Department of Pharmaceutical Sciences, Dr. Harisingh Gour Vishwavidyalaya, Sagar, MP, India.
Sri Aurobindo Institute of Pharmacy, Indore, MP, India.
Comb Chem High Throughput Screen. 2022;25(11):1818-1837. doi: 10.2174/1386207325666211207153943.
The advancement of computing and technology has invaded all the dimensions of science. Artificial intelligence (AI) is one core branch of Computer Science, which has percolated to all the arenas of science and technology, from core engineering to medicines. Thus, AI has found its way for application in the field of medicinal chemistry and heath care. The conventional methods of drug design have been replaced by computer-aided designs of drugs in recent times. AI is being used extensively to improve the design techniques and required time of the drugs. Additionally, the target proteins can be conveniently identified using AI, which enhances the success rate of the designed drug. The AI technology is used in each step of the drug designing procedure, which decreases the health hazards related to preclinical trials and also reduces the cost substantially. The AI is an effective tool for data mining based on the huge pharmacological data and machine learning process. Hence, AI has been used in de novo drug design, activity scoring, virtual screening and in silico evaluation in the properties (absorption, distribution, metabolism, excretion and toxicity) of a drug molecule. Various pharmaceutical companies have teamed up with AI companies for faster progress in the field of drug development, along with the healthcare system. The review covers various aspects of AI (Machine learning, Deep learning, Artificial neural networks) in drug design. It also provides a brief overview of the recent progress by the pharmaceutical companies in drug discovery by associating with different AI companies.
计算机和技术的进步已经渗透到科学的各个领域。人工智能（AI）是计算机科学的一个核心分支，已经渗透到科学和技术的各个领域，从核心工程到医学。因此，人工智能已经在药物化学和医疗保健领域找到了应用的途径。最近，药物设计的传统方法已经被计算机辅助药物设计所取代。人工智能被广泛用于改进药物的设计技术和所需时间。此外，人工智能可以方便地识别靶蛋白，从而提高设计药物的成功率。人工智能技术用于药物设计过程的每一个步骤，这降低了与临床前试验相关的健康危害，同时也大大降低了成本。人工智能是基于庞大的药理学数据和机器学习过程进行数据挖掘的有效工具。因此，人工智能已被用于从头药物设计、活性评分、虚拟筛选和药物分子性质（吸收、分布、代谢、排泄和毒性）的计算评估。各种制药公司已经与人工智能公司合作，以在药物开发领域取得更快的进展，同时也与医疗保健系统合作。本综述涵盖了人工智能（机器学习、深度学习、人工神经网络）在药物设计中的各个方面。它还简要概述了制药公司与不同人工智能公司合作在药物发现方面的最新进展。
