Literature DB >> 29594772

Molecular Dynamics as a Tool for Virtual Ligand Screening.

Grégory Menchon1, Laurent Maveyraud2, Georges Czaplicki3.   

Abstract

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or catalytic enzyme is known experimentally. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to inhibit a particular protein interaction or biological activity. The virtual ligand screening process often relies on docking methods which allow predicting the binding of a molecule into a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of protein flexibility information, no solvation effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions and even in membrane-like environments, and ranking complexes with more accurate binding energy calculations. In this chapter we describe the up-to-date MD protocols that are mandatory supporting tools in the virtual ligand screening (VS) process. Using docking in combination with MD is one of the best computer-aided drug design protocols nowadays. It has proved its efficiency through many examples, described below.

Entities:  

Keywords:  Affinity; Clustering; Docking; Drug design; Interaction energy; Molecular dynamics; Protein–ligand complex; Virtual screening

Mesh:

Substances:

Year:  2018        PMID: 29594772     DOI: 10.1007/978-1-4939-7756-7_9

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

Review 1.  Recent Advances in Application of Computer-Aided Drug Design in Anti-Influenza A Virus Drug Discovery.

Authors:  Dahai Yu; Linlin Wang; Ye Wang
Journal:  Int J Mol Sci       Date:  2022-04-25       Impact factor: 6.208

Review 2.  Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses.

Authors:  Paul Andrei Negru; Denisa Claudia Miculas; Tapan Behl; Alexa Florina Bungau; Ruxandra-Cristina Marin; Simona Gabriela Bungau
Journal:  Biomed Pharmacother       Date:  2022-07-18       Impact factor: 7.419

Review 3.  Predictive Power of In Silico Approach to Evaluate Chemicals against M. tuberculosis: A Systematic Review.

Authors:  Giulia Oliveira Timo; Rodrigo Souza Silva Valle Dos Reis; Adriana Françozo de Melo; Thales Viana Labourdette Costa; Pérola de Oliveira Magalhães; Mauricio Homem-de-Mello
Journal:  Pharmaceuticals (Basel)       Date:  2019-09-16

4.  Discovery of genistein derivatives as potential SARS-CoV-2 main protease inhibitors by virtual screening, molecular dynamics simulations and ADMET analysis.

Authors:  Jiawei Liu; Ling Zhang; Jian Gao; Baochen Zhang; Xiaoli Liu; Ninghui Yang; Xiaotong Liu; Xifu Liu; Yu Cheng
Journal:  Front Pharmacol       Date:  2022-08-25       Impact factor: 5.988

  4 in total

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