Structure-based and data-oriented computational molecular design
The group research interest lies in the development and application of computational methods in rational drug design with focus on structure-based design and ‘big data’ driven decisions in order to develop bioactive molecules and to understand selectivity and promiscuity of protein-ligand interactions. This work is generally aimed at applying and improving the success of computational methods in delivering novel and safe small molecule therapeutics.
The projects can be divided into the application of computational methods in structure-based design projects (blue) and the development of new approaches and methods for the analysis of the huge amount of bioactivity data and protein structures (green). The aim is to use this knowledge for computational molecular design and optimization of new bioactive compounds. It is important to combine application and development projects since this simultaneously facilitates the testing of the newly developed methods and allows familiarization with the limitations of existing methods for further improvement.
For selected projects, the computational work is combined with laboratory work for the development of new bioactive compounds and the proof of new approaches and findings. So, these topics are linked together with the aim to improve the performance of computational methods in delivering novel and safe small molecule therapeutics.
Keywords: medicinal chemistry, computational molecular design, cheminformatics, structure-based design, fragment-based design, artifical intelligence, data-driven decision making