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Csaba Hetenyi

Speaker for pharma conferences 2017-Csaba Hetenyi

Title: Improvements of computational optimization of drug-target interactions

Csaba Hetenyi

Csaba Hetenyi, University of Pecs, Hungary

Biography

Dr. Csaba Hetényi is an Associate Professor in Pharmacology. He has co-authored research articles in prestigious journals J Am Chem Soc, PNAS, EMBO Reports, Bioinformatics, and is also a co-inventor of US patents. Dr. Hetényi has received more than 1500 independent citations for his research results, has a Hirsch-index of 18 and his works were favorably evaluated by several review articles and research papers. In 2011, Dr. Hetényi won a Talentum Academy Award for his research achievements. His present research interest is focused on the development of pharmacoinformatics tools and molecular pathomechanisms of diseases. Dr. Hetényi collaborates with researchers in Sweden, Estonia, Spain, and the USA.

Abstract

Optimization of drug-target interactions is a central issue of structure-based drug design. There are fast docking methods available for calculation of the structure and energy of target-ligand complexes. Docking is the computational alternative of experimental structure determination methods such as X-ray crystallography, and it can help to reduce the costs of the drug discovery process. However, there are various limitations of computational docking such as inadequate input geometries of the target or the ligand, lack of convergence criteria during random search, inappropriate water models and force fields. The present lecture focuses on the problematics of water models. We show, how the correct prediction of hydration structure of target-ligand interfaces can help overcoming the above-mentioned various limitations of docking, and improve calculation of drug-target interactions.

Audience will learn:
The lecture provides practical examples on improvements of calculation of drug-target interactions with the help of open source program packages such as AutoDock, GROMACS, and MobyWat. Such information will help the members of the audience in future drug design projects and improve the efficiency of their job. The message of the lecture will also help teaching of up-to-date solutions of drug design problems.