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HemoPred: a web server for predicting the hemolytic activity of peptides

    Thet Su Win

    Center of Data Mining & Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand

    Department of Medical Laboratory Technology, University of Medical Technology, Yangon 11012, Myanmar

    ,
    Aijaz Ahmad Malik

    Center of Data Mining & Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand

    ,
    Virapong Prachayasittikul

    Department of Clinical Microbiology & Applied Technology, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand

    ,
    Jarl E S Wikberg

    Department of Pharmaceutical Biosciences, BMC, Uppsala University, Sweden

    ,
    Chanin Nantasenamat

    *Author for correspondence:

    E-mail Address: chanin.nan@mahidol.edu

    Center of Data Mining & Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand

    &
    Watshara Shoombuatong

    **Author for correspondence:

    E-mail Address: watshara.sho@mahidol.ac.th

    Center of Data Mining & Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand

    Published Online:https://doi.org/10.4155/fmc-2016-0188

    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.

    Papers of special note have been highlighted as: •• of considerable interest

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