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.

Computational Study of Antimicrobial Peptides for Promising Therapeutic Applications Against Methicillin-resistant Staphylococcus Aureus.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is a causative agent for multiple drug-resistant diseases and is a prime health concern. Currently, antibiotics like vancomycin, daptomycin, fluoroquinolones, linezolid, fifth-generation cephalosporin and others are available in the market for the treatment of MRSA infection. METHODS: With the increasing prevalence of drug-resistant cases, researchers are actively investigating alternative strategies to combat MRSA, including the exploration of peptide therapeutics. This study employed computational methods to prospect for potential Antimicrobial Peptides (AMPs). RESULTS: A total of One hundred and fifty antimicrobial peptides were explored based on physicochemical properties. The results showed that Clavanin B was the most appropriate candidate. Molecular Docking and Molecular Dynamics Simulation results showed the protein-peptide interaction of the MRSA target proteins, Penicillin Binding Protein 2a and Panton-Valentine Leukocidin Toxin, with the Antimicrobial Peptide Clavanin B. CONCLUSION: Currently, the antimicrobial peptide database highlights Clavanin B's role as an anti-HIV peptide. Moreover, this investigation proposes Clavanin B as a viable repurposed drug for treating MRSA, underscoring its potential deployment in the management of MRSA infections.

Anti-microbial Peptides against Methicillin-resistant Staphylococcus aureus: Promising Therapeutics.

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.

Clinico-epidemiological and genomic profile of first Zika Virus outbreak in India at Jaipur city of Rajasthan state.

BACKGROUND: First Zika virus (ZIKV) positive case from North India was detected on routine surveillance of Dengue-Like Illness in an 85-year old female. Objective of the study was to conduct an investigation for epidemiological, clinical and genomic analysis of first ZIKV outbreak in Rajasthan, North India and enhance routine ZIKV surveillance. METHOD: Outbreak investigation was performed in 3 Km radius of the index case among patient contacts, febrile cases, and pregnant women. Routine surveillance was enhanced to include samples from various districts of Rajasthan. Presence of ZIKV in serum and urine samples was detected by real time PCR test and CDC trioplex kit. Few ZIKV positive samples were sequenced using the next-generation sequencing method for genomic analysis. RESULT: On outbreak investigation 153/2043 (7.48%) cases were found positive: 1/153 (0.65%) among contacts, 90/153 (58.8%) in fever cases, 62/153(40.5%) in pregnant females. In routine surveillance, 6/4722 (0.12%) serum samples were ZIKV positive.Majority of patients had mild signs and symptoms, no case of microcephaly and Guillain- Barre Syndrome was seen, 25 (40.3%) pregnant females delivered healthy babies, four (6.4%) reported abortion and three (4.8%) had intrauterine death, one (1.6%) child had colorectal malformation and died after few days of birth. ZIKV was found to belong to Asian lineage, mutation related to enhanced neuro-virulence and transmission in animal models was not found. CONCLUSION: ZIKV was endogenous to India belonging to Asian Lineage. Disease profile of the ZIKV was asymptomatic to mild. No major anomaly was observed in infants born to ZIKV positive mothers; however, long term follow up of these children is required. There is need to scale up surveillance in the virology lab network of India for early detection and control. SUMMARY LINE: Zika virus infection was endogenous due to Asian Lineage with mild disease, no case of microcephaly or Guillain- Barre Syndrome was seen but children need to be followed for anomalies and surveillance of ZIKV needs to be enhanced in the country.