Binding Affinity and Computational Scores for DdpMPyPEPhU and FDA Drugs

5.5 KB XLS file contains computational docking scores comparing a novel compound DdpMPyPEPhU against FDA-approved drugs Lapatinib and Tamoxifen. The dataset includes metrics like Binding Affinity, MM-GBSA, and RMSD for three protein receptors: CDK2, ER-α, and GR. Authored by Shaban Ahmad and last updated in March 2026, it is shared under a CC BY 4.0 license.

Use Cases

• Compare Binding Affinity scores between DdpMPyPEPhU and control drugs across the CDK2, ER-α, and GR receptors.
• Analyze MM-GBSA energy values to assess the stability of ligand-receptor complexes for the tested compounds.
• Evaluate RMSD values from docking simulations to understand conformational changes upon ligand binding.
• Use the computational scores to identify DdpMPyPEPhU as a potential multitarget therapeutic candidate for cancer.

Strengths

• Dataset provides specific computational metrics like Binding Affinity, MM-GBSA, and RMSD for direct comparison.
• Focuses on three well-defined protein receptors with known PDB IDs: 1DI8 (CDK2), 3ERT (ER-α), and 1NHZ (GR).
• Includes control data from two established FDA-approved drugs, Lapatinib and Tamoxifen, for benchmarking.

Limitations

• Very small dataset at only 5.5 KB, indicating limited scope and likely a small number of data points.
• No information provided on the number of rows, columns, or sample data, limiting assessment of comprehensiveness.
• Data is based solely on computational docking studies without experimental validation.

Provenance

Source

figshare, authored by Shaban Ahmad.

Collection Method

Computational molecular docking analysis.

Freshness

Last updated March 2026.