Gergely Zahoránszky-Kőhalmi is a scientist in NCATS’ Division of Preclinical Innovation, where he conducts network pharmacology research and supports early discovery activities, including method development, cheminformatics- and bioinformatics-driven data analysis, molecular modeling and machine learning methods.
Before joining NCATS, Zahoránszky-Kőhalmi worked as a synthetic organic chemist in preclinical drug development and combinatorial chemistry at Sanofi and AMRI Inc. Driven by a growing interest in computer-aided drug design, in 2010 he won a Fulbright Scholarship to perform research on developing and applying network theory-based methods in drug discovery. Working under the supervision of Tudor I. Oprea, M.D., Ph.D., at the University of New Mexico School of Medicine, Zahoránszky-Kőhalmi investigated molecular similarity networks; helped create a network pharmacology-based platform built on the bioactivity database CARLSBAD and developed an information flow-based method to prioritize drug targets for the Illuminating the Druggable Genome research initiative. He also coordinated an Alzheimer’s disease study related to the research project founded by a Pilot Project Award of the University of New Mexico Clinical and Translational Science Center.
Zahoránszky-Kőhalmi received his Ph.D. in biomedical sciences from the University of New Mexico School of Medicine.
Zahoránszky-Kőhalmi’s research interests include devising novel therapeutic strategies by exploiting drug-target and protein-protein interactions, combining machine learning and systems biology methods to predict bioactivity for small molecules, and design and application of artificial intelligence-assisted methods for automated chemistry approaches to accelerate the drug development process.