Background: Metal nanomaterials are widely used in various fields, including targeted therapy
and diagnosis. They are extensively used in targeted drug delivery and local treatments. However,
the toxicity associated with these materials could lead to severe adverse health effects.
Methods: In this study, we investigated the relationships between the toxicity and structures of metal
nanoparticles by using theoretical calculations and quantitative structure-activity relationships. Twenty
four physicochemical descriptors and toxicity data of 23 types of metal nanoparticles were selected as
samples, and a multiple linear regression model was established to obtain a toxicity prediction equation
with 5 descriptors with an R2
of 0.910. Structures of copper nanoparticles were designed based on the
model, and the structure with low toxicity was searched. The multiple nonlinear regression model was
used to further improve the prediction accuracy.
Results: The R2 values were 0.995 in the training set and 0.988 in the test set, which indicated that the
prediction accuracy improved. Based on the result of multiple linear regression, we designed copper
nanoparticles with low toxicity.
Conclusion: The study confirmed that the quantitative structure-activity relationship was a reasonable
method for predicting the toxicity and designing the structures with low toxicity of metal nanoparticles.