Representing and describing nanomaterials in predictive nanoinformatics

Ewelina Wyrzykowska, Alicja Mikolajczyk, Iseult Lynch, Nina Jeliazkova, Nikolay Kochev, Haralambos Sarimveis, Philip Doganis, Pantelis Karatzas, Antreas Afantitis, Georgia Melagraki, Angela Serra, Dario Greco, Julia Subbotina, Vladimir Lobaskin, Miguel A. Bañares, Eugenia Valsami-Jones, Karolina Jagiello, Tomasz Puzyn

    Research output: Contribution to journalReview Articlepeer-review

    Abstract

    Engineered nanomaterials (ENMs) enable new and enhanced products and devices in which matter can be controlled at a near-atomic scale (in the range of 1 to 100 nm). However, the unique nanoscale properties that make ENMs attractive may result in as yet poorly known risks to human health and the environment. Thus, new ENMs should be designed in line with the idea of safe-and-sustainable-by-design (SSbD). The biological activity of ENMs is closely related to their physicochemical characteristics, changes in these characteristics may therefore cause changes in the ENMs activity. In this sense, a set of physicochemical characteristics (for example, chemical composition, crystal structure, size, shape, surface structure) creates a unique ‘representation’ of a given ENM. The usability of these characteristics or nanomaterial descriptors (nanodescriptors) in nanoinformatics methods such as quantitative structure–activity/property relationship (QSAR/QSPR) models, provides exciting opportunities to optimize ENMs at the design stage by improving their functionality and minimizing unforeseen health/environmental hazards. A computational screening of possible versions of novel ENMs would return optimal nanostructures and manage ('design out') hazardous features at the earliest possible manufacturing step. Safe adoption of ENMs on a vast scale will depend on the successful integration of the entire bulk of nanodescriptors extracted experimentally with data from theoretical and computational models. This Review discusses directions for developing appropriate nanomaterial representations and related nanodescriptors to enhance the reliability of computational modelling utilized in designing safer and more sustainable ENMs.

    Original languageEnglish
    Pages (from-to)924-932
    Number of pages9
    JournalNature Nanotechnology
    Volume17
    Issue number9
    DOIs
    Publication statusPublished - Sept 2022
    Publication typeA2 Review article in a scientific journal

    Publication forum classification

    • Publication forum level 3

    ASJC Scopus subject areas

    • Bioengineering
    • Atomic and Molecular Physics, and Optics
    • Biomedical Engineering
    • General Materials Science
    • Condensed Matter Physics
    • Electrical and Electronic Engineering

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