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Sequence-based drug design as a concept in computational drug design

文献类型：期刊论文

作者Chen, Lifan1,2; Fan, Zisheng1,3,4,5; Chang, Jie1,3; Yang, Ruirui1,2,4,5; Hou, Hui1; Guo, Hao1; Zhang, Yinghui1,2; Yang, Tianbiao1,2; Zhou, Chenmao1,3; Sui, Qibang1,2
刊名NATURE COMMUNICATIONS
出版日期2023-07-14
卷号14期号:1页码:21
DOI10.1038/s41467-023-39856-w
通讯作者Zhang, Sulin(slzhang@simm.ac.cn) ; Zheng, Mingyue(myzheng@simm.ac.cn)
英文摘要Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design (SBDD) pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, we propose a sequence-to-drug concept for computational drug design based on protein sequence information by end-to-end differentiable learning. We validate this concept in three stages. First, we design TransformerCPI2.0 as a core tool for the concept, which demonstrates generalization ability across proteins and compounds. Second, we interpret the binding knowledge that TransformerCPI2.0 learned. Finally, we use TransformerCPI2.0 to discover new hits for challenging drug targets, and identify new target for an existing drug based on an inverse application of the concept. Overall, this proof-of-concept study shows that the sequence-to-drug concept adds a perspective on drug design. It can serve as an alternative method to SBDD, particularly for proteins that do not yet have high-quality 3D structures available. Conventional structure-based drug design pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, the authors report a sequence-to-drug concept that discovers drug-like small molecule modulators directly from protein sequences.
WOS关键词PROTEIN INTERACTIONS ; DATABASE ; OPTIMIZATION ; DISCOVERY ; DOCKING ; SPOP ; TRANSFORMER ; PREDICTION ; MK-1439 ; LIGASE
资助项目National Natural Science Foundation of China[T2225002] ; National Natural Science Foundation of China[82273855] ; National Natural Science Foundation of China[91953203] ; National Key Research and Development Program of China[22ZR1474300] ; Youth Innovation Promotion Association CAS[LG202102-01-02] ; Natural Science Foundation of Shanghai[LG-QS-202204-01] ; Lingang Laboratory[E2G805H] ; SIMM-SHUTCM Traditional Chinese Medicine Innovation Joint Research Program ; [2022YFC3400504] ; [2023296]
WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:001033533300016
出版者NATURE PORTFOLIO
源URL[http://119.78.100.183/handle/2S10ELR8/306821]  
专题新药研究国家重点实验室
通讯作者Zhang, Sulin; Zheng, Mingyue
作者单位1.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China
2.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China
3.Nanjing Univ Chinese Med, Sch Chinese Mat Med, 138 Xianlin Rd, Nanjing 210023, Jiangsu, Peoples R China
4.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, 393 Huaxia Middle Rd, Shanghai 200031, Peoples R China
5.ShanghaiTech Univ, Sch Life Sci & Technol, 393 Huaxia Middle Rd, Shanghai 200031, Peoples R China
6.Chinese Acad Sci, Shanghai Inst Mat Med, Dept Analyt Chem, State Key Lab Drug Res, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China
7.Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Sch Pharmaceut Sci & Technol, 1 Sub Lane Xiangshan, Hangzhou 310024, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Lifan,Fan, Zisheng,Chang, Jie,et al. Sequence-based drug design as a concept in computational drug design[J]. NATURE COMMUNICATIONS,2023,14(1):21.
APA Chen, Lifan.,Fan, Zisheng.,Chang, Jie.,Yang, Ruirui.,Hou, Hui.,...&Zheng, Mingyue.(2023).Sequence-based drug design as a concept in computational drug design.NATURE COMMUNICATIONS,14(1),21.
MLA Chen, Lifan,et al."Sequence-based drug design as a concept in computational drug design".NATURE COMMUNICATIONS 14.1(2023):21.

入库方式： OAI收割

来源：上海药物研究所

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