PPI-Miner: A Structure and Sequence Motif Co-Driven Protein-Protein Interaction Mining and Modeling Computational Method

doi:10.1021/acs.jcim.2c01033

	PPI-Miner: A Structure and Sequence Motif Co-Driven Protein-Protein Interaction Mining and Modeling Computational Method
	Wang, Lin1 ; Li, Feng-lei1 ; Ma, Xin-yue1 ; Cang, Yong2 ; Bai, Fang1,3
	2022-11-01
发表期刊	JOURNAL OF CHEMICAL INFORMATION AND MODELING
ISSN	1549-9596
EISSN	1549-960X
发表状态	已发表
DOI	10.1021/acs.jcim.2c01033
摘要	Protein-protein interactions (PPIs) play important roles in biological processes of life, and predicting PPIs becomes a critical scientific issue of concern. Most PPIs occur through small domains or motifs (fragments), which are challenging and laborious to map by standard biochemical approaches because they generally require the cloning of several truncation mutants. Here, we present a computational method, named as PPI-Miner, to fish potential protein interacting partners utilizing protein motifs as queries. In brief, this work first developed a motif-matching algorithm designed to identify the proteins that contain sequential or structural similar motifs with the given query motif. Being aligned to the query motif, the binding mode of the discovered motif and its receptor protein will be initially determined to be used to build PPI complexes accordingly. Eventually, a PPI complex structure could be built and optimized with a designed automatic protocol. Besides discovering PPIs, PPI-Miner can also be applied to other areas, i.e., the rational design of molecular glues and protein vaccines. In this work, PPI-Miner was employed to mine the potential cereblon (CRBN) substrates from human proteome. As a result, 1,739 candidates were predicted, and 16 of them have been experimentally validated in previous studies. The source code of PPI-Miner can be obtained from the GitHub repository (https://github.com/Wang-Lin-boop/PPI-Miner), the webserver is freely available for users (https://bailab.siais.shanghaitech.edu. cn/services/ppi-miner), and the database of predicted CRBN substrates is accessible at https://bailab.siais.shanghaitech.edu.cn/ services/crbn-subslib.
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收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China["2020YFA0509700","2022YFC3400501"] ; Lingang Laboratory[LG202102-01-03] ; Shanghai Science and Technology Development Funds["20QA1406400","22ZR1441400"] ; National Natural Science Foundation of China[82003654]
WOS研究方向	Pharmacology & Pharmacy ; Chemistry ; Computer Science
WOS类目	Chemistry, Medicinal ; Chemistry, Multidisciplinary ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications
WOS记录号	WOS:000892084300001
出版者	AMER CHEMICAL SOC
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/258929
专题	免疫化学研究所_PI研究组_白芳组生命科学与技术学院_PI研究组_仓勇组生命科学与技术学院_博士生信息科学与技术学院_硕士生
通讯作者	Bai, Fang
作者单位	1.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, Sch Life Sci & Technol Informat Sci & Technol, Shanghai 201210, Peoples R China 2.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China 3.Shanghai Clin Res & Trial Ctr, Shanghai 201210, Peoples R China
第一作者单位	免疫化学研究所
通讯作者单位	免疫化学研究所
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	Wang, Lin,Li, Feng-lei,Ma, Xin-yue,et al. PPI-Miner: A Structure and Sequence Motif Co-Driven Protein-Protein Interaction Mining and Modeling Computational Method[J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING,2022.
APA	Wang, Lin,Li, Feng-lei,Ma, Xin-yue,Cang, Yong,&Bai, Fang.(2022).PPI-Miner: A Structure and Sequence Motif Co-Driven Protein-Protein Interaction Mining and Modeling Computational Method.JOURNAL OF CHEMICAL INFORMATION AND MODELING.
MLA	Wang, Lin,et al."PPI-Miner: A Structure and Sequence Motif Co-Driven Protein-Protein Interaction Mining and Modeling Computational Method".JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022).