De novo Designing of the Antimicrobial Peptide as a Curative Agent for Methicillin-Resistant Staphylococcus aureus through a Computational Approach.

BACKGROUND: The emergence of resistance to multiple drugs has posed a multitude of difficulties that demand immediate attention and solutions. Multiple drug resistance arises from the accumulation of numerous genes within a single cell, each conferring resistance to a specific drug, and from the heightened expression of genes responsible for multidrug efflux pumps. These pumps effectively expel a diverse array of drugs from the cell.

OBJECTIVE: The multi-drug-resistant organisms, including methicillin-resistant Staphylococcus aureus, are the hub of numerous diseases, from minute ailments to fatal diseases, like catheter infections. Nowadays, a combination of many antibiotics is given together as a multimodality therapy to cure MRSA infections. However, researchers are exploring novel approaches to find better solutions.

METHODS: De novo designing of the peptide sequences has been done through an in silico tool. The peptides were further screened using different computational methods. Following this, the selection was conducted utilizing physicochemical properties as criteria. Molecular docking of the selected peptide sequence was carried out. Based on the highest docking score, the model complex was chosen for validation purposes by conducting studies through molecular dynamics simulations.

RESULTS: A total of fifty-two novel antimicrobial peptides were designed and evaluated based on various parameters, targeting MRSA-specific proteins PBP2a and PVL toxin. Among these designed peptides, the peptide sequence VILRMFYHWAVKTNGP emerged as the optimal candidate, satisfying all the necessary parameters to be an effective antimicrobial peptide.

CONCLUSION: Molecular docking and MD simulation results showed that the designed peptide sequence could be the possible solution for MRSA treatment.