A Strategy to Predict Antimicrobial Peptides
Description
This template was adapted from the original submission. Edits were made to enhance scientific accuracy, optimal usability and/or to meet industry-leading design standards for science communication.
Antibiotic resistance has sparked interest in antimicrobial peptides (AMPs). Once the AMPs are isolated from an organism, like Agalychnis Spurrelli, they are amplified by molecular cloning and sequencing. These sequences are filtered based on their physical and chemical characteristics using algorithms. Then, pepdite groups are evaluated by molecular docking through a peptide-membrane interaction. Finally, the results can predict which sequences may have the best antimicrobial properties and can be used for further in vitro evaluations.
Acknowledgements
References
Proaño-Bolaños. (2019) Unravelling the Skin Secretion Peptides of the Gliding Leaf Frog, Agalychnis spurrelli (Hylidae). Biomolecules. https://www.mdpi.com/2218-273X/9/11/667
Cuesta. (2019) Molecular Modeling of Four Dermaseptin-related Peptides of the Gliding Tree Frog Agalychnis Spurrelli. J Mol Model. https://pubmed.ncbi.nlm.nih.gov/31422479/
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