title: Receptor-specific scoring functions derived from quantum chemical models improve affinity estimates for in-silico drug discovery.
abstract: The adaptation of forcefield-based scoring function to specific receptors remains an important challenge for in-silico drug discovery. Here we compare binding energies of forcefield-based scoring functions with models that are reparameterized on the basis of large-scale quantum calculations of the receptor. We compute binding energies of eleven ligands to the human estrogen receptor subtype alpha (ERalpha) and four ligands to the human retinoic acid receptor of isotype gamma (RARgamma). Using the FlexScreen all-atom receptor-ligand docking approach, we compare docking simulations parameterized by quantum-mechanical calculation of a large protein fragment with purely forcefield-based models. The use of receptor flexibility in the FlexScreen permits the treatment of all ligands in the same receptor model. We find a high correlation between the classical binding energy obtained in the docking simulation and quantum mechanical binding energies and a good correlation with experimental affinities R=0.81 for ERalpha and R=0.95 for RARgamma using the quantum derived scoring functions. A significant part of this improvement is retained, when only the receptor is treated with quantum-based parameters, while the ligands are parameterized with a purely classical model.
authors: Forschungszentrum Karlsruhe, Institut für Nanotechnologie, Postfach 3640, D-76021 Karlsruhe, Germany.
authors: Bernhard
authors: B
authors: Fischer
authors: Kaori
authors: K
authors: Fukuzawa
authors: Wolfgang
authors: W
authors: Wenzel
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D047628:Estrogen Receptor alpha / Q000737:chemistry; D006801:Humans; D008024:Ligands; D008956:Models, Chemical; D004364:Pharmaceutical Preparations; D011485:Protein Binding; D011789:Quantum Theory; D011956:Receptors, Cell Surface / Q000737:chemistry*; D018168:Receptors, Retinoic Acid / Q000737:chemistry; D000097768:Retinoic Acid Receptor gamma
chemical_list: D047628:Estrogen Receptor alpha; D008024:Ligands; D004364:Pharmaceutical Preparations; D011956:Receptors, Cell Surface; D018168:Receptors, Retinoic Acid; D000097768:Retinoic Acid Receptor gamma; C506487:ESR1 protein, human