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. 2023 Jan 23;62(4):e202214477.
doi: 10.1002/anie.202214477. Epub 2022 Dec 16.

Automated and Efficient Generation of General Molecular Aggregate Structures

Christoph Plett  1 , Stefan Grimme  1
Affiliations

Automated and Efficient Generation of General Molecular Aggregate Structures

Christoph Plett et al. Angew Chem Int Ed Engl. .

Abstract

Modeling intermolecular interactions of complex non-covalent structures is important in many areas of chemistry. To facilitate the generation of reasonable dimer, oligomer, and general aggregate geometries, we introduce an automated computational interaction site screening (aISS) workflow. This easy-to-use tool combines a genetic algorithm employing the intermolecular force-field xTB-IFF for initial search steps with the general force-field GFN-FF and the semi-empirical GFN2-xTB method for geometry optimizations. Compared with the alternative CREST program, aISS yields similar results but with computer time savings of 1-3 orders of magnitude. This allows for the treatment of systems with thousands of atoms composed of elements up to radon, e.g., metal-organic complexes, or even polyhedra and zeolite cut-outs which were not accessible before. Moreover, aISS can identify reactive sites and provides options like site-directed (user-guided) screening.

Keywords: Global Optimization; Non-Covalent Interaction; Quantum Chemistry; Supramolecular Chemistry.

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Conflict of interest statement

There are no conflicts to declare.

Figures

Figure 1
Figure 1
Schematic depiction of the aISS algorithm.
Figure 2
Figure 2
The lowest energy structures for an example set of complexes resulting from the aISS algorithm.
Figure 3
Figure 3
The best structure of the rhodium‐organic cuboctahedra inside the Pd48L96(BF4)96 Goldberg polyhedron found with the aISS//GFN‐FF algorithm. Hydrogen atoms are omitted for clarity. Pd is depicted in light blue, Se in orange, B in pinkish, and Rh in light sea green.
Figure 4
Figure 4
Addition of oxonium to the micelle. Possible interaction sites are marked in blue. The experimentally observed protomer found correctly by aISS is marked in yellow.
Figure 5
Figure 5
Favored interaction site (A) and two directed interaction sites (B, C) of a sodium cation and a tetrahydrofuran‐2,5‐dicarboxylic acid at a faujasite‐based zeolite according to the aISS//GFN2‐xTB algorithm. Hydrogen atoms are omitted for clarity. Sodium cations are depicted in purple, silicon in beige.
Figure 6
Figure 6
Favored interaction site (A) and to the amine directed interaction site (B) according to the aISS//GFN2‐xTB algorithm. Pd is depicted in dark turquoise, Br in dark red, and P in orange.
See this image and copyright information in PMC

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