Metal oxide (MeO) nanoparticles (NPs) have become common in our everyday life over the past years. However, there is still an important knowledge gap regarding their toxicological effect and, in particular, how the different physical and chemical properties of MeO NPs influence their cytotoxicity and the subsequent implications for risk assessment. This work analyses the physicochemical properties of MeO NPs that have been reported as relevant for risk assessment and the experimental and theoretical methods used to obtain them. The surface, physical and chemical properties of NPs have been critically revisited to shed light on the features that can cause toxicity. Due to the large number of existing MeO NPs, in silico studies are necessary to get a good understanding of the NPs' physicochemical properties; therefore this review focuses on the state of the art computational methods used to model MeO NP toxicity: QSAR and QSTR models and their alternative approaches provide a better understanding of MeO NP biological toxicity in organisms.

Understanding the toxicological mechanisms of food contaminants is critical for assessing risks to human health. This review comprehensively examines their adverse effects, tracing the pathway from molecular initiation to systemic organ-level damage. A central focus is placed on the growing trust on computational methods as ethical and practical alternatives to traditional animal testing. The discussion encompasses a multi-scale assessment, detailing atomic-level interactions through Density Functional Tight Binding Molecular docking and Molecular Dynamics (MD) simulations, analyses of toxicity pathway, and prediction of systemic fate using Physiologically Based Pharmacokinetic (PBPK) modeling. We further explore how these in silico insights are integrated with experimental data to build predictive models, including Quantitative Structure-Activity Relationship and machine learning frameworks. Ultimately, this review aims to inform the development of effective strategies for mitigating contaminant risks, thereby advancing public health objectives and supporting the 3Rs principles (Replacement, Reduction, and Refinement) in toxicological science.

Metal oxides (MOs) are the key materials in applications of biomedicine industrial technologies due to their versatile features. Knowing their possible toxicity level is crucial given some specific environments, particularly in water. We have learned that their reactivity almost depends on the electronic structure on the surface of the MOs. Thus, a detailed understanding of the electronic structure on the surface and its reactivity processes is useful for determining the toxicity in MOs and defining good descriptive parameters. We simulated the interaction of ZnO and TiO₂ slab models with water and checked their geometric and electronic structure changes from the bulk of the material to the water interface. To this end, we used the density functional tight binding theory coupled with finite temperature molecular dynamics. We have observed the interaction of water with the MO surface in terms of electronic and geometric parameters for several conditions, such as temperature, hydrogenated or clean, and exposed surface. In doing so, we provide molecular-level insights into topographical and electronic processes on MO surfaces besides finding critical points on the surface that can explain the initialization of dissolution processes. Thus, we reveal information about potential toxicity descriptors in a systematic analysis approach.