EventsMOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed.
Published
This submission belongs to the session 01. CHEMBIO.INFO-01: Cheminfo., Chemom., Comput. Quantum Chem. & Bioinfo. Congress, Cambridge, UK-Chapel Hill and Richmond, USA, 2015 of the event MOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed.
Published date
04 Dec, 2015
Citation
Cristian R Munteanu, António C. Pimenta, Carlos Fernandez-Lozano, André Melo, Maria Natália Cordeiro, Irina S. Moreira, Solvent Accessible Surface Area Hot-Spot Detection Method, in Proceedings of MOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed., 5 December–15 December 2015, MDPI: Basel, Switzerland, doi: 10.3390/MOL2NET-1-F012
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Solvent Accessible Surface Area Hot-Spot Detection Method

António C. Pimenta 2
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1. Information and Communication Technologies Department, Computer Science Faculty, University of A Coruna, Campus de Elviña s/n, 15071, A Coruña, Spain
2. CNC - Center for Neuroscience and Cell Biology; Rua Larga, FMUC, Polo I, 1ºandar, Universidade de Coimbra, 3004-517; Coimbra, Portugal
3. REQUIMTE/Departamento de Química e Bioquímica, Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre s/n, 4169-007 Porto, Portugal
Abstract

The natural tendency of proteins to bind to each other, as well as to many different molecules, forming stable and specific complexes is fundamental to all biological processes. The structural and functional description of protein-protein and protein-ligand complexes and their comprehension is a key concept, not only to increase the scientific knowledge in basic terms but also for the application to the biomedical and pharmaceutical industry. In this work we have look for more accurate ways of predicting the crucial residues for complex binding (Hot-spots) that can be used to model protein structure, dynamics and function. We developed an algorithm based in innovative series of descriptors, which have not been used in hot-spot determination and that can be applied to both protein-protein and protein-nucleic acid interfaces HS detection. A web-server for public use of the new methodological approaches was built and can be accessed at  http://bio-aims.udc.es/MolStructPred.php

Keywords
Hot-spots
conservation
solvent accessible surface area
machine-learning
protein-protein interfaces
protein-nucleic acid interfaces
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