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

作　　者：曾浩 吴国振 邹武新 王哲 宋剑飞 施慧 汪小涧 侯廷军 邓亚峰[1,4] ZENG Hao;WU Guozhen;ZOU Wuxin;WANG Zhe;SONG Jianfei;SHI Hui;WANG Xiaojian;HOU Tingjun;DENG Yafeng(Hangzhou Carbonsilicon AI Technology Co.,Ltd,Hangzhou 310018;College of Pharmaceutical Sciences,Zhejiang University,Hangzhou 310058;Beijing Key Laboratory of Active Substances Discovery and Druggability Evaluation,State Key Laboratory of Bioactive Substances and Functions of Natural Medicines,Peking Union Medical College&Chinese Academy of Medical Sciences,Institute of Materia Medica,Beijing 100050;Department of Automation,Tsinghua University,Beijing 100084,China)

机构地区：[1]杭州碳硅智慧科技发展有限公司,杭州310018 [2]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]清华大学自动化系,北京100084

出　　处：《中国药科大学学报》2024年第3期326-334,共9页Journal of China Pharmaceutical University

摘　　要：以深度学习为代表的新一代人工智能技术已经成为推动新药研发的重要驱动力。本文创造性地提出了一种基于人工智能技术的创新药物分子设计和优化工作流程“分子工厂”,该流程融合了自主研发的智能分子生成模型、高性能分子对接算法以及高精度亲和力预测方法,已作为核心模块被整合进一站式药物设计软件平台DrugFlow,为先导化合物发现和优化提供了一整套成熟的解决方案。利用“分子工厂”模块,针对Menin蛋白开展了抗耐药第2代抑制剂的研发。通过计算和实验的结合,快速获得多个潜力化合物,其中化合物RG-10对Menin野生型、M327I突变体和T349M突变体的IC50分别为9.681 nmol/L、233.2 nmol/L和40.09 nmol/L;与已进入Ⅱ期临床的阳性参照分子SNDX-5613相比,其对M327I和T349M突变体的抑制活性显著提升。上述研究充分展现了“分子工厂”技术在新药研发项目中的独特优势,能快速高效地针对特定蛋白结构产生高质量的活性分子,对推动新药研发具有重大价值和深远意义。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 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] R914[自动化与计算机技术—控制科学与工程]