DisVis
About DisVis
DisVis is a Python package and command line tool to visualize and quantify the accessible interaction space of distance restrained binary biomolecular complexes. It performs a full and systematic 6 dimensional search of the three translational and rotational degrees of freedom to determine the number of complexes consistent with the restraints. In addition, it outputs the percentage of restraints being violated and a density that represents the center-of-mass position of the scanning chain corresponding to the highest number of consistent restraints at every position in space.
Requirements
- Python 3.11+
- A C compiler (to build the extension modules)
The Python packages DisVis needs are listed in pyproject.toml and installed
automatically by pip. GPU acceleration also needs an OpenCL 1.2+ enabled GPU
and the optional gpu packages (see INSTALLATION.md).
See the installation instructions and the manual, or try DisVis in your browser. DisVis is also available as a web service.
Licensing
If this software was useful to your research please cite us
Van Zundert, G.C.P. and Bonvin, A.M.J.J. (2015) DisVis: Visualizing and quantifying accessible interaction space of distance restrained biomolecular complexes. Bioinformatics 31, 3222-3224.
The software itself can be cited with its Zenodo DOI,
10.5281/zenodo.7775093, and
CITATION.cff
gives both references.
Apache License Version 2.0
The elements.py module is licenced under the MIT License, Copyright Christoph Gohlke.
Tested platforms
| Operating System | CPU single | CPU multi | GPU |
|---|---|---|---|
| Linux | Yes | Yes | Yes |
| MacOSX | Yes | Yes | Yes |
| Windows | Yes | Yes | No |
The GPU version has been tested on: NVIDIA GeForce GTX 1080 Ti and RTX 6000 Ada for Linux, and Apple M2 Pro for macOS (and, with the earlier Python 2 version, NVIDIA GeForce GTX 680 and AMD Radeon HD 7730M for Linux)
Reference results and timings for the test cases, on CPUs and GPUs, are in
test-cases/README.md.
Contributing
See CONTRIBUTING.md for the development setup, code style, tests and pull
requests.
AI Declaration
Large language models (LLM) were used in this repository since v3.0.0, for the port to Python 3 and the later changes. The changes were always reviewed by a human before being merged. See aidecl.yaml for machine-readable details of the LLM usage.