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Alpha-helical and beta-sheet membrane- membrane protein dimers: centralizing information
Pedro Filipe 1 , António Preto 1 , Panos Koukos 2 , Alexandre Bonvin 2 , Irina Moreira 3
1  Structural, Computational and Chemical Biology, CNC - Center for Neuroscience and Cell Biology, University of Coimbra
2  Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, Netherlands
3  Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, Netherlands,Center for Neurosciences and Cell Biology (CNC.IBILI), Coimbra, Portugal

Published: 20 December 2017 by MDPI AG in MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition in MOL2NET 2017, International Conference on Multidisciplinary Sciences, 3rd edition session EJIBCE-01; Meeting of Young Researchers in Structural Computational Biology, UC, Coimbra, Portugal, 2017
MDPI AG, 10.3390/mol2net-03-05107
Abstract:

Bioinformatics allows to automatically characterize a large number of proteins from numerous different databases, thus, uncovering new possible interactions between biomolecules in a huge set of individuals in a conscious and cost-efficient way. Membrane proteins are indisputably important for the assurance of major processes in the cell, occupying approximately 25% of the whole cell genome. In this work, some of the major features displayed at Protein Data Bank (original species, chains and ligands, oligomer state, multimeric states, stoichiometry, among others) of membrane proteins listed in the Membrane Proteins with Known 3D Structure database were registered together using manual and automated methods - some of these methods include the usage of python specific tools (like Selenium and BioPython). We aimed to construct a membrane-membrane dimers database that will serve as input for data-mining algorithms to unveiling new functional and evolutionary knowledge.

Keywords: 3D structure, Data mining, Database, dimers, Membrane Membrane, Membrane proteins, Python, Selenium
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