Towards Dynamic Pharmacophore Models by Coarse Grained Molecular Dynamics

Abstract

Pharmacophore models play a crucial role in computer aided drug discovery e.g. in virtual screening, de novo drug design, and lead optimization. Due to the increased numbers of protein structures elucidated, structure-based methods for developing pharmacophore models have started gaining in popularity and are becoming of particular importance. There has been a number of studies combining such methods with the use of MD simulations to model protein flexibility. In the MARTINI forcefield, four heavy atoms are represented with the use of a single interaction centre. Four types of interactions have been parametrised in the model, polar, charged, non-polar and apolar. These interactions coincide with some of the typical features found in a pharmacophore model, allowing the CG atoms to be used as pharmacophoric probes. These probes are then used in CG MD simulations in order to explore protein interaction propensities. This approach, in combination with cavity detection methods, allows for the identification of potential ligand binding sites and the detection of ‘hotspot’ interactions that enhance ligand binding. Using CDK2 as a test case, we demonstrate the ability of this method to recapitulate the positions of moieties that contribute to binding interactions commonly observed for ligands known to bind CDK2 and for which crystal structures are available. When examining the ATP binding site of CDK2, a comprehensive and accurate map of the interactions which play a role in ligand binding is generated. The interaction sites identified are then compared with holo crystal structures and are shown to correctly identify the moieties which contribute to the binding interactions. By calculating the ΔGInt values of the interaction maps, we are able to further focus on the areas of interest and identify which moieties are the driving force behind binding.