HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks
書誌事項
- 公開日
- 2020-07-02
- 権利情報
-
- https://creativecommons.org/licenses/by/4.0
- https://creativecommons.org/licenses/by/4.0
- DOI
-
- 10.1038/s41598-020-67701-3
- 公開者
- Springer Science and Business Media LLC
説明
<jats:title>Abstract</jats:title><jats:p>The growing prevalence of resistance to antibiotics motivates the search for new antibacterial agents. Antimicrobial peptides are a diverse class of well-studied membrane-active peptides which function as part of the innate host defence system, and form a promising avenue in antibiotic drug research. Some antimicrobial peptides exhibit toxicity against eukaryotic membranes, typically characterised by hemolytic activity assays, but currently, the understanding of what differentiates hemolytic and non-hemolytic peptides is limited. This study leverages advances in machine learning research to produce a novel artificial neural network classifier for the prediction of hemolytic activity from a peptide’s primary sequence. The classifier achieves best-in-class performance, with cross-validated accuracy of<jats:inline-formula><jats:alternatives><jats:tex-math>$$85.7\%$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>85.7</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math></jats:alternatives></jats:inline-formula>and Matthews correlation coefficient of 0.71. This innovative classifier is available as a web server at<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://research.timmons.eu/happenn">https://research.timmons.eu/happenn</jats:ext-link>, allowing the research community to utilise it for in silico screening of peptide drug candidates for high therapeutic efficacies.</jats:p>
収録刊行物
-
- Scientific Reports
-
Scientific Reports 10 (1), 10869-, 2020-07-02
Springer Science and Business Media LLC