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CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction

文献类型：期刊论文

作者Wang, Xun3,4; Liu, Dayan4; Zhu, Jinfu2; Rodriguez-Paton, Alfonso1; Song, Tao1,4
刊名BIOMOLECULES
出版日期2021-05-01
卷号11期号:5页码:9
关键词protein-ligand binding affinity 2-D structural CNN spatial attention mechanism
DOI10.3390/biom11050643
英文摘要The binding affinity of small molecules to receptor proteins is essential to drug discovery and drug repositioning. Chemical methods are often time-consuming and costly, and models for calculating the binding affinity are imperative. In this study, we propose a novel deep learning method, namely CSConv2d, for protein-ligand interactions' prediction. The proposed method is improved by a DEEPScreen model using 2-D structural representations of compounds as input. Furthermore, a channel and spatial attention mechanism (CS) is added in feature abstractions. Data experiments conducted on ChEMBLv23 datasets show that CSConv2d performs better than the original DEEPScreen model in predicting protein-ligand binding affinity, as well as some state-of-the-art DTIs (drug-target interactions) prediction methods including DeepConv-DTI, CPI-Prediction, CPI-Prediction+CS, DeepGS and DeepGS+CS. In practice, the docking results of protein (PDB ID: 5ceo) and ligand (Chemical ID: 50D) and a series of kinase inhibitors are operated to verify the robustness.
资助项目National Natural Science Foundation of China[61873280] ; National Natural Science Foundation of China[61873281] ; National Natural Science Foundation of China[61972416] ; Taishan Scholarship[tsqn201812029] ; Major projects of the National Natural Science Foundation of China[41890851] ; Natural Science Foundation of Shandong Province[ZR2019MF012]
WOS研究方向Biochemistry & Molecular Biology
语种英语
WOS记录号WOS:000653400100001
出版者MDPI
源URL[http://119.78.100.204/handle/2XEOYT63/17561]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhu, Jinfu; Song, Tao
作者单位1.Univ Politecn Madrid, Fac Comp Sci, Dept Artificial Intelligence, Campus Montegancedo, Madrid 28660, Spain
2.Beijing Technol & Business Univ, Sch Econ, Beijing 100048, Peoples R China
3.Chinese Acad Sci, High Performance Comp Res Ctr, Inst Comp Technol, Beijing 100190, Peoples R China
4.China Univ Petr, Coll Comp Sci & Technol, Qingdao 266580, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Xun,Liu, Dayan,Zhu, Jinfu,et al. CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction[J]. BIOMOLECULES,2021,11(5):9.
APA Wang, Xun,Liu, Dayan,Zhu, Jinfu,Rodriguez-Paton, Alfonso,&Song, Tao.(2021).CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction.BIOMOLECULES,11(5),9.
MLA Wang, Xun,et al."CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction".BIOMOLECULES 11.5(2021):9.

入库方式： OAI收割

来源：计算技术研究所

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