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Chao Shen
Chao Shen
the First Affiliated Hospital, School of Medicine, Zhejiang University
Verified email at zju.edu.cn
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Year
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models
D Jiang, Z Wu, CY Hsieh, G Chen, B Liao, Z Wang, C Shen, D Cao, J Wu, ...
Journal of cheminformatics 13, 1-23, 2021
4322021
From machine learning to deep learning: Advances in scoring functions for protein–ligand docking
C Shen, J Ding, Z Wang, D Cao, X Ding, T Hou
Wiley Interdisciplinary Reviews: Computational Molecular Science 10 (1), e1429, 2020
2202020
Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein–ligand interaction predictions
D Jiang, CY Hsieh, Z Wu, Y Kang, J Wang, E Wang, B Liao, C Shen, L Xu, ...
Journal of medicinal chemistry 64 (24), 18209-18232, 2021
1332021
PROTAC-DB: an online database of PROTACs
G Weng, C Shen, D Cao, J Gao, X Dong, Q He, B Yang, D Li, J Wu, T Hou
Nucleic acids research 49 (D1), D1381-D1387, 2021
1292021
Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets
Z Wu, M Zhu, Y Kang, ELH Leung, T Lei, C Shen, D Jiang, Z Wang, D Cao, ...
Briefings in bioinformatics 22 (4), bbaa321, 2021
1102021
Combined strategies in structure-based virtual screening
Z Wang, H Sun, C Shen, X Hu, J Gao, D Li, D Cao, T Hou
Physical Chemistry Chemical Physics 22 (6), 3149-3159, 2020
1052020
ADMET evaluation in drug discovery. 19. Reliable prediction of human cytochrome P450 inhibition using artificial intelligence approaches
Z Wu, T Lei, C Shen, Z Wang, D Cao, T Hou
Journal of chemical information and modeling 59 (11), 4587-4601, 2019
1052019
Deep learning approaches for de novo drug design: An overview
M Wang, Z Wang, H Sun, J Wang, C Shen, G Weng, X Chai, H Li, D Cao, ...
Current opinion in structural biology 72, 135-144, 2022
972022
Boosting protein–ligand binding pose prediction and virtual screening based on residue–atom distance likelihood potential and graph transformer
C Shen, X Zhang, Y Deng, J Gao, D Wang, L Xu, P Pan, T Hou, Y Kang
Journal of Medicinal Chemistry 65 (15), 10691-10706, 2022
752022
A magic drug target: Androgen receptor
D Li, W Zhou, J Pang, Q Tang, B Zhong, C Shen, L Xiao, T Hou
Medicinal research reviews 39 (5), 1485-1514, 2019
692019
Can machine learning consistently improve the scoring power of classical scoring functions? Insights into the role of machine learning in scoring functions
C Shen, Y Hu, Z Wang, X Zhang, H Zhong, G Wang, X Yao, L Xu, D Cao, ...
Briefings in Bioinformatics 22 (1), 497-514, 2021
662021
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning
D Jiang, T Lei, Z Wang, C Shen, D Cao, T Hou
Journal of Cheminformatics 12, 1-26, 2020
642020
PROTAC-DB 2.0: an updated database of PROTACs
G Weng, X Cai, D Cao, H Du, C Shen, Y Deng, Q He, B Yang, D Li, T Hou
Nucleic acids research 51 (D1), D1367-D1372, 2023
622023
Relation: A deep generative model for structure-based de novo drug design
M Wang, CY Hsieh, J Wang, D Wang, G Weng, C Shen, X Yao, Z Bing, ...
Journal of Medicinal Chemistry 65 (13), 9478-9492, 2022
532022
Beware of the generic machine learning-based scoring functions in structure-based virtual screening
C Shen, Y Hu, Z Wang, X Zhang, J Pang, G Wang, H Zhong, L Xu, D Cao, ...
Briefings in Bioinformatics 22 (3), bbaa070, 2021
532021
Improving docking-based virtual screening ability by integrating multiple energy auxiliary terms from molecular docking scoring
WL Ye, C Shen, GL Xiong, JJ Ding, AP Lu, TJ Hou, DS Cao
Journal of Chemical Information and Modeling 60 (9), 4216-4230, 2020
442020
Improving structure-based virtual screening performance via learning from scoring function components
GL Xiong, WL Ye, C Shen, AP Lu, TJ Hou, DS Cao
Briefings in bioinformatics 22 (3), bbaa094, 2021
422021
Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power
C Shen, Z Wang, X Yao, Y Li, T Lei, E Wang, L Xu, F Zhu, D Li, T Hou
Briefings in bioinformatics 21 (1), 282-297, 2020
372020
Featurization strategies for protein–ligand interactions and their applications in scoring function development
G Xiong, C Shen, Z Yang, D Jiang, S Liu, A Lu, X Chen, T Hou, D Cao
Wiley Interdisciplinary Reviews: Computational Molecular Science 12 (2), e1567, 2022
352022
Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?
C Shen, G Weng, X Zhang, ELH Leung, X Yao, J Pang, X Chai, D Li, ...
Briefings in Bioinformatics 22 (5), bbaa410, 2021
352021
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