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Alexander Tropsha

Alexander Tropsha

· KH Lee Distinguished Professor and Associate Dean

University of North Carolina at Chapel Hill · Toxicology

Active 1991–2025

h-index93
Citations36.5k
Papers558164 last 5y
Funding$24.0M1 active

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Alexander Tropsha is the KH Lee Distinguished Professor and Associate Dean at the University of North Carolina Eshelman School of Pharmacy. His major research area is Biomolecular Informatics, which involves understanding the relationships between molecular structures—both organic and macromolecular—and their properties, such as activity or function. He focuses on building validated and predictive quantitative models that relate molecular structure to biological function, utilizing statistical and machine learning approaches. These models are exploited to make verifiable predictions about the putative functions of untested molecules.

Research topics

  • Computer Science
  • Machine Learning
  • Medicine
  • Pharmacology
  • Bioinformatics
  • Virology
  • Data science
  • Biology

Selected publications

  • QSAR without borders

    Chemical Society Reviews · 2020 · 829 citations

    Senior authorCorresponding

    Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure-activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes r…

    DOI

  • A critical overview of computational approaches employed for COVID-19 drug discovery

    Chemical Society Reviews · 2021 · 207 citations

    Senior authorCorresponding

    COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the most severe disruptions to societies and economies since the Great Depression. Massive experimental and computational research effort to understand and characterize the disease and rapidly develop diagnostics, vaccines, and drugs has emerged in response to this devastating pandemic and more than 130 000 COVID-19-related research papers have been published in peer-reviewed journals or deposited in preprint se…

    DOI

  • Modeling Protein–Protein and Protein–Ligand Interactions by the <scp>ClusPro</scp> Team in <scp>CASP16</scp>

    Proteins Structure Function and Bioinformatics · 2025-10-20 · 12 citations

    articleOpen access

    In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein-protein and protein-ligand complex structures. For protein-protein docking, we combined physics-based sampling-using ClusPro FFT docking and molecular dynamics-with AlphaFold (AF)-based sampling, followed by AF-based refinement. Our method produced numerous high-accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics-based sampling alongside deep l…

    PublisherOA PDFDOI

  • Phosphorylation-activated G protein signaling stabilizes TCP14 and JAZ3 to repress JA signaling and enhance plant immunity

    Molecular Plant · 2025-06-12 · 10 citations

    articleOpen access
    PublisherOA PDFDOI

  • Protein–ligand data at scale to support machine learning

    Nature Reviews Chemistry · 2025-07-23 · 10 citations

    review
    PublisherDOI

Recent grants

Frequent coauthors

  • Eugene Muratov

    227 shared

  • Denis Fourches

    North Carolina State University

    129 shared

  • Vinícius M. Alves

    101 shared

  • Alexander Golbraikh

    University of North Carolina at Chapel Hill

    84 shared

  • Igor V. Tetko

    64 shared

  • Stephen J. Capuzzi

    University of North Carolina at Chapel Hill

    58 shared

  • Alexandre Varnek

    Centre National de la Recherche Scientifique

    51 shared

  • Hao Zhu

    Obstetrics and Gynecology Hospital of Fudan University

    49 shared

Education

  • Ph.D., Toxicology

    University of North Carolina at Chapel Hill

    1993

  • M.S., Toxicology

    University of North Carolina at Chapel Hill

    1989

  • B.S., Chemistry

    University of Belgrade

    1984

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