glm-mda-diffusion
Minimum dissipation approximation: A fast algorithm for the prediction of diffusive properties of intrinsically disordered proteins
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Repository
Minimum dissipation approximation: A fast algorithm for the prediction of diffusive properties of intrinsically disordered proteins
Basic Info
- Host: GitHub
- Owner: RadostW
- License: gpl-3.0
- Language: Jupyter Notebook
- Default Branch: main
- Size: 125 KB
Statistics
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
glmmdadiffusion
or Globule-Linker-Model, Minimum-Dissipation-Approximation diffusion coefficient calculator

Minimum dissipation approximation is a fast algorithm for predicting the diffusive properties of intrinsically disordered proteins.
Try with Colab
Installation
bash
python3 -m pip install glm_mda_diffusion
Usage as module
Basic usage:
bash
python3 -m glm_mda_diffusion --sequence MGSS[HHHHHH]SSGLVPR
Sample output:
Computed GLM-MDA hydrodynamic radius [Ang]:
12.279165209438174
Usage as package
Basic usage
Python
import glm_mda_diffusion
glm_mda_diffusion.hydrodynamic_radius(sequence = "MGSS[HHHHHH]SSGLVPR")
Advanced usage (all options displayed with default values).
Options steric_radius and hydrodynamic_radius controll linker properties, while effective_density and hydrdation_thickness controll globular region properties.
```Python import glmmdadiffusion
glmmdadiffusion.proteinhydrodynamicradius( sequence="MGSS[HHHHHH]SSGLVPR", stericradius=1.9025, # Ang hydrodynamicradius=4.2, # Ang effectivedensity=0.52, # Da / Ang^3 hydrationthickness=3.0, # Ang ensemblesize=30, bootstraprounds=10, aminoacid_masses={ "A": 71.08, "C": 103.14, "D": 115.09, "E": 129.12, "F": 147.18, "G": 57.06, "H": 137.15, "I": 113.17, "K": 128.18, "L": 113.17, "M": 131.21, "N": 114.11, "P": 97.12, "Q": 128.41, "R": 156.2, "S": 87.08, "T": 101.11, "V": 99.14, "W": 186.21, "Y": 163.18, "Z": 0, "O": 0, "U": 0, "J": 0, "X": 0, "B": 0, }, # Da, ) ```
License
This software is licensed under GPLv3 License
Copyright (C) Radost Waszkiewicz (2023).
How to cite
Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation. Radost Waszkiewicz, Agnieszka Michaś, Michał K. Białobrzewski, Barbara P. Klepka, Maja K. Cieplak-Rotowska, Zuzanna Staszałek, Bogdan Cichocki, Maciej Lisicki, Piotr Szymczak, and Anna Niedźwiecka; J. Phys. Chem. Lett. (2024)
https://doi.org/10.1021/acs.jpclett.4c00312
bibtex
@article{Waszkiewicz_2024,
title = {Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation},
author = {Waszkiewicz, Radost and Michas, Agnieszka and Bia{\l}obrzewski, Micha{\l} K and Klepka, Barbara P and Cieplak-Rotowska, Maja K and Stasza{\l}ek, Zuzanna and Cichocki, Bogdan and Lisicki, Maciej and Szymczak, Piotr and Niedzwiecka, Anna},
year = 2024,
journal = {The Journal of Physical Chemistry Letters},
publisher = {ACS Publications},
volume = 15,
number = 19,
pages = {5024--5033}
}
Bibliography
Diffusion coefficients of elastic macromolecules. B. Cichocki, M. Rubin, A. Niedzwiecka, and P. Szymczak; J. Fluid Mech. (2019)
GRPY: An Accurate Bead Method for Calculation of Hydrodynamic Properties of Rigid Biomacromolecules. P. Zuk, B. Cichocki, and P. Szymczak; Biophys. J. (2018)
Pychastic: Precise Brownian dynamics using Taylor-Ito integrators in Python. R. Waszkiewicz, M. Bartczak, K. Kolasa, and M. Lisicki; SciPost Phys. Codebases (2023)
Owner
- Login: RadostW
- Kind: user
- Company: University of Warsaw
- Website: https://www.fuw.edu.pl/~rwaszkiewicz/
- Repositories: 8
- Profile: https://github.com/RadostW
Mathematician / physicist / computer scientist. PhD student studying soft matter at University of Warsaw
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use GLM-MDA, please cite it as below." authors: - family-names: "Waszkiewicz" given-names: "Radost" orcid: "https://orcid.org/0000-0002-0376-1708" - family-names: "Michaś" given-names: "Agnieszka" - family-names: "Białobrzewski" given-names: "Michał" - family-names: "Klepka" given-names: "Barbara" - family-names: "Cieplak-Rotowska" given-names: "Maja" - family-names: "Staszałek" given-names: "Zuzanna" - family-names: "Cichocki" given-names: "Bogdan" - family-names: "Lisicki" given-names: "Maciej" orcid: "https://orcid.org/0000-0002-6976-0281" - family-names: "Szymczak" given-names: "Piotr" - family-names: "Niedzwiecka" given-names: "Anna" title: "Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation" doi: 10.1021/acs.jpclett.4c00312 date-released: 2024-05-02 url: "https://doi.org/10.1021/acs.jpclett.4c00312" publisher: ACS year: 2024 journal: J. Phys. Chem. Lett
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Dependencies
- numpy *
- pygrpy *
- sarw_spheres *
- scipy *
- numpy *
- pygrpy *
- sarw_spheres *
- scipy *