Longifolene Derivatives for Alzheimer's Disease: 198 Designed Compounds

Ami Thakkar's dataset from 2026 contains computational and experimental data on 198 longifolene derivatives designed as potential Alzheimer's disease therapeutics. The data includes results from molecular docking, MD simulations, cytotoxicity assays, and in vitro evaluations of neuroprotective effects. The dataset is hosted on figshare under a CC-BY-4.0 license.

Use Cases

• Training ML models for virtual screening based on molecular docking scores and MM/GBSA free energy calculations.
• Analyzing structure-activity relationships for longifolene-derived scaffolds based on synthesized compound data.
• Benchmarking new anti-inflammatory or neuroprotective compounds against the reported IC50 and ROS reduction results.

Strengths

• Includes data on 198 specifically designed molecular derivatives.
• Provides experimental validation with cytotoxicity IC50 values exceeding 90 µM and specific results for compound 4f at 0.1 and 0.3 µM concentrations.
• Combines computational (docking, MD simulations) and experimental (synthesis, biological assays) data sources.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analysis.
• The dataset is small at 4.5 MB, potentially limiting the breadth of contained data.

Provenance

Source

figshare, author Ami Thakkar.

Collection Method

Combined computational design (structure-guided molecular docking, MD simulations, MM/GBSA) and experimental synthesis/biological evaluation.

Freshness

Last updated 2026-05-26 11:38:09; freshness should be verified.