Classification of voltage-gated K+ ion channels from 3D pseudo-folding graph representation of protein sequences using genetic algorithm-optimized support vector machines
Voltage-gated K+ ion channels (VKCs) are membrane proteins that regulate the passage of potassium ions through membranes. This work reports a classification scheme of VKCs according to the signs of three electrophysiological variables: activation threshold voltage (Vt), half-activation voltage (Va50 V a 50 ) and half-inactivation voltage (Vh50 V h 50 ). A novel 3D pseudo-folding graph representation of protein sequences encoded the VKC sequences. Amino acid pseudo-folding 3D distances count (AAp3DC) descriptors, calculated from the Euclidean distances matrices (EDMs) were tested for building the classifiers. Genetic algorithm (GA)-optimized support vector machines (SVMs) with a radial basis function (RBF) kernel well discriminated between VKCs having negative and positive/zero Vt, Va50 V a 50 and Vh50 V h 50 values with overall accuracies about 80, 90 and 86%, respectively, in crossvalidation test. We found contributions of the pseudo-core and pseudo-surface of the 3D pseudo-folded proteins to the discrimination between VKCs according to the three electrophysiological variables.
ion channel electrophysiological variables kernel-based methods graph similarity