LIVIA — AlphaFold DB Monomer Subdomain Analysis

Region Pair Summary

Show iLIA/LIR/cLIR columns

Region i	Region j	iLIS	iLISA	LIS	cLIS	LIpDockQ	LIpDockQ2	iLIA	LIR (i/j)	cLIR (i/j)

↓ Download CSV

iLIS: ≥0.551 (1% FPR) ≥0.339 (5% FPR) ≥0.223 (10% FPR) <0.223 (below threshold)

Thresholds based on large-scale Y2H reference sets in yeast, fly, and human predicted using ColabFold. See Kim et al., 2026, for iLIS benchmark details.

Subdomain Interaction Map

Arcs represent subdomains (proportional to length). Lines connect cLIR residue pairs in physical contact.

labels length ticks pLDDT UniProt/Pfam TED label direction

Sequence Viewer

Light background = LIR (PAE ≤ 12 Å). Dark background with white text = cLIR (PAE ≤ 12 Å & Cβ ≤ 8 Å). Each region uses its own color.

Region & Domain Map

Auto-detected regions vs UniProt domains and TED domains (AlphaFold DB). Aligned to residue position.

3D Structure Viewer

Interactive 3D preview powered by Mol* (Sehnal et al. 2021). LIR regions shown as cartoons; cLIR residues highlighted. Drag to rotate, scroll to zoom. If the viewer appears empty, refresh the page.

Visualization Script

Local Interaction Residue (LIR) Display

Fill gaps ≤ residues | Min segment ≥ residues

Gap filling bridges short breaks for continuous cartoon. Min segment removes isolated LIR fragments shorter than the threshold.

Show complete structure (display all residues instead of selected regions only) Gray non-LIR (color non-interacting residues gray) Cutoffs

PAE cutoff (Å):

Cβ cutoff (Å):

Color Scheme

Presets — gradient (LIR light, cLIR dark)

Teal / Coral

Blue / Orange

Purple / Gold

Slate / Rose

Indigo / Tangerine

Green / Red

Presets — high contrast (all 4 colors distinct)

Cyan / Navy / Peach / Crimson

Sky / Indigo / Salmon / Red

Lime / Forest / Gold / Maroon

Mint / DarkTeal / Apricot / Burnt

Orchid / Purple / Yellow / Fire

Blue / Navy / Sage / Ember

Presets — solid

Teal / Coral

Blue / Orange

Purple / Gold

Slate / Rose

Steel / Wheat

Cornflower / Tomato

SkyBlue / Gold

LightGreen / Plum

Salmon / Teal

Presets — coloring modes

pLDDT

bychain

bypolymer

↓ Full structure .pdb ↓ .cxc · for full ↓ Partial structure .pdb ↓ .cxc · for partial

Full structure .pdb = full length (surfaces include the floppy N/C-terminal tails). Partial structure .pdb = trimmed to exactly the LIR segments shown (Fill gaps / Min segment honored) — clean surfaces for post-processing; residue numbers preserved so the script still colors correctly. Download one structure file.

Place the script and .pdb file in the same folder, then open the script in ChimeraX or PyMOL.

Per-Residue Intra-chain LIS & pLDDT

Per-residue metrics for the monomer prediction.

How to Use (Full guide)

Quick Start

Enter a UniProt ID (e.g., P28482) and click Fetch
Define two or more regions of interest by residue range
Click Calculate to compute interaction metrics
Review the PAE map, iLIS scores, and region pair table
Download the script and .pdb file, place them in the same folder, then open the script in ChimeraX (.cxc) or PyMOL (.pml)

AFM-LIS Metrics (Kim et al. 2024; Kim et al. 2026)

iLIS	integrated LIS — √(LIS × cLIS)
iLIA	integrated LIA — √(LIA × cLIA), geometric mean of interface area counts
iLISA	integrated LISA — iLIS × iLIA, overall binding strength
LIS	Local Interaction Score — normalized PAE confidence (0–1)
cLIS	contact-filtered LIS — restricted to direct contacts
LIR	Local Interaction Residues (PAE ≤ 12 Å)
cLIR	contact-filtered LIR (PAE ≤ 12 Å & Cβ ≤ 8 Å)

pDockQ family

LIpDockQ	the pDockQ formula computed only on cLIR pairs (PAE ≤ 12 Å and Cβ ≤ 8 Å), so contacts the PAE does not support no longer count (Kim & Perrimon, 2026)
LIpDockQ2	the pDockQ2 formula on cLIR pairs only, so a small confident interface is not diluted by a large, poorly placed contact surface (Kim & Perrimon, 2026)

Here the two regions of a monomer take the place of the two chains. Because their constants were fitted to DockQ on the original interfaces, LIpDockQ and LIpDockQ2 rank predictions; they are not DockQ estimates.

PAE (Predicted Aligned Error) measures how confidently the model predicts the relative position of two residues — lower values indicate higher confidence.