PSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their Types.

ABSTRACT: Ion channels are a class of membrane proteins that attracts a significant amount of basic research, also being potential drug targets. High-throughput identification of these channels is hampered by the low levels of availability of their structures and an observation that use of sequence similarity offers limited predictive quality. Consequently, several machine learning predictors of ion channels from protein sequences that do not rely on high sequence similarity were developed. However, only one of these methods offers a wide scope by predicting ion channels, their types and four major subtypes of the voltage-gated channels. Moreover, this and other existing predictors utilize relatively simple predictive models that limit their accuracy. We propose a novel and accurate predictor of ion

SUBMITTER: Gao J 

PROVIDER: S-EPMC4820270 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature