Cited by 169Protein Structure and DynamicsAdvanced Physical and Chemical Molecular InteractionsComputational Drug Discovery Methods

Biomolecular simulations: from dynamics and mechanisms to computational assays of biological activity

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Huggins, David J., Biggin, Philip C., Dämgen, Marc A., Essex, Jonathan W., Harris, Sarah A., Henchman, Richard H., Khalid, Syma, Kuzmanic, Antonija +6 more·2019·WIREs Computational Molecular Science

Abstract

Biomolecular simulation is increasingly central to understanding and designing biological molecules and their interactions. Detailed, physics‐based simulation methods are demonstrating rapidly growing impact in areas as diverse as biocatalysis, drug delivery, biomaterials, biotechnology, and drug design. Simulations offer the potential of uniquely detailed, atomic‐level insight into mechanisms, dynamics, and processes, as well as increasingly accurate predictions of molecular properties. Simulations can now be used as computational assays of biological activity, for example, in predictions of drug resistance. Methodological and algorithmic developments, combined with advances in computational hardware, are transforming the scope and range of calculations. Different types of methods are required for different types of problem. Accurate methods and extensive simulations promise quantitative comparison with experiments across biochemistry. Atomistic simulations can now access experimentally relevant timescales for large systems, leading to a fertile interplay of experiment and theory and offering unprecedented opportunities for validating and developing models. Coarse‐grained methods allow studies on larger length‐ and timescales, and theoretical developments are bringing electronic structure calculations into new regimes. Multiscale methods are another key focus for development, combining different levels of theory to increase accuracy, aiming to connect chemical and molecular changes to macroscopic observables. In this review, we outline biomolecular simulation methods and highlight examples of its application to investigate questions in biology. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Free Energy Methods

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  • Molecular simulations of proteins and nucleic acids generally adopt much simplified models where the interactions among atoms in the system are described classically by empirical MM force fields.

    “Molecular simulations of proteins and nucleic acids generally adopt much simplified models [82], where the interactions among atoms in the system are described classically (as opposed to quantum mechanically) by empirical MM force fields.”

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References 214 · Cited by 169

Research works printed but not linked: 2

  1. Fritz, R., Alzate-Morales, J. H., Spencer, J., Mulholland, A. J., & van der Kamp, M. W. (2018). lactamases and predict efficiency of inhibition. Biochemistry, 57 (26), 3560-3563.
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Authors
Huggins, D. J., Biggin, P. C., Dämgen, M. A., Essex, J. W., Harris, S. A., Henchman, R. H., Khalid, S., Kuzmanic, A., Laughton, C. A., Michel, J., Mulholland, A. J., Rosta, E., Sansom, M. S. P., & van der Kamp, M. W.
Affiliations
  • University of Cambridge (GB)
  • University of Oxford (GB)
  • University of Southampton (GB)
  • University of Leeds (GB)
  • University of Manchester (GB)
  • University College London (GB)
  • University of Nottingham (GB)
  • University of Edinburgh (GB)
  • University of Bristol (GB)
  • King's College London (GB)
  • Centre of Computational Chemistry, School of Chemistry University of Bristol Bristol UK
Corresponding author
  • Huggins, David J.
  • Mulholland, Adrian J.
Venue
WIREs Computational Molecular Science
Publisher
Wiley
Published
2018-09-27
Volume
9
Issue
3
ISSN
  • 1759-0876 (ISSN-L)
  • 1759-0884
OpenAlex
W2892745578
Cited by
169
References
214
Citations by year
2026: 10 · 2025: 21 · 2024: 21 · 2023: 22 · 2022: 21 · 2021: 25 · 2020: 29 · 2019: 19 · 2018: 1
FWCI
6.55
Type
journal article
Language
en
Locations
  • Wiley Interdisciplinary Reviews Computational Molecular Science (publishedVersion)
  • Bristol Research (University of Bristol) (publishedVersion, other-oa)
  • Explore Bristol Research (submittedVersion, other-oa)
  • ePrints Soton (University of Southampton) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (submittedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by-nc)
  • Apollo (University of Cambridge) (submittedVersion)
  • Apollo
Funders
  • Royal Society
  • Wellcome Trust
  • Leverhulme Trust
  • Engineering and Physical Sciences Research Council (EP/L000253/1, EP/M022609/1, EP/N024117/1, EP/M015378/1, EP/P011306/1)
  • Biotechnology and Biological Sciences Research Council (BB/M000354/1, BB/L01386X/1, BB/N007700/1, and ERC (project 757850 BioNet))
  • Medical Research Council Canada (ML/L007266/1)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Keywords
biomolecular simulation, molecular dynamics, Monte Carlo methods, atomistic simulation, multiscale methods, electronic structure calculations, free energy methods, drug resistance prediction, drug design, biocatalysis, drug delivery, biomaterials, biotechnology, molecular mechanisms, molecular dynamics simulation

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