In structure-based drug design, the experimental elucidation of protein-ligand complexes plays a central role in the optimization of high-affinity drug candidates starting from weakly bound lead compounds. In most cases, this is done by X-ray crystallography, but when this is not possible, NMR methods can alternatively be applied. We will show how data from two ligand-based methods can augment the scoring function ChemPLP of our docking tool PLANTS for more robust predictions of ligand poses.The first, saturation transfer difference spectroscopy (STD), exploits magnetization transfer from the protein to bound ligands and, in this way, can distinguish between strongly bound and water-exposed parts of these. The degree of saturation can qualitatively be translated into distance constraints between specific protons of the ligand and the surface of the protein. Alternatively, a more sophisticated back-calculation of the STD spectrum is possible.The second approach called INPHARMA (Internuclear NOEs for Pharmacophore Mapping) determines the relative orientation of two competitive ligands in the receptor binding pocket. It is based on the observation of interligand transferred NOEs mediated by spin diffusion through protons of the protein and is, therefore, sensitive to the specific interactions of each of the two ligands with the protein. Agreement between the experimental and a back-calculated spectra based on the full relaxation matrix approach is used to predict the poses of 5 weakly bound cAMP-dependent Protein Kinase (PKA) ligands. We will also demonstrate that, besides this improved function, the careful preparation of the input structures and the docking setup including protonation states and flexible side chains is essential.

Rational molecular design supported by ligand-based NMR techniques

248th National Meeting (2014)

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