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Prediction of G-protein Coupled Receptors and Their Coupling Specificity

Author: GuanCuiPing
Tutor: ZhouYanHong
School: Huazhong University of Science and Technology
Course: Bio - IT
Keywords: G protein -coupled receptors Support Vector Machine Classification model Specific coupling
CLC: Q51
Type: Master's thesis
Year: 2007
Downloads: 117
Quote: 1
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Abstract


G protein-coupled receptors (G-protein coupled receptor, GPCR) drug development in the history of the most valuable drug targets , and is also the largest membrane receptor family of proteins in the body , and in the process of cellular signal transduction bear important role. Currently estimated at least 1% or more of the genes in the human genome is used to encode a sequence of more than 1000 GPCR , and the known non - redundant human GPCR sequence only 900 , so digging new GPCR protein as a candidate drug target , there is a great space for development. GPCR and G protein - specific coupling to predict , using bioinformatics methods has important significance and application value , and can help to further study the function and understand the cellular signal transduction mechanism of the receptor in the cell , provide new ideas for drug development . Feature selection and modeling is one of the key technologies of biological information processing . This study took advantage of the combined sequence features (including , dipeptide , tripeptide of the sequence length , amino acid composition ) and amino acid physicochemical characteristics (including hydrophobic , van der Waals volume , polarity , polarizability , and charge ) and support vector machine the method to build a multi-level classification model , and ultimately the identification of the GPCR family classification and prediction specificity and G-protein -coupled . By cross-validation results show that 97% or more of a GPCR can be correctly identified , family classification , the average accuracy of more than 99% , the specificity coupled predict overall accuracy in more than 90% , performance better than previously reported results . On this basis , the integrated development of a multi-functional analysis of software GPCRFP , and applied to the human genome scale GPCR identification and analysis , the number of candidate reference value results . GPCRFP now provide Web services through http://moe.hgrp.cn/tools/GPCR/index.html access .

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CLC: > Biological Sciences > Biochemistry > Protein
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