Abstract
Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks.
Highlights
G-protein-coupled receptors (GPCRs), known as G proteinlinked receptors (GPLR), serpentine receptor, seven-transmembrane domain receptors, and 7 TM, form the largest family of cell surface receptors
GPCRs share a common global topology that consists of seven transmembrane alpha helices, intracellular C-terminal, an extracellular N-terminal, three intracellular loops and three extracellular loops (Fig. 1)
GPCR-associated proteins may play at least the following four distinct roles in receptor signaling: (1) directly mediate receptor signaling, as in the case of G proteins; (2) regulate receptor signaling through controlling receptor localization and/or trafficking; (3) act as a scaffold, physically linking the receptor to various effectors; (4) act as an allosteric modulator of receptor conformation, altering receptor pharmacology and/or other aspects of receptor function [1,2,3]
Summary
G-protein-coupled receptors (GPCRs), known as G proteinlinked receptors (GPLR), serpentine receptor, seven-transmembrane domain receptors, and 7 TM (transmembrane), form the largest family of cell surface receptors. It would be very useful to develop a computational method for predicting the interactions between drugs and GPCRs in cellular networking based on their sequencesderived features before a drug candidate was synthesized, so as to reduce the unnecessary waste of time and money [27]. This is the goal of the current study. Let us describe how to deal with these steps
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
