TEM Beta-Lactamase Inhibitor Candidates: 55 Shortlisted Compounds with Docking Scores

Aditi Roy published a dataset on 2026-05-20 containing results from a computational drug discovery study targeting TEM beta-lactamase enzymes in Escherichia coli. The data likely includes pharmacokinetic properties and molecular docking scores for 55 antibacterial compounds shortlisted from an initial evaluation of 3576 compounds. The study identifies a lead candidate, compound 344,265, with binding affinities of -8.5 kcal/mol for TEM-1 and -8.4 kcal/mol for TEM-235.

Use Cases

• Ranking potential beta-lactamase inhibitors based on reported binding affinity scores.
• Analyzing drug-likeness and non-toxicity criteria for antibacterial compounds.
• Studying protein-ligand interactions for TEM-1 and TEM-235 enzymes based on described H-bonding and intermolecular forces.
• Comparing molecular docking results with molecular dynamics and density functional theory analyses referenced in the study.

Strengths

• Includes specific binding affinity scores (-8.5 kcal/mol, -8.4 kcal/mol) for a lead compound against two enzyme variants.
• Describes a clear filtering pipeline from 3576 initial compounds to 55 shortlisted candidates.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• Row count and specific column definitions are unknown, limiting assessment of data structure.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 15.2 KB file size suggests a very limited scope, likely containing summary results rather than raw simulation data.

Provenance

Source

Aditi Roy via figshare.

Collection Method

Generated through integrated computational approaches including virtual screening, molecular docking, dynamics, and density functional theory.

Freshness

Last updated 2026-05-20 05:47:55; freshness should be verified.