Machine learning models for exploring structure-property relation for hydroxyapatite nanoparticles (HANPs) are still lacking. A multiscale multisource dataset is presented, including both experimental data (TEM/SEM, XRD/crystallinity, ROS, anti-tumor effects, and zeta potential) and computation results (containing 41,976 data samples with up to 9768 atoms) of nanoparticles with different sizes and morphologies at density functional theory (DFT), semi-empirical DFTB, and force field, respectively. Three geometric descriptors are set for the explainable machine learning methods to predict surface energies and surface stress of HANPs with satisfactory performance. To avoid the pre-determination of features, we also developed a predictive deep learning model within the framework of graph convolution neural network with good generalizability. Energies with DFT accuracy are achievable for large-sized nanoparticles from the learned correlations and scale functions for mapping different theoretical levels and particle sizes. The simulated XRD spectra and crystallinity values are in good agreement with experiments.

The clathrin-associated protein adaptin-2 (AP2) is a distinctive member of the hetero-tetrameric clathrin adaptor complex family. It plays a crucial role in many intracellular vesicle transport pathways. The hydroxyapatite (HAp) nanoparticles can enter cells through clathrin-dependent endocytosis, induce apoptosis, and ultimately inhibit tumor metastasis. Exploring the micro process of the binding of AP2 and HAp is of great significance for understanding the molecular mechanism of HAp’s anti-cancer ability. In this work, we used molecular modeling to study the binding of spherical, rod-shaped, and needle-shaped HAps toward AP2 protein at the atomic level and found that different nanoparticles’ morphology can determine their binding specificity through electrostatic interactions. Our results show that globular HAp significantly changes AP2 protein conformation, while needle-shaped HAP has more substantial binding energy with AP2. Therefore, this work offers a microscopic picture for cargo recognition in clathrin-mediated endocytosis, clarifies the design principles and possible mechanisms of high-efficiency nano-biomaterials, and provides a basis for their potential anti-tumor therapeutic effects.

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Summary Yam is a common ‘medicine food homology’ vegetable in Asia, and its peel is often considered a food residue during processing or cooking. In this work, the effects of hydrogen peroxide modification on the dietary fibres (DFs) from Chinese yam peel (CYP) were investigated. The structural characteristics of soluble dietary fibre (SDF), insoluble dietary fibre (IDF), modified soluble dietary fibre (MSDF) and modified insoluble dietary fibre (MIDF) were analysed using Fourier‐transform infrared spectroscopy, X‐ray diffraction, differential scanning calorimetry, granularity analysis, scanning electron microscopy and GC‐MS (monosaccharide composition). As results, after modification with hydrogen peroxide, the sizes of the DFs were reduced and MIDF exposed more cellulose. Experiments on the physicochemical and functional properties of DFs showed that MSDF and MIDF obtained a better water holding capacity, oil absorption capacity, swelling capacity and absorption abilities with altered structures, which is of great importance in food processing and development.

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