Molecular Drug Docking of Multi Drug Resistant Antibiotics (Gentamicin, Linezolid and Norfloxacin) with Staphylococcus aureus C0673 by Implementing Computational Approach

Background Staphylococcus aureus is an adaptive and versatile microorganism that can cause a wide range of ailments, from intense and short-lived infections to persistent infections that are difficult to cure. Even though S. aureus infections could once be treated with ordinary antibiotics, the rise of drug-resistant organisms is currently a major issue. Numerous antibiotics were used to treat Staphylococcus aureus infections, but over time, the bacteria eventually developed resistance to multiple drugs. Since then, Methicillin-resistant Staphylococcus aureus (MRSA) strain-related nosocomial infections have increased in frequency. Recent advances in bioinformatics and silico screening have boosted our rate and chances of discovering medicinal metabolites. Objectives In this study, we understand and analyse the binding efficiency of Staphylococcus aureus C0673 with three existing antibiotics employing molecular docking studies. Materials and Methods The genomic sequence of Staphylococcus aureus C0673 is retrieved from the Ensemble bacteria database (GCA_00 0638495) and docked with three currently prescribed antibiotics, i.e., Gentamicin, Linezolid and Norfloxacin using HDOCK server. Results and Discussion In the present study Gentamicin, Linezolid and Norfloxacin effectively bind with Staphylococcus aureus C0673. Based on the docking score, the efficiency of the compound against the bacterial protein was assessed. Gentamicin shows higher binding affinity when compared to the other two compounds. Hence, Gentamicin can be considered an eligible candidate by combining with novel medicines to treat the Multi-Drug Resistant protein of Staphylococcus aureus. Conclusion From this research investigation, we conclude that multidrug resistant antibiotics efficiently bind with Staphylococcus aureus C0673. The results obtained from this study play a major role in the field of current bacterial informatics studies.