Alex Tropsha, Ph.D., is an expert in the fields of computational chemistry, cheminformatics and structural bioinformatics who works to develop new methodologies and software tools for computer-assisted drug design. He is creating new approaches to protein 3D structure analysis and prediction based on the principles of statistical geometry. His particular expertise lies in the field of cheminformatics, a discipline where information and informatics methodologies are applied to storing, managing, exploring and exploiting chemical databases. In layman’s terms, cheminformatics combines chemistry and computer science to aid in the discovery of new drugs.
Tropsha has authored more than 190 peer-reviewed papers and 20 books and book chapters. He joined the School’s faculty in 1991 as an assistant professor and director of the Laboratory for Molecular Modeling. He was promoted to associate professor in 1997 and to full professor in 2004 and holds appointments as an adjunct professor in the UNC Department of Biomedical Engineering and in the Department of Computer Science and is a member of the UNC Lineberger Comprehensive Cancer Center. He was named as the K. H. Lee Distinguished Professor in 2008.
As associate dean for pharmacoinformatics and data science, Tropsha serves as the chief informatics officer in the School and provides oversight and strategic direction for the research and training programs in data-rich areas of pharmaceutical sciences.
Ivan Rusyn, Fred Wright, Bryan Roth
Early stages in modern drug discovery often involve screening small molecules for their effects on a selected protein target or a model of a biological pathway. In the past fifteen years, innovative technologies that enable rapid synthesis and high throughput screening of large libraries of compounds have been adopted in almost all major pharmaceutical and biotech companies and have also proliferated to academia leading to the unprecedented growth of available databases of biologically active compounds. Managing, understanding, analyzing and exploiting this data to enable rational design of new experiments requires skills and computational tools.
Tropsha’s Laboratory for Molecular Modeling conducts studies in the broad areas of computer-assisted drug design, cheminformatics and structural bioinformatics. The lab is generally interested in understanding the relationship between biomolecular structure and its function.
The lab is poised to develop
- novel descriptors to characterize complex molecules,
- novel techniques to analyze screening data,
- novel biologically relevant diversity/similarity measures,
- novel tools for virtual screening of compound libraries and the design of novel compound and libraries with high expected hit rates, and
- novel protocols for large scale cheminformatics computing and dissemination of the tools and target property predictors
Education, Certification and Licensure
PhD, biochemistry and pharmacology
Moscow State University
Advisor: Prof Lev S. Yaguzhinski
Thesis: Quantitative Structure-Activity Relationships for Muscarinic and Nicotinic Agonists and Antagonists
Moscow State University
- Isayev, O., Fourches, D., Muratov, E,N,. Oses, C., Rasch K.M., Tropsha, A.*, and Curtarolo, S.* Chem. Mater., 2015, In press. DOI: 10.1021/cm503507h
- Alves VM, Muratov E, Fourches D, Strickland J, Kleinstreuer N, Andrade CH, Tropsha A.* Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds. Toxicol Appl Pharmacol. 2015 Jan 3. doi: 10.1016/j.taap.2014.12.014. [Epub ahead of print].
- Alves VM, Muratov E, Fourches D, Strickland J, Kleinstreuer N, Andrade CH, Tropsha A.* Predicting chemically-induced skin reactions. Part II. QSAR models of skin permeability and the relationships between skin permeability and skin sensitization. Toxicol Appl Pharmacol. 2015 Jan 3. doi: 10.1016/j.taap.2014.12.013. [Epub ahead of print]
- Fourches D, Politi R, Tropsha A.* Target-Specific Native/Decoy Pose Classifier Improves the Accuracy of Ligand Ranking in the CSAR 2013 Benchmark. J Chem Inf Model. 2015, ; 55(1):63-71. doi: 10.1021/ci500519w
- Goldstein JI, Jarskog LF, Hilliard C, Alfirevic A, Duncan L, Fourches D, Huang H, Lek M, Neale BM, Ripke S, Shianna K, Szatkiewicz JP, Tropsha A, van den Oord EJ, Cascorbi I, Dettling M, Gazit E, Goff DC, Holden AL, Kelly DL, Malhotra AK, Nielsen J, Pirmohamed M, Rujescu D, Werge T, Levy DL, Josiassen RC, Kennedy JL, Lieberman JA, Daly MJ, Sullivan PF. Clozapine-induced agranulocytosis is associated with rare HLA-DQB1 and HLA-B alleles. Nat Commun. 2014 Sep 4;5:4757. doi: 10.1038/ncomms5757
- Blatt J, Farag S, Corey SJ, Sarrimanolis Z, Muratov E, Fourches D, Tropsha A, Janzen WP. Expanding the scope of drug repurposing in pediatrics: the Children’s Pharmacy Collaborative. Drug Discov Today. 2014 Nov;19(11):1696-8. doi: 10.1016/j.drudis
- Politi R, Rusyn I, Tropsha A. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods. Toxicol Appl Pharmacol. 2014; 280(1):177-89. PMID: 25058446 [PubMed – as supplied by publisher]
- Mu Q, Jiang G, Chen L, Zhou H, Fourches D, Tropsha A, Yan B.* Chemical basis of interactions between engineered nanoparticles and biological systems. Chem Rev. 2014 114(15):7740-81.
- Low, Y.S. Sedykh, A., Rusyn, I. and Tropsha, A.* Integrative Approaches for Predicting In Vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-Term Biological Assays. Curr. Top. Med. Chem., 2014, 14(11):1356-64.
- Khashan, R., Zheng, W., Tropsha, A. The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling. Mol. Info, 2014, 33, 201-215.