Imidazopyridine SARM1 Modulator Data from Computational Screening

Steven K. Albanese published a dataset on figshare in April 2026 detailing a series of bicyclic SARM1 inhibitors. The data, approximately 2.9 KB in size, originates from a computational drug discovery workflow involving free-energy perturbation simulations and X-ray crystallography. It describes compounds designed to modulate the NAD+ hydrolase enzyme SARM1, which is implicated in neurological axonopathies.

Use Cases

• Analyze the relationship between compound structure and SARM1 inhibition potency based on simulation and crystallography data.
• Identify structural features, such as the imidazo[4,5‑c]pyridine scaffold, that correlate with slow off-rates and cell activity.
• Investigate the paradoxical activation liability where insufficient target engagement increases neurodegeneration biomarkers.
• Model the unique conformational state of residue W662 in the SARM1 catalytic site induced by specific inhibitors.

Strengths

• Data is derived from a multi-method workflow combining free-energy perturbation (FEP+) simulations and X-ray crystallography.
• Includes analysis of a specific paradoxical activation liability for substrate-based inhibitors.

Limitations

• The dataset is very small at 2.9 KB, indicating limited scope and likely a small number of compounds or features.
• Specific column names, row counts, and sample data are unavailable, limiting direct analytical utility.
• Data is focused on a specific chemical series (imidazo[4,5‑c]pyridines), which may limit generalizability.

Provenance

Source

Steven K. Albanese via figshare.

Collection Method

Data generated through computational free-energy perturbation (FEP+) simulations, subsequent hit expansion, and X-ray crystallography validation.

Freshness

Last updated in April 2026, indicating recent publication.