A package for FRET Efficiency prediction of protein structures and trajectories, based on the Rotamer Library Approach (RLA). Can be installed with pip.
Project description
FRETpredict
Overview
A package for FRET Efficiency prediction of protein structures and trajectories, based on the Rotamer Library Approach (RLA).
Installation
To install FRETpredict, use the PyPI package:
pip install FRETpredict
or clone the repo and install locally:
git clone https://github.com/KULL-Centre/FRETpredict.git
cd FRETpredict
pip install -e .
The software requires Python 3.6+.
Testing
pip install pytest
python -m pytest
Code Example
import MDAnalysis
from FRETpredict import FRETpredict
# Create a MDAnalysis.Universe object for the protein structure.
u = MDAnalysis.Universe('tests/test_systems/Hsp90/openHsp90.pdb')
# Create instance of the FRETpredict class
FRET = FRETpredict(protein=u, residues=[452, 637], chains=['A', 'B'], temperature=293,
fixed_R0=True, r0=6.3, electrostatic=True,
libname_1='AlexaFluor 594 C1R cutoff30',
libname_2='AlexaFluor 568 C1R cutoff30',
output_prefix='E30_594_568')
# Run FRET efficiency calculations.
FRET.run()
Tutorials
-
Tutorial_FRETpredict_Hsp90 : Jupyter Notebook with simple tutorials on how to use the code on the Hsp90 system.
-
Generate new rotamer libraries : Jupyter Notebook on how to create and add new rotamer libraries.
Structure
FRETpredict/
├─ FRETpredict/
│ ├─ lib/
│ │ ├─ R0/
│ ├─ FRET.py
│ ├─ lennardjones.py
│ ├─ libraries.py
│ ├─ R0_calculation.py
│ ├─ rotamer_libraries.py
│ ├─ utils.py
│ ├─ __init__.py
├─ tests/
| ├─ test_Hsp90.py
│ ├─ test_systems/
│ │ ├─ Hsp90/
│ ├─ tutorials/
│ │ ├─ genLIB/
│ │ ├─ test/
│ │ ├─ Tutorial_FRETpredict_Hsp90.ipynb
│ │ ├─ Tutorial_generate_new_rotamer_libraries.ipynb
├─ LICENSE
├─ README.md
├─ setup.py
Contributors
Daniele Montepietra (@Monte95)
Project details
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