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

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

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.

enzyme, membrane, molecular dynamics, multiscale, protein, QM/MM
1759-0876
1-23
Huggins, David J.
8803c182-0d61-469e-b9ad-3ffdec0bf8d4
Biggin, Philip C.
c7394f79-450a-46c6-b77a-fadac30ded33
Dämgen, Marc A.
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Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Harris, Sarah A.
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Henchman, Richard H.
668b4af2-bbfa-49f4-abf8-c7a1d17be0e8
Khalid, Syma
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Kuzmanic, Antonija
0652ca16-f776-421c-a63c-70d6f1efdeef
Laughton, Charles A.
0a484097-8092-443e-bc0b-5fec1c16ca45
Michel, Julien
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Mulholland, Adrian J.
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Rosta, Edina
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Sansom, Mark S.P.
ed30b4fc-bc73-4ad7-8c56-f51a67136e4e
van der Kamp, Marc W.
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Huggins, David J.
8803c182-0d61-469e-b9ad-3ffdec0bf8d4
Biggin, Philip C.
c7394f79-450a-46c6-b77a-fadac30ded33
Dämgen, Marc A.
041099ad-b8af-4e9e-b433-3139b29ef940
Essex, Jonathan W.
1f409cfe-6ba4-42e2-a0ab-a931826314b5
Harris, Sarah A.
aa623784-4766-4cba-a26d-330ec1cf453d
Henchman, Richard H.
668b4af2-bbfa-49f4-abf8-c7a1d17be0e8
Khalid, Syma
90fbd954-7248-4f47-9525-4d6af9636394
Kuzmanic, Antonija
0652ca16-f776-421c-a63c-70d6f1efdeef
Laughton, Charles A.
0a484097-8092-443e-bc0b-5fec1c16ca45
Michel, Julien
80831aa7-aac0-4e6d-b9a0-3878eacbf881
Mulholland, Adrian J.
31c4d9a5-7333-4829-8bbe-4bf69adf2aaa
Rosta, Edina
6233f9cc-79b3-4d0c-a4b9-92bad6917c14
Sansom, Mark S.P.
ed30b4fc-bc73-4ad7-8c56-f51a67136e4e
van der Kamp, Marc W.
0d0fd280-dab7-418c-b0eb-2aa5d6f8ef6d

Huggins, David J., Biggin, Philip C., Dämgen, Marc A., Essex, Jonathan W., Harris, Sarah A., Henchman, Richard H., Khalid, Syma, Kuzmanic, Antonija, Laughton, Charles A., Michel, Julien, Mulholland, Adrian J., Rosta, Edina, Sansom, Mark S.P. and van der Kamp, Marc W. (2018) Biomolecular simulations: from dynamics and mechanisms to computational assays of biological activity. Wiley Interdisciplinary Reviews: Computational Molecular Science, 1-23, [e1393]. (doi:10.1002/wcms.1393).

Record type: Article

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.

Full text not available from this repository.

More information

Accepted/In Press date: 23 August 2018
e-pub ahead of print date: 27 September 2018
Keywords: enzyme, membrane, molecular dynamics, multiscale, protein, QM/MM

Identifiers

Local EPrints ID: 427090
URI: http://eprints.soton.ac.uk/id/eprint/427090
ISSN: 1759-0876
PURE UUID: 628ca9eb-e1bb-4b8c-84e8-379338c89d3b
ORCID for Jonathan W. Essex: ORCID iD orcid.org/0000-0003-2639-2746
ORCID for Syma Khalid: ORCID iD orcid.org/0000-0002-3694-5044

Catalogue record

Date deposited: 21 Dec 2018 16:31
Last modified: 07 Oct 2020 01:54

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