Department of Biophysics, All India Institute of Medical Sciences, New Delhi, 110029, India.
Department of Biochemistry, Pt. Jawahar Lal Nehru Memorial Medical College, Raipur, 492001, India.
Mol Divers. 2021 Aug;25(3):1439-1460. doi: 10.1007/s11030-021-10256-w. Epub 2021 Jun 23.
The accumulation of massive data in the plethora of Cheminformatics databases has made the role of big data and artificial intelligence (AI) indispensable in drug design. This has necessitated the development of newer algorithms and architectures to mine these databases and fulfil the specific needs of various drug discovery processes such as virtual drug screening, de novo molecule design and discovery in this big data era. The development of deep learning neural networks and their variants with the corresponding increase in chemical data has resulted in a paradigm shift in information mining pertaining to the chemical space. The present review summarizes the role of big data and AI techniques currently being implemented to satisfy the ever-increasing research demands in drug discovery pipelines.
大量数据在化学信息学数据库中的积累使得大数据和人工智能(AI)在药物设计中不可或缺。这就需要开发新的算法和架构来挖掘这些数据库,并满足各种药物发现过程的特定需求,如虚拟药物筛选、从头分子设计和在这个大数据时代的发现。深度学习神经网络及其变体的发展以及相应的化学数据的增加,导致了与化学空间相关的信息挖掘范式的转变。本综述总结了目前正在实施的大数据和 AI 技术在满足药物发现管道中不断增长的研究需求方面的作用。