Membrane Cholesterol Prediction from Human Receptor using Rough Set based Mean-Shift Approach

In human physiology, cholesterol plays an imperative part in membrane cells which regulates the function of G-protein-coupled receptors (GPCR) family. Cholesterol is individual type lipid structure and about 90 percent cellular present at plasma region. Recognition/interaction Amino acid Consensus (CRAC) sequence, generally referred as CRAC (L/V)-X1−5-(Y)-X1−5-(K/R) new cholesterol-binding domain similar to but exhibits inverse orientation along polypeptide chain i.e. CARC (K/R)-X1−5-(Y/F)-X1−5-(L/V). GPCR treated a biggest super family physiology probably more than 900 protein genes included this Among all proteins responsible for novel drug discovery pharmaceuticals industry. earlier researches researchers did not find required number valid motifs terms helices motif types so they were lacking clinical relevance. The research gap here that able predict effectively are belonging multiple types. To out better sequences from GPCR, we explored hybrid computational model consisting hybridization Rough Set with Mean-Shift algorithm. paper made comparison among our resulted output other techniques such fuzzy C-means (FCM), FCM spectral clustering concluded proposed method targeted well on region have higher biological relevance medicine industry discovery.