glm-mda-diffusion

Minimum dissipation approximation: A fast algorithm for the prediction of diffusive properties of intrinsically disordered proteins

https://github.com/radostw/glm-mda-diffusion

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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
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Created about 2 years ago · Last pushed 10 months ago
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Readme License Citation

README.md

glmmdadiffusion

or Globule-Linker-Model, Minimum-Dissipation-Approximation diffusion coefficient calculator

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Minimum dissipation approximation is a fast algorithm for predicting the diffusive properties of intrinsically disordered proteins.

Try with Colab

Open In 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

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

requirements.txt pypi
  • numpy *
  • pygrpy *
  • sarw_spheres *
  • scipy *
setup.py pypi
  • numpy *
  • pygrpy *
  • sarw_spheres *
  • scipy *