Abbas Amr, Ye Fei
College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China; Pharmaceutical Chemistry Department, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt.
College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Int J Biol Macromol. 2024 Oct;277(Pt 4):134293. doi: 10.1016/j.ijbiomac.2024.134293. Epub 2024 Jul 29.
Proteolysis-targeting chimeras (PROTACs), as heterobifunctional molecules, have garnered significant attention for their ability to target previously undruggable proteins. Due to the challenges in obtaining crystal structures of PROTAC molecules in the ternary complex, a plethora of computational tools have been developed to aid in PROTAC design. These computational tools can be broadly classified into artificial intelligence (AI)-based or non-AI-based methods. This review aims to provide a comprehensive overview of the latest computational methods for the PROTAC design process, covering both AI and non-AI approaches, from protein selection to ternary complex modeling and prediction. Key considerations for in silico PROTAC design are discussed, along with additional considerations for deploying AI-based models. These considerations are intended to guide subsequent model development in the PROTAC design process. Finally, future directions and recommendations are provided.
靶向蛋白降解嵌合体(PROTAC)作为异双功能分子,因其能够靶向先前难以成药的蛋白质而备受关注。由于在获得三元复合物中PROTAC分子的晶体结构方面存在挑战,人们开发了大量计算工具来辅助PROTAC设计。这些计算工具大致可分为基于人工智能(AI)的方法或非基于AI的方法。本综述旨在全面概述PROTAC设计过程的最新计算方法,涵盖从蛋白质选择到三元复合物建模与预测的基于AI和非基于AI的方法。讨论了计算机辅助PROTAC设计的关键考虑因素,以及部署基于AI模型的其他考虑因素。这些考虑因素旨在指导PROTAC设计过程中的后续模型开发。最后,给出了未来的方向和建议。