PyConSolv: A Python Package for Conformer Generation of (Metal-Containing) Systems in Explicit Solvent

Abstract

We introduce PyConSolv, a freely available Python package that automates the generation of conformers of metal- and nonmetal-containing complexes in explicit solvent, through classical molecular dynamics simulations. Using a streamlined workflow and interfacing with widely used computational chemistry software, PyConSolv is an all-in-one tool for the generation of conformers in any solvent. Input requirements are minimal; only the geometry of the structure and the desired solvent in xyz (XMOL) format are needed. The package can also account for charged systems, by including arbitrary counterions in the simulation. A bonded model parametrization is performed automatically, utilizing AmberTools, ORCA, and Multiwfn software packages. PyConSolv provides a selection of preparametrized solvents and counterions for use in classical molecular dynamics simulations. We show the applicability of our package on a number of (transition-metal-containing) systems. The software is provided open source and free of charge.

A human-machine interface for automatic exploration of chemical reaction networks

“…The modular infrastructure of SCINE in general, SCINE CHEMOTON in particular, and of our STEERING WHEEL algorithm form a suitable basis for further extensions of individual parts of automated workflows, such as more advanced Network Expansion Steps (e.g., reaction trials featuring multiple electronic structure models 31 , systematic network refinement with more accurate electronic structure methods 68 or with automated microsolvation approaches 178 – 181 , or more exhaustive conformer generation 174 , 182 – 184 ). Moreover, inclusion of Selection Steps that do not rely on human input, such as general heuristics derived from first principles 71 , results from existing explorations 72 , machine learning 185 , path information 12 , or kinetic simulations 69 , 186 – 192 is straightforward and will further enhance the capabilities of the STEERING WHEEL, which has been implemented into our graphical user interface SCINE HERON, which is available free of charge and open source.…”

From Data to Chemistry: Revealing Causality and Reaction Coordinates through Interpretable Machine Learning in Supramolecular Transition Metal Catalysis

“…81 To generate an appropriate starting structure the system was equilibrated and a 100ns MM/MD simulation was carried out, using the multistep protocol implemented in PyConSolv. 19 We conducted 152 simulation runs using the QM/MM MD protocol of the reductive elimination step, employing GFN2-xTB as QM method. Among these runs, 142 simulations captured the reductive elimination step and were utilized for energy and structural analysis.…”

“…While the majority of computational mechanistic studies are performed with a single structure, with conformer search recently gaining popularity 14,16,17 thanks to easily accessible tools, 18,19 a transition to structure ensembles provides a more complete picture. 14,17 Another crucial aspect which needs to be considered is solvation.…”

“…While widely used implicit solvation models provide remarkable performance, [20][21][22] they cannot describe explicit interactions between solute and solvent. In combination with dispersion corrections and a small basis set, they often favour very compact structures with many intramolecular bonds 7,19 -a poor representation of a solvated system. It is therefore crucial to include explicit solvation in any realistic model, ideally via a full condensed phase calculation or through microsolvation.…”

Solvate Suite: A Command-Line Interface for Molecular Simulations and Multiscale Microsolvation Modeling

“…From theoretical and computational standpoints, a crucial aspect of the microsolvation treatment lies in the arrangement of solvent molecules around the solute. This process can be carried out manually − or through automated methods, − which are often employed specifically in cases where water serves as the solvent molecule.…”