Department of Computer Sciences, Louisiana State University, Baton Rouge, LA, USA.
Department of Mathematics, Louisiana State University, Baton Rouge, LA, USA.
Drug Discov Today. 2022 Apr;27(4):1099-1107. doi: 10.1016/j.drudis.2021.10.022. Epub 2021 Nov 5.
The search for effective drugs to treat new and existing diseases is a laborious one requiring a large investment of capital, resources, and time. The coronavirus 2019 (COVID-19) pandemic has been a painful reminder of the lack of development of new antimicrobial agents to treat emerging infectious diseases. Artificial intelligence (AI) and other in silico techniques can drive a more efficient, cost-friendly approach to drug discovery by helping move potential candidates with better clinical tolerance forward in the pipeline. Several research teams have developed successful AI platforms for hit identification, lead generation, and lead optimization. In this review, we investigate the technologies at the forefront of spearheading an AI revolution in drug discovery and pharmaceutical sciences.
寻找有效药物来治疗新的和现有的疾病是一项艰巨的任务，需要大量的资金、资源和时间投入。2019 年冠状病毒（COVID-19）大流行痛苦地提醒人们，缺乏开发新的抗菌剂来治疗新出现的传染病。人工智能（AI）和其他计算机技术可以通过帮助将具有更好临床耐受性的潜在候选药物推向管道中的下一阶段，从而更有效地、以更低成本发现药物。有几个研究团队已经开发出成功的人工智能平台，用于命中鉴定、先导生成和先导优化。在这篇综述中，我们研究了处于药物发现和药物科学领域人工智能革命前沿的技术。
