4.5 Article

Identification of New Drug Target in Staphylococcus lugdunensis by Subtractive Genomics Analysis and Their Inhibitors through Molecular Docking and Molecular Dynamic Simulation Studies

期刊

BIOENGINEERING-BASEL
卷 9, 期 9, 页码 -

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MDPI
DOI: 10.3390/bioengineering9090451

关键词

drug targets; subtractive genomics; homology modeling; molecular docking; molecular dynamics simulation

资金

  1. Deanship of Scientific Research at King Khalid University through the Large Groups Project [RGP.2/70/43]

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This study aimed to identify novel drug targets in the S. lugdunensis strain N920143 and evaluate potential inhibitors. A DNA-binding response-regulator protein was identified as a new drug target, and two compounds were found to interact favorably with the active site residues of the drug target.
Staphylococcus lugdunensis is a coagulase-negative, Gram-positive, and human pathogenic bacteria. S. lugdunensis is the causative agent of diseases, such as native and prosthetic valve endocarditis, meningitis, septic arthritis, skin abscesses, brain abscess, breast abscesses, spondylodiscitis, post-surgical wound infections, bacteremia, and peritonitis. S. lugdunensis displays resistance to beta-lactam antibiotics due to the production of beta-lactamases. This study aimed to identify potential novel essential, human non-homologous, and non-gut flora drug targets in the S. lugdunensis strain N920143, and to evaluate the potential inhibitors of drug targets. The method was concerned with a homology search between the host and the pathogen proteome. Various tools, including the DEG (database of essential genes) for the essentiality of proteins, the KEGG for pathways analysis, CELLO V.2.5 for cellular localization prediction, and the drug bank database for predicting the druggability potential of proteins, were used. Furthermore, a similarity search with gut flora proteins was performed. A DNA-binding response-regulator protein was identified as a novel drug target against the N920143 strain of S. lugdunensis. The three-dimensional structure of the drug target was modelled and validated with the help of online tools. Furthermore, ten thousand drug-like compounds were retrieved from the ZINC15 database. The molecular docking approach for the DNA-binding response-regulator protein identified ZINC000020192004 and ZINC000020530348 as the most favorable compounds to interact with the active site residues of the drug target. These two compounds were subjected to an MD simulation study. Our analysis revealed that the identified compounds revealed more stable behavior when bound to the drug target DNA-binding response-regulator protein than the apostate.

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