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Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

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Related Experiment Video

Updated: Mar 7, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Multiscale Modelling of Bionano Interface.

Hender Lopez¹, Erik G Brandt², Alexander Mirzoev²

¹School of Physics, Complex and Adaptive Systems Lab, University College Dublin, Belfield, Dublin 4, Ireland.

Advances in Experimental Medicine and Biology

|February 8, 2017

Summary

This summary is machine-generated.

This study introduces a coarse-grained model to predict nanoparticle-protein interactions and their effects on biological membranes. The framework aids in understanding nanoparticle-protein corona formation and potential toxicity.

Keywords:

Cell membrane Coarse-grained molecular dynamics Nanoparticle Protein corona Toxicity

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Last Updated: Mar 7, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

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Published on: April 12, 2019

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Published on: September 11, 2018

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

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Published on: November 12, 2014

Area of Science:

Computational chemistry
Biophysics
Nanomaterial science

Background:

Nanoparticle-biomolecule interactions are crucial for understanding nanoparticle behavior in biological systems.
Predicting the nanoparticle-protein corona and its impact on toxicity remains a challenge.

Purpose of the Study:

To develop a coarse-grained modeling framework for nanoparticle-biomolecule interfaces.
To predict protein adsorption and orientation on nanoparticles.
To investigate nanoparticle interactions with lipid membranes for toxicity assessment.

Main Methods:

Coarse-grained modeling using united-atom representations of lipids and proteins.
Implicit solvent model parameterized from all-atom structures and experimental data.
Homogeneous spheres for nanoparticles interacting via size-dependent central forces.

Main Results:

Accurate prediction of adsorption energies for human blood plasma proteins on nanoparticles.
Determination of preferred protein orientation upon adsorption.
Successful modeling of nanoparticle interaction with lipid bilayers.

Conclusions:

The framework enables ranking proteins by binding affinity for predicting nanoparticle-protein corona.
Provides mechanistic insights into nanoparticle-membrane interactions and potential toxicity.