Thesis supervisors:
Professor Mati Karelson (PhD), Institute of Chemistry, University of Tartu
Research Fellow Kaido Tämm (PhD), Institute of Chemistry, University of Tartu
Late Professor Alan Roy Katritzky (PhD) (Deceased 2014), University of Florida, USA
Opponent:
Dr Eric F. V. Scriven (PhD), University of Florida, USA
Summary
Computational modelling of diverse chemical, biochemical and biomedical properties
Computational modelling plays an important role in the initial phase of drug discovery and has considerably improved in the last decade. Current thesis is focused on several applications in computational chemistry, i.e. conformational analysis, QSAR modelling, fragment-, ligand- based methods, and molecular docking methodologies. As a result, predictive models were generated for following targets: i) the activities of HPV antiviral agents and mosquito repellents; ii) the dual inhibition of Type 2 diabetes mellitus and Alzheimer’s disease; and iii) the relative abundance in chemical ligation. The main task of developed models is to predict the respective activities for novel structures, which are not yet experimentally tested. These models are oriented to strengthen the drug discovery process faster.