Gibbs free energy correlation for automated docking of carbohydrates

• Published in: Journal of computational chemistry Vol. 29; no. 7; pp. 1131 - 1141
• Main Authors: Hill, Anthony D, Reilly, Peter J
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.05.2008; Wiley Subscription Services, Inc
• Subjects: AutoDock; automated docking; Binding Sites; Carbohydrates; Carbohydrates - chemistry; Computer Simulation; Correlation analysis; Crystallography, X-Ray; Gibbs free energy; Hydrogen - chemistry; Hydrogen Bonding; Hydrophobic and Hydrophilic Interactions; Models, Chemical; Models, Molecular; Molecular structure; Proteins; Proteins - chemistry; Reproducibility of Results; Thermodynamics
• ISSN: 0192-8651; 1096-987X
• DOI: 10.1002/jcc.20873

Thermodynamic information can be inferred from static atomic configurations. To model the thermodynamics of carbohydrate binding to proteins accurately, a large binding data set has been assembled from the literature. The data set contains information from 262 unique protein-carbohydrate crystal structures for which experimental binding information is known. Hydrogen atoms were added to the structures and training conformations were generated with the automated docking program AutoDock 3.06, resulting in a training set of 225,920 all-atom conformations. In all, 288 formulations of the AutoDock 3.0 free energy model were trained against the data set, testing each of four alternate methods of computing the van der Waals, solvation, and hydrogen-bonding energetic components. The van der Waals parameters from AutoDock 1 produced the lowest errors, and an entropic model derived from statistical mechanics produced the only models with five physically and statistically significant coefficients. Eight models predict the Gibbs free energy of binding with an error of less than 40% of the error of any similar models previously published.