Nowadays, structure-based ligand design is a frequent method used for the discovery of new lead structures for drug discovery. A key method in this area is molecular docking. In molecular docking, computational methods are used to place small molecules in the binding pocket of the target und to predict the structure of the receptor-ligand complex together with its binding affinity. This approach is very successful but still suffers from false positive and negative predictions. In particular, two aspects are challenging: 1) the treatment of protein flexibility and 2) accurate predicting of binding affinities (”scoringâ). Therefore, improved methods are needed. For evaluating their performance suitable model systems are needed. The ultimate test is to make predictions for a new system and to subsequently verify the predictions using experimental methods. A target, that is suitable for this purpose is Î²-ketoacyl-(acyl-carrier-protein) synthase II (FabF).
FabF is a target for antibiotics. Recently, we determined the crystal structure of FabF from Pseudomonas aeruginosa with high resolution. FabF is therefore a suitable model system to test new approaches in molecular docking in a ”real lifeâ scenario.
For scoring of docking results, typically different functions are used to approximate the binding energies of ligand-receptor complexes. Therefore, we want to test different scoring functions with the available assay results for FabF and other systems for which data in the Brenk group is available to generate ideas about suitable functions. Next, we want to use these functions not only for scoring the complexes but also when placing the ligands into the binding sites. For this docking process, we also aim at improving the treatment of protein flexibility by using modern methods of combinatorial optimization. Finally, we will predict new ligands for FabF. Subsequently, the compounds will be tested for binding affinity and crystal structures of the complexes will be determined. This will also require developing a suitable binding assay. The experimental results will be used to guide the algorithmic developments.