Building up of the predictive quantitative structure-property/activity relationships (QSPRs/QSARs) for nanomaterials usually are impossible owing to the complexity of the molecular architecture of the nano materials. Simplified molecular input-line entry system (SMILES) is a tool to represent the molecular architecture of "traditional" molecules for "traditional" QSPR/QSAR. The quasi-SMILES is a tool to represent features (conditions and circumstances), which accompany the behavior of nanomaterials. Having, the training set and validation set, so-called quantitative feature-property relationships (QFPRs), based on the quasi-SMILES, one can build up model for zeta potentials of metal oxide nanoparticles for situations characterized by different features. (C) 2016 Elsevier B.V. All rights reserved.