In Current protein & peptide science
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.
RESULT : 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.
Sinoliya Priyanka, Solanki Pooran Singh, Piplani Sakshi, Kumar Niraj Ravi Ranjan, Sharma Vinay
2022-Dec-16
Antimicrobial peptide, Artificial Intelligence., Computational approach, MRSA, Multiple drug resistance, Peptide design
