Tools and software for computer-aided drug design and discovery

Document Type

Article

Publication Date

1-1-2023

Abstract

Traditional drug discovery is a time intense, expensive, and complicated procedure. The amalgamation of computer-aided drug design (CADD) and experimental processes can make the whole drug discovery process rational, time efficient, and economical. CADD has two major workflows. One is ligand-based drug design (LBDD) where researchers work with query molecules (ligands), which can be a potential drug for a specific disease. Researchers can check ligands for diverse physicochemical properties and predict their activity against specific diseases. Alternatively, structure-based drug design (SBDD) utilizes protein and enzyme/receptor information and their 3D structures to find the key binding interaction of a prospective drug with specific amino acids. Overall, the CADD approach is highly dependent on applications of commercial and open-source software. With the availability of high-performance computers, supercomputers, cloud-based computing systems, and open-access codes from Github, the CADD process has become extremely viable and effective in terms of reliable drug design and discovery. This chapter discusses the major available tools and software required in different steps of CADD. The provided information can be a valuable resource for the beginners and experienced researchers in the arenas of drug design, computational modeling, chemoinformatics, and medicinal chemistry.

Publication Title

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development

First Page Number

637

Last Page Number

661

DOI

10.1016/B978-0-443-18638-7.00017-7

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