Nanotoxicology: Experimental and Computational Perspectives
Chapter 12: Computational Approaches for Predicting Nanotoxicity at the Molecular Level
Published:03 Nov 2017
Special Collection: 2017 ebook collectionSeries: Issues in Toxicology
Lokesh Baweja, Alok Dhawan, 2017. "Computational Approaches for Predicting Nanotoxicity at the Molecular Level", Nanotoxicology: Experimental and Computational Perspectives, Alok Dhawan, Diana Anderson, Rishi Shanker
Download citation file:
The rapid growth in nanomaterials (NMs), enabled by technology, has increased the likelihood of their exposure to humans and the environment. Understanding the toxicity of NMs is crucial for facilitating applications of NMs in biological settings. Once administered in biological systems, NMs preferentially bind with proteins, and the lipid bilayer, which may have bioadverse or biocompatible affects. Therefore, understanding NM–biomolecule interactions and their consequences is crucial for predicting unprecedented responses elicited by NMs. Multidisciplinary approaches have been required to understand the effect of NMs on the structural organization of biomolecules and their outcomes. Computational approaches such as molecular dynamics (MD) simulations may enable the screening and design of safe NMs for human-related applications. Herein, we have reviewed the current computational approaches involving modelling of NMs and their interaction with biomolecules. The literature has suggested the potential of MD simulations in elucidating the effect of the physicochemical properties of NMs such as curvature, charge and surface chemistry on the conformation of biomolecules with atomic resolution. The results obtained from MD simulations are in close agreement with experiments, suggesting the usefulness of MD simulations in designing safer NMs for biological applications.