WIREs: Computational Molecular Science
WIREs: Computational Molecular Science
5 years ago

Molecular ‘time-machines’ to unravel key biological events for drug design

Molecular ‘time-machines’ to unravel key biological events for drug design
Michelle L. Coote, Aravindhan Ganesan, Khaled Barakat
Molecular dynamics (MD) has become a routine tool in structural biology and structure-based drug design (SBDD). MD offers extraordinary insights into the structures and dynamics of biological systems. With the current capabilities of high-performance supercomputers, it is now possible to perform MD simulations of systems as large as millions of atoms and for several nanoseconds timescale. Nevertheless, many complicated molecular mechanisms, including ligand binding/unbinding and protein folding, usually take place on timescales of several microseconds to milliseconds, which are beyond the practical limits of standard MD simulations. Such issues with traditional MD approaches can be effectively tackled with new generation MD methods, such as enhanced sampling MD approaches and coarse-grained MD (CG-MD) scheme. The former employ a bias to steer the simulations and reveal biological events that are usually very slow, while the latter groups atoms as interaction beads, thereby reducing the system size and facilitating longer MD simulations that can witness large conformational changes in biological systems. In this review, we outline many of such advanced MD methods, and discuss how their applications are providing significant insights into important biological processes, particularly those relevant to drug design and discovery. WIREs Comput Mol Sci 2017, 7:e1306. doi: 10.1002/wcms.1306 For further resources related to this article, please visit the WIREs website. Several complicated biological process usually take place on microseconds to millisecond timescales. This review discusses the use of enhanced sampling molecular dynamics approaches and coarse-graining approaches in studying such complex processes within affordable computational costs.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/wcms.1306

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