Dataset Information

Identification of potential inhibitors against Staphylococcus aureus shikimate dehydrogenase through virtual screening and susceptibility test.

ABSTRACT: Staphylococcus aureus shikimate dehydrogenase (SaSDH) plays a crucial role in the growth of Staphylococcus aureus (S. aureus), but absent in mammals and therefore a potential target for antibacterial drugs to treat drug-resistant S. aureus infection. In this study, a 3D model of SaSDH was constructed by homology modelling and inhibitors of SaSDH were screened through virtual screening. (-)-Gallocatechin gallate and rhodiosin were identified as inhibitors with K_is of 2.47 μM and 73.38 μM, respectively. Molecular docking and isothermal titration calorimetry showed that both inhibitors interact with SaSDH with a K_D of 44.65 μM for (-)-gallocatechin gallate and 16.45 μM for rhodiosin. Both inhibitors had antibacterial activity, showing MICs of 50 μg/mL for (-)-gallocatechin gallate and 250 μg/mL for rhodiosin against S. aureus. The current findings have the potential for identification of drugs to treat S. aureus infections by targeting SaSDH.

SUBMITTER: Zhu M

PROVIDER: S-EPMC10798293 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of potential inhibitors against Staphylococcus aureus shikimate dehydrogenase through virtual screening and susceptibility test.

Zhu Mengfan M Qu Jinfeng J Deng Qi Q

Journal of enzyme inhibition and medicinal chemistry 20240117 1

Staphylococcus aureus shikimate dehydrogenase (SaSDH) plays a crucial role in the growth of Staphylococcus aureus (S. aureus), but absent in mammals and therefore a potential target for antibacterial drugs to treat drug-resistant S. aureus infection. In this study, a 3D model of SaSDH was constructed by homology modelling and inhibitors of SaSDH were screened through virtual screening. (-)-Gallocatechin gallate and rhodiosin were identified as inhibitors with Ki< ...[more]

PMID: 38234148

Similar Datasets

Project description:Staphylococcus aureus is a microorganism with high morbidity and mortality due to antibiotic-resistant strains, making the search for new therapeutic options urgent. In this context, computational drug design can facilitate the drug discovery process, optimizing time and resources. In this work, computational methods involving ligand- and structure-based virtual screening were employed to identify potential antibacterial agents against the S. aureus MRSA and VRSA strains. To achieve this goal, tetrahydroxybenzofuran, a promising antibacterial agent according to in vitro tests described in the literature, was adopted as the pivotal molecule and derivative molecules were considered to generate a pharmacophore model, which was used to perform virtual screening on the Pharmit platform. Through this result, twenty-four molecules were selected from the MolPort® database. Using the Tanimoto Index on the BindingDB web server, it was possible to select eighteen molecules with greater structural similarity in relation to commercial antibiotics (methicillin and oxacillin). Predictions of toxicological and pharmacokinetic properties (ADME/Tox) using the eighteen most similar molecules, showed that only three exhibited desired properties (LB255, LB320 and LB415). In the molecular docking study, the promising molecules LB255, LB320 and LB415 showed significant values in both molecular targets. LB320 presented better binding affinity to MRSA (-8.18 kcal/mol) and VRSA (-8.01 kcal/mol) targets. Through PASS web server, the three molecules, specially LB320, showed potential for antibacterial activity. Synthetic accessibility (SA) analysis performed on AMBIT and SwissADME web servers showed that LB255 and LB415 can be considered difficult to synthesize and LB320 is considered easy. In conclusion, the results suggest that these ligands, particularly LB320, may bind strongly to the studied targets and may have appropriate ADME/Tox properties in experimental studies.

Dataset Information

Identification of potential inhibitors against Staphylococcus aureus shikimate dehydrogenase through virtual screening and susceptibility test.

Publications

Identification of potential inhibitors against <i>Staphylococcus aureus</i> shikimate dehydrogenase through virtual screening and susceptibility test.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets