Antimicrobial peptides (AMPs) are native and safe short peptides with valuable biological effects. Nowadays, these components and their importance have attracted the attention of many researchers to determine their mode of action. Computational peptide engineering can donate a useful insight for investigating the stability and potency of AMPs. In the present study, to improve the effect of CLF36, a chimeric peptide derived camel lactoferrin, the atomic insight into peptide-DNA interaction was analyzed using MD simulation. Targeted mutants were performed in wild type amino acid sequences and obtained engineered peptides were homology modeled for peptide-DNA interaction analysis. SASA, Hydrogen binding and free binding energy analyses revealed that all changes in wild type of peptide in this study improved the peptide-DNA interaction. Our in silico results showed that simultaneous substitution of GLU12 with ALA and also removing SER36 in wild type had more substantial effects on complex formation with DNA. The obtained result of this study could be useful to improve the stability and potency of engineered peptides to use of in the experimental study.
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We are grateful to Xavier Daura and Sahar Roshanak for their contribution to manuscript preparation.
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Pirkhezranian, Z., Tahmoorespur, M., Monhemi, H. et al. Computational Peptide Engineering Approach for Selection the Best Engendered Camel Lactoferrin-Derive Peptide with Potency to Interact with DNA. Int J Pept Res Ther (2020). https://doi.org/10.1007/s10989-019-10012-7
- Antimicrobial peptides
- Camel lactoferrin
- MD simulation