NPCoronaPredict: A Computational Pipeline for the Prediction of the Nanoparticle–Biomolecule Corona

The corona of a nanoparticle immersed in a biological fluid is of key importance to its eventual fate and bioactivity in the environment or inside live tissues. It is critical to have insight into both the underlying bionano interactions and the corona composition to ensure biocompatibility of novel engineered nanomaterials. A prediction of these properties in silico requires the successful spanning of multiple orders of magnitude of both time and physical dimensions to produce results in a reasonable amount of time, necessitating the development of a multiscale modeling approach. Here, we present the NPCoronaPredict open-source software package: a suite of software tools to enable this prediction for complex multicomponent nanomaterials in essentially arbitrary biological fluids, or more generally any medium containing organic molecules. The package integrates several recent physics-based computational models and a library of both physics-based and data-driven parametrizations for nanomaterials and organic molecules. We describe the underlying theoretical background and the package functionality from the design of multicomponent NPs through to the evaluation of the corona.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2024-09-26
DOI
https://doi.org/10.1021/acs.jcim.4c00434
Citations
7
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
1.64

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article

NPCoronaPredict: A Computational Pipeline for the Prediction of the Nanoparticle–Biomolecule Corona

Ian Rouse, Julia Subbotina, Vladimir Lobaskin, David Power
7 citations
Journal of Chemical Information and Modeling
Protein Structure and Dynamics
1.64
article

NPCoronaPredict: A Computational Pipeline for the Prediction of the Nanoparticle–Biomolecule Corona

Ian Rouse, Julia Subbotina, Vladimir Lobaskin, David Power
article en
7 citations

Abstract

The corona of a nanoparticle immersed in a biological fluid is of key importance to its eventual fate and bioactivity in the environment or inside live tissues. It is critical to have insight into both the underlying bionano interactions and the corona composition to ensure biocompatibility of novel engineered nanomaterials. A prediction of these properties in silico requires the successful spanning of multiple orders of magnitude of both time and physical dimensions to produce results in a reasonable amount of time, necessitating the development of a multiscale modeling approach. Here, we present the NPCoronaPredict open-source software package: a suite of software tools to enable this prediction for complex multicomponent nanomaterials in essentially arbitrary biological fluids, or more generally any medium containing organic molecules. The package integrates several recent physics-based computational models and a library of both physics-based and data-driven parametrizations for nanomaterials and organic molecules. We describe the underlying theoretical background and the package functionality from the design of multicomponent NPs through to the evaluation of the corona.

Journal of Chemical Information and ModelingVol. 64(19)
University College Dublin (IE)
Science Foundation Ireland, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 16%
Protein Structure and Dynamics
1.64
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NPCoronaPredict: A Computational Pipeline for the Prediction of the Nanoparticle–Biomolecule Corona — Ian Rouse, Julia Subbotina, et al. · Journal of Chemical Information and Modeling (2024) | TGRS Research Map | TGRS