High throughput virtual screening (HTVS) of peptide library: Technological advancement in ligand discovery.

Autor: Tripathi NM; Biomimetic Peptide Engineering Laboratory, Department of Chemistry, Indian Institute of Technology, Ropar, Punjab, 140001, India., Bandyopadhyay A; Biomimetic Peptide Engineering Laboratory, Department of Chemistry, Indian Institute of Technology, Ropar, Punjab, 140001, India. Electronic address: anupamba@iitrpr.ac.in.
Jazyk: angličtina
Zdroj: European journal of medicinal chemistry [Eur J Med Chem] 2022 Dec 05; Vol. 243, pp. 114766. Date of Electronic Publication: 2022 Sep 13.
DOI: 10.1016/j.ejmech.2022.114766
Abstrakt: High-throughput virtual screening (HTVS) is a leading biopharmaceutical technology that employs computational algorithms to uncover biologically active compounds from large-scale collections of chemical compound libraries. In addition, this method often leverages the precedence of screening focused libraries for assessing their binding affinities and improving physicochemical properties. Usually, developing a drug sometimes takes ages, and lessons are learnt from FDA-approved drugs. This screening strategy saves resources and time compared to laboratory testing in certain stages of drug discovery. Yet in-silico investigations remain challenging in some cases of drug discovery. For the last few decades, peptide-based drug discoveries have received remarkable momentum for several advantages over small molecules. Therefore, developing a high-fidelity HTVS platform for chemically versatile peptide libraries is highly desired. This review summarises the modern and frequently appreciated HTVS strategies for peptide libraries from 2011 to 2021. In addition, we focus on the software used for preparing peptide libraries, their screening techniques and shortcomings. An index of various HTVS methods reported here should assist researchers in identifying tools that could be beneficial for their peptide library screening projects.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2022 Elsevier Masson SAS. All rights reserved.)
Databáze: MEDLINE
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