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|Title:||HemoPred: A web server for predicting the hemolytic activity of peptides|
|Authors:||Thet Su Win|
Aijaz Ahmad Malik
Jarl E. S Wikberg
University of Medical Technology
|Keywords:||Biochemistry, Genetics and Molecular Biology|
|Citation:||Future Medicinal Chemistry. Vol.9, No.3 (2017), 275-291|
|Abstract:||© 2017 Future Science Ltd. Aim: Toxicity arising from hemolytic activity of peptides hinders its further progress as drug candidates. Materials & methods: This study describes a sequence-based predictor based on a random forest classifier using amino acid composition, dipeptide composition and physicochemical descriptors (named HemoPred). Results: This approach could outperform previously reported method and typical classification methods (e.g., support vector machine and decision tree) verified by fivefold cross-validation and external validation with accuracy and Matthews correlation coefficient in excess of 95% and 0.91, respectively. Results revealed the importance of hydrophobic and Cys residues on α-helix and β-sheet, respectively, on the hemolytic activity. Conclusion: A sequence-based predictor which is publicly available as the web service of HemoPred, is proposed to predict and analyze the hemolytic activity of peptides.|
|Appears in Collections:||Scopus 2016-2017|
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