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D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening

文献类型：期刊论文

作者Shi, Yulong1,2,3; Zhang, Xinben1,2; Yang, Yanqing1,2,3; Cai, Tingting1,2; Peng, Cheng1,2,3; Wu, Leyun1,2,3; Zhou, Liping1,2,3; Han, Jiaxin1,2; Ma, Minfei1,2,3; Zhu, Weiliang1,2,3
刊名COMPUTERS IN BIOLOGY AND MEDICINE
出版日期2023-09-01
卷号164页码:8
ISSN号0010-4825
关键词Target prediction Virtual screening Molecular docking Ligand similarity search Deep learning
DOI10.1016/j.compbiomed.2023.107283
通讯作者Zhu, Weiliang(wlzhu@simm.ac.cn) ; Xu, Zhijian(zjxu@simm.ac.cn)
英文摘要Resource- and time-consuming biological experiments are unavoidable in traditional drug discovery, which have directly driven the evolution of various computational algorithms and tools for drug-target interaction (DTI) prediction. For improving the prediction reliability, a comprehensive platform is highly expected as some previously reported webservers are small in scale, single-method, or even out of service. In this study, we integrated the multiple-conformation based docking, 2D/3D ligand similarity search and deep learning approaches to construct a comprehensive webserver, namely D3CARP, for target prediction and virtual screening. Specifically, 9352 conformations with positive control of 1970 targets were used for molecular docking, and approximately 2 million target-ligand pairs were used for 2D/3D ligand similarity search and deep learning. Besides, the positive compounds were added as references, and related diseases of therapeutic targets were annotated for further disease-based DTI study. The accuracies of the molecular docking and deep learning approaches were 0.44 and 0.89, respectively. And the average accuracy of five ligand similarity searches was 0.94. The strengths of D3CARP encompass the support for multiple computational methods, ensemble docking, utilization of positive controls as references, cross-validation of predicted outcomes, diverse disease types, and broad applicability in drug discovery. The D3CARP is freely accessible at https://www.d3pharma.com/D3CARP/index.php.
WOS关键词MOLECULAR DOCKING ; NEURAL-NETWORKS ; WEB SERVER ; DATABASE
资助项目Key project at central government level ; National Key Research and Development Program of China[82,273,851] ; National Natural Science Foundation of China[81,302,699] ; National Natural Science Foundation of China[2,060,302] ; [2022YFA1004304]
WOS研究方向Life Sciences & Biomedicine - Other Topics ; Computer Science ; Engineering ; Mathematical & Computational Biology
语种英语
出版者PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号WOS:001051969000001
源URL[http://119.78.100.183/handle/2S10ELR8/307016]  
专题新药研究国家重点实验室
通讯作者Zhu, Weiliang; Xu, Zhijian
作者单位1.State Key Lab Drug Res, Shanghai 201203, Peoples R China
2.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China
3.Univ Chinese Acad Sci, Sch Pharm, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Shi, Yulong,Zhang, Xinben,Yang, Yanqing,et al. D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening[J]. COMPUTERS IN BIOLOGY AND MEDICINE,2023,164:8.
APA Shi, Yulong.,Zhang, Xinben.,Yang, Yanqing.,Cai, Tingting.,Peng, Cheng.,...&Xu, Zhijian.(2023).D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening.COMPUTERS IN BIOLOGY AND MEDICINE,164,8.
MLA Shi, Yulong,et al."D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening".COMPUTERS IN BIOLOGY AND MEDICINE 164(2023):8.

入库方式： OAI收割

来源：上海药物研究所

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