An electronic environment and contact direction sensitive scoring function for predicting affinities of protein-ligand complexes in Contour(®).

ABSTRACT

Contour(®) is a computational structure-based drug design technology that grows drug-like molecules by assembling context sensitive fragments in well-defined binding pockets. The grown molecules are scored by a novel empirical scoring function developed using high-resolution crystal structures of diverse classes of protein-ligand complexes and associated experimental binding affinities. An atomic model bearing features of the valence bond and VSEPR theories embodying their molecular electronic environment has been developed for non-covalent intermolecular interactions. On the basis of atomic hybridization and polarization states, each atom is modeled by features representing electron lone pairs, p-orbitals, and polar and non-polar hydrogens. A simple formal charge model was used to differentiate between polar and non-polar atoms. The interaction energy and the desolvation contribution of the protein-ligand association energy is computed as a linear sum of pair-wise interactions and desolvation terms. The pair-wise interaction energy captures short-range positive electrostatic interactions via hydrogen bonds, electrostatic repulsion of like charges, and non-bond contacts. The desolvation energy is estimated by calculating the energy required to desolvate interaction surfaces of the protein and the ligand in the complex. The scoring function predicts binding energies of a diverse set of protein-ligand complexes used for training with a correlation coefficient of 0.61. It also performs equally well in predicting association energies of a diverse validation set of protein-ligand complexes with a correlation coefficient of 0.57, which is equivalent to or better than 12 other scoring functions tested against this set including X-Score, GOLD, and DrugScore.