I am a postdoctoral researcher of the Computational Drug Discovery group lead by Prof. Dr. Gerard J.P. van Westen. However, I am also affiliated with the University of Chemistry and Technology, Prague where I am involved with the Department of Informatics and Chemistry lead by Prof. Dr. Daniel Svozil. In my previous work, I developed machine learning models for the prediction of regioselectivity of metabolic enzymes, but more recently I have been focusing on the development and application of tools and algorithms for de novo drug design. During my postdoc in Leiden, I will be working on the integration of novel de novo drug design approaches within a unqiue cheminformatics framework that will be used to search for novel modulators of G-protein coupled receptors as well as other proteins of interest in a collaboration with the groups of Medicinal Chemistry (lead by Prof. Dr. Adriaan IJzerman) and Molecular Pharmacology (lead by Prof. Dr. Laura Heitman).
(1) Šícho, M.; Liu, X.; Svozil, D.; van Westen, G. J. P. GenUI: Interactive and Extensible Open Source Software Platform for de Novo Molecular Generation and Cheminformatics. Journal of Cheminformatics 2021, 13 (1), 73. https://doi.org/10.1186/s13321-021-00550-y.
(2) Šícho, M.; Stork, C.; Mazzolari, A.; de Bruyn Kops, C.; Pedretti, A.; Testa, B.; Vistoli, G.; Svozil, D.; Kirchmair, J. FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes. J. Chem. Inf. Model. 2019, 59 (8), 3400–3412. https://doi.org/10.1021/acs.jcim.9b00376.
(3) Šícho, M.; de Bruyn Kops, C.; Stork, C.; Svozil, D.; Kirchmair, J. FAME 2: Simple and Effective Machine Learning Model of Cytochrome P450 Regioselectivity. J. Chem. Inf. Model. 2017, 57 (8), 1832–1846. https://doi.org/10.1021/acs.jcim.7b00250.