Connecting peptide physicochemical and antimicrobial properties by a rational prediction model
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- dc.contributor.author Torrent, Marcca
- dc.contributor.author Andreu Martínez, Davidca
- dc.contributor.author Nogués, Victòria M.ca
- dc.contributor.author Boix, Esterca
- dc.date.accessioned 2015-04-29T09:17:21Z
- dc.date.available 2015-04-29T09:17:21Z
- dc.date.issued 2011ca
- dc.description.abstract The increasing rate in antibiotic-resistant bacterial strains has become an imperative health issue. Thus, pharmaceutical industries have focussed their efforts to find new potent, non-toxic compounds to treat bacterial infections. Antimicrobial peptides (AMPs) are promising candidates in the fight against antibiotic-resistant pathogens due to their low toxicity, broad range of activity and unspecific mechanism of action. In this context, bioinformatics' strategies can inspire the design of new peptide leads with enhanced activity. Here, we describe an artificial neural network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered are directly derived from the peptide sequence and comprise a complete set of parameters that accurately describe AMPs. Most interesting, the results obtained dovetail with a model for the AMP's mechanism of action that takes into account new concepts such as peptide aggregation. Moreover, this classification system displays high accuracy and is well correlated with the experimentally reported data. All together, these results suggest that the physicochemical properties of AMPs determine its action. In addition, we conclude that sequence derived parameters are enough to characterize antimicrobial peptides.en
- dc.description.sponsorship M.T. is the recipient of a postdoctoral grant from Alianza Cuatro Universidades (Spain). Work supported by the European Union (HEALTH-F3-2008-223414), the Spanish Ministry of Science and Innovation (BIO2008-04487-CO3-02, BFU2009-09371) and the Generalitat de Catalunya (SGR2009-494, SG R2009-795). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
- dc.format.mimetype application/pdfca
- dc.identifier.citation Torrent M, Andreu D, Nogues VM, Boix E. Connecting peptide physicochemical and antimicrobial properties by a rational prediction model. PLoS ONE. 2011;6(2):e16968. DOI: doi:10.1371/journal.pone.0016968ca
- dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0016968
- dc.identifier.issn 1932-6203ca
- dc.identifier.uri http://hdl.handle.net/10230/23495
- dc.language.iso engca
- dc.publisher Public Library of Science (PLoS)ca
- dc.relation.ispartof PLoS ONE. 2011;6(2):e16968
- dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/223414
- dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BIO2008-04487
- dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BFU2009-09371
- dc.rights © 2011 Torrent et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits/nunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.subject.other Pèptidsca
- dc.subject.other Biologia computacionalca
- dc.title Connecting peptide physicochemical and antimicrobial properties by a rational prediction modelen
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca