Tailoring PRMT Inhibition: PRMT7 to PRMT4 Selectivity Shift via T-Shape Strategy

Akshay S. Kulkarni published a dataset on figshare in 2026 describing a hybrid strategy for tuning protein arginine methyltransferase (PRMT) inhibitor selectivity. The data likely contains results from transforming a selective PRMT7 inhibitor (SGC8158, IC50 <2.5 nM) into a selective PRMT4 inhibitor (AK442, IC50 = 2.6 nM) using linker length and T-shape modifications. The dataset is small, with a file size of 757.0 B.

Use Cases

• Training predictive models for PRMT inhibitor selectivity based on linker length and structural modifications mentioned in the description.
• Benchmarking computational docking or molecular dynamics simulations against the described IC50 values for SGC8158 and AK442.
• Analyzing structure-activity relationship trends for arginine methyltransferase inhibitors based on the described 'T-shape' design strategy.

Strengths

• Includes specific IC50 values for key inhibitors (SGC8158 <2.5 nM, AK442 = 2.6 nM) as stated in the description.
• File format is CSV, suggesting a structured, machine-readable format.
• Dataset has a clear CC-BY-NC-4.0 license, defining permissible reuse.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Likely contains experimental or computational results from a study on PRMT inhibitor design.

Freshness

Last updated 2026-05-01 20:03:52; freshness should be verified.