药物发现
计算机科学
计算生物学
计算模型
生化工程
弹头
转化式学习
药物开发
结构生物信息学
药品
降级(电信)
计算复杂性理论
数量结构-活动关系
风险分析(工程)
系统生物学
生物信息学
作者
Massyel S. Martínez-Cortés,Carlos A. Velázquez‐Martínez,José L. Medina-Franco
标识
DOI:10.1016/j.drudis.2026.104627
摘要
Proteolysis-targeting chimeras (PROTACs) represent a transformative strategy in drug discovery, enabling the selective degradation of target proteins rather than merely inhibiting their activity. However, their structural complexity and deviation from conventional drug-like properties present major challenges for traditional design and optimization methods. In this review, we provide a comprehensive overview of recent computational advances that facilitate PROTAC development, encompassing chemoinformatics, structural bioinformatics, molecular modeling and machine learning resources. We highlight computational tools for warhead and linker design, ternary complex modeling and the prediction of degradation efficiency and ADMET profiles. Finally, we discuss current limitations and future perspectives, emphasizing strategies to enhance design effectiveness and accelerate clinical translation.
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