Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme.

ABSTRACT: The glycine-binding site of the N-methyl-D-aspartate receptor (NMDAR) subunit GluN1 is a potential pharmacological target for neurodegenerative disorders. A novel combinatorial ensemble docking scheme using ligand and protein conformation ensembles and customized support vector machine (SVM)-based models to select the docked pose and to predict the docking score was generated for predicting the NMDAR GluN1-ligand binding affinity. The predicted root mean square deviation (RMSD) values in pose by SVM-Pose models were found to be in good agreement with the observed values (n?=?30, r2?=?0.928-0.988, ?=?0.894-0.954, RMSE?=?0.002-0.412, s?=?0.001-0.214), and the predicted pKi values by SVM-Score were found to be in good agreement with the observed values for the training samples (n?=?24, r2?=?0.967, ?=?0.899, RMSE?=?0.295, s?=?0.170) and test samples (n?=?13, q2?=?0.894, RMSE?=?0.437, s?=?0.202). When subjected to various statistical validations, the developed SVM-Pose and SVM-Score models consistently met the most stringent criteria. A mock test asserted the predictivity of this novel docking scheme. Collectively, this accurate novel combinatorial ensemble docking scheme can be used to predict the NMDAR GluN1-ligand binding affinity for facilitating drug discovery.

SUBMITTER: Leong MK 

PROVIDER: S-EPMC5216401 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature