The Computational Medicinal Chemistry team develops and applies experimentally drivenin silico modelling methods for the discovery of bioactive molecules. The integration of the computer-aided discovery and design, synthetic medicinal chemistry, molecular pharmacology, and biochemistry research lines of the Division of Medicinal Chemistry allows the investigation of the structure and function of:
■ G protein-coupled receptors
■ Ligand-gated ion channels
■ Cytochrome P450 enzymes
We have built a track record in protein modelling and virtual screening (VS), exemplified by:
■ Winning the international GPCR DOCK 2010 competition to predict the ligand bound crystal structure of the CXCR4 chemokine receptor.
■ Obtaining the highest structure-based virtual screening hit rate reported for GPCRs.
■ Performing the first successful structure-based virtual screening study to identify small modulators of class B GPCRs (with CNRS).
■ Performing the first successful structure-based virtual fragment screening on the GABAA receptor (with (Med)Uni Vienna).
■ One of the first studies to predict functional selectivity of GPCR ligands using an agonist customized model based on the antagonists bound GPCR crystal structure (with CNRS).
■ Pioneer work in the consideration of water molecules in docking simulations (with ETH-Zurich).
■ Our customized protein modeling strategies have been described in several reviews (CYPs, GPCRs).
In 2009 Dr. Chris de Graaf obtained a personal VENI grant (NWO) to develop selectivestructure-based virtual screening strategies against intended and undesired protein targets. This has so far resulted in computational models to predict and rationalize ligand selectivity between:
■ different receptor/enzyme subtypes (GPCRs, human/parasite PDEs, kinases)
■ orthologs (histamine and chemokine GPCRs)
■ unrelated proteins (GPCRs/LGICs/CYPs)
We are currently building a fragment-based chemogenomics platform, based on in-house experimental fragment screening data, to construct in silico modeling techniques to increase our understanding of the molecular details of ligand selectivity and cross-pharmacology.