Unraveling Torsional Preferences: Comparative Analysis of Torsion Motif Torsional-Angle Distributions across...

Understanding the conformational ensemble of molecules in different environments is at the core of many research efforts. In conformer generation and geometry optimization, the complexity of the conformer space arises from the underlying torsion-angle distributions, which, in the case of force fields and some in silico conformer generators like ETKDG, are derived from accumulated torsion profiles for a predefined set of torsion motifs (termed ″torsion motif torsional-angle distributions″, tmTADs). Comparative studies of conformer generation and global optimization algorithms often neglect that tmTADs are sensitive to the environment they are extracted from, leading to comparisons of conformational ensembles and minimum-energy conformations from, e.g., crystal versus vacuum environments. Here, we present a large-scale comparative study of tmTADs across different environments, namely crystal, vacuum, water, and hexane, where the ensembles in the noncrystal environments are accessed through a computational workflow using the OpenFF-2.0.0 force field in combination with the graph neural network-based implicit solvent (GNNIS) approach. Our results show that the effects in the different environments, such as solvent-solute interactions in water and hexane, and packing effects in the crystal, produce strikingly distinct torsion distributions for most of the selected torsion motifs. In addition to qualitative and quantitative comparison of the extracted tmTADs, we also provide an automated fitting procedure that allows rapid parametrization of the distributions. These newly found parameters can be employed in a solvent-specific conformer generation procedure in the future.