Total views : 379
A Hybridized Clustering Approach based on Rough Set and Fuzzy c-Means to Mine Cholesterol Sequence from ABC Family
Objectives: The current study is focused on design of a computational model for human ABC transporters; wherein the TM-sequences matching the CRAC/CARC motif are extracted. Methods: The postulation of cholesterol binding motif (CRAC/CARC), its presence in different proteins and validating its interaction with cholesterol has indeed established the importance of the motif in cholesterol-mediated modulation of protein/signaling pathway. Several viral proteins and membrane proteins (especially alpha-helical trans membrane proteins) such as GPCR transporters are reported to be modulated by cholesterol. The experimental studies are so far performed on only a few proteins in a family but based on an evolutionary conservation and consensus an exploration can be done confidently within a family. However, the representation of motif has a low consensus yielding several false positives thus reducing its reliability. Findings: A computational hybrid clustering method based on rough set with fuzzy c-means algorithm is used to mine the cholesterol sequence from ABC family. Higher weightage is given to those sequences based on the following parameters: motifs with more number of sub motifs, number of helices bearing the motif in a protein and compliance with the orientation of the cholesterol in the membrane for its interaction with the motif. Improvement: A detailed study in a given super family with an approach to reduce redundancy and enrichment can improve its predictability.
ABC transporter, CRAC/CARC, Fuzzy c-Means, GPCR, Motif, Rough Set.
- Chauhan NB. Membrane dynamics, cholesterol homeostasis, and Alzheimer’s disease. Journal of Lipid Research. 2003; 44(11):2019 –29.
- Oram JF. Molecular basis of cholesterol homeostasis: lessons from Tangier disease and ABCA1. Trends in Molecular Medicine. 2002; 8(4):168 –73.
- Paila YD, Chattopadhyay A. Membrane cholesterol in the function and organization of G-protein coupled receptors. Subcell Biochem. 2010; 51:439–66.
- Schmitz G, Kaminski WE. Phospholipid transporters ABCA1 and ABCA7. In: Broer S, Wagner CA. editors. Membrane Transporter Diseases, Kluwer Academic, Plenum Publishers, New York, 2004; 291–99.
- Tripathy R, Mishra D , Konkimalla VB. A novel fuzzy C-means approach for uncovering cholesterol consensus motif from human G-protein coupled receptors (GPCR). Karbala International Journal of Modern Science. 2015; 1(4):212–24.
- Babu MM, Lee RV, de NS, Groot J, Gsponer G. Intrinsically disordered proteins: regulation and disease. Current opinion in structural Biology. 2011; 21(3):432–40.
- Ahmad N. The vertical transmission of human immunodeficiency virus type 1: molecular and biological properties of the virus. Crit Rev Clin Lab Sci. 2005; 42(1):1–34.
- Abrams EJ, Wiener J, Carter R, Kuhn L, Palumbo P, Nesheim S, Lee F, Vink P, Bulterys M. Maternal health factors and early pediatric antiretroviral therapy influence the rate of perinatal HIV-1 disease progression in children. Aids. 2003; 17(6):867–77.
- Ballesteros J, Weinstein H. Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G proteincoupled receptors. Methods Neurosci, San Diego, CA: Academic Press, 1995; 25(1):366–428.
- Cherezov V, Rosenbaum DM, Hanson MA, Rasmussen SG, Thian FS, Kobilka TS, Choi HJ, Kuhn P, Weis WI, Kobilka BK. High-resolution crystal structure of an engineered human beta2-adrenergic G protein-coupled receptor. Science. 2007; 318(5854):1258–65.
- Zhang Y, Devries ME, Skolnick J. Structure modeling of all identified G protein-coupled receptors in the human genome. PLoS Comput Biol. 2006; 2(2):29.
- Higgins CF. ABC transporters: from microorganisms to man. Annu Rev Cell Biol. 1992; 8(4):67–113.
- Altschul S F, Madden TL, Schaffer AA, Zhang J , Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997; 25(17):3389–402.
- Hubbard TJ, Ailey B, Brenner SE, Murzin AG, Chothi C. SCOP: a Structural Classification of Proteins database. Nucleic Acids Res. 1999; 27(1CC):254–56.
- Patel DC, Albrecht C, Pavitt D. Type 2 diabetes is associated with reduced ATP-binding cassette transporter A1 gene expression, protein and function. PLoS ONE. 2011; 6(7):1–8.
- Wilson B, Angela A, Marcil M, Clee SMLH, Zhang K, Roomp M, Dam VL, Yu Y. Mutations in ABC1 in Tangier disease and familial high-density lipoprotein deficiency. Nature Genetics. 1999; 22(4):336–45.
- Lawn RM, Wade DP, Garvin MR, Wang X, Schwartz K, Porter JG, Seilhamer JJ, Vaughan AM, Oram JF. The Tangier disease gene product ABC1 controls the cellular a polipoprotein-mediated lipid removal pathway. The Journal of Clinical Investigation. 1999; 104(8):R25-R31.
- Mendez AJ. Cholesterol efflux mediated by apolipoproteins is an active cellular process distinct from efflux mediated by passive diffusion. Journal of Lipid Research. 1997; 38(9):1807–21.
- Oram JF, Mendez AJ, Lymp J, Kavanagh TJ, Halbert CL. Reduction in apolipoprotein-mediated removal of cellular lipids by immortalization of human fibroblasts and its reversion by cAMP: lack of effect with Tangier disease cells. Journal of Lipid Research. 1999; 40(10):1769–81.
- Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer. 2002; 2:48–58.
- Patil SB, Kumaraswamy YS. Intelligent and Effective Heart Attack Prediction System Using Data Mining and Artificial Neural Network. European Journal of Scientific Research. 2009; 31(04):642–56.
- Ordonez C. Association rule discovery with the train and test approach for heart disease prediction. IEEE Transactions on Information Technology in Biomedicine. 2006; 10(2):334–43.
- Palaniappan S, Awang R. Intelligent heart disease prediction system using data mining techniques. IEEE/ACS International Conference on Computer Systems and Applications. 2008; 108–15.
- Pawlak Z. Rough sets and data analysis, Fuzzy Systems Symposium. Soft Computing in Intelligent Systems and Information Processing. 1996; 1–6.
- Skowron A, Rauszer C. The discernibility matrices and functions in information systems. Intelligent Decision Support. 1992; 331–62.
- Midelfart H, Komorowski J, Nørsett K, Yadetie F, Sandvik A, Lægreid A. Learning rough set classifiers from gene expression and clinical data. Fundamenta Informaticae. 2002; 53(1):155–83.
- Srimani PK, Koti MS. Knowledge Discovery in Medical Data by using Rough Set Rule Induction Algorithms. Indian Journal of Science and Technology. 2014; 7(7):905–15.
- Anjaneyulu GSGN, Kaushika C, Kumar A. Content based Image Search using Rough Set and Representative Graph. Indian Journal of Science and Technology. 2015; 8(S2):257–61
- Kumar DS, Ezhilarasu P, Prakash J, Kumar KBA. Assimilated Strong Fuzzy C-means in MR Images for Glioblastoma Multiforme. Indian Journal of Science and Technology. 2015; 8(31):1–8.
- Revathy S, Parvaathavarthini B, Rajathi S. Futuristic validation method for rough fuzzy clustering. Indian Journal of Science and Technology. 2015; 8(2):120–27.
- Venu N, Anuradha B. Multil-Kernels Integration for FCM Algorithm for Medical Image Segmentation using Histogram Analysis. Indian Journal of Science and Technology. 2015; 8(34):1–8.
- Ravindraiah R, Reddy SCM, Prasad PR. Detection of Exudates in Diabetic Retinopathy Images using Laplacian Kernel Induced Spatial FCM Clustering Algorithm. Indian Journal of Science and Technology. 2016; 9(15):1–6.
- Kavitha R, Christopher T. An Effective Classification of Heart Rate Data using PSO-FCM Clustering and Enhanced Support Vector Machine. Indian Journal of Science and Technology. 2015; 8(30):1–9.
- Lin PL, Huang PW, Kuo CH, Lai YH. A size-insensitive integrity-based fuzzy c means method for data clustering. Pattern Recognition. 2014; 47(5):2042–56.
- Consortium U. The Universal Protein Resource (UniProt). Nucleic Acids Re. 2007; 35(1):D193–D197.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.