Molecular dynamics simulations are a widely applied tool to investigate systems of varying complexity, ranging from isolated molecules to supercomplexes consisting of several thousands of atoms. Extracting mechanistic insights from the obtained extensive datasets frequently presents a challenge. Here, we introduce the program package MonicaMD, a versatile and efficient tool targeted towards the analysis of molecules and molecular clusters in the context of dynamics simulations. MonicaMD provides clear and especially modular access to structural information, with a focus on internal and collective variables, as well as electrostatic embedding information. Key functionalities are the extraction of structural and electrostatic information in a machine-learning ready format as well as a user friendly workflow including dimensionality reduction, automatic feature-space generation and a templating functionality for generated grids in order to be readily used in conjuction with quantum chemical software. This will allow the user to bridge the strengths of dynamics simulations and the chemical accuracy of quantum mechanics.
Ferdinand Pointner