CG model of liquid-liquid phase behaviour of IDPs

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