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Published June 21, 2021 | Version v1
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CG model of liquid-liquid phase behaviour of IDPs

  • 1. University of Copenhagen
  • 2. University of Copenhagen & CSIC-Institute for Advanced Chemistry of Catalonia

Description

Python code, Jupyter Notebooks and simulation data for reproducing the work of the scientific paper Accurate model of liquid-liquid phase behaviour of intrinsically-disordered proteins from data-driven optimization of single-chain properties by G. Tesei, T. K. Schulze, R. Crehuet, and K. Lindorff-Larsen.

Layout

  • analyses_and_figures.ipynb: Jupyter notebook to analyse all the simulation data and generate plots
  • calcKd.ipynb: Jupyter notebook to calculate B22 and Kd from two-chain simulations
  • calcConc.ipynb: Jupyter notebook to calculate csat and ccon from multi-chain molecular simulations in slab geometry
  • analysis_HP_scales.ipynb: Jupyter notebook to carry out the analysis of the hydrophobicity scales collected by Simm et al. DOI: 10.1186/s40659-016-0092-5
  • single-chain/code/: Python code to simulate and analyse simulations of a single IDP of a given sequence using HOOMD-blue
  • two-chain/code/: Python code to perform two-chain simulations and trajectory analyses of the optimised CG-IDPs model using HOOMD-blue
  • optimization/code/: Python code and bash script to optimise the CG-IDPs model against experimental radii of gyration and intramolecular NMR PRE data
  • multi-chain/code/: Python code to simulate and analyse multi-chain simulations of the CG-IDPs model in slab geometry

Please refer to the README files for further details. 
Python code and Jupyter notebooks are also available on GitHub at github.com/KULL-Centre/papers/tree/master/2021/CG-IDPs-Tesei-et-al.

Files

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Additional details

Funding

InMIND – Intervention in Neurodegenerative disorders via Mechanistic INsight into liquid-like Droplets 101025063
European Commission