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Title 

A combined approach for the classification of G protein-coupled receptors and its application to detect GPCR splice variants

Authors 

H S EoJae Pil ChoiS J NohCheol-Goo HurW Kim

Publisher 

Elsevier

Issue Date 

2007

Citation 

Computational Biology and Chemistry, vol. 31, no. 4, pp. 246-256

Keywords 

G protein-coupled receptorphysicochemical propertyprofile hidden Markov modelsplice varianttransmembrane domain

Abstract 

G protein-coupled receptors (GPCRs) constitute the largest family of cell surface receptors and play a central role in cellular signaling pathways. The importance of GPCRs has led to their becoming the targets of more than 50% of prescription drugs. However, drug compounds that do not differentiate between receptor subtypes can have considerable side effects and efficacy problems. An accurate classification of GPCRs can solve the side effect problems and raise the efficacy of drugs. Here, we introduce an approach that combines a fingerprint method, statistical profiles and physicochemical properties of transmembrane (TM) domains for a highly accurate classification of the receptors. The approach allows both the recognition and classification for GPCRs at the subfamily and subtype level, and allows the identification of splice variants. We found that the approach demonstrates an overall accuracy of 97.88% for subfamily classification, and 94.57% for subtype classification.

ISSN 

1476-9271

Link 

http://dx.doi.org/10.1016/j.compbiolchem.2007.05.002

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2017-04-19


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