Literature DB >> 28910858

Overview of Methods and Strategies for Conducting Virtual Small Molecule Screening.

Xavier Fradera1, Kerim Babaoglu2.   

Abstract

Virtual screening (VS) in the context of drug discovery is the use of computational methods to discover novel ligands with a desired biological activity from within a larger collection of molecules. These techniques have been in use for many years, there is a wide range of methodologies available, and many successful applications have been reported in the literature. VS is often used as an alternative or a complement to High-throughput screening (HTS) or other methods to identify ligands for target validation or medicinal chemistry projects. This unit does not present an exhaustive review of available methods, or document specific instructions on use of individual software packages. Rather, a general overview of the methods available are presented and general strategies are described for VS based on accepted practices and the authors' experience as computational chemists in an industrial research laboratory. First, the most common methods available for VS are reviewed, categorized as either receptor- or ligand-based. Subsequently, strategic considerations are presented for choosing a VS method, or a combination of methods, as well as the necessary steps to prepare, run, and analyze a VS campaign. © 2017 by John Wiley & Sons, Inc.
Copyright © 2017 John Wiley and Sons, Inc.

Entities:  

Keywords:  ligand-based screening; molecular docking; pharmacophore searches; virtual screening

Mesh:

Substances:

Year:  2017        PMID: 28910858     DOI: 10.1002/cpch.27

Source DB:  PubMed          Journal:  Curr Protoc Chem Biol        ISSN: 2160-4762


  13 in total

1.  A computational approach yields selective inhibitors of human excitatory amino acid transporter 2 (EAAT2).

Authors:  Kelly L Damm-Ganamet; Marie-Laure Rives; Alan D Wickenden; Heather M McAllister; Taraneh Mirzadegan
Journal:  J Biol Chem       Date:  2020-02-20       Impact factor: 5.157

2.  Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design.

Authors:  Paul G Francoeur; Tomohide Masuda; Jocelyn Sunseri; Andrew Jia; Richard B Iovanisci; Ian Snyder; David R Koes
Journal:  J Chem Inf Model       Date:  2020-09-10       Impact factor: 4.956

Review 3.  Toxicodynamics of Mycotoxins in the Framework of Food Risk Assessment-An In Silico Perspective.

Authors:  Luca Dellafiora; Chiara Dall'Asta; Gianni Galaverna
Journal:  Toxins (Basel)       Date:  2018-01-23       Impact factor: 4.546

4.  Capturing antibacterial natural products with in silico techniques.

Authors:  Mahmud Masalha; Mahmoud Rayan; Azmi Adawi; Ziyad Abdallah; Anwar Rayan
Journal:  Mol Med Rep       Date:  2018-05-16       Impact factor: 2.952

5.  Novel hits for acetylcholinesterase inhibition derived by docking-based screening on ZINC database.

Authors:  Irini Doytchinova; Mariyana Atanasova; Iva Valkova; Georgi Stavrakov; Irena Philipova; Zvetanka Zhivkova; Dimitrina Zheleva-Dimitrova; Spiro Konstantinov; Ivan Dimitrov
Journal:  J Enzyme Inhib Med Chem       Date:  2018-12       Impact factor: 5.051

6.  Development and evaluation of a deep learning model for protein-ligand binding affinity prediction.

Authors:  Marta M Stepniewska-Dziubinska; Piotr Zielenkiewicz; Pawel Siedlecki
Journal:  Bioinformatics       Date:  2018-11-01       Impact factor: 6.937

7.  In Silico Study Identified Methotrexate Analog as Potential Inhibitor of Drug Resistant Human Dihydrofolate Reductase for Cancer Therapeutics.

Authors:  Rabia Mukhtar Rana; Shailima Rampogu; Noman Bin Abid; Amir Zeb; Shraddha Parate; Gihwan Lee; Sanghwa Yoon; Yumi Kim; Donghwan Kim; Keun Woo Lee
Journal:  Molecules       Date:  2020-07-31       Impact factor: 4.411

8.  Lapatinib, Nilotinib and Lomitapide Inhibit Haemozoin Formation in Malaria Parasites.

Authors:  Ana Carolina C de Sousa; Keletso Maepa; Jill M Combrinck; Timothy J Egan
Journal:  Molecules       Date:  2020-03-29       Impact factor: 4.411

9.  Virtual screening as a tool to discover new β-haematin inhibitors with activity against malaria parasites.

Authors:  Ana Carolina C de Sousa; Jill M Combrinck; Keletso Maepa; Timothy J Egan
Journal:  Sci Rep       Date:  2020-02-25       Impact factor: 4.379

10.  Identification of Novel Influenza Polymerase PB2 Inhibitors Using a Cascade Docking Virtual Screening Approach.

Authors:  Lei Zhao; Jinjing Che; Qian Zhang; Yiming Li; Xiaojia Guo; Lixia Chen; Hua Li; Ruiyuan Cao; Xingzhou Li
Journal:  Molecules       Date:  2020-11-13       Impact factor: 4.411

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