Structural Review
Model quality, interface alternatives, residue hypotheses, and explicit uncertainty when structures are suitable.
From interaction hypothesis to test plan
Protein–Protein Interaction Prediction & Validation
Have a candidate protein pair, a list of possible partners, or an interface question? CD ComputaBio connects computational prioritization with project-specific experimental validation to identify plausible partners, test binding, and examine the interface or functional effect. Each step answers a defined research question and records what remains uncertain.
Partner prioritizationInterface assessmentBinding validationFunctional testing
Start with your scientific question
Can We Support Your PPI Project?
The suitable workflow depends on whether you are evaluating a specified pair, searching for partners, or investigating an interface. Partial inputs are acceptable for an initial feasibility review.
| Your Question | You Provide | What CD ComputaBio Can Do | You Receive |
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| Do these two proteins plausibly interact? |
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| Which partners should we test first? |
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| Where might the interface be? |
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A gene network association, a predicted complex, and direct physical binding are different kinds of evidence. The project report labels them separately.
Illustrative output, not client data
See What a PPI Project Delivers
A useful result shows why a candidate pair moves forward, what the model does and does not support, and the experiment needed to resolve the question.
01Candidate Pairs
02Context Check
03Independent Evidence
04Model Review
05Test Priorities
Decision Summary
Which pairs to test, which need more context, and which should be deprioritized for this program.
Validation Plan
An assay plan with controls; for an agreed integrated project, binding and cellular readouts with quality checks and result interpretation.
From a Complex Hypothesis to Testable Evidence
We can pair structural visualization with an interpretable interface review, then identify experiments that could challenge the proposed interaction.
Protein–Protein Interface Assessment
Interaction metrics
| ΔG | −29.1 kcal/mol | Kd | 4.6 × 10−22 M |
|---|---|---|---|
| IC charged–charged | 43 contacts | IC charged–polar | 47 contacts |
| IC charged–apolar | 123 contacts | IC polar–polar | 14 contacts |
| IC polar–apolar | 48 contacts | IC apolar–apolar | 64 contacts |
| NIS charged | 26.27 | NIS apolar | 41.45 |
Interface and structure summary
| Chain 1 | A | Atoms / residues | 429 / 104 |
|---|---|---|---|
| Chain 1 surface | 59,962 Ų | Chain 2 | B |
| Atoms / residues | 477 / 137 | Chain 2 surface | 72,520 Ų |
| Interface area | 4,440.2 Ų | ΔG (second entry) | −37.6 kcal/mol |
| P-value | 0.493 | H-bonds | 28 |
| Salt bridges | 14 | Disulfides | 0 |
| CSS | 0.000 |
Illustrative values from the supplied figure. IC = interfacial contacts; NIS = non-interacting surface. Calculation methods are unspecified; Kd is not a measured affinity.
| Integrated project stage | Illustrative deliverable | Decision supported |
|---|---|---|
| Computational triage | Ranked pairs or candidate interfaces with traceable evidence and uncertainty. | Which pairs or residues merit laboratory testing? |
| Wet-lab validation | Assay methods, controls, quality checks, and binding or cellular readouts as agreed in scope. | Which hypotheses are supported under the tested conditions? |
| Integrated interpretation | Prediction-versus-experiment comparison and a go/no-go or redesign recommendation. | What should the team do next? |
Delivery scope: Candidate-level network analysis and detailed interface modeling are separate work packages; the report format and methods are agreed at project scoping.
Three ways to engage
Choose the Project That Fits Your Decision
Start with a partner list, a defined pair, or a broader program. Computational and experimental stages are selected from the evidence you already have and the conclusion you need.
Partner Prioritization
Your question: Which possible partners should we test first?
Dry lab: Combine curated interaction evidence, expression and localization context, pathway information, and available omics data into a traceable shortlist.
Wet lab: Select a discovery or targeted confirmation approach, such as Y2H, AP–MS, proximity labeling, or co-IP, according to the biological system and project scope.
You receive: Ranked partners, reasons for inclusion or exclusion, a primary and backup test set, and a suitable validation plan.
Discuss partner prioritizationComplex & Interface Assessment
Your question: How might the pair interact, and which residues matter?
Dry lab: Review complex models and docking hypotheses, model confidence, alternate interfaces, and candidate hotspot or mutation effects; add MD only for a suitable dynamic question.
Wet lab: Confirm binding with an appropriate biophysical method, then challenge the interface with targeted mutations and relevant controls.
You receive: Qualified interface models, residue-level hypotheses, a mutation priority list, and a binding or functional test strategy.
Explore interface modelingPrediction-to-Validation Program
Your question: Which interaction is real and relevant enough to advance?
Dry lab: Integrate candidate nomination, complex assessment, assay results, and follow-up interpretation across decision points.
Wet lab: Sequence binding, cellular association, and functional assays with controls; refine the test set as results arrive.
You receive: An evidence chain from hypothesis to experimental result, a supported go/no-go recommendation, and the next study plan.
Plan an integrated projectAlready have a modeled complex? Molecular dynamics may be useful for selected stability and conformational questions. It cannot turn an unsupported complex into proof of binding.
Integrated capabilities
Computational Analysis & Wet-Lab Validation
We build an evidence chain around the project question. Computational methods prioritize hypotheses and experimental methods test binding, cellular association, or functional impact. Each technique is chosen after feasibility review.
Computational Analysis
Use existing information and structural models to narrow the experimental search space.
- Partner discovery: Review curated PPI records, pathway relationships, omics evidence, expression, and subcellular localization.
- Complex assessment: Evaluate predicted complexes and docking poses against biological constraints, confidence metrics, and alternative orientations.
- Interface and variant analysis: Map candidate contacts, conserved regions, hotspots, and mutation hypotheses; use MD when the question requires conformational sampling.
- Experimental interpretation: Compare positive, negative, and discordant assay outcomes; update candidate rankings and recommend the next test.
Wet-Lab Validation
Select an experimental readout that answers the specific question and supports interpretable controls.
- Partner discovery: Y2H, affinity purification–MS, or proximity labeling may be suitable for different scales and cellular contexts; association and proximity are interpreted separately.
- Direct binding: SPR, BLI, MST, or ITC can assess a defined pair when purified proteins and assay conditions are suitable.
- Cellular association: Co-IP, proximity assays, or live-cell interaction reporters can examine behavior in a relevant biological setting.
- Interface and function: Targeted mutagenesis, binding reassessment, and a disease- or pathway-relevant functional readout challenge the proposed mechanism.
Scope depends on feasibility. Protein expression, assay format, controls, cell model, and sample availability are reviewed before wet-lab execution is included. A proximity or co-complex result is not automatically reported as direct physical binding.
Interpretation that avoids overclaiming
What Counts as Interaction Evidence?
Different observations support different claims. The report makes this distinction visible before a testing recommendation is made.
| Evidence type | What it can support | What it cannot establish alone |
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| Co-expression, pathway, or network association | Biological relevance and a reason to investigate a pair. | Direct physical contact. |
| Curated PPI database or literature record | A prior report that can be checked for assay type, organism, and conditions. | That the interaction occurs in your specific system. |
| Predicted complex or docking model | A possible geometry and candidate interface residues, after quality review. | Binding affinity, cellular occurrence, or causal mechanism. |
| Binding or cellular experiment | Evidence appropriate to the assay and its controls. | Every mechanistic detail without orthogonal follow-up. |
Decision-gated workflow
From Candidate Pair to Validation Plan
Frame the decision
Clarify the organism, cell or disease context, pair or candidate panel, and experimental decision the project must support.
Verify identities and evidence
Check protein IDs, isoforms, domains, localization, literature, interaction records, and existing assay or omics data.
Choose appropriate models
Use sequence, network, or complex-structure approaches only where the inputs and question justify them; review model confidence and failure modes.
Prioritize and explain
Rank hypotheses using independent evidence, label conflicts and uncertainty, and nominate a primary and backup test set.
Validate and learn
For an integrated project, run the agreed binding, cellular, or functional assays with controls. Compare results with predictions, explain discordance, and update the next decision.
From prediction to evidence
Choose an Experiment That Answers the Question
The wet-lab stage is chosen from the specific claim the project must test: direct binding, cellular association, interface dependence, or functional consequence. Results are interpreted together with the computational evidence.
Physical Binding
Consider an orthogonal method such as SPR, BLI, MST, or ITC where protein quality and expected interaction range make it suitable.
Cellular Context
Use co-immunoprecipitation, proximity, or perturbation readouts to ask whether an association is observed in the relevant cellular system.
Interface Challenge
Test selected residue changes or competing partners with matched expression and folding controls before inferring an interface mechanism.
Interpretation Controls
Include negative and positive controls, orthogonal assays where possible, and a plan to investigate discordant results.
The exact assays, controls, and execution arrangements are confirmed during project scoping; method availability depends on the protein pair and biological system.
Why CD ComputaBio
A Project Team for PPI Decisions
Context First
Species, cell type, isoform, and the biological question determine whether an interaction hypothesis is meaningful.
Methods Fit the Question
Network inference, pair review, docking, and MD address different questions. We scope only the analyses the project can support.
Uncertainty Is Visible
Data provenance, model confidence, indirect associations, and contradictory evidence appear in the decision rationale.
Testing Is Planned
The final recommendation connects a testable question to suitable controls, experimental results, and the next decision.
FAQs
Frequently Asked Questions
No. A complex model proposes a possible structure. Its confidence, biological context, and alternative explanations must be reviewed, and an appropriate experiment is needed to establish interaction.
Yes, if there is enough sequence and biological context to scope a useful review. We may use existing predicted models, curated data, and evidence integration; the conclusion will state the limits of those inputs.
Pair or partner prediction asks whether two proteins are plausible interaction candidates. Protein–protein docking investigates possible three-dimensional arrangements for a defined pair. A plausible docked pose does not establish that the pair interacts in cells.
We can scope a context-specific prioritization using a defined protein list and suitable expression, perturbation, pathway, or curated interaction evidence. Dataset quality and experimental test capacity influence the workflow.
For a suitable pair and defensible model, interface analysis can nominate residues for testing. Predicted contacts and computational hotspot scores are hypotheses until challenged by mutagenesis and appropriate binding or functional controls.
That depends on whether the goal is direct binding, cellular association, or functional consequence. SPR or BLI, co-immunoprecipitation, proximity assays, and mutagenesis answer different questions and require distinct controls.
No. We select partner discovery, structural analysis, and experimental methods according to the question and input quality. We explain the methods and limits in the agreed project scope.
A project can connect computational prioritization to selected binding, cellular, or functional validation. Feasibility, assay format, controls, and execution arrangements are agreed during scoping; not every technique suits every protein pair.
Provide protein names or sequences, species and isoforms, the biological system, your existing observations, and the decision you need to make. An initial feasibility discussion can start before every file is ready.
Scientific Context
Interaction databases and predicted complexes are valuable starting points. Their evidence and confidence require context-specific interpretation.
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