Literature DB >> 27108593

The Multifaceted Roles of Molecular Dynamics Simulations in Drug Discovery.

Stephen John Fox1, Jianguo Li, Yaw Sing Tan, Minh N Nguyen, Arumay Pal, Zohra Ouaray, Shilpa Yadahalli, Srinivasaraghavan Kannan2.   

Abstract

Discovery of new therapeutics is a very challenging, expensive and time-consuming process. With the number of approved drugs declining steadily, combined with increasing costs, a rational approach is needed to facilitate, expedite and streamline the drug discovery process. In silico methods are playing key roles in the discovery of a growing number of marketed drugs. The use of computational approaches, particularly molecular dynamics, in drug design is rapidly gaining momentum and acceptance as an essential part of the toolkit for modern drug discovery. From analysing atomistic details for explaining experimentally observed phenomena, to designing drugs with increased efficacy and specificity, the insight that such simulations can provide is generating new ideas and applications that have previously been unexplored. Here we discuss physics-based simulation methodologies and applications in drug design: from locating pockets to designing novel lead compounds, from small molecules to peptides. With developments in hardware, software and theory, the improved predictive abilities of in silico efforts are becoming an essential part of efficient, economic and accurate drug development strategies.

Mesh:

Year:  2016        PMID: 27108593     DOI: 10.2174/1381612822666160425120507

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  4 in total

1.  Single-cell stochastic modelling of the action of antimicrobial peptides on bacteria.

Authors:  Hamid Teimouri; Thao N Nguyen; Anatoly B Kolomeisky
Journal:  J R Soc Interface       Date:  2021-09-15       Impact factor: 4.293

2.  Computational Strategy for Bound State Structure Prediction in Structure-Based Virtual Screening: A Case Study of Protein Tyrosine Phosphatase Receptor Type O Inhibitors.

Authors:  Xuben Hou; David Rooklin; Duxiao Yang; Xiao Liang; Kangshuai Li; Jianing Lu; Cheng Wang; Peng Xiao; Yingkai Zhang; Jin-Peng Sun; Hao Fang
Journal:  J Chem Inf Model       Date:  2018-10-19       Impact factor: 4.956

Review 3.  Synthetic Biology and Computer-Based Frameworks for Antimicrobial Peptide Discovery.

Authors:  Marcelo D T Torres; Jicong Cao; Octavio L Franco; Timothy K Lu; Cesar de la Fuente-Nunez
Journal:  ACS Nano       Date:  2021-02-04       Impact factor: 15.881

Review 4.  Membrane Active Antimicrobial Peptides: Translating Mechanistic Insights to Design.

Authors:  Jianguo Li; Jun-Jie Koh; Shouping Liu; Rajamani Lakshminarayanan; Chandra S Verma; Roger W Beuerman
Journal:  Front Neurosci       Date:  2017-02-14       Impact factor: 4.677

  4 in total

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