Density Functional Theory in the Prediction of Mutagenicity: A Perspective

16Citations
Citations of this article
37Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

As a field, computational toxicology is concerned with using in silico models to predict and understand the origins of toxicity. It is fast, relatively inexpensive, and avoids the ethical conundrum of using animals in scientific experimentation. In this perspective, we discuss the importance of computational models in toxicology, with a specific focus on the different model types that can be used in predictive toxicological approaches toward mutagenicity (SARs and QSARs). We then focus on how quantum chemical methods, such as density functional theory (DFT), have previously been used in the prediction of mutagenicity. It is then discussed how DFT allows for the development of new chemical descriptors that focus on capturing the steric and energetic effects that influence toxicological reactions. We hope to demonstrate the role that DFT plays in understanding the fundamental, intrinsic chemistry of toxicological reactions in predictive toxicology.

Cite

CITATION STYLE

APA

Townsend, P. A., & Grayson, M. N. (2021). Density Functional Theory in the Prediction of Mutagenicity: A Perspective. Chemical Research in Toxicology, 34(2), 179–188. https://doi.org/10.1021/acs.chemrestox.0c00113

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free