Cheminformatics methods are enabling the rational design of nanomaterials with the desired properties. These methods such as Quantitative Nanostructure–Activity Relationships (QNAR) are capable of forecasting the biological activities of nanomaterials based on their structural and/or experimental characteristics. After a brief summary of the basic principles of QNAR modeling, the strengths and limitations of these models regarding their prediction performances, interpretability, and transferability will be discussed. Then, we will show the results regarding our most recent modeling study involving more than 120 functionalized carbon nanotubes. Finally, we will present two key perspectives for the use of molecular modeling on nanomaterials, especially the modeling of mixtures (<i>e.g.,</i> chemical planarization slurries) and the use of molecular dynamics simulations in complement of QNAR models.

QNAR models for the rational design of nanomaterials

253rd National Meeting (2017)

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