In silico bioprospecting of receptors for Doderlin: an antimicrobial peptide isolated from Lactobacillus acidophilus

Elias Jorge Muniz Seif; Marcelo Yudi Icimoto; Pedro Ismael da Silva Junior

doi:10.1007/s40203-023-00149-1

In silico bioprospecting of receptors for Doderlin: an antimicrobial peptide isolated from Lactobacillus acidophilus

In Silico Pharmacol. 2023 Apr 25;11(1):11. doi: 10.1007/s40203-023-00149-1. eCollection 2023.

Authors

Elias Jorge Muniz Seif^{1

2}, Marcelo Yudi Icimoto³, Pedro Ismael da Silva Junior^{1

2}

Affiliations

¹ Postgraduate Program in Molecular Biology, Federal University of São Paulo, São Paulo, Brazil.
² Laboratory for Applied Toxinology (LETA), Center of Toxins, Immune-Response and Cell Signaling (CETICS/CEPID), Butantan Institute, São Paulo, Brazil.
³ Department of Biophysics, Federal University of São Paulo, São Paulo, Brazil.

Abstract

The emergence of resistant bacteria strains against traditional antibiotics and treatments increases each year. Doderlin is a cationic and amphiphilic peptide active against gram-positive, negative and yeast stains. The aim of the present work was prospect potentials receptors associated of antimicrobial activity of Doderlin using in silico bioinformatics tools. To search for potential targets of Doderlin, PharmMapper software was used. Molecular docking between Doderlin and the receptor was performed by PatchDock. Additional interaction and ligand site prediction for each receptor was performed by I-TASSER software. Those PDB Id, 1XDJ (score: 11,746), 1JMH (score: 11,046), 1YR3 (score: 10,578), 1NG3 (score: 10,082) showed highest dock score. Doderlin was found to predicted/real sites co-localize with 1XDJ and 1JMH, enzymes accountable for nitrogenic bases synthesis. The resulting receptor bioprospecting is highly correlated and suggests that Doderlin might act by interfering with DNA metabolism/production of bacteria, altering microorganism homeostasis and growth impairment.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-023-00149-1.

Keywords: Computational biology; DNA metabolism enzymes; Molecular docking simulation; Protein domains.

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