Functionalized metal nanoparticles (NPs) are macromolecular assemblies with a tunable physicochemical profile that makes them interesting for biotechnology, materials science, and energy conversion. In this regard, molecular simulations offer a way to scrutinize the structural and dynamical features of monolayer-protected NPs and their interactions with relevant matrices. Previously, we developed NanoModeler, a webserver that automates the preparation of functionalized gold NPs for atomistic molecular dynamics (MD) simulations. Here, we present NanoModeler CG (www.nanomodeler.it), a new release of NanoModeler that now also allows the building and parametrizing of monolayer-protected metal NPs at a coarse-grained (CG) resolution. This new version extends our original methodology to NPs of eight different core shapes, conformed by up to 800,000 beads and coated by eight different monolayer morphologies. The resulting topologies are compatible with the Martini force field but are easily extendable to any other set of parameters parsed by the user. Finally, we demonstrate NanoModeler CG's capabilities by reproducing experimental structural features of alkylthiolated NPs and rationalizing the brush-to-mushroom phase transition of PEGylated anionic NPs. By automating the construction and parametrization of functionalized NPs, the NanoModeler series offers a standardized way to computationally model monolayer-protected nanosized systems.
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http://dx.doi.org/10.1021/acs.jctc.2c01029 | DOI Listing |
PLoS Comput Biol
January 2025
Department of Physical-Chemistry, Complutense University of Madrid, Madrid, Spain.
Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Central European Institute of Technology, Masaryk University, Kamenice 5, CZ-62500 Brno, Czech Republic.
Understanding the molecular mechanisms of pore formation is crucial for elucidating fundamental biological processes and developing therapeutic strategies, such as the design of drug delivery systems and antimicrobial agents. Although experimental methods can provide valuable information, they often lack the temporal and spatial resolution necessary to fully capture the dynamic stages of pore formation. In this study, we present two novel collective variables (CVs) designed to characterize membrane pore behavior, particularly its energetics, through molecular dynamics (MD) simulations.
View Article and Find Full Text PDFJ Phys Chem B
January 2025
Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, United States.
ModeHunter is a modular Python software package for the simulation of 3D biophysical motion across spatial resolution scales using modal analysis of elastic networks. It has been curated from our in-house Python scripts over the last 15 years, with a focus on detecting similarities of elastic motion between atomic structures, coarse-grained graphs, and volumetric data obtained from biophysical or biomedical imaging origins, such as electron microscopy or tomography. With ModeHunter, normal modes of biophysical motion can be analyzed with various static visualization techniques or brought to life by dynamics animation in terms of single or multimode trajectories or decoy ensembles.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Dipartimento di Bioscienze, Università degli Studi di Milano, Milan 20133, Italy.
The computational study of ligand binding to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by thermodynamic integration, and to probe binding mechanisms, including the description of protein conformational dynamics. The advantages of MD come at a high computational cost, which limits its use.
View Article and Find Full Text PDFJ Chem Phys
December 2024
Institute for Theoretical Physics IV, University of Stuttgart, Heisenbergstr. 3, 70569 Stuttgart, Germany.
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