Molecular ‘time-machines’ to unravel key biological events for drug design
dc.contributor.author | Ganesan, Aravindhan | |
dc.contributor.author | Coote, Michelle | |
dc.contributor.author | Barakat, Khaled | |
dc.date.accessioned | 2020-09-02T01:29:09Z | |
dc.date.available | 2020-09-02T01:29:09Z | |
dc.date.issued | 2017 | |
dc.description.abstract | Molecular dynamics (MD) has become a routine tool in structural biology andstructure-based drug design (SBDD). MD offers extraordinary insights into thestructures and dynamics of biological systems. With the current capabilities ofhigh-performance supercomputers, it is now possible to perform MD simula-tions of systems as large as millions of atoms and for several nanoseconds time-scale. Nevertheless, many complicated molecular mechanisms, including ligandbinding/unbinding and protein folding, usually take place on timescales of sev-eral microseconds to milliseconds, which are beyond the practical limits of stand-ard MD simulations. Such issues with traditional MD approaches can beeffectively tackled with new generation MD methods, such as enhanced sam-pling MD approaches and coarse-grained MD (CG-MD) scheme. The formeremploy a bias to steer the simulations and reveal biological events that are usu-ally very slow, while the latter groups atoms as interaction beads, thereby redu-cing the system size and facilitating longer MD simulations that can witnesslarge conformational changes in biological systems. In this review, we outlinemany of such advanced MD methods, and discuss how their applications areproviding significant insights into important biological processes, particularlythose relevant to drug design and discovery. | en_AU |
dc.description.sponsorship | This work has been funded through the Alberta Cancer Foundation (ACF), Li Ka Shing Applied Virology Insti-tute (LKSAVI), and The Natural Sciences and Engineering Research Council of Canada (NSERC) | en_AU |
dc.format.mimetype | application/pdf | en_AU |
dc.identifier.issn | 1759-0876 | en_AU |
dc.identifier.uri | http://hdl.handle.net/1885/209210 | |
dc.language.iso | en_AU | en_AU |
dc.provenance | https://v2.sherpa.ac.uk/id/publication/19426..."The Accepted Version can be archived in a Non-Commercial Institutional Repository. 12 months embargo" from SHERPA/RoMEO site (as at 2/09/2020). This is the peer reviewed version of the following article: [Ganesan, Aravindhan, Michelle L. Coote, and Khaled Barakat. "Molecular ‘time‐machines’ to unravel key biological events for drug design." Wiley Interdisciplinary Reviews: Computational Molecular Science 7.4 (2017): e1306.], which has been published in final form at [https://dx.doi.org/10.1002/wcms.1306]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions | en_AU |
dc.publisher | Wiley | en_AU |
dc.rights | © 2017 Wiley Periodicals, Inc | en_AU |
dc.source | Wiley Interdisciplinary Reviews: Computational Molecular Science | en_AU |
dc.title | Molecular ‘time-machines’ to unravel key biological events for drug design | en_AU |
dc.type | Journal article | en_AU |
dcterms.accessRights | Open Access | en_AU |
local.bibliographicCitation.issue | 4 | en_AU |
local.bibliographicCitation.startpage | e1306 | en_AU |
local.contributor.affiliation | Coote, Michelle, Research School of Chemistry, The Australian National University | en_AU |
local.contributor.authoremail | michelle.coote@anu.edu.au | en_AU |
local.contributor.authoruid | u4031074 | en_AU |
local.identifier.citationvolume | 7 | en_AU |
local.identifier.doi | 10.1002/wcms.1306 | en_AU |
local.identifier.uidSubmittedBy | u1005913 | en_AU |
local.publisher.url | https://www.wiley.com/en-gb | en_AU |
local.type.status | Accepted Version | en_AU |
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