© Dziemba

PD Dr. Oliver Koch

Independent Group Leader
Computational Medicinal Chemistry and Molecular Design

Institute of Pharmaceutical and Medicinal Chemistry
Corrensstr. 48
48149 Münster

Tel.: +49 (0)251 - 83-33443
Fax: +49 (0)251 - 83-32144

E-Mail: Oliver.Koch@uni-muenster.de


Keywords: computational molecular design, cheminformatics, structure-based design, artifical intelligence, data-driven decision making 

The importance of computational methods in pharmaceutical drug research was recently highlighted in a special issue on computer-aided drug design (CADD) strategies in pharma (A CADD-alog of strategies in pharma). The identification and development of new drugs is nowadays hardly imaginable without the use of computational methods. These methods support the complete development workflow from initial target and hit identification up to the development of the final drug candidates.

My research work is generally aimed at improving the performance of computational methods in delivering novel and safe small molecule therapeutics. One of the ways in which this is achieved is by gaining a better understanding of protein-ligand interactions. This includes the development of new computational methods, and the extension and application of already existing approaches. The computational work is combined with biochemical evaluation and preparative organic synthesis of small molecular compounds. The research projects can be summarized as structure-based design and data-driven decision making combined with artificial intelligence.

Nowadays, a huge amount of bioactivity data and protein structures are publicly available; this era of ‘big data’ is changing the way in which small molecule modulators of protein function are developed. The increase in the number of protein structures, however, and the tremendous amounts of bioactivity data still need new tools and approaches or a better understanding of existing tools for efficient data mining and knowledge discovery. Therefore, my development research projects are focussed on (new) data-oriented methods and artificial intelligence for the analysis of protein-ligand interactions and the underlying framework of protein binding sites. The aim is to use available ‘big’ bioactivity data and protein structures for computational molecular design and optimisation. In addition, new bioactive compounds are also developed with the massive help of computational methods. This also allows to get familiar with the limitation of existing methods for further improvement.

Overall, may main research topics can be summarized with improvement and application of computational methods for the identification of new protein-protein interaction inhibitors and ion channel inhibitors, improvement of scoring functions, and a better understanding of selectivity and promiscuity of ligand binding.

Publications and further information

Please use the following link for my publication list and a short overview about my CV.