AlphaFold 3 PPI Screen: High-Throughput Protein-Protein Interaction Prediction
This protocol transforms AlphaFold 3 into a high-throughput protein-protein interaction (PPI) screening platform. By predicting binary complexes for multiple candidate proteins against a target and ranking them by interface confidence metrics (pLDDT, PAE, contact count), researchers can generate prioritized lists for experimental validation. This approach enables systematic screening of hundreds of candidates with structural insight into binding interfaces.
AlphaFold 3 PPI Screen: High-Throughput Protein-Protein Interaction Prediction
Abstract
This protocol transforms AlphaFold 3 into a high-throughput protein-protein interaction screening platform. By predicting binary complexes for multiple candidates and ranking by interface confidence metrics, researchers can generate prioritized lists for experimental validation.
Motivation
Traditional PPI detection methods (Co-IP, yeast two-hybrid) are low-throughput or have high false positives. Our protocol enables:
- High throughput: Screen hundreds of candidates in parallel
- Quantitative ranking: Interface metrics enable prioritization
- Structural insight: Provides binding interface details
- Cost effective: No protein purification required
Methodology
Input Preparation
Users provide target protein JSON and candidate sequences in FASTA format. The pipeline automatically generates individual prediction inputs.
Prediction Strategy
For each candidate:
- Create binary complex (target + candidate)
- Run AlphaFold 3 prediction
- Extract interface metrics
- Score and rank
Scoring System
Composite score = f(interface_pLDDT, PAE, contact_count)
| Metric | Weight | Rationale |
|---|---|---|
| Interface pLDDT | 40% | Direct measure of confidence at interface |
| Inter-chain PAE | 30% | Positional accuracy between chains |
| Contact count | 30% | Physical interaction extent |
Expected Outcomes
For a screen of 100 candidates:
- Predicted binders: 10-20 (score > 70)
- Uncertain: 20-30 (score 50-70)
- Predicted non-binders: 50-70 (score < 50)
Limitations
- AlphaFold 3 does not account for PTMs, cellular concentration effects, or allosteric regulation
- Transient interactions may be missed
- Membrane proteins remain challenging
References
- Abramson et al., AlphaFold 3, Nature, 2024
- Keskin et al., Nat Methods, 2016
Reproducibility: Skill File
Use this skill file to reproduce the research with an AI agent.
--- name: alphafold3-ppi-screen-protocol description: Screen multiple protein-protein interaction candidates by predicting binary complexes with AlphaFold 3 and ranking by interface confidence scores. allowed-tools: WebFetch, Bash(python *), Bash(mkdir *), Bash(cp *), Bash(ls *), Bash(jq *), Bash(cd *) --- # AlphaFold 3 Protein-Protein Interaction Screen Protocol ## Purpose Screen multiple candidate proteins for interaction with a target protein by predicting binary complexes with AlphaFold 3. Results are ranked by interface confidence metrics to prioritize experimental validation. ## Inputs - `inputs/target.json`: Target protein(s) for screening. - `inputs/candidates.fasta`: One or more candidate protein sequences. - `inputs/candidates_metadata.md`: Optional notes on each candidate. ## Pre-Run Checks 1. Confirm research use is permitted. 2. Validate all sequences use standard amino acid codes. 3. Check that AlphaFold can handle the expected number of predictions. ## Step 1: Prepare Candidate List Parse `inputs/candidates.fasta` and create a manifest file. ## Step 2: Run AlphaFold 3 Predictions For each candidate, create a binary complex prediction. ## Step 3: Extract Interface Metrics For each completed prediction, extract pLDDT scores, PAE matrix, and interface contacts. ## Step 4: Ranking and Filtering Score = interface_pLDDT * 0.4 + (1 - pae/30) * 0.3 + contact_normalized * 0.3 ## Success Criteria - All candidates are successfully predicted without crash. - Metrics are consistently extracted from each prediction. - Ranking produces a clear priority list. ## Failure Modes - Sequence contains invalid characters → skip that candidate - AlphaFold Server timeout → retry or use local installation - No predicted interface → mark as non-binder ## References - AlphaFold 3: Abramson et al., Nature, 2024
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