title: QSAR investigation of NaV1.7 active compounds using the SVM/Signature approach and the Bioclipse Modeling platform.
abstract: A quantitative structure-activity relationship investigation of some NaV1.7 active compounds has been performed by repeated, random, external test set experiments employing structural descriptors (fingerprints) of signature type in combination with support vector machine (SVM) analysis using the radial basis function (RBF) kernel. The results from the investigation show remarkably stable performance from the derived in silico models in terms of statistical measures such as correlation coefficients as well as root mean squared errors (RMSEs) for the randomly selected external test sets. Also, the Bioclipse Modeling platform is utilized for introducing interpretation to the derived models.
authors.affiliation: AstraZeneca Research and Development Södertälje, SE-151 85 Södertälje, Sweden. ulfn@lundbeck.com
authors.forename: Ulf
authors.initials: U
authors.lastname: Norinder
authors.forename: Maria E
authors.initials: ME
authors.lastname: Ek
mesh_terms: D008958:Models, Molecular; D062556:NAV1.7 Voltage-Gated Sodium Channel / Q000737:chemistry* / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship; D060388:Support Vector Machine
chemical_list: D062556:NAV1.7 Voltage-Gated Sodium Channel; C486866:SCN9A protein, human