What question did this study set out to answer?

To identify potential inhibitors targeting TEM β-lactamase using integrated computational methods.

Integrated machine learning, molecular dynamics, and density functional theory approaches for identifying potential inhibitor targeting TEM 𝛽-lactamase in Escherichia coli

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Randomized trial evaluates drug-like properties and binding efficacy of compounds against TEM β-lactamase, suggesting therapeutic potential.

To identify potential inhibitors targeting TEM β-lactamase using integrated computational methods.
Evaluated 3576 antibacterial compounds for drug-like and non-toxic properties.
Shortlisted 55 compounds for virtual screening against TEM β-lactamase.
Conducted molecular docking analysis and molecular dynamics simulations to assess binding affinities.
Compound 344,265 showed high binding affinities with TEM-1 (−8.5 kcal/mol) and TEM-235 (−8.4 kcal/mol).
Molecular dynamics simulations indicated stable protein-ligand interactions.
Density functional theory analysis revealed a moderate HOMO-LUMO energy gap, suggesting chemical stability.

Roy et al. (2026) studied this question.

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Randomized trial evaluates drug-like properties and binding efficacy of compounds against TEM β-lactamase, suggesting therapeutic potential.