Mohammed Idrees, Sagurthi Someswar Rao
Drug Design & Molecular Medicine Laboratory, Department of Genetics & Biotechnology, Osmania University, Hyderabad, 500007, Telangana, India.
Special Center for Molecular Medicine, Jawaharlal Nehru University, New Delhi, 110067, India.
ChemMedChem. 2025 Mar 15;20(6):e202400639. doi: 10.1002/cmdc.202400639. Epub 2024 Dec 20.
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.
首创药物发现(FICDD)提供了针对各种疾病的新型疗法、新的生物学靶点和作用机制(MOA),并为理解未被探索的生物学以及针对未满足的疾病提供了机会。FICDD中用于发现活性和先导分子的当前筛选方法可大致归类并在表型药物发现(PDD)和基于靶点的药物发现(TBDD)下进行讨论。每一类都已进一步分类,并结合文献中的合适例子进行描述,概述了小分子药物发现(SMDD)中应用的筛选方法的当前趋势。同样,本文还强调了功能基因组学、结构生物学、人工智能(AI)、机器学习(ML)以及其他此类先进方法在FICDD中的最新应用。此外,本文还同时概述了在活性发现和优化研究(如从活性到先导(HTL)和先导优化(LO))过程中应用的一些当前药物化学策略。