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A theoretical approach to spot active regions in antimicrobial proteins
Torrent Burgas, Marc (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia Molecular)
Nogués i Bara, M. Victòria (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia Molecular)
Boix i Borràs, Esther (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia Molecular)

Data: 2009
Resum: Background: Much effort goes into identifying new antimicrobial compounds able to evade the increasing resistance of microorganisms to antibiotics. One strategy relies on antimicrobial peptides, either derived from fragments released by proteolytic cleavage of proteins or designed from known antimicrobial protein regions. Results: To identify these antimicrobial determinants, we developed a theoretical approach that predicts antimicrobial proteins from their amino acid sequence in addition to determining their antimicrobial regions. A bactericidal propensity index has been calculated for each amino acid, using the experimental data reported from a high-throughput screening assay as reference. Scanning profiles were performed for protein sequences and potentially active stretches were identified by the best selected threshold parameters. The method was corroborated against positive and negative datasets. This successful approach means that we can spot active sequences previously reported in the literature from experimental data for most of the antimicrobial proteins examined. Conclusion: The method presented can correctly identify antimicrobial proteins with an accuracy of 85% and a sensitivity of 90%. The method can also predict their key active regions, making this a tool for the design of new antimicrobial drugs.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès.
Document: article ; publishedVersion
Publicat a: BMC Bioinformatics, Vol. 10, N. 373 (November 2009) , p.1-9, ISSN 1471-2105

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