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 , a Python tool designed for efficient force-field parameterization of supramolecular structures. 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, 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).
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http://dx.doi.org/10.1021/acs.jctc.4c00850 | DOI Listing |
J Phys Chem B
January 2025
The Njord Centre, Department of Physics, University of Oslo, Sem Sælands vei 24, NO-0316 Oslo, Norway.
Water participates in countless processes on Earth, and the properties of mineral surfaces can be drastically changed in the presence of water. For example, the fracture toughness of silica glass is reduced by 25% for water-filled cracks than for dry cracks [ , , 9341-9354]. An accurate description of water is therefore essential for modeling the behavior of minerals in aqueous environments and, in particular, for modeling dynamic processes such as fracture, where the mechanical response of water may play an important role.
View Article and Find Full Text PDFAlchemical free energy methods using molecular mechanics (MM) force fields are essential tools for predicting thermodynamic properties of small molecules, especially via free energy calculations that can estimate quantities relevant for drug discovery such as affinities, selectivities, the impact of target mutations, and ADMET properties. While traditional MM forcefields rely on hand-crafted, discrete atom types and parameters, modern approaches based on graph neural networks (GNNs) learn continuous embedding vectors that represent chemical environments from which MM parameters can be generated. Excitingly, GNN parameterization approaches provide a fully end-to-end differentiable model that offers the possibility of systematically improving these models using experimental data.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.
Molecular dynamics simulations are pivotal in elucidating the intricate properties of biological molecules. Nonetheless, the reliability of their outcomes hinges on the precision of the molecular force field utilized. In this perspective, we present a comprehensive review of the developmental trajectory of the Amber additive protein force field, delving into researchers' persistent quest for higher precision force fields and the prevailing challenges.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemistry - Ångström Laboratory, Uppsala University, SE-75120 Uppsala, Sweden.
Isonitrile-derivatized amino acids are emerging as highly effective infrared (IR) probes for investigating the structures and dynamics of hydrogen (H)-bonds. These probes enable the quantification of chemical exchange processes in solute-solvent complexes via two-dimensional IR spectroscopy and hold significant promise for site-specific dynamic studies within proteins. Despite their potential, theoretical models that elucidate the solvatochromism of isonitriles remain underdeveloped.
View Article and Find Full Text PDFJ Chem Phys
December 2024
Department of Chemistry, University of Chicago, Chicago, Illinois 60637, USA.
Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics.
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