William J Welsh , Ph.D.

Professor in Bioinformatics and Molecular Design Rutgers UniversityEOHSI – Environmental and Population Health Bio-Sciences
Work Phone: 732-235-3234
Photo of William J Welsh Ph.D.


Research Areas

Dr. Welsh’s laboratory specializes in the development and application of computational tools for pharmaceutical drug discovery, predictive toxicology, and multi-dimensional pattern recognition. His laboratory’s interests extend to the molecular design and modeling of synthetic polymers, protein-material interactions, and protein-ligand interactions. In recent years, his laboratory has participated in the discovery of potential drug candidates for the treatment cancer, severe and chronic pain, and infectious diseases.

Research Highlights

Implemented the Shape Signatures tool for applications relevant to computational toxicology; major accomplishments achieved include:

  1. Development of shape-based regression and classification models to predict inhibitors of acetylcholine esterase;
  2. Development of shape-based classification models to predict ligands to the human Ether-a-go-go gene (hERG) and the humanhydroxytryptophan 2b (5HT2b) receptor, both of which are associated with cardiotoxicity;
  3. Development of shape-based classification models to predict ligand blood-brain barrier (BBB) permeability, which is a prerequisite for CNS activity

Employed molecular modeling approaches to delineate and visualize how human ADA3 regulates the transcriptional activity of RAR(alpha) through direct interaction between LxxLL motifs and the receptor coactivator pocket.
Developed shape-based prioritization and classification approaches to predict human pregnane x receptor activators.
Identified and characterized a binding site for small-molecule PXR antagonists that interact on the outer surface of PXR at the AF-2 domain; major accomplishments achieved include:

  1. Development of a pharmacophore that describes the structural requirements for these PXR antagonists
  2. Computational prediction, and in vitro confirmation, of several low-micromolar PXR antagonists that target this binding site at the AF-2 domain.
  3. Development of a three-dimensional structural model of the PXR.2, the major human PXR splice variant that demonstrates reduced ligand-activated transcriptional activation compared with the wild-type PXR.1.

Using microarray techniques to characterize gene expression profiles predictive of monomethylarsonous acid (MMA(III)) exposure and mode of action of carcinogenesis, we observed increases in transcript abundance of Fosl1, Myc, and Rac1 oncogenes in mouse skin. The results support previous findings of the inducibility of these oncogenes in response to arsenic and support the relevance of these genomic changes in skin tumor induction in the K6/ODC mouse model.

Scholarly Activities

  • Served as an external consultant for the US EPA in preparing instructional materials for the agency’s training program “New Developments in Computational Methods for Risk Assessment” (Sept-Dec 2010).
  • Presented seminar on the topic “Computational Models for Risk Assessment” at the Molecular Operating Environment (MOE) software workshop, located in Monmouth Junction, NJ (October 2010).
  • Presented invited seminar entitled “Chemometric Models to Discriminate USP-grade Heparin from Impure and Contaminated Heparin” at the American Association of Pharmaceutical Scientists meeting in New Orleans, LA (November 15, 2010).
  • Presented invited seminar entitled “Novel Designs of Autophagy Inhibitors as Anticancer Drugs” at the UMDNJ-RWJMS Cancer Institute of New Jersey (November 29, 2010).
  • Presented invited seminar at the U.S. Army Telemedicine and Advanced Technology Research Center (TATRC) Program Review at the Center for Biomaterials Research, Rutgers University, on December 15, 2010.
  • Contributed a talk entitled “Computational Approaches to Accelerate the Discovery of Medical Countermeasures Against Select Agents” at the US DoD Defense Threat Reduction Agency (DTRA) Program Review held in College Station TX on January 10-13, 2011.
  • Presented an invited seminar entitled “Rational Computer-Aided Design of Drugs to Combat Biowarfare Agents” at the New York Center for Structural Biology in New York City on January 21, 2011.
  • Presented an invited seminar entitled “Accelerating Drug Discovery” at the University of Cincinnati Medical Center, Cincinnati OH on February 22, 2011.
  • Presented an invited seminar entitled “Novel Computational Approaches to Accelerate Drug Discovery” at Kean University in New Jersey on March 2, 2011.

Recent Publication

  1. Zhang, VY, O’Connor, SL, Welsh, WJ, James, MH. Machine learning models to predict ligand binding affinity for the orexin 1 receptor. Artif Intell Chem. 2024;2 (1):. doi: 10.1016/j.aichem.2023.100040. PubMed PMID:38476266 PubMed Central PMC10927255
  2. Knowles, LG, Armanious, AJ, Peng, Y, Welsh, WJ, James, MH. Recent advances in drug discovery efforts targeting the sigma 1 receptor system: Implications for novel medications designed to reduce excessive drug and food seeking. Addict Neurosci. 2023;8 :. doi: 10.1016/j.addicn.2023.100126. PubMed PMID:37753198 PubMed Central PMC10519676
  3. Yu, Y, Dong, H, Peng, Y, Welsh, WJ. QSAR-Based Computational Approaches to Accelerate the Discovery of Sigma-2 Receptor (S2R) Ligands as Therapeutic Drugs. Molecules. 2021;26 (17):. doi: 10.3390/molecules26175270. PubMed PMID:34500703 PubMed Central PMC8434483
  4. Peng, Y, Zhang, Q, Welsh, WJ. Novel Sigma 1 Receptor Antagonists as Potential Therapeutics for Pain Management. J Med Chem. 2021;64 (1):890-904. doi: 10.1021/acs.jmedchem.0c01964. PubMed PMID:33372782
  5. Peng, Y, Zhang, Q, Zielinski, RM, Howells, RD, Welsh, WJ. Identification of an irreversible PPARγ antagonist with potent anticancer activity. Pharmacol Res Perspect. 2020;8 (6):e00693. doi: 10.1002/prp2.693. PubMed PMID:33280279 PubMed Central PMC7719157
  6. Peng, Y, Dong, H, Welsh, WJ. Comprehensive 3D-QSAR Model Predicts Binding Affinity of Structurally Diverse Sigma 1 Receptor Ligands. J Chem Inf Model. 2019;59 (1):486-497. doi: 10.1021/acs.jcim.8b00521. PubMed PMID:30497261
  7. Kang, JS, Zhang, AL, Faheem, M, Zhang, CJ, Ai, N, Buynak, JD, Welsh, WJ, Oelschlaeger, P. Virtual Screening and Experimental Testing of B1 Metallo-β-lactamase Inhibitors. J Chem Inf Model. 2018;58 (9):1902-1914. doi: 10.1021/acs.jcim.8b00133. PubMed PMID:30107123 PubMed Central PMC6527342
  8. Kimani, SG, Kumar, S, Bansal, N, Singh, K, Kholodovych, V, Comollo, T, Peng, Y, Kotenko, SV, Sarafianos, SG, Bertino, JR et al.. Small molecule inhibitors block Gas6-inducible TAM activation and tumorigenicity. Sci Rep. 2017;7 :43908. doi: 10.1038/srep43908. PubMed PMID:28272423 PubMed Central PMC5341070
  9. Ai, N, Wood, RD, Yang, E, Welsh, WJ. Niclosamide is a Negative Allosteric Modulator of Group I Metabotropic Glutamate Receptors: Implications for Neuropathic Pain. Pharm Res. 2016;33 (12):3044-3056. doi: 10.1007/s11095-016-2027-9. PubMed PMID:27631130
  10. Groen, N, Guvendiren, M, Rabitz, H, Welsh, WJ, Kohn, J, de Boer, J. Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering. Acta Biomater. 2016;34 :133-142. doi: 10.1016/j.actbio.2016.02.015. PubMed PMID:26876875 PubMed Central PMC4830461
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