DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras

doi:10.1093/bib/bbae358

KMS > 免疫化学研究所

	DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras
	Li, Fenglei1,2 ; Hu, Qiaoyu 3; Zhou, Yongqi1,4 ; Yang, Hao1,4 ; Bai, Fang1,2,4,5
	2024-08-05
发表期刊	BRIEFINGS IN BIOINFORMATICS
ISSN	1467-5463
EISSN	1477-4054
卷号	25 期号:5
发表状态	已发表
DOI	10.1093/bib/bbae358
摘要	PROteolysis TArgeting Chimeras (PROTACs) has recently emerged as a promising technology. However, the design of rational PROTACs, especially the linker component, remains challenging due to the absence of structure-activity relationships and experimental data. Leveraging the structural characteristics of PROTACs, fragment-based drug design (FBDD) provides a feasible approach for PROTAC research. Concurrently, artificial intelligence-generated content has attracted considerable attention, with diffusion models and Transformers emerging as indispensable tools in this field. In response, we present a new diffusion model, DiffPROTACs, harnessing the power of Transformers to learn and generate new PROTAC linkers based on given ligands. To introduce the essential inductive biases required for molecular generation, we propose the O(3) equivariant graph Transformer module, which augments Transformers with graph neural networks (GNNs), using Transformers to update nodes and GNNs to update the coordinates of PROTAC atoms. DiffPROTACs effectively competes with existing models and achieves comparable performance on two traditional FBDD datasets, ZINC and GEOM. To differentiate the molecular characteristics between PROTACs and traditional small molecules, we fine-tuned the model on our self-built PROTACs dataset, achieving a 93.86% validity rate for generated PROTACs. Additionally, we provide a generated PROTAC database for further research, which can be accessed at https://bailab.siais.shanghaitech.edu.cn/service/DiffPROTACs-generated.tgz. The corresponding code is available at https://github.com/Fenglei104/DiffPROTACs and the server is at https://bailab.siais.shanghaitech.edu.cn/services/diffprotacs.
关键词	PROTACs linker generation de-novo drug design deep learning PROTAC database
URL	查看原文
收录类别	SCI
语种	英语
资助项目	Shanghai Science and Technology Development Funds["22ZR1441400","20QA1406400"] ; National Key R&D Program of China["2022YFC3400501","2022YFC3400500"] ; National Natural Science Foundation of China[82003654]
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Mathematical & Computational Biology
WOS记录号	WOS:001283426600003
出版者	OXFORD UNIV PRESS
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/414191
专题	免疫化学研究所信息科学与技术学院生命科学与技术学院生命科学与技术学院_硕士生生命科学与技术学院_博士生信息科学与技术学院_硕士生免疫化学研究所_PI研究组_白芳组
通讯作者	Bai, Fang
作者单位	1.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, 393 Middle Huaxia Rd Pudong New Area, Shanghai 201210, Peoples R China 2.ShanghaiTech Univ, Sch Informat Sci & Technol, 393 Middle Huaxia Rd Pudong New Area, Shanghai 201210, Peoples R China 3.East China Normal Univ, Innovat Ctr AI & Drug Discovery, Sch Pharm, 3663 Zhongshan North Rd, Shanghai 200062, Peoples R China 4.ShanghaiTech Univ, Sch Life Sci & Technol, 393 Middle Huaxia Rd Pudong New Area, Shanghai 201210, Peoples R China 5.Shanghai Clin Res & Trial Ctr, 1599 Keyuan Rd Pudong New Area, Shanghai 201210, Peoples R China
第一作者单位	免疫化学研究所; 信息科学与技术学院
通讯作者单位	免疫化学研究所; 信息科学与技术学院; 生命科学与技术学院
第一作者的第一单位	免疫化学研究所
推荐引用方式 GB/T 7714	Li, Fenglei,Hu, Qiaoyu,Zhou, Yongqi,et al. DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras[J]. BRIEFINGS IN BIOINFORMATICS,2024,25(5).
APA	Li, Fenglei,Hu, Qiaoyu,Zhou, Yongqi,Yang, Hao,&Bai, Fang.(2024).DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras.BRIEFINGS IN BIOINFORMATICS,25(5).
MLA	Li, Fenglei,et al."DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras".BRIEFINGS IN BIOINFORMATICS 25.5(2024).