ROCKET User Guide

Documentation, installation instructions, and tutorials for ROCKET

These resources aim to guide users through refinement of X-ray 💎 and cryo-EM ❄️ protein structures with ROCKET.

The workflow includes OpenFold structure prediction, pre- and post-processing with Phenix, and the core ROCKET refinement functionality 🚀

More details in our preprint.

GitHub - rs-station/ROCKET: AI-powered macromolecular refinementGitHub

Install ROCKET

Installing ROCKET

Tutorial1: Score Subsampled MSAs

Latent State of a Human Serpin with MSA Subsampling

Tutorial2: Refine A Single Chain in CryoET Map

Low Resolution GroEL Sub-Tomogram Average

Tutorial3: Setup with Xray Intensity Data

Launch with Your Own X-ray Data

Tutorial4: Setup with CryoEM/ET Half Maps

Launch with Your Own Cryo-EM Data

APIs

API

Citing

@article{fadini2025alphafold,
  title={AlphaFold as a Prior: Experimental Structure Determination Conditioned on a Pretrained Neural Network},
  author={Fadini, Alisia and Li, Minhuan and McCoy, Airlie J and Terwilliger, Thomas C and Read, Randy J and Hekstra, Doeke and AlQuraishi, Mohammed},
  journal={bioRxiv},
  year={2025}
}