<i>Metallicious</i> : Automated Force-Field Parameterization of Covalently Bound Metals for Supramolecular Structures
Metal ions play a central, functional, and structural role in many molecular structures, from small catalysts to metal-organic frameworks (MOFs) and proteins. Computational studies of these systems typically employ classical or quantum mechanical approaches or a combination of both. Among classical models, only the covalent metal model reproduces both geometries and charge transfer effects but requires time-consuming parameterization, especially for supramolecular systems containing repetitive units. To streamline this process, we introduce <i>metallicious</i>, a Python tool designed for efficient force-field parameterization of supramolecular structures. <i>Metallicious</i> has been tested on diverse systems including supramolecular cages, knots, and MOFs. Our benchmarks demonstrate that parameters accurately reproduce the reference properties obtained from quantum calculations and crystal structures. Molecular dynamics simulations of the generated structures consistently yield stable simulations in explicit solvent, in contrast to similar simulations performed with nonbonded and cationic dummy models. Overall, <i>metallicious</i> facilitates the atomistic modeling of supramolecular systems, key for understanding their dynamic properties and host-guest interactions. The tool is freely available on GitHub (https://github.com/duartegroup/metallicious).
Authors
- Bernadette Lee (ORCID: https://orcid.org/0000-0001-8548-6756)
- Tomasz K. Piskorz (ORCID: https://orcid.org/0000-0003-0716-6874)
- Shaoqi Zhan (ORCID: https://orcid.org/0000-0002-6383-1771)
- Fernanda Duarte (ORCID: https://orcid.org/0000-0002-6062-8209)
Institutions
- Uppsala University (SE)
- University of Oxford (GB)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2024-10-07
- DOI
- https://doi.org/10.1021/acs.jctc.4c00850
- Citations
- 3
- Primary Topic
- Supramolecular Chemistry and Complexes
- Type
- article
- Field-Weighted Citation Impact
- 0.75
Funders
- GlaxoSmithKline
- Merck
- Vertex Pharmaceuticals
- Agency for Science, Technology and Research
- Vetenskapsrådet
- Syngenta International
- Engineering and Physical Sciences Research Council
- John Fell Fund, University of Oxford