Browser-based tools for analyzing protein-protein interactions from structure predictions. All analysis runs locally in your browser — no data leaves your device and no installation is needed.
https://flyark.github.io/LIVIA/
upd1–dome (Drosophila JAK-STAT pathway, orthologous to human IL-6/gp130) — ChimeraX visualization generated by LIVIA script (iLIS: 0.529, ipTM: 0.57)
Left: PAE map (A: upd1, B: dome) showing confident interaction region (blue). Right: ChimeraX structure with LIR (light) and cLIR (dark) coloring.
- Drag & drop — upload prediction files directly into your browser (.zip, .gz, .xz, .cif, .pdb, .json, .npz, .npy)
- Auto-detection — automatically identifies the prediction platform from filenames
- Interaction residue detection — LIR (PAE ≤ 12Å) and cLIR (PAE ≤ 12Å & Cβ ≤ 8Å)
- Confidence scoring — iLIS, iLIA, iLISA, ipSAE, ipTM per chain pair
- Interactive visualizations — PAE/LIS/cLIS heatmaps, sequence viewer, linear contact map, chord diagram
- 3D structure viewer — Mol* viewer with LIR/cLIR coloring
- ChimeraX and PyMOL scripts — color presets (gradient, solid, high contrast, pLDDT, bychain)
- TED domain annotations — domain boundaries from AlphaFold DB displayed alongside detected regions
- CSV download — full metrics with LIR/cLIR residue indices, LIpLDDT/cLIpLDDT per chain
| Page | Description |
|---|---|
| Prediction Analysis | Upload and analyze predictions from AlphaFold3, ColabFold, Boltz, Chai-1, OpenFold3 |
| FlyPredictome | Drosophila PPI analysis from FlyPredictome |
| Ortholog Interactome | Non-fly predictions from FlyPredictome ortholog search |
| AFDB Dimer | Dimer analysis from AlphaFold DB |
| Monomer Subdomain | Intramolecular domain interaction analysis from AlphaFold DB |
| Tutorials | Step-by-step visual walkthroughs with auto-advancing screenshots |
| About | Metric definitions, color schemes, and references |
Prediction Analysis auto-detects the platform from uploaded files:
AlphaFold3 · AlphaFold2 · ColabFold · Boltz-1/2 · Chai-1 · OpenFold3
- iLIS —
sqrt(LIS × cLIS)— integrated Local Interaction Score (Kim et al. 2025) - LIS — average confidence of residue pairs with PAE ≤ 12Å (Kim et al. 2024)
- cLIS — contact-filtered LIS (PAE ≤ 12Å & Cβ ≤ 8Å)
- iLIA —
sqrt(LIA × cLIA)— integrated interaction area - iLISA —
iLIS × iLIA - ipSAE — interaction prediction Score from Aligned Errors (Dunbrack, 2025)
- LIR / cLIR — Local Interaction Residues / contact-filtered LIR
- LIpLDDT / cLIpLDDT — average pLDDT of LIR / cLIR residues per chain
For large-scale batch analysis without a browser, use the command-line tool from AFM-LIS. It supports all the same platforms, auto-detects the prediction format, and outputs CSV.
python lis.py /path/to/predictions/ # auto-detect, process all models
python lis.py /path/to/predictions/ -w 4 # parallel with 4 CPUs
python lis.py alphafold3_output.zip # zip input
python lis.py /path/to/predictions/ -v # verbose error detailsFeatures: .gz/.xz decompression, incremental CSV output (safe to interrupt and resume), progress bar with ETA, sorted output by name and rank.
See AFM-LIS for full documentation and output CSV column reference.
- Tested on Chrome and Safari (macOS/iOS).
- Each prediction platform may produce different confidence calibrations. The iLIS ≥ 0.223 threshold was established using ColabFold/AlphaFold-Multimer predictions. Other platforms may require adjusted thresholds.
- AFM-LIS — Python framework and CLI for iLIS/LIS calculation
- FlyPredictome — Large-scale Drosophila PPI predictions (>1.7 million)
- AlphaFold Protein Structure Database — Predicted protein structures
- Kim, A.-R. et al. (2025). A Structure-Guided Kinase–Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome. bioRxiv. https://doi.org/10.1101/2025.10.10.681672
- Kim, A.-R. et al. (2024). Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer. bioRxiv. https://doi.org/10.1101/2024.02.19.580970
If you use LIVIA in your research, please cite:
@misc{livia,
author = {Kim, Ah-Ram},
title = {LIVIA: Local Interaction Visualization and Analysis},
year = {2025},
publisher = {GitHub},
url = {https://github.com/flyark/LIVIA}
}MIT