Lead optimization evaluation using computer-aided paradigm

Abstract

During the early part of 1970, lead compounds were optimized numerically in the absence of computers. Subsequent to that, a few computer-aided designs were developed but only to a limited extent. Combinatorial chemistry has brought short improvements with drastic failures due to low drug target rates, pharmacokinetic errors and increased toxicity. This paper aimed to apply the concepts of computer-aided drug design to formulation needed for drug development. Integration of computer-aided molecular design to perform computational approaches for investigation of quantitative structure-activity relationships (QSAR) and quantitative structure-properties relationships (QSPR) have improved the potency and selectivity of possible lead compounds prior to clinical trials and hastened the process of drug discovery. These computational algorithms had resolved previous issues and lessened the toxicities and enhanced the pharmacokinetic accountabilities. Virtual screening can assess the therapeutic activity by means of machine learning techniques. Hence, drug candidate optimization can be achieved in a timely and economical manner using computer-aided computational processes.

Keywords: computational approach; QSAR; QSPR; drug design; drug candidate