Computational Tools in Drug-Lead Identification and Development

Drug discovery is a multidisciplinary process, which encompasses scientific areas like chemistry, biology, pharmacology, and computer sciences. In the past decades, drug discovery was very laborious, expensive, and time consuming process. Massive efforts were needed to harness computational capabilities to encompass both chemical and biological domains, aiming to streamline the processes of drug discovery, design, development, and optimization. The introduction of super computers and accurate algorithms revolutionized different methods in drug discovery such as hit identification, hit-to-lead selection, lead optimization, pharmacokinetic analysis, and toxicity assessment. Computer-aided drug discovery (CADD) is a general term that covers various in silico tools and methods associated with drug discovery. The area is still advancing with the application of artificial intelligence in CADD tools and software. This chapter is devoted to expound various tools and methods frequently used in CADD including structure modeling, pharmacokinetics and toxicity prediction, pharmacophore modeling, molecular docking, and molecular dynamics.