Nanoinformatics-Based, Predictive Toxicological Screening of Nanomaterials

Nanoparticles have gained substantial attention in view of their distinctive physicochemical attributes and widespread applications in several fields. However, the prompt development and extensive consumption of nanotechnology may provoke inexorable diffusion of nanoparticles into the environment, associated with potential toxic effects. Hence, the preliminary toxicological screening of nanomaterials becomes indispensable for their harmless utilization and ecological safety. Nanotoxicology deals with the study of undesirable effects attributed to nanoparticles. It includes the nature, intensity, and characteristics of toxic insult caused by individual or combined use of nanoparticles. Nanoinformatics represents a systematic approach for collecting, organizing, validating, storing, sharing, visualizing, modeling, and analyzing data from nanotechnology processes and materials. The conventional nanotoxicity assessment methods using in vitro assays or animal models are time-consuming and relatively expensive, whereas computational modeling of physicochemical properties and existing toxicity data can be effectively used to determine the safety of nanomaterials. Nanoinformatics involves the integration of nanospecific databases (e.g., NanoDatabank, eNanoMapper, Data and Knowledge on Nanomaterials, Online Chemical Modeling Environment, and Nanoparticle Information Library) with modeling frameworks such as quantitative nanostructure-activity/toxicity relationship, molecular docking, physiologically based toxicokinetic models, and molecular dynamics simulation for predictive nanotoxicity assessment. Moreover, the process of computer-aided nanotoxicity prediction can be further expedited using the latest data mining techniques. Challenges in collecting sufficient, high-quality, nanotoxicity data, as well as in standardizing the training data sets require careful consideration to further expand the applications of nanoinformatics techniques in predictive nanotoxicology. This article highlights the current status and future perspective of nanoinformatics-based predictive toxicological screening of nanomaterials.