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Quantitative structure-activity/property relationships (QSAR/QSPR) approaches that have been applied with success in a number of studies are currently used as indispensable tools in the computational analysis of nanomaterials. Evolution of nano-QSAR methodology to the ranks of novel field of knowledge has resulted in the development of new so-called “nano-descriptors” and extension of the statistical approaches domain. This brief review focuses on the critical analysis of advantages and disadvantages of existing methods of nanoparticles’ representation and their analysis in framework of structure-activity relationships. It summarizes recent QSAR/QSPR studies on inorganic nanomaterials. Here the authors describe practices for the QSAR modeling of inorganic nanoparticles, existing datasets, and discuss applicable descriptors and future perspectives of this field. About 50 different (Q)SAR/SPR models for inorganic nanomaterials have been developed during the past 5 years. An analysis of these peer reviewed publications shows that the most popular property of nanoparticles modeled via QSAR is their toxicity towards different bacteria, cell lines, and microorganisms. It has been clearly shown how nano-QSAR can contribute to the elucidation of toxicity mechanisms and different physical properties of inorganic nanomaterials.

Review of Current and Emerging Approaches for Quantitative Nanostructure-Activity Relationship Modeling: The Case of Inorganic Nanoparticles