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2000
Volume 24, Issue 2
  • ISSN: 1389-2037
  • E-ISSN: 1875-5550

Abstract

Background: Multidrug-resistant (MDR) methicillin-resistant Staphylococcus aureus (MRSA) has become a prime health concern globally. These bacteria are found in hospital areas where they are regularly dealing with antibiotics. This brings many possibilities for its mutation, so drug resistance occurs. Introduction: Nowadays, these nosocomial MRSA strains spread into the community and live stocks. Resistance in Staphylococcus aureus is due to mutations in their genetic elements. Methods: As the bacteria become resistant to antibiotics, new approaches like antimicrobial peptides (AMPs) play a vital role and are more efficacious, economical, time, and energy saviours. Results: Machine learning approaches of Artificial Intelligence are the in silico technique which has their importance in better prediction, analysis, and fetching of important details regarding AMPs. Conclusion: Anti-microbial peptides could be the next-generation solution to combat drug resistance among Superbugs. For better prediction and analysis, implementing the in silico technique is beneficial for fast and more accurate results.

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/content/journals/cpps/10.2174/1389203724666221216115850
2023-02-01
2024-11-26
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