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Research Interests:
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

Selected Peer-Reviewed Publications

Tropsha, A.*, Wang, X.S. QSAR Modeling of GPCR ligands: Methodologies and Examples of Applications. Proc., Schering Foundation Res. Symp. Ser., Berlin, 2007 (in press).

Zhang, S., Wei, L., Bastow, K., Zheng, W., Brossi, A., Lee, K.-H., Tropsha, A.* Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents. J. Comp. Aid. Molec. Des., 2007, 2007, 21, 97-112.

Oprea, T.,* Tropsha, A. Target, Chemical and Bioactivity Databases – Integration is Key. Drug Discov. Today, 2006, 3, 357-365.

Kozikowski AP, Roth B, Tropsha A. Why academic drug discovery makes sense. Science, 2006, 313(5791), 1235-36.

Zhang, S., Golbraikh, A., Oloff, S., Kohn, H., and Tropsha, A.* A Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases using Validated ALL-QSAR Models. J. Chem. Info. Mod, 2006, 46, 1984-95.

Chen, X., Tropsha, A.* Calculation of the Relative Binding Affinity of Enzyme Inhibitors Using the Generalized Linear Response Method. J. Chem. Theory. Comput., 2006, 2, 1435-1443.

Votano JR,* Parham M, Hall LM, Hall LH, Kier LB, Oloff S, Tropsha A. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation. J Med Chem., 2006, 49, 7169-81.

Ghoneim OM, Legere JA, Golbraikh A, Tropsha A, Booth RG.* Novel ligands for the human histamine H1 receptor: synthesis, pharmacology, and comparative molecular field analysis studies of 2-dimethylamino-5-(6)-phenyl-1,2,3,4-tetrahydronaphthalenes. Bioorg Med Chem., 2006, 14, 6640-58.

Tropsha, A. Predictive QSAR (Quantitative Structure Activity Relationships) Modeling. In: Comprehensive Medicinal Chemistry II, V. 4 (Computer-Aided Drug Design), J. Mason, Ed., Elsevier, 2006 (in press).

Tropsha, A. Variable Selection QSAR Modeling, Model Validation, and Virtual Screening. In: Ann. Rev. Comp. Chem., Chapter 4, Y. Martin, Ed. , Elsevier, 2006, Chapter 7, 113-126.

Bandyopadhyay, D., Huan, J., Wang, W., Snoeyink, J.,* Prins, J., and Tropsha, A.* Structure-based Function Inference Using Protein Family-Specific Fingerprints. Protein Sci., 2006, 15,1537-43.

Lima, P., Golbraikh, A., Oloff, S., Xiao, Y., Tropsha, A.* Combinatorial QSAR Modeling of P-Glycoprotein Substrates. J. Chem. Info. Model., 2006, 46, 1245-1254.

Zhang, S., Golbraikh, A., Tropsha, A.* The Development of Quantitative Structure-Binding Affinity Relationship (QSBR) Models Based on Novel Geometrical Chemical Descriptors of the Protein-Ligand Interfaces. J. Med. Chem., 2006, 49, 2713-24.

Oloff, S., Zhang, S., Sukumar, N., Breneman, C., and Tropsha, A.* Chemometric Analysis of Ligand Receptor Complementarity: Identifying Complementary Ligands Based on Receptor Information (CoLiBRI). J. Chem. Inf. Model., 2006, 46, 844-851.

Ongoing Research Grants

R21GM076059 (PI: A. Tropsha). Dates: 6/1/06 – 5/31/09.

National Institutes of Health

Robust Computational Framework for predictive ADME-Tox Modeling (NIH Roadmap).

This project focuses on the development of rigorous computational procedures to develop predictive QSPR models of various physical, biological and toxicological endpoints in support of Predictive ADME-Tox program as part of the NIH Roadmap.

P20-HG003898  (PI: A. Tropsha) Dates: 9/30/05-8/29/07.

National Institutes of Health

Carolina Exploratory Center for Cheminformatics Research (NIH Roadmap).

The main goal of this project is to develop an integrated web environment (ChemBench) to provide cheminformatics research support for the Molecular Libraries Initiative as part of the NIH Roadmap.

GM068665 (PI: A. Tropsha) Dates: 8/1/06-7/30/10.

National Institutes of Health

Protein Structure/Function Specific Packing Motifs.

This project explores applications of computational geometry approaches to the analysis of folded protein structures and the elucidation of packing motifs specific to structure and function.

R41 GM074225-01A1 (PI: A. Tropsha). Dates: 09/01/2006 - 02/28/2007

National Institutes of Health

Automated, Web Based Software Development for Predictive QSAR Modeling.

This is a small business technology transfer project that intends to convert the predictive QSAR modeling technology developed in the PI’s lab to the commercial product.

R01-GM66940-01A1 (PI: A. Tropsha). Dates: 7/1/03 – 6/30/07

National Institutes of Health

Predictive QSAR Modeling.

The main objective of this project is to develop, validate, and deliver efficient computational tools for rapid and reliable prediction of biological activity and/or related pharmaceutical properties of drug-like molecules.

R01-MH068655 (PI: Booth; Tropsha co-investigator). Dates 7/1/05 – 6/30/09.

National Institutes of Health

Functional Probes for Brain Histamine H1 Receptors.

This project focuses on the discovery of agonists and antagonists of Histamine H1 receptors using a combination of experimental and computational techniques.

R832720 (F. Wright; A. Tropsha, Project 2 PI). Dates of the Project: 8/1/05 – 7/31/10

Environmental Protection Agency

The Carolina Environmental Bioinformatics Research Center 

The Center will develop novel analytic and computational methods, create efficient user-friendly tools to disseminate the methods to the wider community, and will apply the computational methods to data from molecular toxicology and other studies.  Project 2 (Chem-informatics) will coordinate the compilation and mining of data from relevant external databases and perform analysis and methods development for investigating Quantitative Structure-Activity Relationships of environmental toxicants.

CCF 0523875 (W. Wang; A. Tropsha Co-PI). Dates: 7/15/2005 – 6/30/2008

National Science Foundation

“Identifying Spatial Motifs for Classification of Protein Structure and Function”

This project will undertake a comprehensive analysis of protein structures.  We will mine the protein structures available in the PDB for structural motifs and construct each protein’s signature as a combination of such motifs.

Ongoing Training Grants (PI):

T32 GM067553-01A1 (A. Tropsha; transferred to T. Elston in summer, 2006). Dates: 7/1/05-6/30/10

National Institutes of Health

UNC Predoc. Program in Bioinformatics and Computational Biology.

UNC-General Administration

UNC-CH Research Training Program in Bioinformatics. (A. Tropsha; transferred to T. Elston in summer, 2006). Dates: 07/01/02 – 06/30/08 (competitive renewal granted 07/01/05). 

Recently Completed Grants:

P20-RR20751 (PI: Reed; Tropsha co-investigator). Dates: 6/1/2004 – 5/31/2006.

National Institutes of Health

Carolina Center for Exploratory Genetic Analysis. 

The Center will explore computational and statistical techniques to establish robust genotype-phenotype correlations.

DK58335-01 (R. Falk; A. Tropsha, co-investigator)                            Dates of Project:  7/1/2000 – 6/30/05

National Institutes of Health

“ANCA Glomerulonephritis: From Molecules to Man”

The overall goal of this project is to investigate various factors that influence the development of glomerulonephritis in men.  Our role is to develop molecular models of Proteinase-3, a key enzyme involved with the etiology of the disease

ITR/MCB 0112896 (PI: A. Tropsha).                                                   Dates of Project: 10/1/01-9/30/04

National Science Foundation

“Computational Analysis of Proteins: From Structure to Sequence to Function”

This project employs statistical geometry approach (Delaunay tessellation) to develop pseudopotential for fold recognition and use this potential in both fold recognition and folding simulations.

NIH/NLM LM07071. (PI: A. Tropsha) Dates: 07/01/01 – 06/30/03 (no cost extension granted until 06/30/04).

National Library of Medicine

Duke-UNC Training Program in Medical Informatics.

MH60328-01 (A. Tropsha)                  Dates of Project:  4/15/00-3/31/03

National Institutes of Health

“Design of Novel D1 Dopamine Receptor Ligands”

This project employs QSAR and database mining approaches to discover novel ligands of dopaminergic D1 receptor of non-catechol nature.