GradPose
Welcome to the GitHub repository for the GradPose tool.
GradPose is a novel structural superimposition command-line tool and Python package for PDB files. GradPose uses gradient descent to incrementally approach the optimal rotation matrices (via quaternions) for alignment. It is memory efficient and enables for the quick alignment of thousands to millions of protein structures to a template structure while also providing exact control over which chain and specific residues to align. The tool is designed to overcome the limitations of classical superimposition algorithms, which are not equipped to handle the large number of PDB files produced by researchers today. Our method scales linearly with the number of residues and can also use batch matrix operations effectively even when there are amino-acid insertions or deletions. This makes it more efficient than traditional methods, which tend to scale exponentially with the number of residues and process the pbds individually. Furthermore, if a GPU is available, it can use CUDA acceleration.
This repository contains the source code and documentation for the GradPose tool. Please refer to the documentation for instructions on how to use the tool and for more information about its features and capabilities.
We hope that this tool will be useful to researchers and practitioners in the field of bioinformatics. If you have any questions or suggestions, please don't hesitate to open an issue or submit a pull request. We welcome contributions and feedback from the community.
Install
Install GradPose from PyPI with pip:
pip install gradpose
Examples of usage:
A folder containing N PDBs named 'example_pdb_folder'
gradpose -i example_pdb_folder
or
gradpose example_pdb_folder
The aligned proteins are automatically stored in the folder 'output'. Using another folder name, or overwriting the current folder without creating a second is possible using the -o option.
If the pdbs need to be aligned to a specific template:
gradpose -i example_pdb_folder -t template_example.pdb
If only a spedific part of the proten needs to be aligned, for exmaple, the first 10 amino-acids, animo-acids 12, and the the aminoacids ranging between (and including) 20 and 30:
gradpose -i example_pdb_folder -r 1:10 12 20:30
(Instructions for options coming soon.)
Metadata
Release files for gradpose 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| gradpose-0.1.tar.gz | 16.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gradpose-0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.6 kB
Release files / gradpose-0.1.tar.gz
| Download URL | gradpose-0.1.tar.gz |
|---|---|
| Size | 16.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5eddf3fc17dacad818dd06e952c67807e5a1dd29001f3896005307e634efd121
|
|
BLAKE2b-256 checksum How to use checksums |
7be6934007a23145bd78ce98b146b16eb3ee38ad0d471850bc0ba56a908cfaf5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.3
|
Release files / gradpose-0.1-py3-none-any.whl
| Download URL | gradpose-0.1-py3-none-any.whl |
|---|---|
| Size | 15.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
99e3955fd120cf54d32741d6acd392b094881e66f921a842ec6e273387f5cf67
|
|
BLAKE2b-256 checksum How to use checksums |
578eaaf9eee3beb3dcb229177c272a11dfc5bc97fe6cf2f247267fe011b7614d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.3
|
Security for gradpose 0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.