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ORCIDZhe Wang 0041
Person information
- affiliation: Zhejiang University, Innovation Institute for Artificial Intelligence in Medicine, College of Pharmaceutical Sciences, Hangzhou, China
Other persons with the same name
- Zhe Wang — disambiguation page
- Zhe Wang 0001
![[0000-0002-1367-7139]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-1367-7139")
— Griffith University, School of Information and Communication Technology, Australia - Zhe Wang 0002 — East China University of Science and Technology, Department of Computer Science and Engineering, Shanghai, China (and 1 more)
- Zhe Wang 0003 — Huawei Technologies Co. Ltd. (and 1 more)
- Zhe Wang 0004 — Columbia University, Department of Electrical Engineering, New York, NY, USA
- Zhe Wang 0005 — Nanjing University of Science and Technology, School of Computer Science and Engineering, China (and 3 more)
- Zhe Wang 0006 — SenseTime Group Limited (and 1 more)
- Zhe Wang 0007 — Jilin University, College of Computer Science and Technology, Changchun, China
- Zhe Wang 0008 — University of Stuttgart, Institute of Parallel and Distributed Systems, Germany
- Zhe Wang 0009 — University of Reading, UK
- Zhe Wang 0010 — Tsinghua University, Graduate School at Shenzhen, China
- Zhe Wang 0011 — University of Chinese Academy of Sciences, Beijing, China
- Zhe Wang 0012 — Zhejiang University, State Key Laboratory of Fluid Power and Mechatronic Systems, Hangzhou, China
- Zhe Wang 0013 — University of California, Irvine, CA, USA (and 2 more)
- Zhe Wang 0014 — Chinese Academy of Sciences, Institute of Automation, Beijing, China
- Zhe Wang 0015 — Shanghai Jiao Tong University, Department of Computer Science and Engineering, China
- Zhe Wang 0016 — Michigan State University, Department of Electrical and Computer Engineering, East Lansing, MI, USA
- Zhe Wang 0017 — University of Chinese Academy of Sciences, Institute of Computing Technology, Huairou, Beijing, China
- Zhe Wang 0018 — China Academy of Information and Communications Technology, Beijing, China (and 1 more)
- Zhe Wang 0019 — Peking University, Beijing, China
- Zhe Wang 0020 — University of Southern Caifornia, Los Angeles, CA, USA
- Zhe Wang 0021 — Ohio State University, Department of Electrical and Computer Engineering, Columbus, OH, USA
- Zhe Wang 0022 — McMaster University, Department of Electrical and Computer Engineering, Hamilton, ON, Canada
- Zhe Wang 0023 — Intel, USA (and 2 more)
- Zhe Wang 0024 — Beihang University, School of Computer Science and Engineering, State Key Laboratory of Software Development Environment, Beijing, China
- Zhe Wang 0025 — University of Virginia, Department of Computer Science, Charlottesville, VA, USA
- Zhe Wang 0026 — Northwestern Polytechnical University, Shaanxi Engineering Laboratory for Transmissions and Controls, Xi'an, China
- Zhe Wang 0027 — Tianjin University of Technology, Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems, China
- Zhe Wang 0028 — Boston University, Bioinformatics Program, MA, USA
- Zhe Wang 0029 — Lincoln University, Christchurch, New Zealand (and 2 more)
- Zhe Wang 0030 — Duke University, Department of Mathematics, Durham, NC, USA
- Zhe Wang 0031 — Beijing University of Posts and Telecommunications, School of Cyberspace Security, China
- Zhe Wang 0032 — University of Toyama, Faculty of Engineering, Japan
- Zhe Wang 0033 — University of Waterloo, School of Computer Science, ON, Canada
- Zhe Wang 0034 — Qufu Normal University, Department of Physical Education, Rizhao, China
- Zhe Wang 0035 — Tsinghua University, Department of Electrical Engineering, State Key Laboratory of Power System, Beijing, China
- Zhe Wang 0036 — Oakland University, Department of Chemistry, Rochester, MI, USA (and 3 more)
- Zhe Wang 0037 — Guangxi University for Nationalities, Institute of Artificial Intelligence, Nanning, China (and 1 more)
- Zhe Wang 0038 — Beijing Jiaotong University, Institute of Information Science, China
- Zhe Wang 0039 — Central China Normal University, School of Public Administration, Wuhan, China
- Zhe Wang 0040 — Chongqing University, School of Big Data and Software Engineering, China
- Zhe Wang 0042 — University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter, UK
- Zhe Wang 0043 — Xijing Hospital, Fourth Military Medical University, Xi'an, China
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Journal Articles
- 2024
[j30]Xing Zhang, Jianbo Tong, Tianhao Wang, Tianyue Wang, Lei Xu, Zhe Wang, Tingjun Hou, Peichen Pan:
Dissecting the role of ALK double mutations in drug resistance to lorlatinib with in-depth theoretical modeling and analysis. Comput. Biol. Medicine 169: 107815 (2024)- [j29]Tianhao Wang, Jianbo Tong, Xing Zhang, Zhe Wang, Lei Xu, Peichen Pan, Tingjun Hou:
Structure-based virtual screening of novel USP5 inhibitors targeting the zinc finger ubiquitin-binding domain. Comput. Biol. Medicine 174: 108397 (2024) - [j28]Xing Zhang, Jianbo Tong, Tianhao Wang, Zhe Wang, Shukai Gu, Lei Xu, Tingjun Hou, Peichen Pan:
In-depth theoretical modeling to explore the mechanism of TPX-0131 overcoming lorlatinib resistance to ALKL1196M/G1202R mutation. Comput. Biol. Medicine 183: 109265 (2024) - [j27]Nanqi Hong, Dejun Jiang, Zhe Wang, Huiyong Sun, Hao Luo, Lingjie Bao, Mingli Song, Yu Kang, Tingjun Hou:
TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides. J. Chem. Inf. Model. 64(13): 5016-5027 (2024) - [j26]Qirui Deng, Zhe Wang, Sutong Xiang, Qinghua Wang, Yifei Liu, Tingjun Hou, Huiyong Sun:
RLpMIEC: High-Affinity Peptide Generation Targeting Major Histocompatibility Complex-I Guided and Interpreted by Interaction Spectrum-Navigated Reinforcement Learning. J. Chem. Inf. Model. 64(16): 6432-6449 (2024) - [j25]Kexin Xu, Zhe Wang, Sutong Xiang, Rongfan Tang, Qirui Deng, Jingxuan Ge, Zhiliang Jiang, Kaimo Yang, Tingjun Hou, Huiyong Sun:
Characterizing the Cooperative Effect of PROTAC Systems with End-Point Binding Free Energy Calculation. J. Chem. Inf. Model. 64(19): 7666-7678 (2024) - 2023
- [j24]Dong Wang, Zhenxing Wu, Chao Shen, Lingjie Bao, Hao Luo, Zhe Wang, Hucheng Yao, De-Xin Kong, Cheng Luo, Tingjun Hou:
Learning with uncertainty to accelerate the discovery of histone lysine-specific demethylase 1A (KDM1A/LSD1) inhibitors. Briefings Bioinform. 24(1) (2023) - [j23]Lingling Wang, Lei Xu, Zhe Wang, Tingjun Hou, Haiping Hao, Huiyong Sun:
Cooperation of structural motifs controls drug selectivity in cyclin-dependent kinases: an advanced theoretical analysis. Briefings Bioinform. 24(1) (2023) - [j22]Shukai Gu, Chao Shen, Jiahui Yu, Hong Zhao, Huanxiang Liu, Liwei Liu, Rong Sheng, Lei Xu, Zhe Wang, Tingjun Hou, Yu Kang:
Can molecular dynamics simulations improve predictions of protein-ligand binding affinity with machine learning? Briefings Bioinform. 24(2) (2023) - [j21]Zhe Wang, Haiyang Zhong, Jintu Zhang, Peichen Pan, Dong Wang, Huanxiang Liu, Xiaojun Yao, Tingjun Hou, Yu Kang:
Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets. J. Chem. Inf. Model. 63(21): 6525-6536 (2023) - [j20]Sutong Xiang, Zhe Wang, Rongfan Tang, Lingling Wang, Qinghua Wang, Yang Yu, Qirui Deng, Tingjun Hou, Haiping Hao, Huiyong Sun:
Exhaustively Exploring the Prevalent Interaction Pathways of Ligands Targeting the Ligand-Binding Pocket of Farnesoid X Receptor via Combined Enhanced Sampling. J. Chem. Inf. Model. 63(23): 7529-7544 (2023) - [j19]Xujun Zhang, Odin Zhang, Chao Shen, Wanglin Qu, Shicheng Chen, Hanqun Cao, Yu Kang, Zhe Wang, Ercheng Wang, Jintu Zhang, Yafeng Deng, Furui Liu, Tianyue Wang, Hongyan Du, Langcheng Wang, Peichen Pan, Guangyong Chen, Chang-Yu Hsieh, Tingjun Hou:
Efficient and accurate large library ligand docking with KarmaDock. Nat. Comput. Sci. 3(9): 789-804 (2023) - 2022
- [j18]Rongfan Tang, Pengcheng Chen, Zhe Wang, Lingling Wang, Haiping Hao, Tingjun Hou, Huiyong Sun:
Characterizing the stabilization effects of stabilizers in protein-protein systems with end-point binding free energy calculations. Briefings Bioinform. 23(3) (2022) - [j17]Zhe Wang, Hong Pan, Huiyong Sun, Yu Kang, Huanxiang Liu, Dongsheng Cao, Tingjun Hou:
fastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation. Briefings Bioinform. 23(5) (2022) - [j16]Yang Yu, Zhe Wang, Lingling Wang, Sheng Tian, Tingjun Hou, Huiyong Sun:
Predicting the mutation effects of protein-ligand interactions via end-point binding free energy calculations: strategies and analyses. J. Cheminformatics 14(1): 56 (2022) - [j15]Jiahui Yu, Jike Wang, Hong Zhao, Junbo Gao, Yu Kang, Dong-Sheng Cao, Zhe Wang, Tingjun Hou:
Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism. J. Chem. Inf. Model. 62(12): 2973-2986 (2022) - [j14]Qinghua Wang, Zhe Wang, Sheng Tian, Lingling Wang, Rongfan Tang, Yang Yu, Jingxuan Ge, Tingjun Hou, Haiping Hao, Huiyong Sun:
Determination of Molecule Category of Ligands Targeting the Ligand-Binding Pocket of Nuclear Receptors with Structural Elucidation and Machine Learning. J. Chem. Inf. Model. 62(17): 3993-4007 (2022) - 2021
- [j13]Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Haiyang Zhong, Gaoang Wang, Xiaojun Yao, Lei Xu, Dong-Sheng Cao, Tingjun Hou:
Can machine learning consistently improve the scoring power of classical scoring functions? Insights into the role of machine learning in scoring functions. Briefings Bioinform. 22(1): 497-514 (2021) - [j12]Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Jinping Pang, Gaoang Wang, Haiyang Zhong, Lei Xu, Dong-Sheng Cao, Tingjun Hou:
Beware of the generic machine learning-based scoring functions in structure-based virtual screening. Briefings Bioinform. 22(3) (2021) - [j11]Zhenxing Wu, Minfeng Zhu, Yu Kang, Elaine Lai-Han Leung, Tailong Lei, Chao Shen, Dejun Jiang, Zhe Wang, Dong-Sheng Cao, Tingjun Hou:
Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets. Briefings Bioinform. 22(4) (2021) - [j10]Jike Wang, Huiyong Sun, Jiawen Chen, Dejun Jiang, Zhe Wang, Zhenxing Wu, Xi Chen, Dong-Sheng Cao, Tingjun Hou:
DeepChargePredictor: a web server for predicting QM-based atomic charges via state-of-the-art machine-learning algorithms. Bioinform. 37(22): 4255-4257 (2021) - [j9]Xujun Zhang, Chao Shen, Xueying Guo, Zhe Wang, Gaoqi Weng, Qing Ye, Gaoang Wang, Qiaojun He, Bo Yang, Dong-Sheng Cao, Tingjun Hou:
ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions. J. Cheminformatics 13(1): 6 (2021) - [j8]Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dong-Sheng Cao, Jian Wu, Tingjun Hou:
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models. J. Cheminformatics 13(1): 12 (2021) - [j7]Chao Shen, Xueping Hu, Junbo Gao, Xujun Zhang, Haiyang Zhong, Zhe Wang, Lei Xu, Yu Kang, Dong-Sheng Cao, Tingjun Hou:
The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction. J. Cheminformatics 13(1): 81 (2021) - 2020
- [j6]Chao Shen, Zhe Wang, Xiaojun Yao, Youyong Li, Tailong Lei, Ercheng Wang, Lei Xu, Feng Zhu, Dan Li, Tingjun Hou:
Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power. Briefings Bioinform. 21(1): 282-297 (2020) - [j5]Dejun Jiang, Tailong Lei, Zhe Wang, Chao Shen, Dong-Sheng Cao, Tingjun Hou:
ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning. J. Cheminformatics 12(1): 16 (2020) - [j4]Ercheng Wang, Hui Liu, Junmei Wang, Gaoqi Weng, Huiyong Sun, Zhe Wang, Yu Kang, Tingjun Hou:
Development and Evaluation of MM/GBSA Based on a Variable Dielectric GB Model for Predicting Protein-Ligand Binding Affinities. J. Chem. Inf. Model. 60(11): 5353-5365 (2020) - 2019
- [j3]Zhe Wang, Xuwen Wang, Youyong Li, Tailong Lei, Ercheng Wang, Dan Li, Yu Kang, Feng Zhu, Tingjun Hou:
farPPI: a webserver for accurate prediction of protein-ligand binding structures for small-molecule PPI inhibitors by MM/PB(GB)SA methods. Bioinform. 35(10): 1777-1779 (2019) - [j2]Zhenxing Wu, Tailong Lei, Chao Shen, Zhe Wang, Dong-Sheng Cao, Tingjun Hou:
ADMET Evaluation in Drug Discovery. 19. Reliable Prediction of Human Cytochrome P450 Inhibition Using Artificial Intelligence Approaches. J. Chem. Inf. Model. 59(11): 4587-4601 (2019) - [j1]Gaoqi Weng, Ercheng Wang, Zhe Wang, Hui Liu, Feng Zhu, Dan Li, Tingjun Hou:
HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA. Nucleic Acids Res. 47(Webserver-Issue): W322-W330 (2019)
Coauthor Index
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