Biophys J 2023:S0006-3495(23)00091-7. [PMID: 36738105 PMCID: PMC10398237 DOI: 10.1016/j.bpj.2023.01.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/24/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.
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Affiliation(s)
- Marcelo C R Melo
- Auburn University, Department of Physics, Auburn University, Auburn, Alabama
| | - Rafael C Bernardi
- Auburn University, Department of Physics, Auburn University, Auburn, Alabama.
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30
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Csizi K, Reiher M. Universal
QM
/
MM
approaches for general nanoscale applications. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2023. [DOI: 10.1002/wcms.1656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
| | - Markus Reiher
- Laboratorium für Physikalische Chemie ETH Zürich Zürich Switzerland
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31
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Depta PN, Dosta M, Wenzel W, Kozlowska M, Heinrich S. Hierarchical Coarse-Grained Strategy for Macromolecular Self-Assembly: Application to Hepatitis B Virus-Like Particles. Int J Mol Sci 2022; 23:ijms232314699. [PMID: 36499027 PMCID: PMC9740473 DOI: 10.3390/ijms232314699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/01/2022] [Accepted: 11/14/2022] [Indexed: 11/27/2022] Open
Abstract
Macromolecular self-assembly is at the basis of many phenomena in material and life sciences that find diverse applications in technology. One example is the formation of virus-like particles (VLPs) that act as stable empty capsids used for drug delivery or vaccine fabrication. Similarly to the capsid of a virus, VLPs are protein assemblies, but their structural formation, stability, and properties are not fully understood, especially as a function of the protein modifications. In this work, we present a data-driven modeling approach for capturing macromolecular self-assembly on scales beyond traditional molecular dynamics (MD), while preserving the chemical specificity. Each macromolecule is abstracted as an anisotropic object and high-dimensional models are formulated to describe interactions between molecules and with the solvent. For this, data-driven protein-protein interaction potentials are derived using a Kriging-based strategy, built on high-throughput MD simulations. Semi-automatic supervised learning is employed in a high performance computing environment and the resulting specialized force-fields enable a significant speed-up to the micrometer and millisecond scale, while maintaining high intermolecular detail. The reported generic framework is applied for the first time to capture the formation of hepatitis B VLPs from the smallest building unit, i.e., the dimer of the core protein HBcAg. Assembly pathways and kinetics are analyzed and compared to the available experimental observations. We demonstrate that VLP self-assembly phenomena and dependencies are now possible to be simulated. The method developed can be used for the parameterization of other macromolecules, enabling a molecular understanding of processes impossible to be attained with other theoretical models.
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Affiliation(s)
- Philipp Nicolas Depta
- Institute of Solids Process Engineering and Particle Technology (SPE), Hamburg University of Technology, 21073 Hamburg, Germany
- Correspondence:
| | - Maksym Dosta
- Institute of Solids Process Engineering and Particle Technology (SPE), Hamburg University of Technology, 21073 Hamburg, Germany
- Boehringer Ingelheim Pharma GmbH & Co Kg., 88400 Biberach an der Riss, Germany
| | - Wolfgang Wenzel
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - Mariana Kozlowska
- Institute of Nanotechnology (INT), Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - Stefan Heinrich
- Institute of Solids Process Engineering and Particle Technology (SPE), Hamburg University of Technology, 21073 Hamburg, Germany
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32
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Wang Y, Liu T, Xie J, Cheng M, Sun L, Zhang S, Xin J, Zhang N. A review on application of molecular simulation technology in food molecules interaction. Curr Res Food Sci 2022; 5:1873-1881. [PMID: 36276243 PMCID: PMC9579209 DOI: 10.1016/j.crfs.2022.10.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/07/2022] [Accepted: 10/09/2022] [Indexed: 11/06/2022] Open
Abstract
Molecular simulation is a new technology to analyze the interaction between molecules. This review mainly summarizes the application of molecular simulation technology in the food industry. This technology has been employed to assess structural changes of biomolecules, the interaction between components, and the mechanism of physical and chemical property alterations. These conclusions provide a deeper understanding of the molecular interaction mechanism in foods, break through the limitations of scientific experiments and avoid blind and time-consuming scientific research. In this paper, the advantages and development trends of molecular simulation technology in the food research field are described. This methodology can be used to contribute to further studies of the mechanism of molecular interactions in food, confirm experimental results and provide new ideas for research in the field of food sciences.
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Affiliation(s)
- Yan Wang
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China
| | - Tianjiao Liu
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China
| | - Jinhui Xie
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China
| | - Meijia Cheng
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China
| | - Lirui Sun
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China
| | - Shuai Zhang
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China
| | - Jiaying Xin
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China,State Key Laboratory for Oxo Synthesis & Selective Oxidation, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, 730000, PR China
| | - Na Zhang
- Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, 150076, PR China,Corresponding author.
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33
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Chen J, Harper JB, Ho J. Improving the Accuracy of Quantum Mechanics/Molecular Mechanics (QM/MM) Models with Polarized Fragment Charges. J Chem Theory Comput 2022; 18:5607-5617. [PMID: 35952004 DOI: 10.1021/acs.jctc.2c00491] [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
This paper introduces an economical approach for improving the accuracy and convergence of quantum mechanics/molecular mechanics (QM/MM) models. The approach is tested on a series of neutral and charged amino acids embedded in a 160-water cluster, where their intramolecular proton transfer energies (neutral amino acid → zwitterionic amino acid) were previously obtained at the ωB97X-D/6-31G(d) level of theory. When the charges on the MM atoms were replaced with those obtained at the same QM level of theory used to treat the QM atoms, this significantly improved the accuracy and convergence of the QM/MM models. In particular, the QM/MM model converged to within 1.4 kcal mol-1 of directly calculated DFT energies for smaller (by as many as 20 waters) QM regions. The use of atomic charges obtained from the natural population analysis yielded the most significant improvement, while other charge schemes such as Mulliken, electrostatic potential, or CM5 led to poorer outcomes. It is further demonstrated that the QM atomic charges can be accurately estimated in a highly efficient manner using an iterative fragmentation approach based on the moving-domain QM/MM method. Similar observations were made when the approach was used to predict the barrier of an SN2 reaction. Thus, the use of QM-quality atomic charges on MM atoms represents a simple and easy-to-implement strategy for improving the accuracy of QM/MM models.
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Affiliation(s)
- Junbo Chen
- School of Chemistry, The University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Jason B Harper
- School of Chemistry, The University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Junming Ho
- School of Chemistry, The University of New South Wales, Sydney, New South Wales 2052, Australia
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34
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Feng S, Li Y, Zhang R, Zhang Q, Wang W. Origin of metabolites diversity and selectivity of P450 catalyzed benzo[a]pyrene metabolic activation. JOURNAL OF HAZARDOUS MATERIALS 2022; 435:129008. [PMID: 35490637 DOI: 10.1016/j.jhazmat.2022.129008] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 04/19/2022] [Accepted: 04/22/2022] [Indexed: 06/14/2023]
Abstract
Polycyclic Aromatic Hydrocarbon (PAHs) presents one of the most abundant class of environmental pollutants. Recent study shows a lab-synthesized PAHs derivative, helicenium, can selectively kill cancer cells rather than normal cells, calling for the in-depth understanding of the metabolic process. However, the origin of metabolites diversity and selectivity of P450 catalyzed PAHs metabolic activation is still unclear to a great extent. Here we systematically investigated P450 enzymes catalyzed activation mechanism of a representative PAHs, benzo[a]pyrene (BaP), and found the corresponding activation process mainly involves two elementary steps: electrophilic addition and epoxidation. Electrophilic addition step is evidenced to be rate determining step. Two representative binding modes of BaP with P450 were found, which enables the electrophilic addition of Heme (FeO) to almost all the carbons of BaP. This electrophilic addition was proposed to be accelerated by the P450 enzyme environment when compared with the gas phase and water solvent. To dig deeper on the origin of metabolites diversity, we built several linear regression models to explore the structural-energy relationships. The selectivity was eventually attributed to the integrated effects of structural (e.g. O-C distance and O-C-Fe angle) and electrostatic parameters (e.g. charge of C and O) from both BaP and P450.
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Affiliation(s)
- Shanshan Feng
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Yanwei Li
- Environment Research Institute, Shandong University, Qingdao 266237, PR China.
| | - Ruiming Zhang
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Qingzhu Zhang
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
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35
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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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36
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Nazemi A, Steeves AH, Kastner DW, Kulik HJ. Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase. J Phys Chem B 2022; 126:4069-4079. [PMID: 35609244 DOI: 10.1021/acs.jpcb.2c02260] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The Mo/W-containing metalloenzyme formate dehydrogenase (FDH) is an efficient and selective natural catalyst that reversibly converts CO2 to formate under ambient conditions. In this study, we investigate the impact of the greater protein environment on the electrostatic potential (ESP) of the active site. To model the enzyme environment, we used a combination of classical molecular dynamics and multiscale quantum-mechanical (QM)/molecular-mechanical (MM) simulations. We leverage charge shift analysis to systematically construct QM regions and analyze the electronic environment of the active site by evaluating the degree of charge transfer between the core active site and the protein environment. The contribution of the terminal chalcogen ligand to the ESP of the metal center is substantial and dependent on the chalcogen identity, with similar, less negative ESPs for Se and S terminal chalcogens in comparison to O regardless of whether the metal is Mo or W. The orientation of the side chains and conformations of the cofactor also affect the ESP, highlighting the importance of sampling dynamic fluctuations in the protein. Overall, our observations suggest that the terminal chalcogen ligand identity plays an important role in the enzymatic activity of FDH, suggesting opportunities for a rational bioinspired catalyst design.
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Affiliation(s)
- Azadeh Nazemi
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Adam H Steeves
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - David W Kastner
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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Hognon C, Marazzi M, García-Iriepa C. Atomistic-Level Description of the Covalent Inhibition of SARS-CoV-2 Papain-like Protease. Int J Mol Sci 2022; 23:ijms23105855. [PMID: 35628665 PMCID: PMC9143025 DOI: 10.3390/ijms23105855] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 05/13/2022] [Accepted: 05/21/2022] [Indexed: 12/25/2022] Open
Abstract
Inhibition of the papain-like protease (PLpro) of SARS-CoV-2 has been demonstrated to be a successful target to prevent the spreading of the coronavirus in the infected body. In this regard, covalent inhibitors, such as the recently proposed VIR251 ligand, can irreversibly inactivate PLpro by forming a covalent bond with a specific residue of the catalytic site (Cys111), through a Michael addition reaction. An inhibition mechanism can therefore be proposed, including four steps: (i) ligand entry into the protease pocket; (ii) Cys111 deprotonation of the thiol group by a Brønsted-Lowry base; (iii) Cys111-S- addition to the ligand; and (iv) proton transfer from the protonated base to the covalently bound ligand. Evaluating the energetics and PLpro conformational changes at each of these steps could aid the design of more efficient and selective covalent inhibitors. For this aim, we have studied by means of MD simulations and QM/MM calculations the whole mechanism. Regarding the first step, we show that the inhibitor entry in the PLpro pocket is thermodynamically favorable only when considering the neutral Cys111, that is, prior to the Cys111 deprotonation. For the second step, MD simulations revealed that His272 would deprotonate Cys111 after overcoming an energy barrier of ca. 32 kcal/mol (at the QM/MM level), but implying a decrease of the inhibitor stability inside the protease pocket. This information points to a reversible Cys111 deprotonation, whose equilibrium is largely shifted toward the neutral Cys111 form. Although thermodynamically disfavored, if Cys111 is deprotonated in close proximity to the vinylic carbon of the ligand, then covalent binding takes place in an irreversible way (third step) to form the enolate intermediate. Finally, due to Cys111-S- negative charge redistribution over the bound ligand, proton transfer from the initially protonated His272 is favored, finally leading to an irreversibly modified Cys111 and a restored His272. These results elucidate the selectivity of Cys111 to enable formation of a covalent bond, even if a weak proton acceptor is available, as His272.
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Affiliation(s)
- Cécilia Hognon
- Grupo de Reactividad y Estructura Molecular (RESMOL), Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Alcalá de Henares, 28801 Madrid, Spain;
| | - Marco Marazzi
- Grupo de Reactividad y Estructura Molecular (RESMOL), Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Alcalá de Henares, 28801 Madrid, Spain;
- Instituto de Investigación Química “Andrés M. del Río” (IQAR), Universidad de Alcalá, Alcalá de Henares, 28801 Madrid, Spain
- Correspondence: (M.M.); (C.G.-I.)
| | - Cristina García-Iriepa
- Grupo de Reactividad y Estructura Molecular (RESMOL), Departamento de Química Analítica, Química Física e Ingeniería Química, Universidad de Alcalá, Alcalá de Henares, 28801 Madrid, Spain;
- Instituto de Investigación Química “Andrés M. del Río” (IQAR), Universidad de Alcalá, Alcalá de Henares, 28801 Madrid, Spain
- Correspondence: (M.M.); (C.G.-I.)
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38
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Yang Z, Hajlasz N, Kulik HJ. Computational Modeling of Conformer Stability in Benenodin-1, a Thermally Actuated Lasso Peptide Switch. J Phys Chem B 2022; 126:3398-3406. [PMID: 35481742 DOI: 10.1021/acs.jpcb.2c00762] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Benenodin-1 is a thermally actuated lasso peptide rotaxane switch with two primary translational isomers that differ in the relative position of the residue Gln15. The conversion from one conformer to the other involves substantial enthalpy-entropy compensation: one conformer is energetically favored and the other is entropically favored. Here, we take a multi-scale quantum mechanical (QM) and classical molecular dynamic (MD) approach to reveal residue-specific sources of these differences in stability. QM reveals that the two benenodin-1 conformers involve distinct hydrogen bonding networks, with the enthalpically favored conformer having more intra-peptide hydrogen bonds between the Gln15 side chain and nearby residues. The evaluation of configurational entropy over the MD-sampled geometries reveals that the entropically favored conformer has enhanced conformational flexibility. By computing the by-residue-sum entropies, we identify the role of Gln15 and neighboring Glu14 in mediating the entropic variation during the switching process. These computational insights help explain the effects of Glu14Ala and Gln15Ala mutations on the conformational population of benenodin-1 observed experimentally.
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Affiliation(s)
- Zhongyue Yang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Natalia Hajlasz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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Schöller A, Kearns F, Woodcock HL, Boresch S. Optimizing the Calculation of Free Energy Differences in Nonequilibrium Work SQM/MM Switching Simulations. J Phys Chem B 2022; 126:2798-2811. [PMID: 35404610 PMCID: PMC9036525 DOI: 10.1021/acs.jpcb.2c00696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/24/2022] [Indexed: 11/27/2022]
Abstract
A key step during indirect alchemical free energy simulations using quantum mechanical/molecular mechanical (QM/MM) hybrid potential energy functions is the calculation of the free energy difference ΔAlow→high between the low level (e.g., pure MM) and the high level of theory (QM/MM). A reliable approach uses nonequilibrium work (NEW) switching simulations in combination with Jarzynski's equation; however, it is computationally expensive. In this study, we investigate whether it is more efficient to use more shorter switches or fewer but longer switches. We compare results obtained with various protocols to reference free energy differences calculated with Crooks' equation. The central finding is that fewer longer switches give better converged results. As few as 200 sufficiently long switches lead to ΔAlow→high values in good agreement with the reference results. This optimized protocol reduces the computational cost by a factor of 40 compared to earlier work. We also describe two tools/ways of analyzing the raw data to detect sources of poor convergence. Specifically, we find it helpful to analyze the raw data (work values from the NEW switching simulations) in a quasi-time series-like manner. Principal component analysis helps to detect cases where one or more conformational degrees of freedom are different at the low and high level of theory.
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Affiliation(s)
- Andreas Schöller
- Faculty
of Chemistry, Department of Computational Biological Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Vienna, Austria
- Vienna
Doctoral School in Chemistry (DoSChem), University of Vienna, Währingerstrasse 42, A-1090 Vienna, Austria
| | - Fiona Kearns
- Department
of Chemistry, University of South Florida, 4202 E. Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - H. Lee Woodcock
- Department
of Chemistry, University of South Florida, 4202 E. Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - Stefan Boresch
- Faculty
of Chemistry, Department of Computational Biological Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Vienna, Austria
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40
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Deng J, Cui Q. Electronic Polarization Is Essential for the Stabilization and Dynamics of Buried Ion Pairs in Staphylococcal Nuclease Mutants. J Am Chem Soc 2022; 144:4594-4610. [PMID: 35239338 PMCID: PMC9616648 DOI: 10.1021/jacs.2c00312] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Buried charged residues play important roles in the modulation of protein stabilities and conformational dynamics and make crucial contributions to protein functions. Considering the generally nonpolar nature of protein interior, a key question concerns the contribution of electronic polarization to the stabilization and properties of buried charges. We answer this question by conducting free energy simulations using the latest polarizable CHARMM force field based on Drude oscillators for a series of Staphylococcal nuclease mutants that involve a buried Glu-Lys pair in different titration states and orientations. While a nonpolarizable model suggests that the ionized form of the buried Glu-Lys pair is more than 40 kcal/mol less stable than the charge-neutral form, the two titration states are comparable in stability when electronic polarization is included explicitly, a result better reconcilable with available experimental data. Analysis of free energy components suggests that additional stabilization of the ionized Glu-Lys pair has contributions from both the enhanced salt-bridge strength and stronger interaction between the ion-pair and surrounding protein residues and penetrated water. Despite the stronger direct interaction between Glu and Lys, the ion-pair exhibits considerably larger and faster structural fluctuations when polarization is included, due to compensation of interactions in the cavity. Collectively, observations from this work provide compelling evidence that electronic polarization is essential to the stability, hydration, dynamics, and therefore function of buried charges in proteins. Therefore, our study advocates for the explicit consideration of electronic polarization for mechanistic and engineering studies that implicate buried charged residues, such as enzymes and ion transporters.
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Affiliation(s)
- Jiahua Deng
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Qiang Cui
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States.,Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States.,Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States
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41
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Gundelach L, Fox T, Tautermann CS, Skylaris CK. BRD4: quantum mechanical protein–ligand binding free energies using the full-protein DFT-based QM-PBSA method. Phys Chem Chem Phys 2022; 24:25240-25249. [PMID: 36222107 DOI: 10.1039/d2cp03705j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Fully quantum mechanical approaches to calculating protein–ligand free energies of binding have the potential to reduce empiricism and explicitly account for all physical interactions responsible for protein–ligand binding.
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Affiliation(s)
- Lennart Gundelach
- University of Southampton, Faculty of Engineering Science and Mathematics, Chemistry, University Road, Southampton, SO17 1BJ, UK
| | - Thomas Fox
- Boehringer Ingelheim Pharma GmbH & Co KG, Medicinal Chemistry, Birkendorfer Str 65, 88397, Biberach, Germany
| | - Christofer S. Tautermann
- Boehringer Ingelheim Pharma GmbH & Co KG, Medicinal Chemistry, Birkendorfer Str 65, 88397, Biberach, Germany
| | - Chris-Kriton Skylaris
- University of Southampton, Faculty of Engineering Science and Mathematics, Chemistry, University Road, Southampton, SO17 1BJ, UK
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Nakamura T, Yokaichiya T, Fedorov DG. Quantum-Mechanical Structure Optimization of Protein Crystals and Analysis of Interactions in Periodic Systems. J Phys Chem Lett 2021; 12:8757-8762. [PMID: 34478310 DOI: 10.1021/acs.jpclett.1c02510] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
A fast quantum-mechanical approach, density-functional tight-binding combined with the fragment molecular orbital method and periodic boundary conditions, is used to optimize atomic coordinates and cell parameters for a set of protein crystals: 1ETL, 5OQZ, 3Q8J, 1CBN, and 2VB1. Good agreement between experimental and calculated structures is obtained for both atomic coordinates and cell parameters. Sterical clashes present in the experimental structures are corrected by simulations. The partition analysis is extended to treat periodic boundary conditions and applied to analyze protein-solvent interactions in crystals.
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Affiliation(s)
- Taiji Nakamura
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Tomoko Yokaichiya
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
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