Alexander Tropsha, PhD
- Development of new methodologies and software tools for computer-assisted drug design
- Development of new approach to protein 3D structure analysis and prediction based on the principles of statistical geometry
Alex Tropsha 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 125 peer-reviewed papers and twenty 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 research, Tropsha serves as the School’s chief research officer. He creates strategies to increase support for the research enterprise, oversees the School’s research centers, and works to cultivate and expand partnerships with entities within the University and with pharmaceutical and biotechnology companies.
Ivan Rusyn, Fred Wright, Bryan Roth
Most Recent Publications
- Zhang L, Fourches D, Sedykh A, Zhu H, Golbraikh A, Ekins S, Clark J, Connelly MC, Sigal M, Hodges D, Guiguemde WA, Guy RK, Tropsha A.* The Discovery of Novel Antimalarial Compounds Enabled by QSAR-based Virtual Screening. J Chem Inf Model. 2013 Jan. 23. [Epub ahead of print].
- Sedykh A, Fourches D, Duan J, Hucke O, Garneau M, Zhu H, Bonneau P, Tropsha A.* Human Intestinal Transporter Database: QSAR Modeling and Virtual Profiling of Drug Uptake, Efflux and Interactions. Pharm Res. 2012 Dec 27. [Epub ahead of print]
- Martin, T.; Harten, P.; Young, D.; Muratov, E.; Golbraikh, Al.; Zhu, H.; Tropsha, A.* Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?. J Chem Inf Model, 2012, 52(10):2570-8.
- Khashan R, Zheng W, Tropsha A.* Scoring protein interaction decoys using exposed residues (SPIDER): A novel multi-body interaction scoring function based on frequent geometric patterns of interfacial residues. Proteins. 2012 80(9):2207-17. PMC3409293
- Tropsha, A. Recent trends in statistical QSAR modeling of environmental chemical toxicity. EXS. 2012;101:381-411.
Rusyn, I*, Sedykh, A., Low, Y., Guyton, K.Z., and Tropsha, A.* Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data. Tox. Sci., 2012, 127(1):1-9. PMC3327873
- Hajjo R, Setola V, Roth BL, Tropsha A.* Chemocentric informatics approach to drug discovery: identification and experimental validation of selective estrogen receptor modulators as ligands of 5-hydroxytryptamine-6 receptors and as potential cognition enhancers. J Med Chem. 2012 Jun 28;55(12):5704-19. PMC3401608
- Do crystal structures obviate the need for theoretical models of GPCRs for structure based virtual screening. Tang H, Wang XS, Hsieh JH, Tropsha A. Proteins. 2012 Jan 17. doi: 10.1002/prot.24035. [Epub ahead of print] PMID: 22275072 [PubMed - as supplied by publisher]
- Quantitative high-throughput screening for chemical toxicity in a population-based in vitro model. Lock EF, Abdo N, Huang R, Xia M, Kosyk O, O'Shea SH, Zhou YH, Sedykh A, Tropsha A, Austin CP, Tice RR, Wright FA, Rusyn I. Toxicol Sci. 2012 Jan 19. [Epub ahead of print] PMID: 22268004 [PubMed - as supplied by publisher]
- Discrete molecular dynamics distinguishes nativelike binding poses from decoys in difficult targets. Proctor EA, Yin S, Tropsha A, Dokholyan NV. Biophys J. 2012 Jan 4;102(1):144-51. Epub 2012 Jan 3. PMID: 22225808 [PubMed - in process]
- Quantitative structure - property relationship modeling of remote liposome loading of drugs. Cern A, Golbraikh A, Sedykh A, Tropsha A, Barenholz Y, Goldblum A. J Control Release. 2011 Dec 1. [Epub ahead of print] PMID: 22154932 [PubMed - as supplied by publisher]