Dr. Lirong Wang is an Assistant Professor of Pharmaceutical Sciences, Scientific Administrator of Computational Chemical Genomics Screening (CCGS) Center (http://www.cbligand.org/CCGS/), School of Pharmacy.

Dr. Wang obtained his PhD degree from University of Science and Technology of China in 2007. He then received postdoctoral training in Dr. Xiang-Qun Xie group at the School of Pharmacy, University of Pittsburgh.

His research mainly focuses on chemogenomics/chemoinformatics algorithm and online tools development. He is the author or coauthor of more than 50 journal articles and he has designed a lot of online tools of chemogenomics/chemoinformatics, such as TargetHunter, BBB Predictor and HTDocking.

Dr. Wang is the (M)PI of R01 R01MH116046,  and has or had been a co-investigator or key personal in the NIH funded projects P30 PDA035778A, R01 NLM 015417, R01 DA025612, NIGMP50 UPCMLD project and NCI UP-CDC project. Dr. Wang has served as ad hoc reviewer for AAPS Journal, JCIM, Bioinformatics, JMC, Journal of Cheminformatics.

Target identification, chemogenomics/chemoinformatics database,  structure-based and ligand-based drug design, bioinformatics database, signaling pathway, data mining & machine learning algorithms on diseases like drug abuse, Alzheimer's Disease, TBI, and psychosis.  

1. Lirong Wang*, Shifan Ma*, Ziheng Hu, Terence Francis McGuire, and Xiang-Qun Xie, “Chemogenomics Systems Pharmacology Mapping of Potential Drug Targets for Treatment of Traumatic Brain Injury” Journal of neurotrauma, in press
2. Yuemin Bian, Xibing He, Yankang Jing, Lirong Wang, Junmei Wang, Xiang-Qun Xie, “Computational systems pharmacology analysis of cannabidiol: a combination of chemogenomics-knowledgebase network analysis and integrated in silico modeling and simulation” Acta Pharmacologica Sinica, in press
3. Jing Y, Bian Y, Hu Z, Wang L, Xie XS. “Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era”. AAPS J. 2018 Mar 30;20(3):58. doi: 10.1208/s12248-018-0210-0.
4. Nanyi Wang, Lirong Wang# and Xiang-Qun Xie#, “ProSelection: A novel algorithm to select proper protein structure subsets for in silico target identification and drug discovery research” J Chem Inf Model. 2017 Nov 27;57(11):2686-2698. doi: 10.1021/acs.jcim.7b00277. Epub 2017 Oct 26.
5. Yu Zhang* Lirong Wang*, Haizi Cheng, Yahui Ding, Zhiwei Feng, Tao Cheng, Yingdai Gao and Xiang-Qun Xie* “StemCellCKB: An Integrated Stem Cell-Specific Chemogenomics Knowledge Base for Target Identification and Systems-Pharmacology Research” J. Chem. Inf. Model., 2016, 56 (10), pp 1995–2004
6. Xiaomeng Xu, Shifan Ma, Zhiwei Feng, Guanxing Hu, Lirong Wang#, and Xiang-Qun Xie# “Chemogenomics Knowledgebase and Systems Pharmacology for Hallucinogen Target Identification - Salvinorin A as a Case Study” J MOL GRAPH MODEL , Volume 70, November 2016, Pages 284–295
7. Hai Zhang, Shifan Ma, Zhiwei Feng, Dongyao Wang, Chengjian Li, Yan Cao, Xiaofei Chen, Aijun Liu, Zhenyu Zhu, Junping Zhang, Guoqing Zhang, Yifeng Chai#, Lirong Wang#, and Xiang-Qun Xie# “Disease-Specific Chemogenomics Knowledgebase-Guided Systems Pharmacology Approach for Target Identification and Drug Synergy and Antagonism Mechanism Study of A Combinational Herbal Formulations” Sci Rep. 2016 Sep 28;6:33963. doi: 10.1038/srep33963.
8. Jianping Hu, Ziheng Hu, Yan Zhang, Xiaojun Gou, Ying Mu, Lirong Wang# and Xiang-Qun Xie# “Metal binding mediated conformational change of XPA protein:a potential cytotoxic mechanism of Nickel in the nucleotide excision repair” J Mol Model. 2016 Jul;22(7):156. doi: 10.1007/s00894-016-3017-x. Epub 2016 Jun 16.
9. Xiang-Qun Xie#*, Lirong Wang*, Junmei Wang*, Zhaojun Xie, Peng Yang, Qin Ouyang “In Silico Chemogenomics Knowledgebase and Computational System Neuropharmacology Approach for Cannabinoid Drug Research” DOI: 10.1016/B978-0-12-800634-4.00019-6 Chapter in book: Neuropathology of Drug Addictions and Substance Misuse, pp.183-195
10. Zhang Z, Li HM, Zhou C, Li Q, Ma L, Zhang Z, Sun Y, Wang L, Zhang X, Zhu B, Hong YS, Wu CZ, Liu H. “Non-benzoquinone geldanamycin analogs trigger various forms of death in human breast cancer cells” J Exp Clin Cancer Res. 2016 Sep 22;35(1):149.
11. Zhou A, Hu J, Wang L, Zhong G, Pan J, Wu Z, Hui A “Combined 3D-QSAR, molecular docking, and molecular dynamics study of tacrine derivatives as potential acetylcholinesterase (AChE) inhibitors of Alzheimer's disease” J Mol Model. 2015 Oct;21(10):277. doi: 10.1007/s00894-015-2797-8. Epub 2015 Oct 5.
12. Yingdai Gao, Peng Yang, Hongmei Shen, Hui Yu, Xianmin Song, Liyan Zhang, Peng Zhang, Haizi Cheng, Zhaojun Xie, Sha Hao, Yahui Ding, Lirong Wang, Haibin Liu, Yanxin Li, Hui Cheng, Weimin Miao, Weiping Yuan, Youzhong Yuan, Tao Cheng, Xiang-Qun Xie “Small-molecule inhibitors targeting INK4 protein p18 INK4C enhance ex vivo expansion of haematopoietic stem cells”, 2015, Nature Communications 02/2015; 6. DOI: 10.1038/ncomms7328
13. Qin Ouyang*, Lirong Wang*, Ying Mu and Xiang-Qun Xie “Modeling Skin Sensitization Potential of Mechanistically Hard-to-be-Classified Aniline and Phenol Compounds with Quantum Mechanistic Properties”, BMC Pharmacology and Toxicology 2014.
14. Rentian Feng, Qin Tong, Zhaojun Xie, Lirong Wang, Suzanne Lentzsch, G. David Roodman, Charles Sfeir, and Xiang-Qun Xie, “Targeting Cannabinoid Receptor-2 Pathway by Phenylacetylamide Suppresses the Proliferation of Human Myeloma Cells Through Mitotic Dysregulation and Cytoskeleton Disruption” Mol Carcinog. 2015 Dec;54(12):1796-806. doi: 10.1002/mc.22251. Epub 2015 Jan 16.
15. Feng, Z., M. H. Alqarni, P. Yang, Q. Tong, A. Chowdhury, L. Wang and X.-Q. Xie (2014). "Modeling, Molecular Dynamics Simulation and Mutation Validation for Structure of Cannabinoid Receptor 2 Based on Known Crystal Structures of GPCRs." J. Chem. Inf. Model., 2014, 54 (9), pp 2483–2499
16. Liu, Haibin; Wang, Lirong; Su, Weiwei and Xiang-Qun Xie. (2014) Advances in recent patent and clinical trial drug development for Alzheimer's disease. Pharm Pat Anal 3:429-47
17. Cai Z, Ouyang Q, Zeng D, Nguyen KN, Modi J, Wang L, White AG, Rogers BE, Xie XQ, Anderson CJ, “64Cu-labeled somatostatin analogues conjugated with cross-bridged phosphonate-based chelators via strain-promoted click chemistry for PET imaging: in silico through in vivo studies.” J Med Chem. 2014 Jul 24;57(14):6019-29. doi: 10.1021/jm500416f. Epub 2014 Jul 11.
18. Shujing Sheng*, Jinxu Wang*, Lirong Wang*, Hong Liu, Peibo Li, Menghua Liu, Chaofeng Long, Chengshi Xie, Xiangqun Xie, Weiwei Su, “Network pharmacology Analyses of the Antithrombotic pharmacological mechanism of Fufang Xueshuantong capsule with experimental support using disseminated intravascular coagulation rats.” Journal of ethnopharmacology. 05/2014; DOI:10.1016/j.jep.2014.04.048(*these authors contributed equally).
19. Liu H*, Wang L*, Lv M, Pei R, Li P, Pei Z, Wang Y, Su W, Xie X-Q “AlzPlatform: An Alzheimer's Disease Domain-specific Chemogenomics Knowledgebase for Polypharmacology and Target Identification Research”. Journal of Chemical Information and Modeling, DOI: 10.1021/ci500004h
Publication Date (Web): March 5, 2014 (*these authors contributed equally).
20. Lirong Wang, Xiang-Qun Xie "Computational target fishing: what should chemogenomics researchers expect for the future of in silico drug design and discovery?" Future Medicinal Chemistry, March 2014, Vol. 6, No. 3, Pages 247-249.
21. Xiang-Qun Xie, Lirong Wang, Haibin Liu, Qin Ouyang, Cheng Fang, Weiwei Su “Chemogenomics knowledgebased polypharmacology analyses of drug abuse related G-protein coupled receptors and their ligands”. Frontiers in Pharmacology 2014; 5:3. DOI:10.3389/fphar.2014.00003
22. Haibin Liu, Fengyin Liang,Weiwei Su,Ning Wang,Mingliang Lv,Peibo Li,Zhong Pei,Yan Zhang,Xiang-Qun Xie,Lirong Wang,Yonggang Wang, “Lifespan extension by n-butanol extract from seed of Platycladus orientalis in Caenorhabditis elegans”, J Ethnopharmacol. 2013 May 20;147(2):366-72. doi: 10.1016/j.jep.2013.03.019. Epub 2013 Mar 21.PMID: 23523941
23. Matthew LaPorte , Sammi Tsegay , Ki Bum Hong , Chunliang Lu , Cheng Fang , Lirong Wang , Xiang-qun (Sean) Xie , and Paul E. Floreancig “Construction of a Spirooxindole Amide Library through Nitrile Hydrozirconation-Acylation-Cyclization Cascade”. ACS Comb Sci. 2013 Jun 3(accepted) PMID:23731121
24. Yang P, Wang L, Feng R, Almehizia AA, Tong Q, Myint KZ, Ouyang Q, Alqarni MH, Wang L, Xie XQ. “Novel Triaryl Sulfonamide Derivatives as Selective Cannabinoid Receptor 2 Inverse Agonist and Osteoclast Inhibitor: Discovery, Optimization and Biological Evaluation.” J Med Chem. 2013 Mar 14;56(5):2045-58. doi: 10.1021/jm3017464. Epub 2013 Mar 1. PMID: 23406429
25. Ma C*, Wang L*, Yang P, Tong Q, Myint KZ, and Xie XQ. “LiCABEDS II. Modeling of Ligand Selectivity for G-protein Coupled Cannabinoid Receptors”, J Chem Inf Model. 2013 Jan 28;53(1):11-26. doi: 10.1021/ci3003914. Epub 2013 Jan 15 (*these authors contributed equally) PMID: 23278450
26. Lirong Wang, Chao Ma, Peter Wipf, Haibin Liu, Weiwei Su and Xiang-Qun Xie. “TargetHunter: An In Silico Target Identification Tool for Predicting Therapeutic Potential of Small Organic Molecules Based on Chemogenomic Database”. AAPS J. 2013 Apr;15(2):395-406. doi: 10.1208/s12248-012-9449-z. Epub 2013 Jan 5. PMID:23292636
27. Manuj Tandon*, Lirong Wang*, Qi Xu, Xiang-Qun Xie, Peter Wipf* and Q. Jane Wang*. “A Targeted Library Screen Reveals a New Selective Inhibitor Scaffold for Protein Kinase D”. Plos One 2012;7(9):e44653. doi: 10.1371/journal.pone.0044653 (*these authors contributed equally) PMID: 23028574
28. Yang P, Myint KZ, Tong Q, Feng R, Cao H, Almehizia AA, Hamed AM, Wang L, Bartlow P, Gao Y, Gertsch J, Teramachi J, Kurihara N, Roodman GD, Cheng T, Xie XQ. “Lead Discovery, Chemistry Optimization and Biological Evaluation Studies of Novel Bi-amide Derivatives as CB2 Receptor Inverse Agonists and Osteoclast Inhibitors.” J Med Chem. 2012 Nov 26;55(22):9973-87. doi: 10.1021/jm301212u. Epub 2012 Oct 31. PMID: 23072339
29. Kay M. Brummond, John Goodell, Matthew LaPorte, Lirong Wang and Xiang-Qun Xie. “Synthesis and In Silico Screening of a Library of Carboline-Containing Compounds”. Beilstein J. Org. Chem. 2012, 8, 1048–1058. PMID:23019432
30. Kyaw-Zeyar Myint, Lirong Wang, Qin Tong and Xiang-Qun Xie. “Fingerprint-based Artificial Neural Networks QSAR (FANN-QSAR) for Ligand Biological Activity Predictions”. Mol. Pharm. 2012, 9(10):2912-23. PMID: 22937990
31. Ajay Srinivasan, Lirong Wang, Cari J. Cline,Zhaojun Xie,Robert W. Sobol, Xiang-Qun Xie and Barry Gold. “Identification and characterization of human apurinic/apyrimidinic endonuclease-1 inhibitors”. Biochemistry, 2012, 51 (31), pp 6246–6259. PMID: 22788932
32. Peng Yang, Lirong Wang and Xiang-Qun Xie. Latest advances in novel cannabinoid CB2 ligands for drug abuse and their therapeutic potential. Future 2012, 4(2):187-204.
33. Lirong Wang*, Chao Ma* and Xiang-Qun Xie. “Linear and Non-linear Support Vector Machine for the Classification of Human 5-HT1A Ligand Functionality”, Molecular Informatics, 2012. 31(1): p. 85-95.
34. Yuxun Zhang, Zhaojun Xie, Lirong Wang, Brielle Schreiter, John S Lazo, Jurg Gertsch, Xiang-Qun Xie. “Mutagenesis and computer modeling studies of a GPCR conserved residue W5.43(194) in ligand recognition and signal transduction for CB2 receptor”, Int Immunopharmacol. 11( 9), Sep. 2011, 1303–1310
35. Kyaw Myint, Chao Ma, Lirong Wang and Xiang-Qun Xie. “Fragment-based QSAR Algorithm Development for Compound Bioactivity Prediction”, SAR QSAR Environ Res. 2011 Jun;22(3):385-410
36. Chao Ma, Lirong Wang and Xiang-Qun Xie. “GPU Accelerated Chemical Similarity Calculation for Compound Library Comparison”, J. Chem. Inf. Model., Publication Date (Web): June 21, 2011
37. Thomas O. Painter, Lirong Wang, Supriyo Majumder, Xiang-Qun Xie and Kay M. Brummond. “Diverging DOS Strategy Using an Allene-Containing Tryptophan Scaffold and a Library Design that Maximizes Biologically Relevant Chemical Space While Minimizing the Number of Compounds”, ACS Comb Sci. 2011 Mar 14;13(2):166-74
38. Chao Ma, Lirong Wang and Xiang-Qun Xie. “Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps (LiCABEDS) and Its Application on Modeling Ligand Functionality for 5HT-Subtype GPCR Families”, J Chem Inf Model. 2011 Mar 28;51(3):521-31.
39. Lirong Wang, Zhaojun Xie, Peter Wipf and Xiang-Qun Xie. “Residue Preference Mapping of Ligand Fragments in PDB”, J Chem Inf Model. 25;51(4):807-15. Epub 2011 Mar 18.
40. Wenlong Xu, Minghui Wang, Xianghua Zhang, Lirong Wang and Huanqing Feng. “SDED: A novel filter method for cancer-related gene selection”, Bioinformation 2008, 2, (7), 301-3.
41. Lirong Wang, Zhaohui Jiang, Wenlong Xu and Huanqing Feng. “Analysis of Abnormal Transcription Factors and Pathways from Gastric Cancer Chips”, Journal of University of Science and Technology of China 2007, 12, 1539-04(in Chinese)
42. Minghui Wang, Lirong Wang, Wenlong Xu, Xiaojun Lin, Zhaohui Jiang and Huanqing Feng “Phosphorylation Site Prediction Based on K-Nearest Neighbor Algorithm and BLOSUM62 Matrix ”, Chinese Journal of Biomedical Engineering 2007, 26, 404-408 (in Chinese)
43. Yu Xue, Ao Li, Lirong Wang, Huanqing Feng and Xuebiao Yao. “PPSP: prediction of PK-specific phosphorylation site with Bayesian decision theory”, BMC Bioinformatics 2006, 7, 163.
44. Lirong Wang and Huanqing Feng. “Mining Biomedical Literature Based on Bayesian Statistics”, Chinese Journal of Biomedical Engineering 2006, 25, 438-441(in Chinese)

NIH 1R01MH116046-01A1 (Sweet, Kofler and Wang ) 09/25/2018-06/30/2023
Individuals who develop psychotic symptoms such as delusions or hallucinations during Alzheimer disease have a more rapid deterioration and worse outcomes. In this grant we will evaluate whether compensations in the proteins present in brain synapses confer resilience to psychosis onset during Alzheimer disease, and whether genetic factors associated with resilience to psychosis in Alzheimer disease induce similar, protective compensations in an animal model. Finally, we will use the profile of protein compensation to identify novel medications that may treat and/or prevent psychosis in Alzheimer disease.
My role in this project: PI(multiple PI)

DOD W81XWH-16-1-049 (Xie, PI) 09/01/2016-08/30/19
Chemogenomics Systems Pharmacology Approach for TBI and AD Research
Military personnel and other individuals who suffer from traumatic brain injury (TBI) face an increased risk for developing several long-term health problems including AD-like dementia, aggression, memory loss, depression, and symptoms similar to those of AD. We plan to apply computational approaches, animal models and clinical data analysis to find the mechanisms that cause TBI to lead to AD.
My role in this project: Co-Investigator

NIDA P30 PDA035778A (Xie, PI) 07/01/2014-06/30/19
NIDA Core “Center of Excellence” grant program
The overall goal of the Computational Drug Abuse Research (CDAR) Center is to advance state-of-the art computational technologies for research toward the prevention and treatment of drug abuse (DA).
My role in this project: Co-Investigator and core-coordinator