Metadata-Version: 2.1
Name: glm-mda-diffusion
Version: 1.1
Summary: Minimum dissipation approximation: A fast algorithm for the prediction of diffusive properties of intrinsically disordered proteins
Home-page: https://github.com/RadostW/glm-mda-diffusion/
Author: Radost Waszkiewicz
Author-email: radost.waszkiewicz@gmail.com
License: GNU GPLv3
Project-URL: Documentation, https://github.com/RadostW/glm_mda_diffusion
Project-URL: Source, https://github.com/RadostW/glm_mda_diffusion
Platform: UNKNOWN
Description-Content-Type: text/markdown
License-File: LICENSE

# glm_mda_diffusion

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

![Banner](sequence_and_shape_banner.png)

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

# 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 glm_mda_diffusion

glm_mda_diffusion.protein_hydrodynamic_radius(
    sequence="MGSS[HHHHHH]SSGLVPR",
    steric_radius=1.9025,  # Ang
    hydrodynamic_radius=4.2,  # Ang
    effective_density=0.52,  # Da / Ang^3
    hydration_thickness=3.0,  # Ang
    ensemble_size=30,
    bootstrap_rounds=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

*Minimum dissipation approximation: A fast algorithm for the prediction of diffusive properties of intrinsically disordered proteins.* 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. (submitted 2023)

# 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; Biophysical Journal (2018)

 - *Pychastic: Precise Brownian dynamics using Taylor-Ito integrators in Python.* R. Waszkiewicz, M. Bartczak, K. Kolasa, and M. Lisicki;  SciPost Phys. Codebases (2023)


