MARATTO

preprint · Research Square

Identification of Potential Inhibitors Against Staphylococcus Aureus: In Silico Analysis of the LLM Gene as a Therapeutic Target

Abstract

Abstract Staphylococcus aureus is a bacterium that poses a significant global health threat due to its versatile pathogenicity and increasing antibiotic resistance. To counteract this menace, researchers have been exploring strategic approaches, such as targeting the bacterium's essential genes. In this study, the focus is on the LLM gene, which is crucial for bacterial lysis and methicillin resistance. In silico analysis was conducted to identify the protein as a potential therapeutic target. Various computational techniques, including molecular docking and molecular dynamics simulations, were employed to assess the inhibitory potential of different compounds against this target, benchmarking them against the standard drug, Tunicamycin. Through virtual screening, twenty-two ligands were docked against the protein receptor and six promising inhibitors were indetified, namely: ZINC06605913, ZINC06905586, ZINC35022243, ZINC40483738, ZINC90417652, and ZINC85428484. Among these, Zinc 90417652 (ZIN) emerged as a frontrunner, demonstrating superior binding affinity and stability metrics compared to Tunicamycin. Molecular dynamics analyses, spanning RMSD, RMSF, Rg, SASA, and MM-PBSA, validated the stability and dynamics of the LLM protein in the presence of ZIN. Further, binding free energy evaluations accentuated ZIN's superior binding profile, and residue decomposition analyses pinpointed key residues integral to this enhanced binding. Overall, the findings of this study highlight the potential of Zinc 90417652 as a lead candidate for the development of potent antimicrobial agents against Staphylococcus aureus, offering a promising avenue for combating this global health threat.

Research topics

  • Synthesis and biological activity
  • Computational Drug Discovery Methods
  • Biochemical and Structural Characterization

Sustainable Development Goals

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.21203/rs.3.rs-3504303/v1

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.