Xujun Zhang
Xujun Zhang
College of Pharmaceutical Science, Zhejiang University
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Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning
J Wang, CY Hsieh, M Wang, X Wang, Z Wu, D Jiang, B Liao, X Zhang, ...
Nature Machine Intelligence 3 (10), 914-922, 2021
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
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
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
Knowledge-based BERT: a method to extract molecular features like computational chemists
Z Wu, D Jiang, J Wang, X Zhang, H Du, L Pan, CY Hsieh, D Cao, T Hou
Briefings in Bioinformatics 23 (3), bbac131, 2022
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
VAD-MM/GBSA: a variable atomic dielectric MM/GBSA model for improved accuracy in protein–ligand binding free energy calculations
E Wang, W Fu, D Jiang, H Sun, J Wang, X Zhang, G Weng, H Liu, P Tao, ...
Journal of Chemical Information and Modeling 61 (6), 2844-2856, 2021
Identification of active molecules against Mycobacterium tuberculosis through machine learning
Q Ye, X Chai, D Jiang, L Yang, C Shen, X Zhang, D Li, D Cao, T Hou
Briefings in Bioinformatics 22 (5), bbab068, 2021
The impact of cross-docked poses on performance of machine learning classifier for protein–ligand binding pose prediction
C Shen, X Hu, J Gao, X Zhang, H Zhong, Z Wang, L Xu, Y Kang, D Cao, ...
Journal of cheminformatics 13, 1-18, 2021
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling
O Zhang, J Zhang, J Jin, X Zhang, RL Hu, C Shen, H Cao, H Du, Y Kang, ...
Nature Machine Intelligence 5 (9), 1020-1030, 2023
Efficient and accurate large library ligand docking with KarmaDock
X Zhang, O Zhang, C Shen, W Qu, S Chen, H Cao, Y Kang, Z Wang, ...
Nature Computational Science 3 (9), 789-804, 2023
A generalized protein–ligand scoring framework with balanced scoring, docking, ranking and screening powers
C Shen, X Zhang, CY Hsieh, Y Deng, D Wang, L Xu, J Wu, D Li, Y Kang, ...
Chemical Science 14 (30), 8129-8146, 2023
TocoDecoy: a new approach to design unbiased datasets for training and benchmarking machine-learning scoring functions
X Zhang, C Shen, B Liao, D Jiang, J Wang, Z Wu, H Du, T Wang, W Huo, ...
Journal of Medicinal Chemistry 65 (11), 7918-7932, 2022
Proteome-wide profiling of the covalent-Druggable cysteines with a structure-based deep graph learning network
H Du, D Jiang, J Gao, X Zhang, L Jiang, Y Zeng, Z Wu, C Shen, L Xu, ...
Research, 2022
Discovery of novel non-steroidal selective glucocorticoid receptor modulators by structure-and IGN-based virtual screening, structural optimization, and biological evaluation
X Hu, J Pang, C Chen, D Jiang, C Shen, X Chai, L Yang, X Zhang, L Xu, ...
European Journal of Medicinal Chemistry 237, 114382, 2022
ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions
X Zhang, C Shen, X Guo, Z Wang, G Weng, Q Ye, G Wang, Q He, B Yang, ...
Journal of Cheminformatics 13, 1-9, 2021
TB-IECS: an accurate machine learning-based scoring function for virtual screening
X Zhang, C Shen, D Jiang, J Zhang, Q Ye, L Xu, T Hou, P Pan, Y Kang
Journal of Cheminformatics 15 (1), 63, 2023
CarsiDock: a deep learning paradigm for accurate protein–ligand docking and screening based on large-scale pre-training
H Cai, C Shen, T Jian, X Zhang, T Chen, X Han, Z Yang, W Dang, ...
Chemical Science 15 (4), 1449-1471, 2024
MetalProGNet: a structure-based deep graph model for metalloprotein–ligand interaction predictions
D Jiang, Z Ye, CY Hsieh, Z Yang, X Zhang, Y Kang, H Du, Z Wu, J Wang, ...
Chemical Science 14 (8), 2054-2069, 2023
Deep geometry handling and fragment-wise molecular 3d graph generation
O Zhang, Y Huang, S Cheng, M Yu, X Zhang, H Lin, Y Zeng, M Wang, ...
arXiv preprint arXiv:2404.00014, 2024
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