G721 Series: Structure-Activity Data for CHI3L1 Modulators in Alzheimer's Disease

A 2026 dataset by Baljit Kaur on figshare details the structure-guided optimization of CHI3L1-binding small molecules for Alzheimer's disease. It includes a structure-activity map for 24 prioritized derivatives, with biophysical data such as binding affinity (Kd) ranging from 45 μM to 236 μM. The dataset identifies G721-0377 as a lead compound with improved affinity and functional efficacy in reversing astrocytic dysfunction.

Use Cases

• Training QSAR models based on the structure-activity relationship map for 24 derivatives.
• Benchmarking virtual screening pipelines using the commercially available analogues of G721-0282.
• Analyzing correlations between biophysical properties (e.g., Kd, solubility, permeability) and functional outcomes described in the study.

Strengths

• Includes specific biophysical metrics such as binding affinity (Kd) values ranging from 45 μM to 236 μM.
• Focuses on a lead compound (G721-0377) with validated functional efficacy in restoring amyloid uptake and lysosomal activity in vitro.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• All functional studies were conducted in vitro, as noted in the description.

Provenance

Source

figshare, author Baljit Kaur.

Collection Method

Data likely generated through virtual screening of commercially available analogues and subsequent biophysical/functional in vitro assays.

Freshness

Last updated 2026-04-28 18:34:20; freshness should be verified.