https://github.com/elkins/synth-saxs

A lightweight Python library for simulating Small-Angle X-ray Scattering (SAXS) profiles from protein coordinates.
https://github.com/elkins/synth-saxs

biophysics protein saxs simulation structural-biology

Last synced: 22 days ago
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A lightweight Python library for simulating Small-Angle X-ray Scattering (SAXS) profiles from protein coordinates.

• Host: GitHub
• URL: https://github.com/elkins/synth-saxs
• Owner: elkins
• Created: 2026-05-19T02:48:17.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2026-05-27T00:35:03.000Z (28 days ago)
• Last Synced: 2026-05-27T02:21:03.882Z (28 days ago)
• Topics: biophysics, protein, saxs, simulation, structural-biology
• Language: Python
• Homepage: https://elkins.github.io/synth-saxs/
• Size: 654 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 🧬 synth-saxs: Differentiable SAXS Simulation

[![PyPI version](https://img.shields.io/pypi/v/synth-saxs.svg)](https://pypi.org/project/synth-saxs/)

[![Supported Python versions](https://img.shields.io/pypi/pyversions/synth-saxs.svg)](https://pypi.org/project/synth-saxs/)

[![Tests](https://github.com/elkins/synth-saxs/actions/workflows/test.yml/badge.svg)](https://github.com/elkins/synth-saxs/actions/workflows/test.yml)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

[![JAX](https://img.shields.io/badge/Accelerated_by-JAX-blue.svg)](https://github.com/google/jax)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

`synth-saxs` is a JAX-powered simulator for back-calculating Small-Angle X-ray Scattering (SAXS) profiles from protein coordinates.

---

### 🧪 For Structural Biologists

*   **Guinier Analysis:** Automatically calculate Radius of Gyration ($R_g$) and forward scattering $I(0)$.

*   **Hydration Modeling:** Explicit support for solvation shell effects on scattering intensity.

### 🤖 For Machine Learning Geeks

*   **Differentiable Debye:** The entire Debye formula is implemented in JAX, allowing gradients to flow from the scattering profile back to atomic positions.

*   **Fast Integration:** JIT-compilable kernels for sub-millisecond SAXS prediction from large structures.

---

## 📦 Installation

```bash

pip install synth-saxs

```

## 📜 License

Distributed under the MIT License. See `LICENSE` for more information.