Education and Professional Experiences

• 2013-now Professor, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
• 2009-2013 Professor, Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University, Suzhou, China.
• 2004-2009 Postdoctor and research scientist, College of Chemistry and Biochemistry, UCSD, USA.
• 2002-2004 Postdoctor, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
• 1997-2002 Ph.D. in Computational Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing, China. (Supervisor: Professor Xiaojie Xu)
• 1992-1997 B.Sc, College of Chemistry and Molecular Engineering, Peking University, Beijing, China. (Supervisor: Professor Xiaojie Xu)

Professional Services

• Editors and advisory editors for the following journals: Journal of Cheminformatics, Journal of Chemical Information and Modeling, International Journal of Molecular Sciences (Molecular Informatics Section), Frontiers in Pharmacology (associate editor of Experimental Pharmacology and Drug Discovery Section), Current Pharmaceutical Design, Chemical Biology & Drug Design, Mini-Reviews in Medicinal Chemistry, Theoretical Biology & Medical Modelling, Current Computer-aided Drug Design, Medicinal Chemistry, Computational and Mathematical Methods in Medicine, Genomics, Proteomics & Bioinformatics (2015~2017), Journal of Pharmaceutics, Journal of Molecular Graphics & Modeling, Heliyon.
• Guest editors for the following journals: Advanced Drug Delivery Reviews, Current Drug Targets, Evidence-Based Complementary and Alternative Medicine, Combinatorial Chemistry & High Throughput Screening.

Selected Publications

• Zhenxing Wu, Odin Zhang, Xiaorui Wang, Li Fu, Huifeng Zhao, Jike Wang, Hongyan Du, Dejun Jiang, Yafeng Deng, Dongsheng Cao*, Chang-Yu Hsieh*, Tingjun Hou*, Leveraging Language Model for Advanced Multi-Property Molecular Optimization via Prompt Engineering, Nature Machine Intelligence, 2024, accepted.
• Mingyang Wang, Shuai Li, Jike Wang, Odin Zhang, Hongyan Du, Dejun Jiang, Zhenxing Wu, Yafeng Deng, Yu Kang, Peichen Pan, Dan Li, Xiaorui Wang, Tingjun Hou*, Chang-Yu Hsieh*, ClickGen: Directed Exploration of Synthesizable Chemical Space Leading to the Rapid Synthesis of Novel and Active Lead Compounds via Modular Reactions and Reinforcement Learning, Nature Communications, 2024, accepted.
• Xiaorui Wang, Xiaodan Yin, Dejun Jiang, Huifeng Zhao, Zhenxing Wu, Odin Zhang, Jike Wang, Yuquan Li, Yafeng Deng, Huanxiang Liu, Pei Luo, Yuqiang Han, Tingjun Hou*, Xiaojun Yao*, Chang-Yu Hsieh*, Multi-Modal Deep Learning Enables Ultrafast and Accurate Annotation of Enzymatic Active Sites, Nature Communications, 2024, 15, 7348.
• Yuqiang Han, Xiaoyang Xu, Chang-Yu Hsieh, Keyan Ding, Hongxia Xu, Renjun Xu, Tingjun Hou*, Qiang Zhang*, Huajun Chen*, Retrosynthesis prediction with an iterative string editing model, Nature Communications, 2024, 15, 6404.
• Xiaohong Zhu, Mengqi Luo, Ke An, Danfeng Shi, Tingjun Hou*, Arieh Warshel*, Chen Bai*, Exploring the activation mechanism of metabotropic glutamate receptor 2, Proceedings of the National Academy of Sciences, 2024, 121, e2401079121.
• Xujun Zhang, Chao Shen, Haotian Zhang, Yu Kang, Chang-Yu Hsieh*, Tingjun Hou*, Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening, Accounts of Chemical Research, 2024, 57, 1500-1509.
• Jiacai Yi, Shaohua Shi, Li Fu, Ziyi Yang, Peifei Nie, Aiping Lu, Chengkun Wu, Yafeng Deng, Changyu Hsieh, Xiangxiang Zeng, Tingjun Hou*, Dongsheng Cao*, OptADMET: an open substructure modification guiding workspace for multiple ADMET property optimization, Nature Protocols, 2024, 19, 1105-1121.
• Odin Zhang, Tianyue Wang, Gaoqi Weng, Dejun Jiang, Ning Wang, Xiaorui Wang, Huifeng Zhao, Jialu Wu, Ercheng Wang, Guangyong Chen, Yafeng Deng, Peichen Pan, Yu Kang*, Chang-Yu Hsieh*, Tingjun Hou*, Learning on topological surface and geometric structure for 3D molecular generation, Nature Computational Science, 2023, 3, 849-859.
• 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, Nature Computational Science, 2023, 3, 789-804.
• Odin Zhang, Jintu Zhang, Jieyu Jin, Xujun Zhang, RenLing Hu, Chao Shen, Hanqun Cao, Hongyan Du, Yu Kang, Yafeng Deng, Furui Liu*, Guangyong Chen*, Chang-Yu Hsieh*, Tingjun Hou*, ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling, Nature Machine Intelligence, 2023, 5, 1020-1030.
• Zhenxing Wu, Jike Wang, Hongyan Du, Dejun Jiang, Yu Kang, Dan Li, Peichen Pan, Yafeng Deng, Dongsheng Cao, Chang-Yu Hsieh*, Tingjun Hou*, Substructure Mask Explanation (SME): an intuitive graph neural network explanation approach for mining structure-activity information from molecular property prediction models, Nature Communications, 2023, 14, 2585.
• Weitao Fu, Hao Yang, Chenxian Hu, Jianing Liao, Zhou Gong, Minkui Zhang, Shuai Yang, Shangxiang Ye, Yixuan Lei, Rong Sheng, Zhiguo Zhang, Xiaojun Yao, Chun Tang*, Dan Li*, Tingjun Hou*, Small-Molecule Inhibition of Androgen Receptor Dimerization as a Strategy against Prostate Cancer, ACS Central Science, 2023, 9, 675-684.
• Rui Shi, Peichen Pan, Rui Lv, Chongqing Ma, Enhui Wu, Ruochen Guo, Zhihao Zhao, Hexing Song, Joe Zhou, Yang Liu, Guoqiang Xu, Tingjun Hou*, Zhenhui Kang*, Jian Liu*, High-throughput glycolytic inhibitor discovery targeting glioblastoma by graphite dots-assisted LDI mass spectrometry, Science Advances, 2022, 8, eabl4923.
• Xin Chai, Huiyong Sun, Wenfang Zhou, Changwei Chen, Luhu Shan, Yuhui Yang, Junzhao He, Jinping Pang, Liu Yang, Xinyue Wang, Sunliang Cui, Yaqin Fu, Xiaohong Xu, Lei Xu, Xiaojun Yao, Dan Li*, Tingjun Hou*, Discovery of N-(4-(Benzyloxy)-phenyl)-sulfonamide Derivatives as Novel antagonists of the human androgen receptor targeting the activation function 2, Journal of Medicinal Chemistry, 2022, 65, 2507-2521.
• Xueping Hu, Jinping Pang, Jintu Zhang, Chao Shen, Xin Chai, Ercheng Wang, Haiyi Chen, Xuwen Wang, Mojie Duan, Weitao Fu, Lei Xu, Yu Kang, Dan Li*, Hongguang Xia*, Tingjun Hou*, Discovery of novel GR ligands towards druggable GR antagonist conformations identified by MD Simulations and Markov state model analysis, Advanced Science, 2022, 9, 2102435.
• Dejun Jiang, Chang-Yu Hsieh, Zhenxing Wu, Yu Kang, Jike Wang, Ercheng Wang, Ben Liao, Chao Shen, Lei Xu, Jian Wu*, Dongsheng Cao*, Tingjun Hou*, InteractionGraphNet: a novel and efficient deep graph representation learning framework for accurate protein-ligand interaction predictions, Journal of Medicinal Chemistry, 2021, 64, 18209-18232.
• Weitao Fu, Minkui Zhang, Jianing Liao, Qing Tang, Yixuan Lei, Zhou Gong, Luhu Shan, Mojie Duan, Xin Chai, Jinping Pang, Chun Tang, Xuwen Wang, Xiaohong Xu, Dan Li*, Rong Sheng*, Tingjun Hou*, Discovery of a novel androgen receptor antagonist manifesting evidence to disrupt the dimerization of the ligand-binding domain via attenuating the hydrogen-bonding network, Journal of Medicinal Chemistry, 2021, 64, 17221-17238.
• Qing Ye, Chang-Yu Hsieh, Ziyi Yang, Yu Kang, Jiming Chen, Dongsheng Cao*, Shibo He*, Tingjun Hou*, A unified drug-target interaction prediction framework based on knowledge graph and recommendation system, Nature Communications, 2021, 12, 6775.
• Gaoqi Weng, Dan Li, Yu Kang*, Tingjun Hou*, Integrative modeling of PROTAC-mediated ternary complexes, Journal of Medicinal Chemistry, 2021, 64, 16271-16281.
• Jike Wang, Chang-Yu Hsieh, Mingyang Wang, Xiaorui Wang, Zhenxing Wu, Dejun Jiang, Benben Liao, Xujun Zhang, Bo Yang, Qiaojun He, Dongsheng Cao*, Xi Chen*, Tingjun Hou*, Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning, Nature Machine Intelligence, 2021, 3, 914-922.
• Haiyi Chen, Yu Kang, Mojie Duan*, Tingjun Hou*, Regulation mechanism for the binding between the SARS-CoV-2 spike protein and host angiotensin-converting enzyme II, Journal of Physical Chemistry Letters, 2021, 12, 6252-6261.
• Weitao Fu, Ercheng Wang, Di Ke, Hao Yang, Lingfeng Chen, Jingjing Shao, Xueping Hu, Lei Xu, Na Liu*, Tingjun Hou*, Discovery of a novel Fusarium Graminearum Mitogen-activated Protein Kinase (FgGpmk1) inhibitor for the treatment of fusarium head blight,Journal of Medicinal Chemistry, 2021, 64, 13841-13852.
• Yongchang Xu, Haiyi Chen, Huimin Zhang, Saif Ullah, Tingjun Hou*, Youjun Feng*, The MCR-3 inside linker appears as a facilitator of colistin resistance, Cell Reports, 2021, 35, 109135.
• Guoli Xiong, Zhenxing Wu, Jiacai Yi, Li Fu, Zhijiang Yang, Changyu Hsieh, Mingzhu Yin, Xiangxiang Zeng, Chengkun Wu, Aiping Lu, Xiang Chen, Tingjun Hou*, Dongsheng Cao*, ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties, Nucleic Acids Research, 2021, 49(W1), W5-W14.
• Zhenxing Wu, Dejun Jiang, Jike Wang, Chang-Yu Hsieh*, Dongsheng Cao*, Tingjun Hou*, Mining toxicity information from large amounts of toxicity data, Journal of Medicinal Chemistry, 2021, 64, 6924-6936.
• Gaoqi Weng, Chao Shen, Dongsheng Cao, Junbo Gao, Xiaowu Dong, Qiaojun He, Bo Yang, Dan Li*, Jian Wu*, Tingjun Hou*, PROTAC-DB: an online database of PROTACs, Nucleic Acids Research, 2021, 49(D1), D1381-D1387.
• Hongyan Du, Junbo Gao, Gaoqi Weng, Junjie Ding, Xin Chai, Jinping Pang, Yu Kang, Dan Li, Dongsheng Cao*, Tingjun Hou*, CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors, Nucleic Acids Research, 2021, 49(D1), D1122-D1129.
• Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dongsheng Cao*, Tingjun Hou*, Hyperbolic Relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method, Briefings in Bioinformatics, 2021, 22, bbab112.
• Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng 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, Journal of Cheminformatics, 2021, 13, 12.
• Jie Dong, Minfeng Zhu, Yonghuan Yun, Aiping Lu, Tingjun Hou*, Dongsheng Cao*, BioMedR: An R/CRAN Package for Integrated Data Analysis Pipeline in Biomedical Study, Briefings in Bioinformatics, 2021, 22, 474-484.
• Gaoqi Weng, Junbo Gao, Zhe Wang, Ercheng Wang, Xueping Hu, Xiaojun Yao, Dongsheng Cao*, Tingjun Hou*, Comprehensive evaluation of fourteen docking programs on protein-peptide complexes, Journal of Chemical Theory and Computation, 2020, 16, 3959-3969.
• Ziyi Yang, Junhong He, Aiping Lu, Tingjun Hou*, Dongsheng Cao*, The Application of Negative Design to Design More Desirable Virtual Screening Library, Journal of Medicinal Chemistry, 2020, 63, 4411-4429.
• Chao Shen, Junjie Ding, Zhe Wang, Dongsheng Cao, Xiaoqin Ding, Tingjun Hou*, From machine learning to deep learning: advances in scoring functions for computational docking,WIRES Computational Molecular Science, 2020, 10, e1429.
• Ercheng Wang, Huiyong Sun, Junmei Wang, Zhe Wang, Hui Liu, John Zenghui Zhang*, Tingjun Hou*, End-Point binding free energy calculation with MM/PBSA and MM/GBSA: strategies and applications in drug design, Chemical Reviews, 2019, 119, 9478-9508.
• 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 Research, 2019, 47, W322-W330.
• 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, Bioinformatics, 2019, 35, 1777-1779.
• Peichen Pan, Huidong Yu, Qinglan Liu, Xiaotian Kong, Hu Chen, Jiean Chen, Qi Liu, Dan Li, Yu Kang, Huiyong Sun, Wenfang Zhou, Sheng Tian, Sunliang Cui, Feng Zhu, Youyong Li, Yong Huang*, Tingjun Hou*, Combating drug-resistant mutants of ALK with potent and selective Type-I1/2 inhibitors by stabilizing unique DFG-shifted loop conformation, ACS Central Science, 2017, 3, 1208-1220.
• Tailong Lei, Huiyong Sun, Yu Kang, Feng Zhu. Hui Liu, Wenfang Zhou, Zhe Wang, Dan Li, Youyong Li, Tingjun Hou*, ADMET evaluation in drug discovery. 18. Reliable prediction of chemical-induced urinary tract toxicity by boosting machine learning approaches, Molecular Pharmaceutics, 2017, 14, 3935-3953.
• Huiyong Sun, Pengcheng Chen, Dan Li, Youyong Li, Tingjun Hou*, Directly-binding rather than induced-fit dominated binding affinity difference in (S) and (R)-crizotinib bound MTH1, Journal of Chemical Theory and Computation, 2016, 12, 851-860.
• Hui Liu, Tingjun Hou*, CaFE: a tool for binding affinity prediction using end-point free energy methods,Bioinformatics, 2016, 32, 2216-2218.
• Sheng Tian, Junmei Wang, Youyong Li, Tingjun Hou*, The application of in silico drug-likeness predictions in pharmaceutical research, Advanced Drug Delivery Reviews, 2015, 86, 2-10.
• Huiyong Sun, Youyong Li, Sheng Tian, Junmei Wang, Tingjun Hou*, P-loop conformation governed Crizotinib resistance in G2032R-mutated ROS1 tyrosine kinase: clues from free energy landscape, PLoS Computational Biologys, 2014, 10, e1003729.
• Huiyong Sun, Youyong Li, Sheng Tian, Lei Xu, Tingjun Hou*, Assessing the performance of MM/PBSA and MM/GBSA methods. 4. accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set, Physical Chemistry Chemical Physics, 2014, 16, 16719-16729.
• Qian Zhang, Wei Zhang, Youyong Li, Junmei Wang, Jian Zhang, Tingjun Hou*, MORT: a powerful foundational library for computational biology and CADD, Journal of Cheminformatics, 2014, 6, 36.
• Lei Xu, Yu Zhang, Longtai Zheng, Chunhua Qiao, Youyong Li, Dan Li, Xuechu Zhen*, Tingjun Hou*, Discovery of novel inhibitors targeting macrophage migration inhibitory factor via structure-based virtual screening and bioassays, Journal of Medicinal Chemistry, 2014, 57, 3737-3745.
• Lei Xu, Huiyong Sun, Youyong Li, Junmei Wang, Tingjun Hou*, Assessing the performance of MM/PBSA and MM/GBSA methods. 3. the impact of force fields and ligand charge models, Journal of Physical Chemistry B, 2013, 117, 8408-8421.
• Tingjun Hou*, Nan Li, Youyong Li, Wei Wang, Characterization of domain-peptide interaction interface: prediction of SH3 domain-mediated protein-protein interaction network in yeast by generic structure-based models,Journal of Proteome Research, 2012, 11, 2982-2995.
• Sheng Tian, Junmei Wang, Youyong Li, Xiaojie Xu, Tingjun Hou*, Drug-likeness analysis of Traditional Chinese Medicines: prediction of drug-likeness using machine learning approaches, Molecular Pharmaceutics, 2012, 9, 2875-2886.
• Tingjun Hou*, Junmei Wang, Youyong Li, Wei Wang*, Assessing the performance of the MM/PBSA and MM/GBSA methods: II. the accuracy of ranking poses generated by molecular docking calculations, Journal of Computational Chemistry, 2011, 32, 866-877.
• Tingjun Hou*, Junmei Wang, Youyong Li, Wei Wang*, Assessing the performance of the MM/PBSA and MM/GBSA methods: I. The accuracy of binding free energy calculations based on molecular dynamics simulations, Journal of Chemical Information and Modeling, 2011, 51, 69-82.
• Jing Zhang#, Tingjun Hou# (Co-first authors), Wei Wang, Jun S. Liu, A Bayesian method for detecting combinatorial mutation patterns responsible for HIV drug resistance, Proceedings of the National Academy of Sciences, 2010, 107, 1321-1326.
• Tingjun Hou*, Yon Yu, Molecular dynamics and free energy studies on the wild-type and double mutant HIV-1 protease complexed with amprenavir and two amprenavir-related inhibitors: mechanism for binding and drug resistance, Journal of Medicinal Chemistry, 2007, 50, 1177-1188.

Education and Professional Experiences

• 2022-now Professor, College of Pharmaceutical Sciences, Zhejiang University.
• 2013-2022 Associate Professor, College of Pharmaceutical Sciences, Zhejiang University.
• 2013 Lecturer, College of Pharmaceutical Sciences, Zhejiang University.
• 2010-2013 Alexander von Humboldt fellowship in the research group of Prof. Dr. Albrecht Bindereif, Institute of Biochemistry, Justus-Liebig-University Giessen, Germany.
• 2009-2010 Postdoc in the research group of Prof. Dr. Roland K. Hartmann, Institute of Pharmaceutical Chemistry, Philipps-University Marburg, Germany.
• 2005-2009 Ph. D. Institute of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. (Supervisor: Prof. Dr. Roland K. Hartmann)
• 2001-2004 M. Sc. Department of Medicinal Chemistry, China Pharmaceutical University, Nanjing, China. (Supervisor: Prof. Dr. Xiaoming Wu)
• 1996-2000 B. Sc. Institute of Pharmacy, China Pharmaceutical University, Nanjing, China

Research Interests

• Design and discovery of novel drugs: based on specific targets, computer aided drug design (CADD) methods such as molecular docking, dynamic simulation, and free energy computation etc. are utilized to design drug candidates. The biological activities of the candidates are assessed with relevant enzyme, cell and bacteria, and are further verified and explored at molecular level by biochemical and molecular biological means. At present, we principally focus on the design and discovery of the drugs against mycobacterium tuberculosis using BCG as model, and against prostate cancer aiming at androgen receptor.

Selected Publications

• Wang XY, Chai X, Shan LH, Xu XH, Xu L, Hou TJ, Sun HY*, Li D*, A Potent New-scaffold Androgen Receptor Antagonist Discovered on the Basis of a MIEC-SVM Model, Acta Pharmacol Sin, 2024, 45, 1978-1991.
• Sun Y, Wang HT, Li YR, Li ZX, Mao ZH, Zhang MY, Shao YX, Ye JQ, Li D*, Shan LH*, The Design, Synthesis and Bioactivity Evaluation of Novel Androgen Receptor Degraders Based on Hydrophobic Tagging, Bioorg Chem, 2024, 146, 107309.
• Chen HY, Zhou YX, Wang XY, Chai X, Wang Z, Wang EC, Xu L, Hou TJ*, Li D*, Duan MJ*, Discovery of Novel Anti-Resistance AR Antagonists Guided by Funnel Metadynamics Simulation, Adv Sci, 2024, 11, 2309261.
• Yang L, Hu XP, Lu Y, Xu RL, Xu YP, Ma WL, Alam MS, Zhang TY, Chai X, Lei YX, Ye Q, Dong XW, Kang Y, Che JX*, Hou TJ*, Li D*, Discovery of N-(1-(6-oxo-1,6-dihydropyrimidine)-pyrazole) Acetamide Derivatives as Novel Noncovalent DprE1 Inhibitors against Mycobacterium tuberculosis, J Med Chem, 2024, 67, 1914-1931.
• Zhong HY, Wang XY, Chen SC, Wang Z, Wang HT, Xu L, Hou TJ, Yao XJ*, Li D*, Pan PC*, Discovery of Novel Inhibitors of BRD4 for Treating Prostate Cancer: A Comprehensive Case Study for Considering Water Networks in Virtual Screening and Drug Design, J Med Chem, 2024, 67, 138−151.
• Fu W, Yang H, Hu CX, Liao JN, Gong Z, Zhang MK, Yang S, Ye SX, Lei YX, Sheng R, Zhang ZG, Yao XJ, Tang C*, Li D*, Hou TJ*, Small-Molecule Inhibition of Androgen Receptor Dimerization as a Strategy against Prostate Cancer, ACS Cent Sci, 2023, 9, 675-684.
• Li D, Bao XD, Pang JP, Hu XP, Wang LL, Wang JJ, Yang ZX, Xu L, Wang SY, Weng QJ*, Cui SL*, Hou TJ*, Discovery and Optimization of N-acyl-6-sulfonamide-tetrahydroquinoline Derivatives as Novel Non-steroidal Selective Glucocorticoid Receptor Modulators, J Med Chem, 2022, 65, 15710–15724.
• Weng GQ, Cai XY, Cao DS, Du HY, Shen C, Deng YF, He QJ, Yang B, Li D*, Hou TJ*, PROTAC-DB 2.0: an updated database of PROTACs, Nucleic Acids Res, 2023, 51(D1), D1367-D1372.
• Chen CW, Chai X, Hu XP, Lou SY, Li D*, Hou TJ*, Cui SL*, Discovery of 2-(1-(3-Chloro-4-cyanophenyl)-1H-pyrazol-3-yl)acetamides as Potent, Selective, and Orally Available Antagonists Targeting the Androgen Receptor, J Med Chem, 2022, 65, 13074-13093.
• Hu XP, Pang JP, Chen CW, Jiang DJ, Shen C, Chai X, Yang L, Zhang XJ, Xu L, Cui SL, Hou TJ, Li D*, Discovery of novel non-steroidal selective glucocorticoid receptor modulators by structure-and IGN-based virtual screening, structural optimization, and biological evaluation, Eur J Med Chem, 2022, 237, 114382.
• Pang JP, Hu XP, Wan YX, Liao JN, Chai X, Wang XW, Shen C, Wang JJ, Zhang LL, Wang ZY, Zhu F, Weng QJ, Xu L, Hou TJ, Li D*, Discovery of a novel nonsteroidal selective glucocorticoid receptor modulator by virtual screening and bioassays, Acta Pharmacol Sin, 2022, 43, 2429-2438.
• Chai X, Sun HY, Zhou WF, Chn CW, Shan LH, Yang YH, He JZ, Pang JP, Yang L, Wang XY, Cui SL, Fu YQ, Xu XH, Xu L, Yao XJ, Li D*, Hou TJ*, Discovery of N-(4-(Benzyloxy)-phenyl)-sulfonamide Derivatives as novel antagonists of the human androgen receptor targeting the activation function 2, J Med Chem, 2022, 65, 2507-2521.
• Hu XP, Yang L, Chai X, Lei YX, Shah Alam M, Liu L, Shen C, Jiang DJ, Wang Z, Liu ZY, Xu L, Wan KL, Zhang TY, Yin YL, Cao DS*, Li D*, Hou TJ*, Discovery of novel DprE1 inhibitors via computational bioactivity fingerprints and structure-based virtual screening, Acta Pharmacol Sin, 2022, 43, 1605-1615.
• Hu XP, Pang JP, Zhang JT, Shen C, Chai X, Wang EC, Chen HY, Wang XW, Duan MJ, Fu WT, Xu L, Kang Y, Li D*, Xia HG*, Hou TJ*, Discovery of novel GR ligands towards druggable GR antagonist conformations identified by MD Simulations and Markov state model analysis, Adv Sci, 2022, 9, 2102435.
• Fu WT, Zhang MK, Liao JN, Tang Q, Lei YX, Gong Z, Shan LH, Duan MJ, Chai X, Pang JP, Tang C, Wang XW, Xu XH, Li D*, Sheng R*, Hou TJ*, Discovery of a novel androgen receptor antagonist manifesting evidence to disrupt the dimerization of the ligand-binding domain via attenuating the hydrogen-bonding network, J Med Chem, 2021, 64, 17221-17238.
• Ye Q, Chai X, Jiang DJ, Yang L, Shen C, Zhang XJ, Li D*, Cao DS*, Hou T*. Identification of Active Molecules against Mycobacterium Tuberculosis through Machine Learning, Brief Bioinform, 2021, doi: 10.1093/bib/bbab068.
• Pang JP, Shen C, Zhou WF, Wang YX, Shan LH, Chai X, Shao Y, Hu XP, Zhu F, Zhu DY, Xiao L, Xu L, Xu XH, Li D*, Hou T*. Discovery of Novel Antagonists Targeting the DNA Binding Domain of Androgen Receptor by Integrated Docking-Based Virtual Screening and Bioassays, Acta Pharmacol Sin, 2021, Mar 25. doi: 10.1038/s41401-021-00632-5.
• Weng G, Shen C, Cao D, Gao J, Dong X, He Q, Yang B, Li D*, Wu J,* Hou T*. PROTAC-DB: an Online Database of PROTACs, Nucleic Acids Res, 2021, 49 (D1), D1381-D1387.
• Tang Q, Fu WT, Zhang MK, Wang EC, Shan LH, Chai X, Pang JP, Wang XW, Xu XH, Xu L, Li D*, Sheng R*, Hou TJ*, Novel Androgen Receptor Antagonist Identified by Structure-based Virtual Screening, Structural Optimization, and Biological Evaluation, Eur J Med Chem, 2020, 192: 112156.
• Hu X, Chai X, Wang X, Duan M, Pang J, Fu W, Li D*, Hou T*. Advances in the Computational Development of Androgen Receptor Antagonists, Drug Discov Today, 2020, 25: 1453-61.
• Shen C, Liu H, Wang XW, Lei TL, Wang EC, Xu L, Yu HD, Li D*, Yao XJ*, Importance of Incorporating Protein Flexibility in Molecule Modeling: A Theoretical Study on Type I1/2 NIK Inhibitors, Front Pharmacol, 2019, 10: 345.
• Li D, Zhou WF, Pang JP, Tang Q, Zhong BL, Shen C, Xiao L, Hou TJ*, A Magic Drug Target: Androgen Receptor, Med Res Rev, 2019, 39, 1485-1514.
• Zhou WF, Duan MJ, Fu WT, Pang JP, Tang Q, Sun HY, Xu L, Chang S, Li D*, Hou, TJ*, Discovery of Novel Androgen Receptor Ligands by Structure-based Virtual Screening and Bioassays, Genomics Proteomics Bioinformatics, 2018, 16, 416-27.
• Tang XY, Wang Z, Lei TL, Zhou WF, Chang S, Li D*, Importance of Protein Flexibility on Molecular Recognition: Modeling Binding Mechanisms of Aminopyrazine Inhibitors to Nek2, Phys Chem Chem Phys, 2018, 20,5591-5605.
• Chen F, Sun HY, Liu H, Li D*, Li YY, Hou TJ*, Prediction of Luciferase Inhibitors by the High-performance MIEC-GBDT Approach Based on Interaction Energetic Patterns, Phys Chem Chem Phys, 2017, 19, 10163-76.
• Zhang Q, Feng T, Xu L, Sun HY, Pan PC, Li YY, Li D*, Hou TJ*, Recent advances on protein-protein docking, Current Drug Targets, 2016, 17, 1586-1594.
• Liu H, Li D, Li YY, Hou TJ*, Atomistic molecular dynamics simulations of ATP-binding cassette transporters, WIREs Computational Molecular Science, 2016, 6, 255-265.
• Guan Y, Sun HY, Pan PC, Li YY, Li D*, Hou TJ*, Exploring resistance mechanisms of HCV NS3/4A protease mutations to MK5172: insight from molecular dynamics simulations and free energy calculations, Molecular Biosystems, 2015, 11, 2568-78.
• Li D, Chen L, Li YY, Tian S, Sun HY, Hou TJ*, ADMET evaluation in drug discovery. 13. development of in silico prediction models for P-Glycoprotein substrates. Molecular Pharmaceutics, 2014, 11, 716-26.
• Pan PC, Li L, Li YY, Li D*, Hou TJ*, Insights into susceptibility of antiviral drugs against the E119G mutant of 2009 influenza A (H1N1) neuraminidase by molecular dynamics simulations and free energy calculations, Antiviral Research, 2013, 100, 356-64.
• Preußer C, Rossbach O, Hung LH, Li D, Bindereif A*, Genome-wide RNA-binding analysis of the trypanosome U1 snRNP proteins U1C and U1-70K reveals cis/trans-spliceosomal network, Nucleic Acids Research, 2014, 42, 6603-15.
• Li D, Gössringer M, Hartmann RK*,Archaeal-bacterial chimeric RNase P RNAs: towards understanding RNA's architecture, function and evolution, Chembiochem, 2011, 12, 1536-43.
• Li D, Meyer MH, Willkomm DK, Keusgen M, Hartmann RK*, Analysis of bacterial RNase P RNA and protein interaction by a magnetic biosensor technique, Biochimie, 2010, 92, 772-8.
• Li D, Willkomm DK, Hartmann RK*, Minor changes largely restore catalytic activity of archaeal RNase P RNA from Methanothermobacter thermoautotrophicus, Nucleic Acids Research, 2009, 37, 231-42.
• Li D, Willkomm DK, Schön A, Hartmann RK*, RNase P of the Cyanophora paradoxa cyanelle: a plastid ribozyme, Biochimie, 2007, 89, 1528-38.

Research Interests

• Computational biology: Development of structure-based virtual screening methodologies and multiscale simulations of target-ligand recognition.
• Medicinal chemistry: Discovery and design of small molecule inhibitors against important protein targets.
• Cancer biology and cancer immunotherapy: Identification of new targeted therapies and immunotherapy against cancer, especially brain tumors.

Education and Professional Experiences

• 2007-2011 B. Sc. in Material Science and Engineering, College of Chemistry, Chemical Engineering and Materials Science, Soochow University, Jiangsu, China.
• 2011-2014 M. Sc. in Inorganic Chemistry, Institute of Functional Nano and Soft Material, Soochow University, Jiangsu, China.
• 2014-2019 Ph.D. in Medicinal Chemistry, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
• 2017-2019 Joint-Ph.D. in the Department of Cancer Biology Harvard Medical School, Dana-Farber Cancer Institute, U.S.
• 2019-2021 Research Fellow in the Department of Cancer Biology Harvard Medical School and Dana-Farber Cancer Institute, U.S.
• 2021-now Distinguished Research Fellow, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Selected Publications

• 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, Nature Computational Science, 2023, 3, 789-804.
• Xujun Zhang, Chao Shen, Tianyue Wang, Yafeng Deng, Yu Kang, Dan Li, Tingjun Hou*, Peichen Pan*, ML-PLIC: a web platform for characterizing protein–ligand interactions and developing machine learning-based scoring functions, Briefings in Bioinformatics, 2023, 24, bbad295.
• Chao Shen, Xujun Zhang, Chang-Yu Hsieh, Yafeng Deng, Dong Wang, Lei Xu, Jian Wu, Dan Li, Yu Kang, Tingjun Hou*, Peichen Pan*, A generalized protein-ligand scoring framework with balanced scoring, docking, ranking and screening powers, Chemical Science, 2023, 14, 8129-8146.
• Gaoang Wang, Lei Xu, Haiyi Chen, Yifei Liu, Peichen Pan*, Tingjun Hou*, Recent advances in computational studies on voltage-gated sodium channels: drug design and mechanism studies, WIRES Computational Molecular Science, 2023, 13, e1641.
• Chao Shen, Xujun Zhang, Yafeng Deng, Junbo Gao, Dong Wang, Lei Xu, Peichen Pan*, Tingjun Hou*, Yu Kang*, Boosting Protein-Ligand Binding Pose Prediction and Virtual Screening Based on Residue-Atom Distance Likelihood Potential and Graph Transformer, Journal of Medicinal Chemistry, 2022, 65, 10691-10706.
• Hongyan Du, Dejun Jiang, Junbo Gao, Xujun Zhang, Lingxiao Jiang, Yundian Zeng, Zhenxing Wu, Chao Shen, Lei Xu, Dongsheng Cao*, Tingjun Hou*, Peichen Pan*, Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network, Research, 2022, 9873564.
• Rui Shi#, Peichen Pan#(Co-first authors), Rui Lv, Chongqing Ma, Enhui Wu, Ruochen Guo, Zhihao Zhao, Hexing Song, Joe Zhou, Yang Liu, Guoqiang Xu, Tingjun Hou*, Zhenhui Kang*, Jian Liu*, High-throughput glycolytic inhibitor discovery targeting glioblastoma by graphite dots-assisted LDI mass spectrometry, Science Advances, 2022, 8, eabl4923.
• Kong, Xiaotian#, Peichen Pan#(Co-first authors), Huiyong Sun, Hongguang Xia, Xuwen Wang, Youyong Li, and Tingjun Hou*, Drug Discovery Targeting Anaplastic Lymphoma Kinase (ALK). Journal of Medicinal Chemistry, 2019, 62 (24), 10927-10954.
• Chen, Changwei#, Peichen Pan#(Co-first authors), Ziyang Deng, Dahai Wang, Qifan Wu, Lei Xu, Tingjun Hou*, Sunliang Cui*. Discovery of 3,6-diaryl-1H-pyrazolo[3,4-b]pyridines as potent anaplastic lymphoma kinase (ALK) inhibitors. Bioorganic & Medicinal Chemistry Letters, 2019, 29 (7), 912-916.
• Peichen Pan, Jiean Chen, Xijian Li, Miyang Li, Huidong Yu, Jean J Zhao, Jing Ni, Xuwen Wang, Huiyong Sun, Sheng Tian, Feng Zhu, Feng Liu, Yong Huang*, Tingjun Hou*. Structure-based Drug Design and Identification of H2O-soluble and Low Toxic Hexacyclic Camptothecin Derivatives with Improved Efficacy in both Cancer and Lethal Inflammation Models In Vivo. Journal of Medicinal Chemistry, 2018, 61 (19), 8613–8624.
• Peichen Pan, Huidong Yu, Qinglan Liu, Xiaotian Kong, Hu Chen, Jiean Chen, Qi Liu, Dan Li, Yu Kang, Huiyong Sun, Wenfang Zhou, Sheng Tian, Sunliang Cui, Feng Zhu, Youyong Li, Yong Huang*, Tingjun Hou*, Combating drug-resistant mutants of ALK with potent and selective Type-I1/2 inhibitors by stabilizing unique DFG-shifted loop conformation. ACS Central Science, 2017, 3, 1208-1220.
• Peichen Pan, Huiyong Sun, Hui Liu, Dan Li, Wenfang Zhou, Xiaotian Kong, Youyong Li, Huidong Yu, Tingjun Hou*. In Silico Exploration for Novel Type-I Inhibitors of Tie-2/TEK: The Performance of Different Selection Strategy in Selecting Virtual Screening Candidates. Scientific Reports, 2016, 6.
• Peichen Pan, Sheng Tian, Huiyong Sun, Xiaotian Kong, Wenfang Zhou, Dan Li, Youyong Li, Tingjun Hou*. Identification and Preliminary SAR Analysis of Novel Type-I Inhibitors of TIE-2 via Structure-Based Virtual Screening and Biological Evaluation in in vitro Models. Journal of Chemical Information and Modeling, 2015, 55: 2693-2704.
• Peichen Pan, Youyong Li, Huidong Yu, Tingjun Hou*, Molecular principle of topotecan resistance by topoisomerase I mutations through molecular modeling approaches, Journal of Chemical Information and Modeling, 2013, 53, 997-1006.
• Peichen Pan, Mingyun Shen, Huidong Yu, Youyong Li, Dan Li, Tingjun Hou*, Advances in the development of Rho-associated protein kinase (ROCK) inhibitors, Drug Discovery Today, 2013, 18, 1323–1333.
• Peichen Pan, Lin Li, Youyong Li, Dan Li*, Tingjun Hou*, Insights into susceptibility of antiviral drugs against the E119G mutant of 2009 influenza A (H1N1) neuraminidase by molecular dynamics simulations and free energy calculations, Antiviral Research, 2013, 100, 356–364.

Research Interests

• Development of protein-ligand scoring, docking and virtual screening methodologies and their applications in important drug targets.

Education and Professional Experiences

• 2013-2017 B. Sc. in Pharmacy, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
• 2017-2022 Ph.D. in Medicinal Chemistry, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
• 2022-2024 Postdoc, Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Hangzhou, China.
• 2024-now Distinguished Research Fellow, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Selected Publications

• Chao Shen#, Jianfei Song#, Chang-Yu Hsieh, Dongsheng Cao, Yu Kang, Wenling Ye, Zhenxing Wu, Jike Wang, Odin Zhang, Xujun Zhang, Hao Zeng, Heng Cai, Yu Chen, Linkang Chen, Hao Luo, Xinda Zhao, Tianye Jian, Tong Chen, Dejun Jiang, Mingyang Wang, Qing Ye, Jialu Wu, Hongyan Du, Hui Shi, Yafeng Deng*, Tingjun Hou*, DrugFlow: an AI-driven one-stop platform for innovative drug discovery, Journal of Chemical Information and Modeling, 2024, 64, 5381-5391.
• Heng Cai#, Chao Shen#, Tianye Jian, Xujun Zhang, Tong Chen, Xiaoqi Han, Zhuo Yang, Wei Dang, Chang-Yu Hsieh, Yu Kang, Peichen Pan, Xiangyang Ji, Jianfei Song*, Tingjun Hou*, Yafeng Deng*, CarsiDock: a deep learning paradigm for accurate protein-ligand docking and screening based on large-scale pre-training, Chemical Science, 2024, 15, 1449-1471.
• Chao Shen, Xujun Zhang, Chang-Yu Hsieh, Yafeng Deng, Dong Wang, Lei Xu, Jian Wu, Dan Li, Yu Kang*, Tingjun Hou*, Peichen Pan*, A generalized protein–ligand scoring framework with balanced scoring, docking, ranking and screening powers, Chemical Science, 2023, 14, 8129-8146.
• Chao Shen, Xujun Zhang, Yafeng Deng, Junbo Gao, Dong Wang, Lei Xu, Peichen Pan*, Tingjun Hou*, Yu Kang*, Boosting Protein-Ligand Binding Pose Prediction and Virtual Screening Based on Residue-Atom Distance Likelihood Potential and Graph Transformer, Journal of Medicinal Chemistry, 2022, 65, 10691-10706.
• Guoli Xiong#, Chao Shen#, Ziyi Yang, Dejun Jiang, Shao Liu, Aiping Lu, Tingjun Hou*, Dongsheng Cao*, Featurization strategies for protein-ligand interactions and their applications in scoring function development, WIRES Computational Molecular Science, 2022, 12, e1567.
• Jinping Pang#, Chao Shen#, Wenfang Zhou, Yunxia Wang, Luhu Shan, Xin Chai, Ying Shao, Xueping Hu, Feng Zhu, Danyan Zhu, Li Xiao, Lei Xu, Xiaohong Xu, Dan Li*, Tingjun Hou*, Discovery of novel antagonists targeting the DNA binding domain of androgen receptor by integrated docking-based virtual screening and bioassays, Acta Pharmacologica Sinica, 2022, 43, 229-239.
• Chao Shen, Xueping Hu, Junbo Gao, Xujun Zhang, Haiyang Zhong, Zhe Wang, Lei Xu, Yu Kang*, Dongsheng Cao*, Tingjun Hou*, The impact of cross-docked poses on performance of machine learning classifier for protein–ligand binding pose prediction, Journal of Cheminformatics, 2021, 13, 81.
• Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Jinping Pang, Gaoang Wang, Haiyang Zhong, Lei Xu, Dongsheng Cao*, Tingjun Hou*, Beware of the generic machine learning-based scoring functions in structure-based virtual screening, Briefings in Bioinformatics, 2021, 22, bbaa070.
• Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Haiyang Zhong, Gaoang Wang, Xiaojun Yao, Lei Xu, Dongsheng 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 in Bioinformatics, 2021, 22, 497-514.
• Chao Shen, Gaoqi Weng, Xujun Zhang, Elaine Lai-Han Leung, Xiaojun Yao, Jinping Pang, Xin Chai, Dan Li, Ercheng Wang, Dongsheng Cao*, Tingjun Hou*, Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?, Briefings in Bioinformatics, 2021, 22, bbaa410.
• Chao Shen#, Junjie Ding#, Zhe Wang, Dongsheng Cao, Xiaoqin Ding, Tingjun Hou*, From machine learning to deep learning: advances in scoring functions for computational docking, WIRES Computational Molecular Science, 2020, 10, e1429.
• 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 in Bioinformatics, 2020, 21, 282-297.
• Wenling Ye#, Chao Shen#, Guoli Xiong, Junjie Ding, Aiping Lu, Tingjun Hou*, Dongsheng Cao*, Improving docking-based virtual screening ability by integrating multiple energy auxiliary terms from molecular docking scoring, Journal of Chemical Information and Modeling, 2020, 60, 4216-4230.

Education and Professional Experiences

• 2010/9-2014/6: B.E., Jiangsu University
• 2014/9-2016/6: M.S., Huazhong Agricultural University (supervisor: Professor De-Xin Kong)
• 2016/7-2017/7: RA, Kunming Institute of Botany, Chinese Academy of Sciences
• 2017/9-2021/6: Ph.D., Huazhong Agricultural University (supervisor: Professor De-Xin Kong)
• 2021/8-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• Theoretical predictions of GPCR ligand selectivity based on deep learning.
• Development of virtual screening methodologies based on machine learning.

Selected Publications

• Wang, D., Chen, N. H.; Alex G. T.; Jin Y. T.; Wen C. C.; Kong, D. X.*, Accelerating the Identification of Subtype Selective Inhibitors via Three-Dimensional Biologically Relevant Spectrum (BRS-3D): The Monoamine Oxidase Subtypes as a Case Study, Bioorg. Chem., 2020, 106, 104503.

Education and Professional Experiences

• 2016/9-2022/6: Ph.D., Zhejiang University
• 2022/7-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• Design, synthesis and bioactivity evaluation of novel androgen receptor antagonists.

Selected Publications

• Xin Chai, Huiyong Sun, Wenfang Zhou, Changwei Chen, Luhu Shan, Yuhui Yang, Junzhao He, Jinping Pang, Liu Yang, Xinyue Wang, Sunliang Cui, Yaqin Fu, Xiaohong Xu, Lei Xu, Xiaojun Yao, Dan Li*, Tingjun Hou*. Discovery of N-(4-(Benzyloxy)-phenyl)-sulfonamide Derivatives as Novel Antagonists of the Human Androgen Receptor Targeting the Activation Function 2, Journal of Medicinal Chemistry, 2022,65, 2507-2521
• Changwei Chen#, Xin Chai#(co-first authors), Xueping Hu, Shengying Lou, Dan Li*, Tingjun Hou*, Sunliang Cui*, Discovery of 2-(1-(3-Chloro-4-cyanophenyl)-1H-pyrazol-3-yl)acetamides as Potent, Selective, and Orally Available Antagonists Targeting the Androgen Receptor, Journal of Medicinal Chemistry, 2022, 65, 13074-13093
• Qing Ye, Xin Chai#(co-first authors), Dejun Jiang, Liu Yang, Chao Shen, Xujun Zhang, Dan Li*, Dongsheng Cao*, Tingjun Hou*, Identification of Active Molecules against Mycobacterium Tuberculosis through Machine Learning, Briefings in Bioinformatics, 2021, 22, bbab068

Education and Professional Experiences

• 2014/9-2018/6: B.Sc., Zhejiang University
• 2018/9-2023/6: Ph.D., Zhejiang University (supervisor: Professor Tingjun Hou)
• 2023/7-present: Postdoc, Zhejiang University (In cooperation with Prof. Feng Zhu)

Research Interests

• My research direction is theoretical predictions of druggability based on machine learning and artificial intelligent techniques.

Selected Publications

• Zhenxing Wu, Dejun Jiang, Jike Wang, Xujun Zhang, Hongyan Du, Lurong Pan, Changyu Hsieh*, Dongsheng Cao*, Tingjun Hou*, Knowledge-based BERT: a method to extract molecular features like computational chemists, Briefings in Bioinformatics, 2022, 23, bbac131.
• Zhenxing Wu, Dejun Jiang, Jike Wang, Chang-Yu Hsieh*, Dongsheng Cao*, Tingjun Hou*, Mining Toxicity Information from Large Amounts of Toxicity Data, Journal of Medicinal Chemistry, 2021, 64, 6924-6936.
• Zhenxing Wu, Dejun Jiang, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Dongsheng Cao*, Tingjun Hou*, Hyperbolic Relational Graph Convolution Networks Plus: a Simple but Highly Efficient QSAR-modeling Method, Briefings in Bioinformatics, 2021, 22, bbab112.

Education and Professional Experiences

• 2016/9-2022/12: Ph.D., School of Computer Science, Wuhan University
• 2023/7-present: Postdoc, College of Pharmaceutical Sciences, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• molecular design and protein design based on artificial intelligence.

Selected Publications

• Jike Wang, Chang-Yu Hsieh, Mingyang Wang, Xiaorui Wang, Zhenxing Wu, Dejun Jiang, Benben Liao, Xujun Zhang, Bo Yang, Qiaojun He, Dongsheng Cao*, Xi Chen*, Tingjun Hou*, Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning, Nature Machine Intelligence, 2021, 3, 914-922.
• Jike Wang, Xiaorui Wang, Huiyong Sun, Mingyang Wang, Yundian Zeng, Dejun Jiang, Zhenxing Wu, Zeyi Liu, Ben Liao, Xiaojun Yao, Chang-Yu Hsieh*, Dongsheng Cao*, Xi Chen*, Tingjun Hou*, ChemistGA: A Chemical Synthesizable Accessible Molecular Generation Algorithm for Real-World Drug Discovery, Journal of Medicinal Chemistry, 2022, 65, 12482-12496.
• Jike Wang, Huiyong Sun, Jiawen Chen, Dejun Jiang, Zhe Wang, Zhenxing Wu, Xi Chen*, Dongsheng Cao*, Tingjun Hou*, DeepChargePredictor: A web server for predicting QM-based atomic charges via state-of-the-art machine-learning algorithms, Bioinformatics, 2021, 37, 4255-4257.

• 2012/9-2016/6: B.Sc., Liaoning University of Traditional Chinese Medicine
• 2016/9-2019/6: M.Sc., China Medical University
• 2019/9-2023/6: Ph.D., Zhejiang University
• 2023/7-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• Artificial intelligence for molecular generation and drug design, de novo drug design.

Selected Publications

• Mingyang Wang, Chang-Yu Hsieh, Jike Wang, Dong Wang, Gaoqi Weng, Chao Shen, Xiaojun Yao, Zhitong Bing, Honglin Li*, Dongsheng Cao*, Tingjun Hou*, RELATION: A Deep Generative Model for Structure-Based De Novo Drug Design, Journal of Medicinal Chemistry, 2022, 65, 9478-9492.
• Mingyang Wang, Huiyong Sun, Jike Wang, Jinping Pang, Xin Chai, Lei Xu, Honglin Li*, Dongsheng Cao*, Tingjun Hou*, Comprehensive assessment of deep generative architectures for de novo drug design, Briefings in Bioinformatics, 2022, 23, bbab544.
• Mingyang Wang, Zhe Wang, Huiyong Sun, Jike Wang, Chao Shen, Gaoqi Weng, Xin Chai, Honglin Li*, Dongsheng Cao*, Tingjun Hou*, Deep learning approaches for de novo drug design: an overview, Current Opinion in Structural Biology, 2022, 72, 135-144.

• 2013/9-2017/6: B.Sc., Liaoning University
• 2017/9-2023/6: Ph.D., Liaoning University
• 2023/7-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• Theoretical predictions of druggability based on artificial intelligent.

Selected Publications

• Li S, Wang L, Meng J, et al. De Novo design of potential inhibitors against SARS-CoV-2 Mpro[J]. Computers in Biology and Medicine, 2022, 147: 105728.

Research Interests

• Drug design of photodynamic therapy based on artificial intelligence method.

Selected Publications

• Chen K., Zhao J.* Anthryl-Appended Platinum(II) Schiff Base Complexes: Exceptionally Small Stokes Shift, Triplet Excited States Equilibrium, and Application in Triplet–Triplet-Annihilation Upconversion. Inorg. Chem. 2020, 59, 14731−14745.
• Chen K., Zhao J.* Intersystem Crossing and Electron Spin Selectivity in Anthracene-Naphthalimide Compact Electron Donor-Acceptor Dyads Showing Different Geometry and Electronic Coupling Magnitudes. Chem. Eur. J. 2021, 27, 7572 –7587.

Education and Professional Experiences

• 2015/9-2019/6: B.Sc., Zhejiang University
• 2019/9-2024/6: Ph.D., Zhejiang University (supervisor: Professor Tingjun Hou)
• 2024/7-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• Methodological Study on Machine Learning-Based Molecular Docking.

Selected Publications

• Xujun Zhang, Chao Shen, Haotian Zhang, Yu Kang, Chang-Yu Hsieh*, Tingjun Hou*, Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening, Accounts of Chemical Research, 2024, 57, 1500-1509.
• 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, Nature Computational Science, 2023, 3, 789-804.
• Xujun Zhang, Chao Shen, Tianyue Wang, Yu Kang, Dan Li, Peichen Pan, Jike Wang, Gaoang Wang, Yafeng Deng, Lei Xu, Dongsheng Cao*, Tingjun Hou*, Zhe Wang*, Topology-Based and Conformation-Based Decoys Database: An Unbiased Online Database for Training and Benchmarking Machine-Learning Scoring Functions, Journal of Medicinal Chemistry, 2023, 66, 9174-9183.
• Xujun Zhang, Chao Shen, Ben Liao, Dejun Jiang, Jike Wang, Zhenxing Wu, Hongyan Du, Tianyue Wang, Wenbo Huo, Lei Xu, Dongsheng Cao*, Chang-Yu Hsieh*, Tingjun Hou*, TocoDecoy: A New Approach to Design Unbiased Datasets for Training and Benchmarking Machine-Learning Scoring Functions, Journal of Medicinal Chemistry, 2022, 65, 7918-7932.
• Xujun Zhang, Chao Shen, Chang-Yu Hsieh*, Tingjun Hou*, Harnessing deep learning for enhanced ligand docking, Trends in Pharmacological Sciences, 2024, 45, 103-106.
• Tianyue Wang#, Xujun Zhang#, Odin Zhang#, Guangyong Chen, Peichen Pan, Ercheng Wang, Jike Wang, Jialu Wu, Donghao Zhou, Langcheng Wang, Ruofan Jin, Shicheng Chen, Chao Shen, Yu Kang*, Chang-Yu Hsieh*, Tingjun Hou*, Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoop, Research, 2024, 7, 0408.

Education and Professional Experiences

• 2014/9-2018/6: B.Sc., Lanzhou University
• 2018/9-2021/6: M.Sc., Lanzhou University (supervisor: Professor Xiaojun Yao)
• 2021/9-2024/8: Ph.D., Macau university of science and technology (supervisor: Professor Xiaojun Yao and Pei Luo, co-supervised with Professor Tingjun Hou)
• 2024/9-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• My research direction is the machine learning-based computer-aided synthesis planning algorithms and enzymatic synthesis planning algorithms.

Selected Publications

• Xiaorui Wang, Xiaodan Yin, Dejun Jiang, Huifeng Zhao, Zhenxing Wu, Odin Zhang, Jike Wang, Yuquan Li, Yafeng Deng, Huanxiang Liu, Pei Luo, Yuqiang Han, Tingjun Hou*, Xiaojun Yao*, Chang-Yu Hsieh*, Multi-Modal Deep Learning Enables Ultrafast and Accurate Annotation of Enzymatic Active Sites, Nature Communications, 2024, 15, 7348.
• Xiaorui Wang#, Yuquan Li#, Jiezhong Qiu, Guangyong Chen, Huanxiang Liu, Benben Liao*, Chang-Yu Hsieh*, Xiaojun Yao*, RetroPrime: A Diverse, Plausible and Transformer-based Method for Single-Step Retrosynthesis Predictions, Chemical Engineering Journal, 2024, 420, 129845.
• Xiaorui Wang#, Chang-Yu Hsieh#*, Xiaodan Yin, Jike Wang, Yuquan Li, Yafeng Deng, Dejun Jiang, Zhenxing Wu, Hongyan Du, Hongming Chen, Yun Li, Huanxiang Liu, Yuwei Wang, Pei Luo, Tingjun Hou*, Xiaojun Yao*, Generic Interpretable Reaction Condition Predictions with Open Reaction Condition Datasets and Unsupervised Learning of Reaction Center, Research, 2024, 6, 0231.
• Jike Wang#, Xiaorui Wang#, Huiyong Sun, Mingyang Wang, Yundian Zeng, Dejun Jiang, Zhenxing Wu, Zeyi Liu, Ben Liao, Xiaojun Yao, Chang-Yu Hsieh*, Dongsheng Cao*, Xi Chen*, Tingjun Hou*, ChemistGA: A Chemical Synthesizable Accessible Molecular Generation Algorithm for Real-world Drug Discovery, Journal of Medicinal Chemistry, 2024, 65, 12482-12496.
• Xiaodan Yin#, Xiaorui Wang#, Yuquan Li, Jike Wang, Yuwei Wang, Yafeng Deng, Tingjun Hou, Huanxiang Liu, Pei Luo, Xiaojun Yao*, CODD-Pred: A Web Server for Efficient Target Identification and Bioactivity Prediction of Small Molecules, Journal of Chemical Information and Modeling, 2024, 63, 6169-6176.

Education and Professional Experiences

• 2014/9-2018/6: B.Sc., Lanzhou University
• 2018/9-2021/6: M.Sc., Lanzhou University (supervisor: Professor Xiaojun Yao)
• 2021/9-2024/8: Ph.D., Macau university of science and technology (supervisor: Professor Xiaojun Yao and Pei Luo, co-supervised with Professor Tingjun Hou)
• 2024/9-present: Postdoc, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• My research focuses on the prediction of small molecule properties and chemical reaction properties based on machine learning.

Selected Publications

• Xiaodan Yin#, Chang-Yu Hsieh#*, Xiaorui Wang, Zhenxing Wu, Qing Ye, Honglei Bao, Yafeng Deng, Hongming Chen, Pei Luo, Huanxiang Liu, Tingjun Hou*, Xiaojun Yao*, Enhancing Generic Reaction Yield Prediction through Reaction Condition-Based Contrastive Learning, Research, 2024, 7, 0292.
• Xiaodan Yin#, Xiaorui Wang#, Yuquan Li, Jike Wang, Yuwei Wang, Yafeng Deng, Tingjun Hou, Huanxiang Liu, Pei Luo, Xiaojun Yao*, CODD-Pred: A Web Server for Efficient Target Identification and Bioactivity Prediction of Small Molecules, Journal of Chemical Information and Modeling, 2024, 63, 6169-6176.
• Xiaodan Yin, Kun-Yuan Ma, Yu-Ling Wang, Yu Sun, Xiao-Fei Shang, Zhong-Min Zhao, Ren-Xuan Wang, Yong-Jia Chen, Jia-Kai Zhu, Ying-Qian Liu*, Design, synthesis, and antifungal evaluation of 8-hydroxyquinoline metal complexes against phytopathogenic fungi, Journal of Agricultural and Food Chemistry, 2020, 68, 11096-11104.
• Jing-Wen Peng#, Xiaodan Yin#, Hu Li, Kun-Yuan Ma, Zhi-Jun Zhang, Rui Zhou, Yu-Ling Wang, Guan-Fang Hu, Ying-Qian Liu*, Design, synthesis, and structure–activity relationship of quinazolinone derivatives as potential fungicides, Journal of Agricultural and Food Chemistry, 2021, 69, 4604-4614.

Research Interests

• I am interested in molecular dynamics and accelerated sampling method developing.

Selected Publications

• Xueping Hu#, Jinping Pang#, Jintu Zhang#(co-first authors), Chao Shen, Xin Chai, Ercheng Wang, Haiyi Chen, Xuwen Wang, Mojie Duan, Weitao Fu, Lei Xu, Yu Kang, Dan Li*, Hongguang Xia*, Tingjun Hou*, Discovery of novel GR ligands towards druggable GR antagonist conformations identified by MD Simulations and Markov state model analysis, Advanced Science, 2022, 9, 2102435.

Research Interests

• I am working on development of algorithm for covalent drug design and discovery.

Selected Publications

• Hongyan Du, Dejun Jiang, Junbo Gao, Xujun Zhang, Lingxiao Jiang, Yundian Zeng, Zhenxing Wu, Chao Shen, Lei Xu, Dongsheng Cao*, Tingjun Hou*, Peichen Pan*, Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network, Research, 2022, 9873564.
• Hongyan Du, Junbo Gao, Gaoqi Weng, Junjie Ding, Xin Chai, Jinping Pang, Yu Kang, Dan Li, Dongsheng Cao*, Tingjun Hou*, CovalentInDB: a comprehensive database facilitating the discovery of covalent inhibitors, Nucleic Acids Research, 2021, 49(D1), D1122-D1129.

Research Interests

• targetedcancer drug development based on artificial intelligence.

Research Interests

• Discovery of small molecule inhibitors targeting androgen receptor and its activity detection.

Research Interests

• Molecule generation.

Research Interests

• Theoretical prediction of druggability based on artificial intelligence.

Research Interests

• Drug design of voltage-gated sodium channels.

Selected Publications

• Gaoang Wang, Jiahui Yu, Hongyan Du, Chao Shen, Xujun Zhang, Yifei Liu, Yangyang Zhang, Dongsheng Cao, Peichen Pan*, Tingjun Hou*, VGSC-DB: an online database of voltage-gated sodium channels, Journal of Cheminformatics, 2022, in press.
• Gaoang Wang, Lei Xu, Haiyi Chen, Yifei Liu, Peichen Pan*, Tingjun Hou*, Recent advances in computational studies on voltage-gated sodium channels: drug design and mechanism studies, WIRES Computational Molecular Science, 2022, in press.

Research Interests

• Modify the formula of boost potential in enhanced sampling methods.

Research Interests

• Predicting ADMET properties through machine learning and artificial intelligence approaches.

Selected Publications

• Jialu Wu, Yue Wan, Zhenxing Wu, Shengyu Zhang, Dongsheng Cao*, Chang-Yu Hsieh*, Tingjun Hou*, MF-SuP-pKa: Multi-fidelity modeling with subgraph pooling mechanism for pKa prediction, Acta Pharmaceutica Sinica B, 2022, in press.
• Jialu Wu, Yu Kang, Peichen Pan*, Tingjun Hou*, Machine learning methods for pKa prediction of small molecules: advances and challenges, Drug Discovery Today, 2022, in press.
• Jialu Wu, Junmei Wang, Zhenxing Wu, Shengyu Zhang, Yafeng Deng, Yu Kang, Dongsheng Cao*, Chang-Yu Hsieh*, Tingjun Hou*, ALipSol: An attention-driven mixture-of-experts model for lipophilicity and solubility prediction, Journal of Chemical Information and Modeling, 2022, in press.

Research Interests

• Artificial intelligence assisted drug discovery, Research on molecular generation technology based on Artificial Intelligence.

Research Interests

• Artificial Intelligence Aided Drug Design.

Selected Publications

• 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 in Bioinformatics, 2023, 24, bbad008.
• Shukai Gu, Huanxiang Liu, Liwei Liu, Tingjun Hou*, Yu Kang*, Artificial intelligence methods in kinase targets profiling: advances and challenges, Drug Discovery Today, 2023.

Research Interests

• Research on GPCR personalized scoring method based on machine learning.

Research Interests

• Screening and discovery of covalent inhibitors.

Research Interests

• Theoretical prediction of antibody-antigen interactions using artificial intelligence.

Research Interests

• Enzyme-Molecule Interactions Research based on Artificial Intelligence.

Research Interests

• Prediction of druggability based on the artificial intelligence technology.

Research Interests

• The applicaition of GNN and large language model in protein.

Selected Publications

• Tianyue Wang#, Xujun Zhang#, Odin Zhang#, Guangyong Chen, Peichen Pan, Ercheng Wang, Jike Wang, Jialu Wu, Donghao Zhou, Langcheng Wang, Ruofan Jin, Shicheng Chen, Chao Shen, Yu Kang*, Chang-Yu Hsieh*, Tingjun Hou*, Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoop, Research, 2024, 7, 0408.
• Tianyue Wang, Langcheng Wang, Xujun Zhang, Chao Shen, Odin Zhang, Jike Wang, Jialu Wu, Ruofan Jin, Donghao Zhou, Shicheng Chen, Liwei Liu, Xiaorui Wang, Chang-Yu Hsieh, Guangyong Chen, Peichen Pan*, Yu Kang*, Tingjun Hou*, Comprehensive Assessment of Protein Loop Modeling Programs on Large-scale Datasets: Prediction Accuracy and Efficiency, Briefings in Bioinformatics, 2024, 25, bbad486.
• Odin Zhang#, Tianyue Wang#, Gaoqi Weng, Dejun Jiang, Ning Wang, Xiaorui Wang, Huifeng Zhao, Jialu Wu, Ercheng Wang, Guangyong Chen, Yafeng Deng, Peichen Pan, Yu Kang*, Chang-Yu Hsieh*, Tingjun Hou*, Learning on topological surface and geometric structure for 3D molecular generation, Nature Computational Science, 2023, 3, 849-859.

Research Interests

• Development of androgen receptor antagonists.

Research Interests

• Computer-aided drug design and mechanism research.

Research Interests

• Design and discovery of peptide drugs and cyclic peptide drugs based on artificial intelligence and physical methods.

Research Interests

• Immune-related drug design based on artificial intelligence.

Selected Publications

• Jingxuan Ge, Dejun Jiang, Huiyong Sun, Yu Kang, Peichen Pan, Yafeng Deng, Chang-Yu Hsieh*, Tingjun Hou*, Deep-learning-based prediction framework for protein-peptide interactions with structure generation pipeline, Cell Reports Physical Science, 2024, 5, 101980.
• Jingxuan Ge, Shimeng Li, Gaoqi Weng, Huating Wang, Meijing Fang, Huiyong Sun, Yafeng Deng, Chang- Yu Hsieh, Dan Li*, Tingjun Hou*, PROTAC-DB 3.0: an updated database of PROTACs with extended pharmacokinetic parameters, Nucleic Acids Research, 2024, in press.

Research Interests

• Deep network theory and applications embedded in statistical physics.

Selected Publications

• Odin Zhang#, Tianyue Wang#, Gaoqi Weng, Dejun Jiang, Ning Wang, Xiaorui Wang, Huifeng Zhao, Jialu Wu, Ercheng Wang, Guangyong Chen, Yafeng Deng, Peichen Pan, Yu Kang*, Chang-Yu Hsieh*, Tingjun Hou*, Learning on topological surface and geometric structure for 3D molecular generation, Nature Computational Science, 2023, in press.
• Odin Zhang, Jintu Zhang, Jieyu Jin, Xujun Zhang, RenLing Hu, Chao Shen, Hanqun Cao, Hongyan Du, Yu Kang, Yafeng Deng, Furui Liu*, Guangyong Chen*, Chang-Yu Hsieh*, Tingjun Hou*, ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling, Nature Machine Intelligence, 2023, 5, 1020-1030.
• 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, Nature Computational Science, 2023, 3, 789-804.

Research Interests

• AI and physics-driven binding free energy calculation/prediction method.

Selected Publications

• Renling Hu, Jintu Zhang, Yu Kang, Peichen Pan, Yafeng Deng, Chang-Yu Hsieh*, Tingjun Hou*, Comprehensive, Open-Source, and Automated Workflow for Multisite λ-Dynamics in Lead Optimization, Journal of Chemical Theory and Computation, 2024, 20, 11465-11478.

Research Interests

• Research on druggability prediction based on artificial intelligence technology and machine learning.

Research Interests

• Drug design and discovery for Androgen receptor.

Research Interests

• Drug screening and bioactivity evaluation targeting glucocorticoid receptors.

Research Interests

• Development and application of drug design methods based on machine learning and artificial intelligence technology.

Research Interests

• Molecular Generation Based on Machine Learning.

Research Interests

• Development and application of drug design methods based on machine learning and artificial intelligence technology.

Research Interests

• Drug design algorithms and application based on deep generative models.

Research Interests

• Structure-based drug discovery and design.

Research Interests

• Research on downstream applications of graph deep learning in omics.

Research Interests

• Discovery and bioactivity evaluation of novel androgen receptor antagonists.

Research Interests

• Research on Molecular Generation Targeting RNA.

Research Interests

• Development and application of drug design methods based on artificial intelligence technology.

Research Interests

• Development of novel modulators targeting glucocorticoid receptor by virtual screening and bioassays.

Research Interests

• Protein docking conformation generation.

Research Interests

• CADD.

Research Interests

• Drug properties prediction based on single cell large models.

Research Interests

• CADD.

Research Interests

• Application of fluorescent protein sensors in detecting intracellular signaling pathways.

Research Interests

• Sequence generation and prediction based on machine learning and artificial intelligence.

Research Interests

• Computer Aided Drug Design.

Research Interests

• Covalent molecular docking and molecule generation.

Research Interests

• Machine Learning Training Methods for Blood-Brain Barrier Penetrating Peptides.

Research Interests

• Affinity Prediction based on Antibody Language Model.

Research Interests

• AI Aided Molecule Toxicity Prediction.

Research Interests

• Discovery of active small molecules targeting nuclear receptors.

Education and Professional Experience

• 09.2002-06.2006, B. Sc., Jilin Agricultural University, Changchun, China
• 09.2007-06.2010, M. Sc., Department of Chemistry, Northeast Normal University, Changchun, China
• 09.2010-12.2013, Ph. D., Institute of Functional Nano & Soft Materials, Soochow University, Suzhou, China
• 01.2014-12.2015, Postdoc, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
• 01.2016-present, Associate Research Fellow, Institute of Bioinformatics and Medical Engineering, Jisuang University of Technology, Changzhou, China

Research Interests

• The methodology development and application of computer aided drug design (CADD). Design and discovery of novel drug candidates for important targets (MIF and HIV integrase) by the combination of CADD techniques (such as molecular docking, molecular dynamic simulation, free energy calculations, etc.) and experimental assays.

Selected Publications

• Xu L, Li YY, Sun HY, Zhen XC, Qiao CH, Tian S, Hou TJ*, Current developments of macrophage migration inhibitory factor (MIF) inhibitors, Drug Discovery Today, 2013, 18, 592-600.
• Xu L, Zhang Y, Zheng LT, Qiao CH, Li YY, Li D, Zhen XC, Hou TJ *, Discovery of novel inhibitors targeting macrophage migration inhibitory factor via structure-based virtual screening and bioassays, Journal of Medicinal Chemistry, 2014, 57, 3737-3745.
• Xu L, Li YY, Li D, Xu P, Tian S, Sun HY, Liu H, Hou TJ*, Exploring the Binding Mechanisms of MIF to CXCR2 by Theoretical Approaches, Physical Chemistry Chemical Physics, 2015, 15, 3370-3382.
• Xu L, Sun HY, Li YY, Wang JM, Hou TJ*, Assessing the Performance of MM/PBSA and MM/GBSA Methods. 3. The Impact of Force Fields and Ligand Charge Models, Journal of Physical Chemistry B, 2013, 117, 8408-8421.
• Xu L, Li YY, Sun HY, Li Dan, Hou TJ*, Structural basis of the interactions between CXCR4 and CXCL12/SDF-1 revealed by theoretical approaches, Molecular Biosystems, 2013, 9, 2107-2117.

Education and Professional Experience

• 09.2003-06.2007, B. Sc., Computer Science and Technology, South China Agricultural University, China
• 09.2007-06.2010, M. Sc., Technology of Computer Application, South China Agricultural University, China
• 09.2010-06.2013, Ph. D., Institute of Functional Nano & Soft Materials, Soochow University, Suzhou, China
• 07.2013-06.2015, Postdoc, School of Pharmacy, University of Pittsburgh, USA
• 07.2015-06.2017, Research Associate, School of Pharmacy, University of Pittsburgh, USA
• 07.2017-present, Assistant Professor, School of Pharmacy, University of Pittsburgh, USA

Research Interests

• Computational systems pharmacology analysis and clinical big-data analysis: construction of knowledgebase (including targets, small molecules, drugs, related signaling pathway, experimental protocol, references, tools/algorithms for visualization and analyses) ，collaboration with hospital clinician for statistical analysis and prediction, etc.; Multi-scale simulation of targets and novel drug design for GPCRs, ion channel, and other important targets：lead compound for novel targets (APE1, p18, p62, KLF4, TRPM8), multiple-function “hybrid” compounds’ design (e.g., CB2-TRPV1, CB2-CCR2), computation-guided lead optimization (CB2, TNFα, p18, p62); The development of GPU-accelerated algorithms, AI artificial drug design platform, software/app, etc.

Selected Publications

• Hyunjoo Cha-Molstad#, Ji Eun Yu#, Zhiwei Feng#(equal-first author), Su Hyun Lee#, Jung Gi Kim #, Peng Yang#, Young Dong Yoo, Joonsung Hwang, Terry McGuire , Sang Mi Shim, Hyun Dong Song, Srinivasrao Ganipisetti, Nuozhou Wang , Jun Min Jang, Min Jae Lee, Seung Jun Kim, Kyung Ho Lee, Jin Tae Hong, Aaron Ciechanover, Inhee Mook-Jung, Xiang-Qun Xie*, Yong Tae Kwon*, and Bo Yeon Kim*, The N-end rule pathway mediates autophagic proteolysis, Nature Communications, 2017, 8, 102.
• Ying Xue#, Zhiwei Feng#(equal -first author), Xiaoye Li#, Ziheng Hu, Qing Xu, Zi Wang, Jiahui Cheng, Hongtao Shi, Qibing Wang,Hongyi Wu, Xiangqun Xie*, Qianzhou Lv*, The efficacy and safety of cilostazol as an alternative to aspirin after coronary stent implantation in patients with intolerance to aspirin: A combination of clinical study and computational system pharmacology analysis, Acta Pharmacologica Sinica, 2017, 1-8, doi:10.1038/aps.2017.85.
• Zhiwei Feng, Larry V. Pearce, Xiaomeng Xu, Xiaole Yang, Peng Yang, Peter M. Blumberg*, and Xiang-Qun Xie*, Structural Insight into Tetrameric hTRPV1 from Homology Modeling, Molecular Docking, Molecular Dynamics Simulation, Virtual Screening and Bioassay Validations, Journal Chemical Information Modeling, 2015, 55, 572–588.
• Xiaotian Sun#, Zhiwei Feng# (equal-first author), Tingjun Hou, Youyong Li*, Mechanism of Graphene Oxide as an Enzyme Inhibitor from Molecular Dynamics Simulations, ACS Applied Materials & Interfaces, 2014, 6 (10), 7153–7163.
• Zhiwei Feng, Tingjun Hou, Youyong Li*, The Studies on the Interactions between β2 Adrenergic Receptor and Gs Protein by Molecular Dynamics Simulations, Journal Chemical Information Modeling, 2012, 52, 1005-1014.
• Zhiwei Feng

Education and Professional Experience

• 09.2004-06.2008, B. Sc., Hefei University, Hefei, China
• 09.2007-06.2008, United training, USTC, Hefei, China
• 09.2008-06.2011, M. Sc., Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University, Suzhou, China
• 09.2011-06.2014, Ph. D., Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University, Suzhou, China
• 06.2014-08.2016, Postdoc, College of Pharmaceutical Sciences, Soochow University, Suzhou, China
• 09.2016-present, Associate Professor, College of Pharmaceutical Sciences, Soochow University, Suzhou, China

Research Interests

• Development and application of CADD methods in drug discovery pipeline, including: theoretical predictions of important ADME/T properties and drug-likeness; development and application of novel parallel virtual screening strategy; investigation of interaction patterns between small chemicals and related drug targets; drug design and development for hot targets, such as kinases and GPCRs.

Selected Publications

• Sheng Tian, Junmei Wang, Youyong Li, Dan Li, Lei Xu, Tingjun Hou*, The application of in silico drug-likeness predictions in pharmaceutical research, Advanced Drug Delivery Reviews, 2015, 23, 2-10.
• Sheng Tian, Huiyong Sun, Peichen Pan, Dan Li, Xuechu Zhen*, Youyong Li*, Tingjun Hou*, Assessing an Ensemble Docking-Based Virtual Screening Strategy for Kinase Targets by Considering Protein Flexibility, Journal of Chemical Information and Modeling, 2014, 54(10), 2664-2679.
• Sheng Tian, Huiyong Sun, Youyong Li, Dan Li, Tingjun Hou*, Development and evaluation of an integrated virtual screening strategy by combining molecular docking and pharmacophore searching based on multiple protein structures, Journal of Chemical Information and Modeling, 2013, 53(10), 2743-2756.
• Sheng Tian, Youyong Li, Dan Li, Xiaojie Xu, Junmei Wang, Qian Zhang, Tingjun Hou*, Modeling compound-target interaction network of Traditional Chinese Medicines for type II diabetes mellitus: insight for polypharmacology and drug design, Journal of Chemical Information and Modeling, 2013, 53(7), 1787–1803.
• Sheng Tian, Junmei Wang, Youyong Li, Xiaojie Xu, Tingjun Hou*, Drug-likeness Analysis of Traditional Chinese Medicines: Prediction of Drug-likeness Using Machine Learning Approaches, Molecular Pharmaceutics, 2012, 9(10), 2875-2886.

Education and Professional Experience

• 09.2005-06.2009, B.E. in Pharmaceutical Engineering, Huaiyin Institute of Technology, Huaiyin
• 09.2009-06.2011, M.S. in Computer-Aided Drug Design (Supervisor: Tingjun Hou), Institute of Functional Nano & Soft Material; FUNSOM, Soochow University, Suzhou
• 07.2011-06.2014, Ph.D. in Tumor Pharmacology (Supervisor: Xinliang Mao and Tingjun Hou), Hematology Center, Cyrus Tang Medical Institute, Soochow University, Suzhou
• 03.2015-09.2016, Postdoctor in Medicinal Chemistry (partner: Tingjun Hou), School of Pharmaceutical Sciences, Zhejiang University, Hangzhou
• 09.2016-present, Associate Professor, School of Pharmaceutical Sciences, Jiangnan University, Wuxi, China

Research Interests

• Construct and validate 3D models for drug design: homology modeling, virtual screening, similarity search, pharmacophore modeling, molecular docking, MD simulations and free energy calculation; QSAR study of small chemical compounds of NS3/NS4A protease; studies on isoform-specific binding mechanisms of phosphoinositide 3-kinase inhibitors by combining MD stimulation and free energy calculation; design of the PI3K/AKT pathway inhibitors for the treatment of multiple myeloma; design of the ROCK and HDAC inhibitors for the treatment of cancer; virtual-screening based on multiple structures inhibitors of USP7 for the treatment of cancer.

Selected Publications

• Jingyu Zhu, Tingjun Hou*, Xinliang Mao*. Discovery of selective phosphatidylinositol 3-kinase inhibitors to treat hematological malignancies. Drug Discovery Today. 2015; 20(8): 988-94.
• Jingyu Zhu, Chunhua Qiao, Tingjun Hou*, Xinliang Mao*. A novel PI3K inhibitor PIK-C98 displays potent preclinical activity against multiple myeloma. Oncotarget. 2015; (1): 185-95.
• Jingyu Zhu, Peichen Pan, Youyong Li, Biyin Cao, Xinliang Mao, Tingjun Hou*. Theoretical studies on beta and delta isoform-specific binding mechanisms of phosphoinositide 3-kinase inhibitors. Molecular Biosystems, 2014; 10(3): 454-66.
• Jingyu Zhu, Tingjun Hou*, Xinliang Mao*. Targeting the phosphatidylinositol 3-kinase/AKT pathway for the treatment of multiple myeloma. Current Medicinal Chemistry. 2014; 21(27): 3173-87.
• Jingyu Zhu, Youyong Li, Huidong Yu, Liling Zhang, Xinliang Mao, Tingjun Hou*. Insight into the structural requirements of narlaprevir-type inhibitors of NS3/NS4A protease based on hqsar and molecular field analyses. Combinatorial Chemistry & High Throughput Screening, 2012; 15(6): 439-50.

Education and Professional Experience

• 09.2006-06.2010, B. Sc., College of pharmacy, Soochow University, Suzhou, China
• 09.2010-06.2015, Ph. D., Institute of Functional Nano & Soft Materials, Soochow University, Suzhou, China
• 07.2015-present, Research & Development Supervisor, Yangtze river pharmaceutical group

Selected Publications

• Mingyun Shen, Peichen Pan, Youyong Li, Dan Li, Huidong Yu*, Tingjun Hou*, Farnesyltransferase (FTase) and geranylgeranyltransferase I (GGTase-I): structures, mechanism, inhibitors and molecular modeling, Drug Discovery Today, 2015, 20, 267-76.
• Mingyun Shen, Sheng Tian, Youyong Li, Qian Li, Xiaojie Xu, Junmei Wang, Tingjun Hou*, Drug-likeness analysis of Traditional Chinese Medicines: 1. Property distributions of Drug-like compounds, Non-drug-like compounds and Natural compounds from Traditional Chinese Medicines, Journal of Cheminformatics, 2012, 4, 31.
• Mingyun Shen, Huidong Yu, Youyong Li, Pixu Li, Peichen Pan, Shunye Zhou, Liling Zhang, Shang Li, Simon Ming-Yuen Lee*, Tingjun Hou*, Discovery of Rho-kinase inhibitors by docking-based virtual screening, Molecular Biosystems, 2013, 9, 1511-1521.
• Mingyun Shen, Shunye Zhou, Youyong Li, Peichen Pan, Liling Zhang, Tingjun Hou*, Discovery and optimization of triazine derivatives as ROCK1 inhibitors: molecular docking, molecular dynamics simulations and free energy calculations, Molecular Biosystems, 2013, 9, 361-374.
• Mingyun Shen , Sheng Tian, Peichen Pan, Huiyong Suna , Dan Li, Youyong Li, Hefeng Zhou, Chuwen Li, Simon Ming-Yuen Lee*, Tingjun Hou*, Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and Bioassays. Scientific Reports, 2015, 5, 602.

Education and Professional Experience

• 09.2004-07.2008, B. Sc., Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China
• 09.2008-12.2014, M. Sc. & Ph. D., College of Environmental Science and Engineering, Tongji University, Shanghai, China
• 06.2015-08.2017, Postdoc, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
• 09.2017-present, Associate Professor, College of Life and Environmental Sciences, Shanghai Normal University, Shanghai, China

Selected Publications

• Fu Chen, Huiyong Sun, Hui Liu, Dan Li, Youyong Li, Tingjun Hou. Prediction of luciferase inhibitors by the high-performance MIEC-GBDT approach based on interaction energetic patterns. 2017, Physical Chemistry Chemical Physics, 19(15), 10163-10176.
• Fu Chen, Hui Liu, Huiyong Sun, Peichen Pan, Youyong Li, Dan Li, Tingjun Hou. Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein–protein binding free energies and re-rank binding poses generated by protein–protein docking. 2016, Physical Chemistry Chemical Physics, 18(32), 22129-22139.
• Fu Chen, Shu-Shen Liu, Mo Yu, Rui Qu, Meng-Chao Wang. Blocking the entrance of AMP pocket results in hormetic stimulation of imidazolium-based ionic liquids to firefly luciferase. 2015, Chemosphere, 132, 108-113.

Education and Professional Experience

• 09.2001-07.2005, B. Sc., College of Pharmaceutical Sciences, Wuhan University, Wuhan, China
• 09.2005-12.2010, Ph. D., College of Life Sciences, Wuhan University, Wuhan, China
• 05.2014-12.2017, Postdoc, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
• 01.2018-present, Lecturer, College of Informatics, Huazhong Agricultural University, Wuhan, China

Selected Publications

• Hui Liu, Fu Chen, Huiyong Sun, Dan Li, Tingjun Hou*, Improving the efficiency of non-equilibrium sampling in the aqueous environment via implicit-solvent simulations, Journal of Chemical Theory and Computation, 2017, 13, 1827-1836.
• Hui Liu, Tingjun Hou*, CaFE: a tool for binding affinity prediction using end-point free energy methods, Bioinformatics, 2016, 32, 2216-2218.
• Hui Liu, Dan Li, Youyong Li, Tingjun Hou*, Atomistic molecular dynamics simulations of ATP-binding cassette transporters, WIREs Computational Molecular Science, 2016, 6, 255-265.

Education and Professional Experience

• 09.2005-06.2009, B. Sc., College of Life Sciences, Ludong University, Yantai, China
• 09.2009-06.2012, M. Sc., College of Life Sciences, Shandong University of Technology, Zibo, China
• 09.2012-06.2015, Ph. D., Institute of Functional Nano & Soft Materials, Soochow University, Suzhou, China
• 07.2015-05.2018, Postdoc, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
• 06.2018-present, Associate Research Fellow, School of Pharmacy, China Pharmaceutical University, Nanjing, China

Selected Publications

• Huiyong Sun, Tingjun Hou*, Hongyu Zhang*, Finding chemical drugs for genetic diseases, Drug Discovery Today, 2014, 19, 1836-1840. (Feature article)
• Huiyong Sun, Pengcheng Chen, Dan Li, Youyong Li, Tingjun Hou*, Directly Binding Rather than Induced-Fit Dominated Binding Affinity Difference in (S)- and (R)-Crizotinib Bound MTH1, Journal of Chemical Theory and Computation, 2016, 12, 851-860.
• Huiyong Sun, Youyong Li, Sheng Tian, Junmei Wang, Tingjun Hou*, P-loop Conformation Governed Crizotinib Resistance in G2032R-Mutated ROS1 Tyrosine Kinase: Clues from Free Energy Landscape, PLoS Computational Biology, 2014, 10, e1003729.
• Huiyong Sun, Youyong Li*, Dan Li, Tingjun Hou*, Insight into Crizotinib Resistance Mechanisms Caused by Three Mutations in ALK Tyrosine Kinase using Free Energy Calculation Approaches, Journal of Chemical Information and Modeling, 2013, 53, 2376-2389.
• Huiyong Sun, Youyong Li, Mingyun Shen, Dan Li, Yu Kang, Tingjun Hou*, Characterizing Drug-Target Residence Time with Metadynamics: How to Achieve Dissociation Rate Efficiently without Losing Accuracy against Time-Consuming Approaches, Journal of Chemical Information and Modeling, 2017, 57, 1895-1906.

Research Interests

• I am mainly engaged in receptor-based virtual screening of large-scale small molecules database. In addition, another major research direction is to use combined computer modeling methods, such as molecular docking, molecular dynamics simulations, enhanced sampling, and free energy calculation techniques, to explore the binding mechanism of inhibitors.

Selected Publications

• Xiaotian Kong, Huiyong Sun, Peichen Pan, Sheng Tian, Dan Li, Youyong Li*, Tingjun Hou*, Molecular Principle of Cyclin-dependent Kinases Selectivity of 4-(Thiazol-5-yl)-2-(phenylamino) pyrimidine-5-carbonitrile Derivatives Revealed by Molecular Modeling Studies, Physical Chemistry Chemical Physics, 2016, 18, 2034-2046.
• Xiaotian Kong, Peichen Pan, Dan Li, Sheng Tian, Youyong Li*, Tingjun Hou*, Importance of Protein Flexibility in Ranking Inhibitor Affinities: Modeling the Binding Mechanisms of Piperidine Carboxamides as Type I1/2 ALK Inhibitors, Physical Chemistry Chemical Physics, 2015, 17, 6098-6113.
• Huiyong Sun, Peichen Pan, Sheng Tian, Lei Xu, Xiaotian Kong, Youyong Li, Dan Li, Tingjun Hou*, Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery, Scientific Reports, 2016, 6, 24817.

Education and Professional Experiences

• September 2006 – June 2010, Bachelor of Science in Life Sciences, College of Marine Life Sciences, Ocean University of China (Tutor: Baoqin Han)
• September 2006 – June 2013, Master of Science in Biophysics, School of Life Science and Technology, University of Electronic Science and Technology of China (Tutor: Chaoyi Li)
• September 2006 – December 2017, Doctor of Philosophy in Pharmacology, College of Pharmaceutical Sciences, Zhejiang University (Tutor: Tingjun Hou)
• March 2018 – March 2021, Postdoctoral/Assistant Researcher in College of Pharmaceutical Sciences, Zhejiang University (Co-supervisor: Tingjun Hou)

Research Interests

• I am working on computational toxicology and in silico ADME model development. The objective of my study is to propose novel and improved prediction models of drug toxicity and metabolism using various chemoinformatics and bioinformatics approaches. My further study is to develop computational models to interpret the mechanism of toxic actions.

Selected Publications

• Tailong Lei, Huiyong Sun, Yu Kang, Feng Zhu. Hui Liu, Wenfang Zhou, Zhe Wang, Dan Li, Youyong Li, Tingjun Hou*, ADMET evaluation in drug discovery. 18. Reliable prediction of chemical-induced urinary tract toxicity by boosting machine learning approaches. Molecular Pharmaceutics, 2017, 14, 3935-3953.
• Tailong Lei, Fu Chen, Hui Liu, Huiyong Sun, Yu Kang, Dan Li, Youyong Li, Tingjun Hou*, ADMET evaluation in drug discovery. 17. Development of quantitative and qualitative prediction models for chemical-induced respiratory toxicity. Molecular Pharmaceutics, 2017, 14, 2407-2421.
• Tailong Lei, Youyong Li, Yunlong Song; Dan Li, Huiyong Sun, Tingjun Hou. ADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modeling. J. Cheminformatics, 2016, 8, 1-6.

Education and Professional Experience

• 09.2009-06.2013: B. Sc., College of Plant Protection, Shandong Agricultural University, Taian, China
• 09.2013-06.2018: Ph. D., College of Science, China Agricultural University, Beijing, China
• 07.2018-12.2021: Postdoc, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
• 01.2022-present, Associate Professor, Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao, China

Selected Publications

• Xueping Hu, Jinping Pang, Jintu Zhang, Chao Shen, Xin Chai, Ercheng Wang, Haiyi Chen, Xuwen Wang, Mojie Duan, Weitao Fu, Lei Xu, Yu Kang, Dan Li*, Hongguang Xia*, Tingjun Hou*, Discovery of novel GR ligands towards druggable GR antagonist conformations identified by MD Simulations and Markov state model analysis, Advanced Science, 2022, 9, e2102435.
• Xueping Hu, Jinping Pang, Changwei Chen, Dejun Jiang, Chao Shen, Xin Chai, Liu Yang, Xujun Zhang, Lei Xu, Sunliang Cui, Tingjun Hou, Dan Li*, Discovery of novel non-steroidal selective glucocorticoid receptor modulators by structure- and IGN-based virtual screening, structural optimization, and biological evaluation, European Journal of Medicinal Chemistry, 2022, 237, 114382.
• Xueping Hu, Liu Yang, Xin Chai, Yixuan Lei, Md Shah Alam, Lu Liu, Chao Shen, Dejun Jiang, Zhe Wang, Zhiyong Liu, Lei Xu, Kanglin Wan, Tianyu Zhang, Yuelan Yin, Dongsheng Cao*, Dan Li*, Tingjun Hou*, Discovery of novel DprE1 inhibitors via computational bioactivity fingerprints and structure-based virtual screening, Acta Pharmacologica Sinica, 2021, in press.
• Xueping Hu, Xin Chai, Xuwen Wang, Mojie Duan, Jinping Pang, Weitao Fu, Dan Li*, Tingjun Hou*, Advances in the computational development of androgen receptor antagonists, Drug Discovery Today, 2020, 25, 1453-1461.
• Xueping Hu, Xiaojuan Ma, Jialin Cui, Haishan Liu, Bin Zhu, Jin Xie, Pei Liang, Li Zhang*, Identification of 1-phenyl-4-cyano-5-aminopyrazoles as novel ecdysone receptor ligands by virtual screening, structural optimization, and biological evaluations, Chemical Biology & Drug Design, 2021, 97, 184-195.

Research Interests

• Current research interests on (1) Enhanced sampling methodology and its applications, such as drug screening by combining enhanced sampling methods and molecular docking for important targets; (2) Simulations of co-translational protein folding using all-atom molecular dynamics.

Selected Publications

• Wang, E., Wang, J., Chen, C., et al. Computational evidence that fast translation speed can increase the probability of cotranslational protein folding. Scientific Reports, 2015, 5, 15316.
• Wang, E., Chen, C.,Wang, E., et al. Simulation study of the role of the ribosomal exit tunnel on protein folding. Physical Review E, 2013, 87, 022701.

Education and Professional Experiences

• 2008/9-2012/6: B.E., College of Pharmaceutical Sciences, Wenzhou Medical University (Supervisor: Liang Guang)
• 2012/9-2015/6: M.S., College of Pharmaceutical Sciences, Wenzhou Medical University (Supervisor: Liang Guang)
• 2015/10-2016/2: Research Assistant, College of Pharmaceutical, SciencesZhejiang University
• 2015/2-2019/4: PhD, College of Pharmaceutical Sciences, Zhejiang University (Supervisor: Prof. Hou Tingjun)
• 2019/7-present：Postdoc, College of Pharmaceutical Sciences, Zhejiang University (In cooperation with Prof. Tingjun Hou)

Research Interests

• I’m working on benchmark evaluation of different molecular docking approaches based on large-scale databases and development of combined strategies for structure-based virtual screening. The objective of my study is to propose improved protocols to overcome the challenges in docking and virtual screening, such as the bias of protein flexibility and the inaccurate prediction of binding affinity. Another research direction is to design and discover novel small molecule inhibitors against PD1/PD-L1 by using structure-based drug design techniques.

Selected Publications

• 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, Bioinformatics, 2019, 35, 1777–1779.
• Zhe Wang, Yu Kang, Dan Li, Huiyong Sun, Xiaowu Dong, Xiaojun Yao, Lei Xu, Shan Chang, Youyong Li, Tingjun Hou*, Benchmark Study Based on 2P2IDB to Gain Insights into the Discovery of Small-Molecule PPI Inhibitors. The Journal of Physical Chemistry B, 2018, 122, 2544-2555.
• Zhe Wang, Huiyong Sun, Xiaojun Yao, Dan Li, Lei Xu, Youyong Li, Sheng Tian and Tingjun Hou*, Comprehensive evaluation of ten docking programs on a diverse set of protein-ligand complexes: the prediction accuracy of sampling power and scoring power. Physical Chemistry Chemical Physics, 2016, 18, 12964-12975.

Research Interests

• I’m working on virtual screening for angiotensin II type 1 receptor.

Selected Publications

• Haiyi Chen, Yuxin Zhou, Xinyue Wang, Xin Chai, Zhe Wang, Ercheng Wang, Lei Xu, Tingjun Hou, Mojie Duan, Dan Li, Discovery of Novel Anti-resistance AR Antagonists Guided by Funnel Metadynamics Simulation, Advanced Science, 2024, 11, e2309261.
• Haiyi Chen, Yu Shi, Man Huang, Ting Lu, Huimin Zhang, Chun Zhou, Tingjun Hou, Youjun Feng, Recognition and acquisition of FakB2-loaded exogenous fatty acid (eFA) by a streptococcal FakA kinase, Science Bulletin, 2024, online.
• Haiyi Chen, Yu Kang, Mojie Duan*, Tingjun Hou*, Regulation Mechanism for the Binding between the SARS-CoV-2 Spike Protein and Host Angiotensin-Converting Enzyme II, The Journal of Physical Chemistry Letters, 2021, 12, 6252-6261.
• Yongchang Xu#, Haiyi Chen#, Huimin Zhang#, Saif Ullah#, Tingjun Hou, Youjun Feng, The MCR-3 inside linker appears as a facilitator of co listin resistance, Cell Reports, 2021, 35, 109135.

Research Interests

• Theoretical predictions of ADME/T and druggability; application the latest artificial intelligence algorithms, such as deep learning, in QSAR modeling and ADME/T prediction.

Selected Publications

• Dejun Jiang, Huiyong Sun, Jike Wang, Changyu Hsieh, Yuquan Li, Zhenxing Wu, Dongsheng Cao*, Jian Wu*, Tingjun Hou*, Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning, Briefings in Bioinformatics, 2022, 65, 10691-10706
• Dejun Jiang, Chang-Yu Hsieh, Zhenxing Wu, Yu Kang, Jike Wang, Ercheng Wang, Ben Liao, Chao Shen, Lei Xu, Jian Wu*, Dongsheng Cao*, Tingjun Hou*, InteractionGraphNet: a novel and efficient deep graph representation learning framework for accurate protein-ligand interaction predictions, Journal of Medicinal Chemistry, 2021, 64, 18209-18232
• Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng 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, Journal of Cheminformatics, 2021, 13, 12.

Research Interests

• Deep learning-enhanced free-energy calculations.

Selected Publications

• Huang, J.; Buratto, D.; Zhou, R. Probing the electrostatic aggregation of nanoparticles with oppositely charged molecular ions. Aggregate. 2023, 00, e324.

Education Experience

• 09.2008 to 06.2012: Soochow University, Life science college, Bachelor
• 09.2012 to 06.2012: Soochow University, Institute of Functional Nano and Soft Materials, Master
• 01.2016 to now: University of Queensland, Institute for molecular bioscience, PhD

Selected Publications

• Qian Zhang*, Riccardo E Marioni, Matthew R Robinson, Jon Higham, Duncan Sproul, Naomi R Wray, Ian J Deary, Allan F McRae, Peter M Visscher, Genotype effects contribute to variation in longitudinal methylome patterns in older people, Genome Medicine, 2018, 10, 75.
• Peter M Visscher*, Naomi R Wray, Qian Zhang, Pamela Sklar, Mark I. McCarthy, Matthew A. Brown, JianYang, 10 Years of GWAS Discovery: Biology, Function, and Translation, American Journal of Human Genetics, 2017, 6, 5-22.
• Qian Zhang, Wei Zhang, Youyong Li, Junmei Wang, Liling Zhang, Tingjun Hou*, A rule-based algorithm for automatic bond type perception, Journal of Cheminformatics, 2012, 4, 26.
• Qian Zhang, Junmei Wang, Ginés D Guerrero, José M Cecilia, José M García, Youyong Li, Horacio Pérez-Sánchez, Tingjun Hou*, Accelerated Conformational Entropy Calculations Using Graphic Processing Units, Journal of Chemical Information and Modeling, 2013, 53, 2057–2064.

Research Interests

• My research is focusing on the design and discovery of novel antagonists targeting androgen receptor by means of structure-based virtual screening and preclinical bioassays. In addition, I try to explore the resistance mechanism of androgen receptor antagonists via molecular modeling techniques.

Selected Publications

• Mojie Duan, Na Liu, Wenfang Zhou, Dan Li, Minghui Yang*, Tingjun Hou*, Structural diversity of ligand-binding androgen receptors revealed by microsecond long molecular dynamics simulations and enhanced sampling, Journal of Chemical Theory and Computation, 2016, 12, 4611-4619.

Research Interests

• The major objectives of my research are to reveal the resistance mechanisms of androgen receptor antagonists induced by amino acid mutations and structure-based virtual screening to discovery new small molecule inhibitors targeting androgen receptor for the treatment of prostate cancer. In addition, conventional molecular dynamics simulations and enhanced sampling are used to revealing how the allosteric inhibitors affect dimerization of HIF-2α/ARNT complex.

Research Interests

• I am working on the design and discovery of novel small molecule inhibitors targeting androgen receptor by structure-based virtual screening and preclinical bioassays.

Research Interests

• My research direction is to design inhibitors targeting kinases by using personalized and integrated virtual screening strategy, and analyze the structures and physicochemical properties of important virtual screening libraries.

Selected Publications

• Jun Shang, Ben Hu, Junmei Wang, Feng Zhu, Yu Kang, Dan Li, Huiyong Sun, De-Xin Kong, Tingjun Hou*, Cheminformatic Insight into the Differences between Terrestrial and Marine Originated Natural Products, Journal of Chemical Information and Modeling,  2018, online.
• Jun Shang, Huiyong Sun, Hui Liu, Fu Chen, Sheng Tian, Peichen Pan, Dan Li, Dexin Kong*, Tingjun Hou*, Comparative analyses of structural features and scaffold diversity for purchasable compound libraries, Journal of Cheminformatics,  2017, 9, 25.

Education and Professional Experiences

• 2007.09-2010.06: College of Pharmaceutical Sciences, Hunan University of Chinese Medicine Bachelor of Science
• 2011.09-2014.06: Key Laboratory of Modern Preparation of TCM, Ministry of Education, Jiangxi University of Traditional Chinese Medicine Master of Medicine (Advisor: Prof. Jian-Qun Liu)
• 2014.08-2018.07: State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences Ph.D. (Advisor: Prof. Wei-Lie Xiao)
• 2018.09-present: College of Pharmaceutical Sciences, Zhejiang University Postdoctor (In cooperation with Prof. Tingjun Hou)

Research Interests

• The drug design and discovery based on the interactions between natural products and important disease related targets.

Selected Publications

• Junbo Gao,Shuangjing Yang, Ziru Yan, et al. Isolation, Characterization, and the Structure-Activity Relationship Analysis of Abietane Diterpenoids from Callicarpa bodinieri as Spleen Tyrosine Kinase Inhibitors. Journal of natural products, 2018, 81, 998-1006.
• Junbo Gao, Xingjie Zhang, Ruihan Zhang，et al. In Vitro Human Dihydroorotate Dehydrogenase Inhibitory, Anti-inflammatory and Cytotoxic Activities of Alkaloids from the Seeds of Nigella glandulifera. Planta medica, 2018, 84, 1013-1021.

Education and Professional Experiences

• 2008/9-2012/6: B.E., College of Material Science and Engineering, China University of Technology and Mining, Xuzhou, China
• 2012/9-2015/6: M.S., College of Material Science and Engineering, South China University of Technology, Guangzhou, China. (Supervisor: Prof. Haohao HUANG)
• 2015/2-2019/4: PhD, Laboratoire de Physiques des Solides, Université Paris-Sacalay, France. (Supervisor: Prof. Guillaume TRESSET & Prof. Yevs LANSAC)
• 2020/7-now：Postdoc, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. (In cooperation with Prof. Tingjun Hou)

Research Interests

• (1)Assessing the performance of structure-based drug design methods on GPCRs. (2)Insight into the constitutive activity of melanocortin-4 receptor (MC4R), and developing MC4R agonists.

Selected Publications

• Chen, J., Chevreuil, M., Combet, S., Lansac, Y., & Tresset, G. (2017). Investigating the thermal dissociation of viral capsid by lattice model, Journal of Physics: Condensed Matter, 29(47), 474001.
• Chen, J., Lansac, Y., & Tresset, G. (2018). Interactions between the Molecular Components of the Cowpea Chlorotic Mottle Virus Investigated by Molecular Dynamics Simulations, The Journal of Physical Chemistry B, 122(41), 9490-9498.

Education and Professional Experiences

• 2010/9-2014/6: B.E., College of Chemistry and Chemical Engineering, Lanzhou University
• 2014/9-2020/6: PhD., College of Chemistry and Chemical Engineering, Lanzhou University (Supervisor: Xiaojun Yao)
• 2015/12-2020/6: Visiting Student, College of Pharmaceutical Sciences, Zhejiang University, Co-supervised with Prof. Tingjun Hou
• 2020/7-present：Postdoc, College of Pharmaceutical Sciences, Zhejiang University (In cooperation with Prof. Tingjun Hou

Research Interests

• I am working on the design and discovery of novel small molecule inhibitors targeting BRD4 by using structure-based drug design techniques.

Selected Publications

• Haiyang Zhong, Zhe Wang, Xuwen Wang, Hui Liu, Dan Li, Huanxiang Liu, Xiaojun Yao* and Tingjun Hou*, Importance of crystalline water network in docking-based virtual screening: a case study of BRD4, Physical Chemistry Chemical Physics, 2019,21, 25276-25289.

Education and Professional Experiences

• 2010/9-2014/6: B.E., School of Physics and Electricity, Shandong Normal University
• 2014/9-2020/6: PhD., East China Normal University, State Key Laboratory of Precision Spectral Science and Technology, Master and PhD (supervisor: Professor Zhang Zenghui)
• 2020/7-present：Postdoc, College of Pharmaceutical Sciences, Zhejiang University (In cooperation with Prof. Tingjun Hou

Research Interests

• Molecular dynamics simulation of metalloprotein and ligand systems and development of polarization field.

Selected Publications

• Shuaizhen Tian, Jinzhe Zeng, XiaoLiu, John Z.H. Zhang and Tong Zhu. Understanding the selectivity of inhibitors toward PI4KIIIα and PI4KIIIβ based molecular modeling, Physical Chemistry Chemical Physics, 2019, 21, 22103-22112.

Education and Professional Experiences

• 2010/9-2014/6: B.S., College of Chemistry, Sichuan University
• 2014/9-2019/6: Ph.D., State Key Laboratory of Precision Spectral Science and Technology, East China Normal University (supervisor: Professor Zenghui Zhang)
• 2021/8-present: Postdoc, College of Pharmaceutical Sciences, Zhejiang University (In cooperation with Professor Tingjun Hou)

Research Interests

• In silico drug design and structure-based drug discovery.

Selected Publications

• Dading Huang, Yifei Qi, Jianing Song, and John Z.H. Zhang, Calculation of hot spots for protein-protein interaction in p53/PMI-MDM2/MDMX complexes., J. Comput. Chem., 2019, 40, 1045-1056.

Research Interests

• I am working on the drug discovery and design based on some important targets, aiming to discover and design novel leading compounds against the key targets relevant to cancers and other diseases by using an integrated computer aided drug design protocol and a series of biological experiments.

Selected Publications

• Xuwen Wang, Peichen Pan, Youyong Li, Dan Li, Tingjun Hou*, Exploring the prominent performance of CX-4945 derivatives as protein kinase CK2 inhibitors by a combined computational study, Molecular BioSystems, 2014, 10, 1196-1210.

Research Interests

• My research direction is the development and application of structure-based virtual screening approaches based on flexible targets.

Selected Publications

• Gaoqi Weng, Xuanyan Cai, Dongsheng Cao, Hongyan Du, Chao Shen, Yafeng Deng, Qiaojun He, Bo Yang, Dan Li*, Tingjun Hou*, PROTAC-DB 2.0: an updated database of PROTACs, Nucleic Acids Research, 2022, in press.
• Gaoqi Weng, Dan Li, Yu Kang*, Tingjun Hou*, Integrative modeling of PROTAC-mediated ternary complexes, Journal of Medicinal Chemistry, 2021, 64, 16271-16281.
• 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 Research, 2019, 47, W322-W330.

Research Interests

• I am working on Computer aided drug design

Selected Publications

• Tianli Xie, Jie Yu, Weitao Fu, Zhe Wang, Lei Xu, Shan Chang, Ercheng Wang, Feng Zhu, Su Zeng, Yu Kang*, Tingjun Hou*, Insight into the selective binding mechanism of DNMT1 and DNMT3A inhibitors: a molecular simulation study, Physical Chemistry Chemical Physics, 2019, accepted.
• Jie Yu, Tianli Xie, Zhe Wang, Xuwen Wang, Su Zeng, Yu Kang*, Tingjun Hou*, DNA Methyltransferases: Emerging Targets for the Discovery of Inhibitors as Potent Anticancer Drugs, Drug Discovery Today, 2019, accept.

Research Interests

• Drug screening and target discovery based on multi-modal biomedical knowledge.

Selected Publications

• Qing Ye, Ruolan Xu, Dan Li, Yu Kang, Yafeng Deng, Feng Zhu, Jiming Chen*, Shibo He, Chang-Yu Hsieh*, Tingjun Hou*, Integrating multi-modal deep learning on knowledge graph for the discovery of synergistic drug combinations against infectious diseases, Cell Reports Physical Science, 2023, 8, 101520.
• Qing Ye, Chang-Yu Hsieh, Ziyi Yang, Yu Kang, Jiming Chen, Dongsheng Cao*, Shibo He*, Tingjun Hou*, A unified drug-target interaction prediction framework based on knowledge graph and recommendation system, Nature Communications, 2021, 12, 6775.
• Qing Ye, Xin Chai, Dejun Jiang, Liu Yang, Chao Shen, Xujun Zhang, Dan Li*, Dongsheng Cao*, Tingjun Hou*, Identification of Active Molecules against Mycobacterium Tuberculosis through Machine Learning, Briefings in Bioinformatics, 2021, 22, bbab068.