药物发现
计算生物学
班级(哲学)
数据科学
计算机科学
表型筛选
生物信息学
生物
人工智能
表型
遗传学
基因
作者
Idrees Mohammed,Someswar Rao Sagurthi
标识
DOI:10.1002/cmdc.202400639
摘要
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.
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