ProSutra - Protein Modeling and Validation Pipeline

ProSutra provides a protein structure workflow with modeling, validation, and report generation utilities.
You can run it as a CLI pipeline, Streamlit app, or Electron desktop app.

Achievements

1. Aavishkar Research Convention (University of Mumbai, 2025-26)
   ProSutra was presented at the 20th Aavishkar Inter-Collegiate/Institute/Department Research Convention (Zonal Round) hosted at D.G. Ruparel College, Mumbai, under the Pure Sciences category (Postgraduate level). The project advanced to the podium round from Zone I (Mumbai I).
2. SRIJNA National Level Poster Competition
   ProSutra was presented at SRIJNA (GNIRD, Guru Nanak Khalsa College, Matunga, Mumbai) and received Second Place for research relevance, technical innovation, and presentation clarity.

Thesis

The thesis copy is available in this repository at:

Thesis/ProSutra_Thesis.pdf

User Installation Guide

1. Prerequisites

Install these first:

1. Python 3.10+ (3.11/3.12 recommended)
2. pip
3. Git
4. Optional for desktop app: Node.js 18+ and npm
5. External tools you plan to use:
   • Modeller
   • DSSP (mkdssp)
   • FreeSASA
   • VoroMQA (voronota-voromqa)
   • MolProbity / Phenix (if used in your flow)

2. Clone the project

git clone https://github.com/<your-username>/<your-repo>.git
cd <your-repo>

3. Create virtual environment and install Python dependencies

Windows PowerShell:

python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
pip install -r requirements.txt

Linux/macOS:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -r requirements.txt

4. Create local config files

Windows PowerShell:

Copy-Item .env.example .env
Copy-Item scripts/config.json.template scripts/config.json
Copy-Item streamlit_app/config.example.json streamlit_app/config.json

Linux/macOS:

cp .env.example .env
cp scripts/config.json.template scripts/config.json
cp streamlit_app/config.example.json streamlit_app/config.json

5. Fill credentials and tool paths

Update these local files:

1. .env
2. scripts/config.json
3. streamlit_app/config.json

Set:

1. Robetta username/password
2. QMEAN email/token
3. Paths to installed binaries (voromqa_path, dssp_path, freesasa_path, phenix_path if needed)

Run ProSutra

CLI pipeline (scripts/main.py)

Modeling:

python scripts/main.py model --sequence "YOUR_SEQUENCE_HERE" --job-name "my_protein" --modeller --robetta

Validation:

python scripts/main.py validate --pdb-file "/path/to/your/model.pdb" --project-name "validation_project"

Reporting:

python scripts/main.py report --model-dir "/path/to/your/results/validation_project/model_20260105_123456" --out-pdf "report.pdf"

Streamlit app

streamlit run streamlit_app/app.py

Electron app (optional)

cd electron-app
npm install
npm start

GitHub-Ready Setup

Before committing:

1. Keep local secrets in ignored files only:
   • streamlit_app/config.json (copy from streamlit_app/config.example.json)
   • scripts/config.json (copy from scripts/config.json.template)
   • .env (copy from .env.example)
2. Do not commit cookie/session files (cookies.json, electron-app/cookies.json)
3. Keep local heavy tool folders out of git (Modeller10.7/, VoroMQA/, output folders)

Upload To GitHub (First Time)

Run from project root:

git init
git branch -M main
git add .
git status
git commit -m "Initial commit: ProSutra pipeline"
git remote add origin https://github.com/<your-username>/<your-repo>.git
git push -u origin main