HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation.

Journal: Bioinformatics (Oxford, England)
Published Date: Jun 1, 2020

Abstract

MOTIVATION: Therapeutic peptides failing at clinical trials could be attributed to their toxicity profiles like hemolytic activity, which hamper further progress of peptides as drug candidates. The accurate prediction of hemolytic peptides (HLPs) and its activity from the given peptides is one of the challenging tasks in immunoinformatics, which is essential for drug development and basic research. Although there are a few computational methods that have been proposed for this aspect, none of them are able to identify HLPs and their activities simultaneously.

Authors

  • Md Mehedi Hasan
    Nutrition and Clinical Services Division, International Center for Diarrheal Disease and Research, Bangladesh (icddr,b), Dhaka, Bangladesh.
  • Nalini Schaduangrat
    Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand.
  • Shaherin Basith
    Department of Physiology, Ajou University School of Medicine, Suwon, Korea.
  • Gwang Lee
    Department of Physiology, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Watshara Shoombuatong
    Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand.
  • Balachandran Manavalan
    Department of Physiology, Ajou University School of Medicine, Suwon, Republic of Korea.

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