A Novel Strategy for Prediction of Cellular Cholesterol Signature Motif from G Protein-Coupled Receptors based on Rough Set and FCM Algorithm

In present era, both soft computing and artificial intelligence techniques have been implemented as problem solver in bioinformatics, as conventional methods are not sufficient for handling huge amount of data. The principal focus of research in all pharmaceutical industries is on human proteins like G protein-coupled receptors (GPCRs), ATP-binding cassette (ABC) transporter etc. Membrane protein plays a significant role for every human being and all drug targets have been considered using this protein. In this manuscript, our focal point of research is on membrane protein that is GPCR family and cholesterol target process on the transmembrane region. Among all living organisms, GPCR acts as the largest superfamily and it includes numerous classes. From the last decades to till date GPCR sequence prediction and classification have been a challenging factor for all biomedicine scientists. GPCR family is also known as 7-pass transmembrane protein receptors. Every time membrane cholesterol has targets for the binding sites of membrane protein in both N terminus and C terminus of the cell membrane. For this purpose, a computational Rough-Fuzzy C-Means (FCM) based approach is implemented for prediction and this method helps to find out valid amino acid sequence which has biological relevance for clinical drug discovery.