Predicting biomolecule adsorption on nanomaterials: a hybrid framework of molecular simulations and machine learning
Ewelina Wyrzykowska, Mateusz Balicki, Iwona Anusiewicz, Ian Rouse, Vladimir Lobaskin, Piotr Skurski, Tomasz Puzyn
Abstract
= 1.88) helps in understanding and predicting the interactions between NMs (including carbon-based materials, metals, metal oxides, metalloids, and cadmium selenide) and biomolecules (including amino acids and amino acid derivatives). The model facilitates safe and sustainable design of nanomaterials for various applications, particularly for nanomedicine, by providing insight into nano-bio interactions, identification of toxicity risk and optimizing functionalization for safety according to the risk mitigation policy of regulatory authorities. Additionally, a dedicated application has been developed and is available on GitHub, enabling researchers to analyze the surface properties of nanomaterials belonging to the above-mentioned groups of NMs.