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Title: PAAP: A web server for predicting antihypertensive activity of peptides
Authors: Thet Su Win
Nalini Schaduangrat
Virapong Prachayasittikul
Chanin Nantasenamat
Watshara Shoombuatong
Mahidol University
University of Medical Technology
Keywords: Biochemistry, Genetics and Molecular Biology;Pharmacology, Toxicology and Pharmaceutics
Issue Date: 1-Jan-2018
Citation: Future Medicinal Chemistry. Vol.10, No.15 (2018), 1749-1767
Abstract: © 2018 Newlands Press. Aim: Hypertension is associated with development of cardiovascular disease and has become a significant health problem worldwide. Naturally-derived antihypertensive peptides have emerged as promising alternatives to synthetic drugs. Materials & methods: This study introduces predictor of antihypertensive activity of peptides constructed using random forest classifier as a function of various combinations of amino acid, dipeptide and pseudoamino acid composition descriptors. Results: Classification models were assessed via independent test set that demonstrated accuracy of 84.73%. Feature importance analysis revealed the preference of proline and hydrophobic amino acids at the C-terminal as well as the preference of short peptides for robust activity. Conclusion: Model presented herein serves as a useful tool for predicting and analysis of antihypertensive activity of peptides.
ISSN: 17568927
Appears in Collections:Scopus 2018

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