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Nanomaterials in biological environment: a review of computer modelling studies

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Abstract

Nanotechnology is set to impact a vast range of fields, including computer science, materials technology, engineering/manufacturing and medicine. As nanotechnology grows so does exposure to nanostructured materials, thus investigation of the effects of nanomaterials on biological systems is paramount. Computational techniques can allow investigation of these systems at the nanoscale, providing insight into otherwise unexaminable properties, related to both the intentional and unintentional effects of nanomaterials. Herein, we review the current literature involving computational modelling of nanoparticles and biological systems. This literature has highlighted the common modes in which nanostructured materials interact with biological molecules such as membranes, peptides/proteins and DNA. Hydrophobic interactions are the most favoured, with π-stacking of the aromatic side-chains common when binding to a carbonaceous nanoparticle or surface. van der Waals forces are found to dominate in the insertion process of DNA molecules into carbon nanotubes. Generally, nanoparticles have been observed to disrupt the tertiary structure of proteins due to the curvature and atomic arrangement of the particle surface. Many hydrophobic nanoparticles are found to be able to transverse a lipid membrane, with some nanoparticles even causing mechanical damage to the membrane, thus potentially leading to cytotoxic effects. Current computational techniques have revealed how some nanoparticles interact with biological systems. However, further research is required to determine both useful applications and possible cytotoxic effects that nanoparticles may have on DNA, protein and membrane structure and function within biosystems.

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Acknowledgments

The authors would like to thank the Australian Research Council for providing funding for the project (DP0984565).

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Makarucha, A.J., Todorova, N. & Yarovsky, I. Nanomaterials in biological environment: a review of computer modelling studies. Eur Biophys J 40, 103–115 (2011). https://doi.org/10.1007/s00249-010-0651-6

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