EventsMOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed.
Published
This submission belongs to the session 01. CHEMBIOINFO-03: Chem-Bioinformatics Congress Cambridge, UK-Chapel Hill and Richmond, USA, 2017 of the event MOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed.
Published date
20 Dec, 2017
Citation
Pedro Matos Filipe, António José Preto, Panos Koukos, Alexandre Bonvin, Irina Moreira, Alpha-helical and beta-sheet membrane- membrane protein dimers: centralizing information, in Proceedings of MOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed., 15 January–15 December 2017, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-03-05107
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Alpha-helical and beta-sheet membrane- membrane protein dimers: centralizing information

António José Preto 1
Panos Koukos 2
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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. Center for Neurosciences and Cell Biology (CNC.IBILI), Coimbra, Portugal
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
selenium
biopython
original species
chains and ligands
oligomer state
multimeric states
stoichiometry
Poster
mol2net-03_MOL2NET-2017-PF.pdf
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