Computational methods and key considerations for in silico design of proteolysis targeting chimera (PROTACs)

被引:9
作者
Abbas, Amr [1 ,2 ]
Ye, Fei [1 ]
机构
[1] Zhejiang Sci Tech Univ, Coll Life Sci & Med, Hangzhou 310018, Peoples R China
[2] Cairo Univ, Fac Pharm, Pharmaceut Chem Dept, Cairo 11562, Egypt
基金
中国国家自然科学基金;
关键词
PROTAC; Artificial intelligence; Machine learning; Deep learning; Drug design; Computational tools; TERNARY COMPLEX-FORMATION; E3 UBIQUITIN LIGASES; PROTEIN-DEGRADATION; CHAMELEONIC PROPERTIES; FRAGMENT LINKING; PREDICTION; DISCOVERY; RECOGNITION; LIGANDS; RULE;
D O I
10.1016/j.ijbiomac.2024.134293
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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 nonAI-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.
引用
收藏
页数:14
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