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metadata
title: B-cell Epitope Prediction Server
emoji: 🧬
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.36.2
app_file: app.py
pinned: false
license: mit

🧬 B-cell Epitope Prediction Server

A web-based interface for B-cell epitope prediction using the ReCEP model.

📋 How to Use

1. Input Protein Structure

Choose one of two input methods:

Option A: PDB ID

  • Enter a 4-character PDB ID (e.g., "5I9Q")
  • Specify the chain ID (e.g., "A")

Option B: Upload PDB File

  • Upload a PDB structure file (.pdb or .ent format)
  • Optionally specify a custom PDB ID
  • Specify the chain ID

2. Configure Prediction Parameters

Basic Parameters:

  • Chain ID: Target protein chain (default: A)

Advanced Parameters (Optional):

  • Radius: Spherical region radius in Ångstroms (default: 19.0)
  • Top-k Regions: Number of top regions to analyze (default: 7)
  • Encoder: Protein encoder type (ESM-C only now)
  • Device Configuration: CPU or GPU processing (CPU Only now)
  • Threshold: Custom prediction threshold (leave empty for auto, required)

3. View Results

The application provides:

Prediction Summary

  • Protein information (PDB ID, chain, length, sequence)
  • Prediction statistics (epitope count, coverage rate, etc.)
  • Top-k region centers
  • Predicted epitope residues
  • Binding region residues

Download Options

  • JSON Results: Complete prediction data with metadata
  • CSV Results: Residue-level predictions for analysis
  • 3D Visualization: Interactive HTML file with 3Dmol.js viewer

4. 3D Visualization

The downloadable HTML file includes:

  • Display Modes:
    • Predicted Epitopes: Highlight predicted epitope residues
    • Probability Gradient: Color residues by prediction confidence
  • Representation Styles: Cartoon, Surface, Stick, Sphere
  • Interactive Controls: Rotate, zoom, pan, reset view, save image

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

Note: This is a research tool for B-cell epitope prediction. Results should be validated through experimental methods for clinical or commercial applications.