Protein-Protein Interaction Tool

Interaction Input Panel

Protein A Name

Protein B Name

Interaction Type

Cellular Context

Protein A Concentration (nM)

Protein B Concentration (nM)

Temperature (°C)

Sequence Identity (%)

Interface Area (Å²)

Expression Correlation (-1 to 1)

Co-localization Score (0 to 1)

Experimental Evidence (%)

Domain Compatibility (%)

Co-evolution Score (%)

PTM Compatibility (%)

Literature Support Count

Mutation Penalty (%)

Measured ΔG Optional (kcal/mol)

Leave blank to use the modeled free energy.

Use measured ΔG as working affinity

Reset

Example Data Table

Protein Pair	Type	Interface Area (Å²)	Evidence (%)	Co-localization	Sample Interpretation
EGFR × GRB2	Regulatory	1650	81	0.88	Strong signaling-associated interaction under activated conditions.
TP53 × MDM2	Stable	1435	89	0.84	Well-supported binding with strong regulatory consequences.
BCL2 × BAX	Transient	1240	68	0.73	Context-dependent interaction influenced by stress signaling.

Formula Used

This tool uses a weighted biological scoring model. It combines structural, evolutionary, localization, and evidence signals, then converts the working free energy into an estimated dissociation constant and occupancy value.

Normalized Inputs

n_corr = (expression correlation + 1) / 2

n_area = interface area / 3000

n_lit = min(literature count / 100, 1)

Modeled Free Energy

ΔG_model = -(2.2 + 3.6n_area + 1.9n_dom + 1.7n_exp + 1.3n_coev + 1.0n_coloc + 0.9n_corr + 0.8n_ptm + 0.7n_lit + 0.5n_seq) × interaction factor × context factor × (1 - 0.45m)

Binding Affinity and Occupancy

Kd = exp(ΔG / RT)

Occupancy = [Protein B] / ([Protein B] + Kd)

Confidence and Stability

Confidence = weighted evidence score × mutation penalty adjustment

Stability Index = occupancy, free energy strength, and interaction type blend

How to Use This Calculator

Enter the two protein names and choose the expected interaction type.
Add concentration, temperature, and structural evidence values.
Provide localization, co-evolution, literature, and mutation penalty inputs.
Optionally enter a measured free energy and enable the override box.
Click Calculate Interaction to display the result above the form.
Use the export buttons to save the summary in CSV or PDF format.

FAQs

1. What does the confidence score represent?

It summarizes how strongly the entered evidence supports a real interaction. Higher values mean stronger combined support from experiments, localization, domains, evolution, and literature.

2. Is the predicted Kd a laboratory measurement?

No. It is a model-based estimate unless you provide a measured free energy and enable the override option.

3. Why can occupancy be high even with moderate affinity?

Occupancy depends on both affinity and concentration. A moderate binder can still show high occupancy if the interacting partner concentration is sufficiently high.

4. What happens when co-localization is low?

The tool lowers biological support indirectly because proteins that rarely occupy the same compartment are less likely to interact in living cells.

5. How does mutation penalty affect the result?

It reduces modeled binding strength and confidence. Use larger penalties when interface mutations are expected to damage binding geometry or chemistry.

6. Can this tool be used for membrane proteins?

Yes. Choose the membrane context so the scoring reflects a more suitable environmental factor for that interaction setting.

7. Which fields influence stability the most?

Working free energy, partner concentration, and interaction type have the strongest direct effect on the stability index in this implementation.

8. Can I use this result in a publication?

Use it as a screening or reporting aid. Published conclusions should still rely on experimental validation, structural analysis, and statistical support.