Information Theory-Based Scoring Function for the Structure-Based Prediction of Protein−Ligand Binding Affinity Export

@article{KulhariaGJ08, abstract = {PMID: 18767831 The development and validation of a new knowledge based scoring function (SIScoreJE) to predict binding energy between proteins and ligands is presented. SIScoreJE efficiently predicts the binding energy between a small molecule and its protein receptor. Protein−ligand atomic contact information was derived from a Non-Redundant Data set (NRD) of over 3000 X-ray crystal structures of protein−ligand complexes. This information was classified for individual ” atom contact pairs” (ACP) which is used to calculate the atomic contact preferences. In addition to the two schemes generated in this study we have assessed a number of other common atom-type classification schemes. The preferences were calculated using an information theoretic relationship of joint entropy. Among 18 different atom-type classification schemes ” ScoreJE Atom Type set2” (SATs2) was found to be the most suitable for our approach. To test the sensitivity of the method to the inclusion of solvent, Single-body Solvation Potentials (SSP) were also derived from the atomic contacts between the protein atom types and water molecules modeled using AQUARIUS2. Validation was carried out using an evaluation data set of 100 protein−ligand complexes with known binding energies to test the ability of the scoring functions to reproduce known binding affinities. In summary, it was found that a combined SSP/ScoreJE (SIScoreJE) performed significantly better than ScoreJE alone, and SIScoreJE and ScoreJE performed better than GOLD::GoldScore, GOLD::ChemScore, and XScore.}, address = {Department of Physical Biochemistry, Max Planck Institute of Molecular Physiology, Otto Hahn Strasse 11, Dortmund, Germany 44227, and Institute of Molecular and Cellular Biology, University of Leeds, Leeds, U.K. LS2 9JT}, author = {Kulharia, Mahesh and Goody, Roger S. and Jackson, Richard M.}, citeulike-article-id = {3206153}, citeulike-linkout-0 = {http://dx.doi.org/10.1021/ci800125k}, citeulike-linkout-1 = {http://pubs.acs.org/doi/abs/10.1021/ci800125k}, day = {27}, doi = {10.1021/ci800125k}, journal = {Journal of Chemical Information and Modeling}, keywords = {affinity, atom, binding, contact, database, function, ligand, pair, protein, scoring}, month = {October}, number = {10}, pages = {1990--1998}, posted-at = {2008-09-08 14:16:28}, priority = {2}, title = {Information Theory-Based Scoring Function for the Structure-Based Prediction of Protein−Ligand Binding Affinity}, url = {http://dx.doi.org/10.1021/ci800125k}, volume = {48}, year = {2008} }

TY - JOUR ID - KulhariaGJ08 L3 - citeulike-article-id:3206153 N2 - PMID: 18767831 The development and validation of a new knowledge based scoring function (SIScoreJE) to predict binding energy between proteins and ligands is presented. SIScoreJE efficiently predicts the binding energy between a small molecule and its protein receptor. Protein−ligand atomic contact information was derived from a Non-Redundant Data set (NRD) of over 3000 X-ray crystal structures of protein−ligand complexes. This information was classified for individual “atom contact pairs” (ACP) which is used to calculate the atomic contact preferences. In addition to the two schemes generated in this study we have assessed a number of other common atom-type classification schemes. The preferences were calculated using an information theoretic relationship of joint entropy. Among 18 different atom-type classification schemes “ScoreJE Atom Type set2” (SATs2) was found to be the most suitable for our approach. To test the sensitivity of the method to the inclusion of solvent, Single-body Solvation Potentials (SSP) were also derived from the atomic contacts between the protein atom types and water molecules modeled using AQUARIUS2. Validation was carried out using an evaluation data set of 100 protein−ligand complexes with known binding energies to test the ability of the scoring functions to reproduce known binding affinities. In summary, it was found that a combined SSP/ScoreJE (SIScoreJE) performed significantly better than ScoreJE alone, and SIScoreJE and ScoreJE performed better than GOLD::GoldScore, GOLD::ChemScore, and XScore. IS - 10 JF - Journal of Chemical Information and Modeling AD - Department of Physical Biochemistry, Max Planck Institute of Molecular Physiology, Otto Hahn Strasse 11, Dortmund, Germany 44227, and Institute of Molecular and Cellular Biology, University of Leeds, Leeds, U.K. LS2 9JT EP - 1998 TI - Information Theory-Based Scoring Function for the Structure-Based Prediction of Protein−Ligand Binding Affinity VL - 48 SP - 1990 KW - affinity KW - atom KW - binding KW - contact KW - database KW - function KW - ligand KW - pair KW - protein KW - scoring AU - Kulharia, Mahesh AU - Goody, Roger AU - Jackson, Richard PY - 2008/10/27/ UR - http://dx.doi.org/10.1021/ci800125k ER -