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生物纳米相互作用:将蛋白质、多糖、脂质和核酸结合到磁性纳米颗粒上。

Bio-nano interactions: binding proteins, polysaccharides, lipids and nucleic acids onto magnetic nanoparticles.

作者信息

Abarca-Cabrera Lucía, Fraga-García Paula, Berensmeier Sonja

机构信息

Bioseparation Engineering Group, Department of Mechanical Engineering, Technical University of Munich, 85748, Garching bei München, Germany.

出版信息

Biomater Res. 2021 Apr 21;25(1):12. doi: 10.1186/s40824-021-00212-y.


DOI:10.1186/s40824-021-00212-y
PMID:33883044
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8059211/
Abstract

The major interest in nanoparticles as an application platform for biotechnology arises from their high surface-to-volume ratio. Iron oxide nanoparticles (IONPs) are particularly appealing due to their superparamagnetic behavior, which enables bioseparation using external magnetic fields. In order to design advanced biomaterials, improve binding capacities and develop innovative processing solutions, a thorough understanding of the factors governing organic-inorganic binding in solution is critical but has not yet been achieved, given the wide variety of chemical and physical influences. This paper offers a critical review of experimental studies of the interactions between low cost IONPs (bare iron oxides, silica-coated or easily-functionalized surfaces) and the main groups of biomolecules: proteins, lipids, nucleic acids and carbohydrates. Special attention is devoted to the driving forces and interdependencies responsible of interactions at the solid-liquid interface, to the unique structural characteristics of each biomolecular class, and to environmental conditions influencing adsorption. Furthermore, studies focusing on mixtures, which are still rare, but absolutely necessary to understand the biocorona, are also included. This review concludes with a discussion of future work needed to fill the gaps in knowledge of bio-nano interactions, seeking to improve nanoparticles' targeting capabilities in complex systems, and to open the door for multipurpose recognition and bioseparation processes.

摘要

纳米颗粒作为生物技术应用平台的主要吸引力源于其高比表面积。氧化铁纳米颗粒(IONPs)因其超顺磁性行为特别具有吸引力,这种行为使得能够利用外部磁场进行生物分离。为了设计先进的生物材料、提高结合能力并开发创新的加工解决方案,鉴于存在各种各样的化学和物理影响因素,全面了解溶液中有机 - 无机结合的控制因素至关重要,但目前尚未实现。本文对低成本IONPs(裸氧化铁、二氧化硅包覆或易于功能化的表面)与主要生物分子组(蛋白质、脂质、核酸和碳水化合物)之间相互作用的实验研究进行了批判性综述。特别关注了固 - 液界面相互作用的驱动力和相互依赖性、每种生物分子类别的独特结构特征以及影响吸附的环境条件。此外,还包括对混合物的研究,这类研究仍然很少,但对于理解生物冠层绝对必要。本综述最后讨论了填补生物 - 纳米相互作用知识空白所需的未来工作,旨在提高纳米颗粒在复杂系统中的靶向能力,并为多用途识别和生物分离过程打开大门。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/53d3dba66582/40824_2021_212_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/c9ba29b8b289/40824_2021_212_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/d9b7e200c818/40824_2021_212_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/53d3dba66582/40824_2021_212_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/c9ba29b8b289/40824_2021_212_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/d9b7e200c818/40824_2021_212_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14b5/8059211/53d3dba66582/40824_2021_212_Fig3_HTML.jpg

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[5]
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[6]
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[7]
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[8]
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[9]
Biocorona on Iron Oxide Nanoparticles in a Complex Biotechnological Environment: Analysis of Proteins, Lipids, and Carbohydrates.

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[10]
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本文引用的文献

[1]
The Biomolecular Corona of Lipid Nanoparticles for Gene Therapy.

Bioconjug Chem. 2020-9-16

[2]
Best practice in reporting corona studies: Minimum information about Nanomaterial Biocorona Experiments (MINBE).

Nano Today. 2019-10

[3]
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Sep Purif Technol. 2020-10

[4]
Experimental characterization and simulation of amino acid and peptide interactions with inorganic materials.

Eng Life Sci. 2017-7-26

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Preparation, surface functionalization and application of FeO magnetic nanoparticles.

Adv Colloid Interface Sci. 2020-4-24

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Design of Functional Magnetic Nanocomposites for Bioseparation.

Colloids Surf B Biointerfaces. 2020-7

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Front Chem. 2020-2-25

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Understanding the Lipid and Protein Corona Formation on Different Sized Polymeric Nanoparticles.

Sci Rep. 2020-1-24

[9]
Improved protein structure prediction using potentials from deep learning.

Nature. 2020-1-15

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Potential clinical applications of the personalized, disease-specific protein corona on nanoparticles.

Clin Chim Acta. 2019-10-31

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