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Study · In silico · 2023

1 result

Computational Screening of Approved Drugs for Inhibition of the Antibiotic Resistance Gene mecA in Methicillin-Resistant Staphylococcus aureus (MRSA) Strains.

Otarigho B, Falade MO

Biotech (Basel (Switzerland))31 Mar 2023Cited by 8 (Europe PMC)

PMID37092469 (opens in a new tab)PMCIDPMC10123713 (opens in a new tab)DOI10.3390/biotech12020025 (opens in a new tab)PepBankPUB-37092469
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Summary

Antibiotic resistance is a critical problem that results in a high morbidity and mortality rate. The process of discovering new chemotherapy and antibiotics is challenging, expensive, and time-consuming, with only a few getting approved for clinical use. Therefore, screening already-approved drugs to combat pathogens such as bacteria that cause serious infections in humans and animals is highly encouraged. In this work, we aim to identify approved antibiotics that can inhibit the mecA antibiotic resistance gene found in methicillin-resistant Staphylococcus aureus (MRSA) strains. The MecA protein sequence was utilized to perform a BLAST search against a drug database containing 4302 approved drugs. The results revealed that 50 medications, including known antibiotics for other bacterial strains, targeted the mecA antibiotic resistance gene. In addition, a structural similarity approach was employed to identify existing antibiotics for S. aureus, followed by molecular docking. The results of the docking experiment indicated that six drugs had a high binding affinity to the mecA antibiotic resistance gene. Furthermore, using the structural similarity strategy, it was discovered that afamelanotide, an approved drug with unclear antibiotic activity, had a strong binding affinity to the MRSA-MecA protein. These findings suggest that certain already-approved drugs have potential in chemotherapy against drug-resistant pathogenic bacteria, such as MRSA.
CC BYText from Europe PMC. Highlighted sentences are the source of results.

Results from this study1

1 result from studies that gave the peptide. No result from this study comes from people.

  1. 01Computer modelIn silicoActivity measurement

    In a computational screen, afamelanotide showed a strong predicted binding affinity to the MRSA MecA protein.

    In plain wordsIn a computer screen, afamelanotide was predicted to bind strongly to a MRSA resistance protein. No lab test was done.

    Peptide
    Melanotan I (afamelanotide)
    Outcome
    Not applicablePredicted binding affinity to MRSA MecA protein
    Study

    n: not reported in source

    Structural similarity search and molecular docking
    Outcome group
    Receptor activity and mechanism · Infection
    Studied dose
    Dose not stated

    Source sentences

    Summary
    Furthermore, using the structural similarity strategy, it was discovered that afamelanotide, an approved drug with unclear antibiotic activity, had a strong binding affinity to the MRSA-MecA protein.
    1 context sentence
    Summary · context
    In addition, a structural similarity approach was employed to identify existing antibiotics for S. aureus, followed by molecular docking.

AI wrote and checked these results. AI can make mistakes, so check important results against the source.

Version history

PepBank keeps every version of the data on this study. Status changes from Retraction Watch, Europe PMC and Crossref are listed with their source.

  1. Version 2Current

    13 Oct 2026, 21:44 UTC

    Study results updated

  2. Version 1

    13 Oct 2026, 16:31 UTC

    First added · source update from Europe PMC

Subjects

Terms as the source lists them.

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