Publication: PAAP: A web server for predicting antihypertensive activity of peptides
Issued Date
2018-01-01
Resource Type
ISSN
17568927
17568919
17568919
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2-s2.0-85051583109
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Mahidol University
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SCOPUS
Bibliographic Citation
Future Medicinal Chemistry. Vol.10, No.15 (2018), 1749-1767
Suggested Citation
Thet Su Win, Nalini Schaduangrat, Virapong Prachayasittikul, Chanin Nantasenamat, Watshara Shoombuatong PAAP: A web server for predicting antihypertensive activity of peptides. Future Medicinal Chemistry. Vol.10, No.15 (2018), 1749-1767. doi:10.4155/fmc-2017-0300 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/45287
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Title
PAAP: A web server for predicting antihypertensive activity of peptides
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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.