Predictive Interactions of Chiral Nanoparticles and Proteins—From Catalysis to Vaccines

Biomimetic nanoparticles (NPs) are known to serve as nanoscale adjuvants, enzyme mimics, and amyloid fibrillation inhibitors. Their further development requires better understanding of their interactions with proteins. The abundant knowledge about protein-protein interactions can serve as a guide for designing protein-NP assemblies, but the chemical and biological inputs used in computational packages for protein-protein interactions are not applicable to inorganic NPs. Analyzing chemical (CH), geometrical (GE), and graph-theoretical (GT) descriptors for protein complexes, we found that GE and GT descriptors that are uniformly applicable to biological and inorganic nanostructures can predict interaction sites in protein pairs with accuracy &gt;80% and classification probability ~90%. We extended the protein-trained machine learning algorithms to inorganic biomimetic NPs and found a nearly exact match between experimental and predicted interaction sites with proteins. These findings can be extended to other organic and inorganic NPs to predict their assemblies with chemically dissimilar structures.[1]<br/>The design principles of and predictictive capabilities of NP-protein interactions have been utilized for formation of complexes of plasmonic NPs with proteins. They enabled polarization-based drug discovery platforms for Alzheimer syndrome,[2] materials for chiral catalysis,[3] and chiral antiviral vaccines.[4]<br/>References<br/>[1] Minjeong Cha, et al Unifying Structural Descriptors for Biological and Bioinspired Nanoscale Complexes, <i>Nature Computational Science, </i><b>2022</b>, <i>2</i>, 243–252.<br/>[2] Jun Lu, et al, Enhanced optical asymmetry in supramolecular chiroplasmonic assemblies with long-range order, <i>Science</i>, <b>2021</b>, 371, 6536, 1368.<br/>[3] Shuang Jiang, et al. Chiral Ceramic Nanoparticles of Tungsten Oxide and Peptide Catalysis, Journal of the American Chemical Society, <b>2017</b>, 139 (39), 13701–13712.<br/>[4] L. Xu, et al, Enantiomer-Dependent Immunological Response to Chiral Nanoparticles<b>, </b><i>Nature,</i><b> 2022</b>, 601, 366–373.