Antimicrobial Binding Predictions for Borrelia Burgdorferi Ribosome

A 2026 analysis by Swati R. Manjari compiles structural data on medically important antimicrobials (MIAs) binding to bacterial ribosomes. The dataset likely contains computational predictions for MIA binding to the 30S ribosomal subunit of the Lyme disease pathogen Borrelia burgdorferi. It is shared under a CC-BY-NC-4.0 license on figshare.

Use Cases

• Predict binding affinities of antimicrobials to bacterial ribosomes based on structural analogy and energy minimization methods described.
• Aid in structure-guided design of narrow-spectrum antibiotics based on the analysis of MIA binding variability.
• Benchmark computational docking methods using the reported single-point binding free energy computations.
• Study the conformational sensitivity of antibiotic binding in the ribosomal decoding center as described in the analysis.

Strengths

• Focuses on a specific, medically relevant bacterial pathogen (Borrelia burgdorferi).
• Analysis is based on more than two decades of high-resolution structural studies, as stated in the description.
• Dataset is shared under a clear, open license (CC-BY-NC-4.0).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (111.1 KB), indicating limited scope, likely containing summary or parameter data rather than raw structural files.

Provenance

Source

figshare

Collection Method

Compiled from previously reported high-resolution structures and analyzed using structural analogy, restrained energy minimization, and single-point binding free energy computations.

Time Range

Analysis published in 2026.

Freshness

Last updated 2026-04-30 15:04:52; freshness should be verified.

Geography

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