中国药科大学学报2024，Vol.55Issue(3)：326-334,9.DOI:10.11665/j.issn.1000-5048.2024040904
基于人工智能驱动分子工厂技术的Menin抑制剂优化
Optimization of Menin inhibitors based on artificial intelligence-driven molecular factory technology
曾浩 1吴国振 1邹武新 1王哲 2宋剑飞 1施慧 1汪小涧 3侯廷军 2邓亚峰4
作者信息
- 1. 杭州碳硅智慧科技发展有限公司,杭州 310018
- 2. 杭州碳硅智慧科技发展有限公司,杭州 310018||浙江大学药学院,杭州 310058
- 3. 中国医学科学院、北京协和医学院药物研究所,天然药物活性物质与功能国家重点实验室,活性物质发现与适药化研究北京市重点实验室,北京 100050
- 4. 杭州碳硅智慧科技发展有限公司,杭州 310018||清华大学自动化系,北京 100084
- 折叠
摘要
Abstract
The new generation of artificial intelligence technology,represented by deep learning,has emerged as a crucial driving force in the advancement of new drug research and development.This article creatively proposes a workflow named"Molecular Factory"for the design and optimization of drug molecules based on artificial intelligence technology.This workflow integrates intelligent molecular generation models,high-performance molecular docking algorithms,and accurate protein-ligand binding affinity prediction methods.It has been integrated as a core module into DrugFlow,a one-stop drug design software platform,providing a comprehensive set of mature solutions for the discovery and optimization of lead compounds.Utilizing the"Molecular Factory"module,we conducted the research of second-generation inhibitors against Menin that can combat drug resistance.Through the integration of computational and experimental approaches,we rapidly identified multiple promising compounds.Among them,compound RG-10 exhibited the IC50 values of 9.681 nmol/L,233.2 nmol/L,and 40.09 nmol/L against the wild-type Menin,M327I mutant,and T349M mutant,respectively.Compared to the positive reference molecule SNDX-5613,which has entered Phase Ⅱ clinical trials,RG-10 demonstrated significantly enhanced inhibitory activity against the M327I and T349M mutants.These findings fully demonstrate the unique advantages of the"Molecular Factory"technology in practical drug design and development scenarios.It can rapidly and efficiently generate high-quality active molecules targeting specific protein structures,holding significant value and profound implications for advancing new drug discovery.关键词
分子工厂/人工智能/分子生成/分子对接/Menin抑制剂Key words
molecular factory/artificial intelligence/molecule generation/molecular docking/Menin inhibitor分类
信息技术与安全科学引用本文复制引用
曾浩,吴国振,邹武新,王哲,宋剑飞,施慧,汪小涧,侯廷军,邓亚峰..基于人工智能驱动分子工厂技术的Menin抑制剂优化[J].中国药科大学学报,2024,55(3):326-334,9.
