A theoretical approach to spot active regions in antimicrobial proteins
<p>Abstract</p> <p>Background</p> <p>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 proteoly...
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| Format: | Article |
| Language: | English |
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BMC
2009-11-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/10/373 |
| _version_ | 1818496491203854336 |
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| author | Boix Ester Nogués Victòria M Torrent Marc |
| author_facet | Boix Ester Nogués Victòria M Torrent Marc |
| author_sort | Boix Ester |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> |
| first_indexed | 2024-12-10T18:33:34Z |
| format | Article |
| id | doaj.art-56d8e6a228134251b18c5e4387081cd6 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-10T18:33:34Z |
| publishDate | 2009-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-56d8e6a228134251b18c5e4387081cd62022-12-22T01:37:53ZengBMCBMC Bioinformatics1471-21052009-11-0110137310.1186/1471-2105-10-373A theoretical approach to spot active regions in antimicrobial proteinsBoix EsterNogués Victòria MTorrent Marc<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p>http://www.biomedcentral.com/1471-2105/10/373 |
| spellingShingle | Boix Ester Nogués Victòria M Torrent Marc A theoretical approach to spot active regions in antimicrobial proteins BMC Bioinformatics |
| title | A theoretical approach to spot active regions in antimicrobial proteins |
| title_full | A theoretical approach to spot active regions in antimicrobial proteins |
| title_fullStr | A theoretical approach to spot active regions in antimicrobial proteins |
| title_full_unstemmed | A theoretical approach to spot active regions in antimicrobial proteins |
| title_short | A theoretical approach to spot active regions in antimicrobial proteins |
| title_sort | theoretical approach to spot active regions in antimicrobial proteins |
| url | http://www.biomedcentral.com/1471-2105/10/373 |
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