A QSAR modeling approach for predicting myeloid antimicrobial peptides with high sequence similarity.

Autor: Waghu FH; Biomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai, India., Gawde U; Biomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai, India., Gomatam A; Molecular Simulations Group, Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Mumbai, India., Coutinho E; Molecular Simulations Group, Department of Pharmaceutical Chemistry, Bombay College of Pharmacy, Mumbai, India., Idicula-Thomas S; Biomedical Informatics Centre, Indian Council of Medical Research-National Institute for Research in Reproductive Health, Mumbai, India.
Jazyk: angličtina
Zdroj: Chemical biology & drug design [Chem Biol Drug Des] 2020 Dec; Vol. 96 (6), pp. 1408-1417. Date of Electronic Publication: 2020 Jul 26.
DOI: 10.1111/cbdd.13749
Abstrakt: Microbial resistance to conventional antibiotics has led to a surge in antimicrobial peptide (AMP) rational design initiatives that rely heavily on algorithms with good prediction accuracy and sensitivity. We present a quantitative structure-activity relationship (QSAR) approach for predicting activity of cathelicidins, an AMP family with broad-spectrum activity. The best multiple linear regression model built against Escherichia coli ATCC 25922 could accurately predict activity of three rationally designed peptides CP, DP, and Mapcon, having high sequence similarity. On further experimental validation of the rationally designed peptides, CP was found to exhibit high antimicrobial activity with negligible hemolysis. Here, we provide CP, an AMP with potential therapeutic applications and a family-based QSAR model for AMP prediction.
(© 2020 John Wiley & Sons A/S.)
Databáze: MEDLINE
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