Ranking models of transmembrane -barrel proteins using Z-coordinate predictions
نویسندگان
چکیده
منابع مشابه
Ranking models of transmembrane β-barrel proteins using Z-coordinate predictions
MOTIVATION Transmembrane β-barrels exist in the outer membrane of gram-negative bacteria as well as in chloroplast and mitochondria. They are often involved in transport processes and are promising antimicrobial drug targets. Structures of only a few β-barrel protein families are known. Therefore, a method that could automatically generate such models would be valuable. The symmetrical arrangem...
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Transmembrane beta-barrel (TMB) proteins are embedded in the outer membrane of gram-negative bacteria, mitochondria, and chloroplasts. Despite their importance, very few nonhomologous TMB structures have been determined by X-ray diffraction because of the experimental difficulty encountered in crystallizing transmembrane proteins. We introduce the program partiFold to investigate the folding la...
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MOTIVATION Transmembrane β barrel proteins (TMBs) are found in the outer membrane of Gram-negative bacteria, chloroplast and mitochondria. They play a major role in the translocation machinery, pore formation, membrane anchoring and ion exchange. TMBs are also promising targets for antimicrobial drugs and vaccines. Given the difficulty in membrane protein structure determination, computational ...
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Dynamic Monte Carlo studies have been performed on various diamond lattice models of 8-proteins. Unlike previous work, no bias toward the native state is introduced; instead, the protein is allowed to freely hunt through all of phase space to find the equilibrium conformation. Thus, these systems may aid in the elucidation of the rules governing protein folding from a given primary sequence; in...
متن کاملSHORT COMMUNICATION Prediction of Transmembrane Regions of -Barrel Proteins Using ANN- and SVM-Based Methods
This article describes a method developed for predicting transmembrane -barrel regions in membrane proteins using machine learning techniques: artificial neural network (ANN) and support vector machine (SVM). The ANN used in this study is a feed-forward neural network with a standard back-propagation training algorithm. The accuracy of theANN-basedmethod improved significantly, from70.4% to 80....
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2012
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/bts233