Virtuelles Screening an Homologiemodellen
Virtuelles Screening auf der Basis von Homologiemodellen
Protein homology models have been used in conjunction with virtual screening to successfully identify novel inhibitors over the past few years. However, it is widely accepted that docking to homology models is more challenging and less successful than docking to X-ray structures of proteins. We have tested a variety of methods to improve the quality of homology models for in silico screening, for example by energy-based refinement of binding site residues. The homology modeling and refinement protocols are based on the GROMACS force field and consider explicit solvent molecules whereas the docking is carried out using GOLD. Refinement of the binding site is carried out by applying all-atom based force field methods and different solvation models. Test cases so far include GPCR models (histamine H3-receptor), nuclear hormone receptors (CAR), kinases (c-Kit) and histone modifying enzymes (SIRT, HDAC, PRMT). Significant enrichment of known ligands was obtained when using the homology models for screening. The validated and refined homology models (at ~50% sequence identity) perform comparably to X-ray structures. In several cases so far we have together with our experimental collaborators identified new ligands based on our docking results, which represent interesting lead compounds for novel targets. Our findings suggest that high quality homology models may be used as structural basis for lead finding and compound optimization of yet not crystallized protein targets.