New predictive models for blood-brain barrier permeability of drug-like molecules.

ABSTRACT:

Purpose

The goals of the present study were to apply a generalized regression model and support vector machine (SVM) models with Shape Signatures descriptors, to the domain of blood-brain barrier (BBB) modeling.

Materials and methods

The Shape Signatures method is a novel computational tool that was used to generate molecular descriptors utilized with the SVM classification technique with various BBB datasets. For comparison purposes we have created a generalized linear regression model with eight MOE descriptors and these same descriptors were also used to create SVM models.

Results

The generalized regression model was tested on 100 molecules not in the model and resulted in a correlation r2 = 0.65. SVM models with MOE descriptors were superior to regression models,

SUBMITTER: Kortagere S 

PROVIDER: S-EPMC2803117 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature