Current Approaches and Strategies Applied in First-in-class Drug Discovery

ChemMedChem. 2024 Dec 8:e202400639. doi: 10.1002/cmdc.202400639. Online ahead of print.

Abstract

First-in-class drug discovery (FICDD) offers novel therapies, new biological targets and mechanisms of action (MOAs) toward targeting various diseases and provides opportunities to understand unexplored biology and to target unmet diseases. Current screening approaches followed in FICDD for discovery of hit and lead molecules can be broadly categorized and discussed under phenotypic drug discovery (PDD) and target-based drug discovery (TBDD). Each category has been further classified and described with suitable examples from the literature outlining the current trends in screening approaches applied in small molecule drug discovery (SMDD). Similarly, recent applications of functional genomics, structural biology, artificial intelligence (AI), machine learning (ML), and other such advanced approaches in FICDD have also been highlighted in the article. Further, some of the current medicinal chemistry strategies applied during discovery of hits and optimization studies such as hit-to-lead (HTL) and lead optimization (LO) have been simultaneously overviewed in this article.

Keywords: Artificial Intelligence; First-in-class drug discovery; Functional genomics and structural biology; current screening approaches; medicinal chemistry strategies.

Publication types

  • Review