A QSAR modeling approach for predicting myeloid antimicrobial peptides with high sequence similarity
| Autor: | Ulka Gawde, Evans C. Coutinho, Anish Narasimhan Gomatam, Faiza Hanif Waghu, Susan Idicula-Thomas |
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| Rok vydání: | 2019 |
| Předmět: |
Models
Molecular Pore Forming Cytotoxic Proteins Quantitative structure–activity relationship Antimicrobial peptides Quantitative Structure-Activity Relationship Peptide Computational biology 01 natural sciences Biochemistry Hemolysis Structure-Activity Relationship Similarity (network science) Drug Discovery Escherichia coli Humans Amino Acid Sequence Pharmacology chemistry.chemical_classification 010405 organic chemistry Chemistry Organic Chemistry Rational design Reproducibility of Results Antimicrobial 0104 chemical sciences Cathelicidins 010404 medicinal & biomolecular chemistry Klebsiella pneumoniae Cheminformatics Pseudomonas aeruginosa Molecular Medicine |
| Zdroj: | Chemical biologydrug designREFERENCES. 96(6) |
| ISSN: | 1747-0285 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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