Receptor ligand binding: complex structure prediction and affinity evaluation

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The reliable and fast computation of binding free energies of small molecules to the active sites of proteins is crucial for structure-based drug design and for the understanding of protein-ligand interactions. Rigorous treatments involve computationally expensive methods like free energy perturbation approaches, which are, however, incompatible with the need for fast methods in e.g. drug screening or lead discovery. In turn, commonly used fast methods involve empirically derived scoring functions and usually do not include receptor and/or ligand flexibility. Hence, such methods are inherently limited in accuracy. The proposed project aims at the development of a fast conformational search for possible proteinligand conformations based on available structural data combined with a physical effective energy function for the computation of free energy differences. The first step involves the efficient prediction of protein-ligand conformations based on geometric considerations, aimed at efficiently sampling the available configurational space of ligand-receptor conformations. Subsequently, entropy estimates are used for weighting of the sampled conformations, in order to generate canonical ensembles. These ensembles allow an accurate determination of binding energies by (ensemble) averaging an energy function which is based on physical chemistry (force field) and an efficient continuum electrostatic approach to evaluate solvation free energy. Together, these two steps — the generation of alternative conformations and the computation of free energies using canonical ensemble averaging—are anticipated to allow an accurate and efficient estimation of relative binding affinities. In subsequent steps the method may be extended towards novel lead discovery or docking strategies, fully taking into account protein and ligand flexibilities.