Vaccine-TLR2 Model Binding Affinity and Kd Predictions

A 5.5 KB Excel file contains predicted binding affinity and dissociation constant (Kd) values for a vaccine-Toll-like receptor 2 (TLR2) model. The dataset was created by Md. Nazmussakib Shuvo and uploaded to figshare in April 2026. It provides computational predictions for vaccine component interactions with the immune receptor TLR2.

Use Cases

• Validate computational docking or binding affinity prediction models against the provided Kd values.
• Screen predicted binding affinities to prioritize vaccine candidates for experimental TLR2 binding assays.
• Correlate structural features of vaccine components with their predicted Kd values for mechanistic insight.

Strengths

• Dataset is openly licensed under CC-BY-4.0 for reuse.
• Provides specific predictions for the immunologically relevant TLR2 target.
• File size of 5.5 KB indicates a focused, readily downloadable resource.

Limitations

• The dataset is very small at 5.5 KB, indicating extremely limited scope, likely fewer than 100 data points.
• Contains only computational predictions without accompanying experimental validation data.
• No sample data or column descriptions are available to assess data structure.

Provenance

Source

Md. Nazmussakib Shuvo via figshare.

Collection Method

Computational prediction, likely from molecular docking or machine learning modeling.

Freshness

Last updated in April 2026, indicating a recent or future-dated upload.