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基于3D的生成性PROTAC链接器设计与强化学习
Baiqing Li1, Ting Ran1, Hongming Chen1
1Guangzhou Laboratory, Guangzhou 510005, Guangdong Province, China.
Briefings in bioinformatics
|September 6, 2023
概括
针对蛋白质溶解的嵌合体 (PROTACs) 提供有针对性的蛋白质降解. 一个新的3D生成模型,PROTAC-INVENT,设计了PROTAC连接器,用于改进药物发现.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 针对蛋白质溶解的嵌合体 (PROTACs) 利用无素-蛋白质酶系统进行选择性蛋白质降解.
- 在PROTAC中,有对感兴趣的蛋白质 (POI) 的核弹头和由链接器连接的E3-酶连接体.
- 理性链接器设计是复杂的,往往缺乏3D结构信息.
研究的目的:
- 介绍PROTAC-INVENT,这是一个用于PROTAC链接器设计的新型3D生成模型.
- 为了生成具有假定3D结合形状的PROTAC结构.
- 通过先进的计算方法提高 PROTAC 开发的效率.
主要方法:
- 开发PROTAC-INVENT,这是一个PROTACs的3D生成模型.
- 与强化学习 (RL) 进行联合培训,以优化2D和3D属性.
- 为 PROTACs,标蛋白和 E3 连接酶生成 SMILES 和 3D 构造.
主要成果:
- PROTAC-INVENT成功地产生了 PROTAC SMILES 和相应的 3D 结合形状.
- 该模型证明了在创建合理的3D PROTAC结构时的实用性.
- 3D 形态生成工作流作为一个高效的 PROTAC 对接协议.
结论:
- PROTAC-INVENT为合理的 PROTAC 链接器设计提供了一种新的方法.
- 该模型有助于生成3D PROTAC形状,帮助药物发现.
- 开发的工作流程提高了PROTAC对接和设计效率.
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