A novel rough set based affinity propagation method for cholesterol prediction from ABC transporter

In biological science, all functions of membrane protein are being modulated by membrane cholesterol. Cholesterol plays a prime role in plasma membrane. The present research emphasized on design of a hybrid rough set based affinity propagation model for prediction of cholesterol sequence from Adenosine Triphosphate Binding Cassette transporters (ABC transporters). Each and every time trans-membrane helix sequences of ABC are evaluated and targeted with cholesterol to find out new valid motif signature. Cholesterol sequences are generated using the formula like Cholesterol Recognition Aminoacid Consensus (CRAC) for forward pattern and reverse of CRAC is CARC for backward pattern. The hypothesis of cholesterol binding motif modulates the signalling pathway of helical membrane protein. Many types of membrane proteins are reported till now, among them G-Protein Coupled Receptors (GPCR) and ABC are important as they are needed for drug discovery. ABC transporter super family is aimed in this work. In experimental study, we explored our hybrid method to find out motif consensus. Finally, from the results we report that our novel technique work efficiently identifying valid motif consensus from ABC protein sequences and is helpful for clinical drug target for human diseases.