Electronic Notebook: Anion-Cation Contrast of Caffeine Solvation in Salt Solutions

This is supporting information for the scientific manuscript by Hervø-Hansen et al. (Physical Chemistry Chemical Physics, 2022, doi: 10.1039/D1CP04129K) on the solvation free energy of caffeine in various electrolyte solutions using the energy-representation theory of solvation in combination with all-atom simulations. All figures within the analysis are publication ready and can be reproduced by running the provided Jupyter notebooks (.ipynb). For running the simulation we recommend you clone the repository, else the original dataset can be analyzed through the use of Binder, which will open the notebook in an executable environment and can be accessed here.

Layout

• PDB_files PDB files for various chemical species utilized.
• Simulations Directory containing raw ermod results and processed results. The directory is also used for location of trajectories and corresponding analysis upon reproduction.
• force_fields Directory containing force parameters files (in gromacs format) for the various chemical species utilized.
• images Directory containing publication ready figures and images imported in the Juypter notebooks.
• Simulations.ipynb Jupyter notebook for running molecular dynamics simulations using OpenMM for the KB and OPLS force fields.
• Analysis.ipynb Jupyter notebook for analysis of simulations using the KB force field and production of publication ready figures.
• Analysis_OPLS.ipynb Jupyter notebook for analysis of simulations using the OPLS force field and production of publication ready figures.
• Auxiliary.py Python file containing assisting functions to conduct non-parametric bootstrapping and calculate mean volumes over multiple trajectories.
• environment.yml Conda environment file to recreate the simulation environment. The environment most importantly contains Numpy, Scipy, OpenMM, OpenMMTools, parmed, mdtraj, and Packmol.

Usage

To open the notebook, install Python via Miniconda and make sure all required packages are loaded by issuing the following terminal commands

   conda env create -f environment.yml
   conda activate caffeine
   jupyter-notebook