Faculty of Pharmaceutical Sciences, Setsunan University.
Chem Pharm Bull (Tokyo). 2024;72(9):794-799. doi: 10.1248/cpb.c23-00790.
Recently, remarkable progress has been achieved in artificial intelligence (AI), including machine learning. Various AI models have been proposed for drug discovery, including the design of small molecules, activity prediction, and three-dimensional (3D) structure prediction of proteins. AI consists of diverse elements, including information retrieval and machine learning, and can be used in a wide range of drug discovery scenarios. In this review, we focused on AI for small-molecule drug discovery with respect to molecular design, activity prediction, and prediction of the binding poses of compounds to target molecules. We also discussed the applications of AI in academic drug discovery.
最近，人工智能（AI）取得了显著的进展，包括机器学习。已经提出了各种 AI 模型用于药物发现，包括小分子的设计、活性预测和蛋白质的三维（3D）结构预测。AI 包括信息检索和机器学习等多种元素，可应用于广泛的药物发现场景。在这篇综述中，我们专注于 AI 在小分子药物发现方面的应用，包括分子设计、活性预测和化合物与靶分子结合构象的预测。我们还讨论了 AI 在学术药物发现中的应用。
