title: Ligand-specific scoring functions: improved ranking of docking solutions.
abstract: Molecular docking is a powerful computational method that has been widely used in many biomolecular studies to predict geometry of a protein-ligand complex. However, while its conformational search algorithms are usually able to generate correct conformation of a ligand in the binding site, the scoring methods often fail to discriminate it among many false variants. We propose to treat this problem by applying more precise ligand-specific scoring filters to re-rank docking solutions. In this way specific features of interactions between protein and different types of compounds can be implicitly taken into account. New scoring functions were constructed including hydrogen bonds, hydrophobic and hydrophilic complementarity terms. These scoring functions also discriminate ligands by the size of the molecule, the total hydrophobicity, and the number of peptide bonds for peptide ligands. Weighting coefficients of the scoring functions were adjusted using a training set of 60 protein-ligand complexes. The proposed method was then tested on the results of docking obtained for an additional 70 complexes. In both cases the success rate was 5-8% better compared to the standard functions implemented in popular docking software.
authors.affiliation: MM Shemyakin & Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia. pyrkov@nmr.ru
authors.forename: T V
authors.initials: TV
authors.lastname: Pyrkov
authors.forename: J P
authors.initials: JP
authors.lastname: Priestle
authors.forename: E
authors.initials: E
authors.lastname: Jacoby
authors.forename: R G
authors.initials: RG
authors.lastname: Efremov
mesh_terms: D006860:Hydrogen Bonding; D057927:Hydrophobic and Hydrophilic Interactions; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding
chemical_list: D008024:Ligands