Abstract:
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.
