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Gaussian accelerated molecular dynamics for elucidation of drug pathways

Bhattarai, Apurba
; 
Miao, Yinglong
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Abstract
Introduction: Understanding pathways and mechanisms of drug binding to receptors is important for rational drug design. Remarkable advances in supercomputing and methodological developments have opened a new era for application of computer simulations in predicting drug-receptor interactions at an atomistic level. Gaussian accelerated molecular dynamics (GaMD) is a computational enhanced sampling technique that works by adding a harmonic boost potential to reduce energy barriers. GaMD enables free energy calculations without the requirement of predefined collective variables. GaMD has proven useful in biomolecular simulations, in particular, the prediction of drug-receptor interactions. Areas covered: Herein, the authors review recent GaMD simulation studies that elucidated pathways of drug binding to proteins including the G-protein-coupled receptors and HIV protease. Expert opinion: GaMD is advantageous for enhanced simulations of, amongst many biological processes, drug binding to target receptors. Compared with conventional molecular dynamics, GaMD speeds up biomolecular simulations by orders of magnitude. GaMD enables routine drug binding simulations using personal computers with GPUs or common computing clusters. GaMD and, more broadly, enhanced sampling simulations are expected to dramatically increase our capabilities to determine the mechanisms of drug binding to a wide range of receptors in the near future. This will greatly facilitate computer-aided drug design.
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This is an Accepted Manuscript of an article published by Taylor & Francis in Expert Opinion on Drug Discovery on 29 Oct 2018, available online: http://www.tandfonline.com/10.1080/17460441.2018.1538207.
Date
2018-10-29
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Taylor & Francis
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Molecular Biosciences Scholarly Works
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Keywords
Gaussian accelerated molecular dynamics, Enhanced sampling, Drug pathways, GPCRs, HIV protease, Computer-aided drug design
Citation
Bhattarai, A., & Miao, Y. (2018). Gaussian accelerated molecular dynamics for elucidation of drug pathways. Expert opinion on drug discovery, 13(11), 1055–1065. doi:10.1080/17460441.2018.1538207
URI
https://hdl.handle.net/1808/31915
DOI
10.1080/17460441.2018.1538207
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