Project files provided as supporting information to the manuscript "Detailed insight in the chignolin folding process from maximally informative low-resolution representations of its isocommittor hypersurfaces"

Project files provided as supporting information to the manuscript "Detailed insight in the chignolin folding process from maximally informative low-resolution representations of its isocommittor hypersurfaces" March 18, 2026 Alessia Guadagnin Pattaro, Roberto Menichetti, Raffaello Potestio ================================== The repository is organized as follows: - `DATA_ANALYSIS`: contains all the jupyter notebook to reproduce all the plots reported in the paper. The folder is further divided into the following subfolders. - `0_DATA`: contains the raw/processed data needed to run the notebooks - `2_C_3_B_FREE_ENERGY`: calculation of free energy-related plots (Figures 5 and 10) - `3_A_1_MEOW_FULL_FOLDED_UNFOLDED`: analysis of the results of mapping entropy optimization workflow applied on the full trajectory, and on the folded and unfolded trajectories separated by FONC and RMSD (Figures 6, 7, SI-4) - `3_A_2_PCA`: PCA analysis on triplets of amino acids (Figure 8). Warning: it takes about ~40 minutes to completely run - `3_B_1_MEOW_E_20IH`: analysis of the results of mapping entropy optimization workflow applied to the transition region (Figures 9, SI-5, SI-6) - `3_B_2_MSD_KMEDOIDS`: application of K-medoids clustering to the MSD matrices (Figures SI-10 and SI-11). Warning: for notebooks 0 and 1 use the dedicated conda environment sklearn_extra, provided in the folder with install instructions. - `3_B_3_ih_1_ih_12_SUBSETS`: analysis of the division of IH_1 and IH_{12} into two clusters according to MSD and d(D3, G7) (Figures SI-12, SI-13, SI-15, SI-16, 12) - `3_B_4_FREE_ENERGY_PROGRESSION`: free energy landscapes of the whole committor range and IH_0 (Figures SI-7, SI-8, SI-9) - `3_B_5_FONC_H_BONDS`: FONC decomposition (`FONC.ipynb`, generating Figures 11 and SI-14) and analysis of H-bonds formed by Thr6 (`hbonds_thr6.ipynb`, generating Figure SI-17) - `SI_ANALYSIS_FULLTRAJ`: RMSF of chignolin trajectory (Figure SI-3) - `SI_RMSD_F_U`: division of RMSD of chignolin trajectory into folded and unfolded, produces the data for `3_A_1_MEOW_FULL_FOLDED_UNFOLDED` (Figures SI-1 and SI-2) - `EXCOGITO_RESULTS`: the raw data obtained after the optimization of mapping entropy on the systems where it was applied (the prefix refers to the paper section and the `DATA_ANALYSIS` folder where the data was processed): - `3_A_1_FONC_FOLDED` - `3_A_1_FONC_UNFOLDED` - `3_A_1_FULLTRAJ` - `3_A_1_SI_RMSD_FOLDED` - `3_A_1_SI_RMSD_UNFOLDED` - `3_B_1_MEOW_E_20IH` - `3_B_3_MEOW_E_ih_1` - `3_B_3_MEOW_E_ih_12` All the notebooks can be run with ease by installing a conda environment with the provided yml file in the following way: `conda env create --file chignolin2026.yml` Then select the environment named `chignolin2026` when choosing a kernel for your notebook. For any inquiry or issue contact [e-mail] or [e-mail]