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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.07819 |
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| _version_ | 1866914711074766848 |
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| author | Rouse, Ian Power, David Subbotina, Julia Lobaskin, Vladimir |
| author_facet | Rouse, Ian Power, David Subbotina, Julia Lobaskin, Vladimir |
| contents | 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 modelling approach. Here, we present the NPCoronaPredict open-source software package: a suite of software tools to enable this prediction for complex multi-component 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 parameterisations for nanomaterials and organic molecules. We describe the underlying theoretical background and the package functionality from the design of multi-component NPs through to the evaluation of the corona. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_07819 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | NPCoronaPredict: A computational pipeline for the prediction of the nanoparticle-biomolecule corona Rouse, Ian Power, David Subbotina, Julia Lobaskin, Vladimir Mesoscale and Nanoscale Physics Biological Physics Computational Physics 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 modelling approach. Here, we present the NPCoronaPredict open-source software package: a suite of software tools to enable this prediction for complex multi-component 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 parameterisations for nanomaterials and organic molecules. We describe the underlying theoretical background and the package functionality from the design of multi-component NPs through to the evaluation of the corona. |
| title | NPCoronaPredict: A computational pipeline for the prediction of the nanoparticle-biomolecule corona |
| topic | Mesoscale and Nanoscale Physics Biological Physics Computational Physics |
| url | https://arxiv.org/abs/2403.07819 |