Computational methods to predict the reactivity of nanoparticles through structure–property relationships

Abstract

Importance of the field: Innovative biomedical techniques operational at the nanoscale level are being developed in therapeutics, including advanced drug delivery systems and targeted nanotherapy. Given the large number of nanoparticles that are being developed for possible biomedical use, the use of computational methods in the assessment of their properties is of key importance.

Areas covered in this review: Among the in silico methods, quantum mechanics is still used rarely in the study of nanostructured particles. This review provides an overview of some of the main quantum mechanics methods that are already used in the assessment of chemicals. Furthermore, classical tools used in the chemistry field are described, to show their potential also in the pharmacological field.

What the reader will gain: The current status of computational methods in terms of availability and applicability to nanoparticles, and recommendations for further research are highlighted.

Take home message: The in silico modelling of nanoparticles can assist in targeting and filling gaps in knowledge on the effects of these particular particles. Computational models of the behaviour of nanoparticles in biological systems, including simulation models for predicting intermolecular interactions and harmful side effects, can be highly valuable in screening candidate particles for potential biomedical use in diagnostics, imaging and drug delivery.

Keywords::

• carbon nanoneedle
• chemical hardness
• computational modelling
• conceptual density functional theory
• electrophilicity
• energy decomposition analysis
• Fukui function
• nanomedicine
• structure–property relationship

Notes

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