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Modular self-assembly of biomolecules in two dimensions (2D) is straightforward with DNA but has been difficult to realize with proteins, due to the lack of modular specificity similar to Watson-Crick base pairing. Here we describe a general approach to design 2D arrays using de novo designed pseudosymmetric protein building blocks. A homodimeric helical bundle was reconnected into a monomeric building block, and the surface was redesigned in Rosetta to enable self-assembly into a 2D array in the C12 layer symmetry group. Two out of ten designed arrays assembled to micrometer scale under negative stain electron microscopy, and displayed the designed lattice geometry with assembly size up to 100 nm under atomic force microscopy. The design of 2D arrays with pseudosymmetric building blocks is an important step toward the design of programmable protein self-assembly via pseudosymmetric patterning of orthogonal binding interfaces.
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http://dx.doi.org/10.1021/jacs.9b01978 | DOI Listing |
J Colloid Interface Sci
September 2025
Department of Chemistry, State Key Laboratory of Porous Materials for Separation and Conversion, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, and iChEM, Fudan University, Shanghai 200438, China. Electronic address:
We present a coordination-inspired strategy for assembling binary nanocrystal superlattices (BNSLs) using CdSe nanotetrapods as symmetry-encoding building blocks. Exploiting their intrinsic tetrahedral geometry, which mimics the sp hybridization of carbon atoms in a diamond lattice, we encode spatially defined binding sites that guide regioselective coassembly with spherical nanocrystals. By tuning the size ratio between components, we achieve both three-dimensional and two-dimensional BNSLs with long-range structural order.
View Article and Find Full Text PDFSci Robot
September 2025
University of Chicago, Chicago, IL 60637, USA.
Reading fluency is a vital building block for developing literacy, yet the best way to practice fluency-reading aloud-can cause anxiety severe enough to inhibit literacy development in ways that can have an adverse effect on students through adulthood. One promising intervention to mitigate oral reading anxiety is to have children read aloud to a robot. Although observations in prior work have suggested that people likely feel more comfortable in the presence of a robot instead of a human, few studies have empirically demonstrated that people feel less anxious performing in front of a robot compared with a human or used objective physiological indicators to identify decreased anxiety.
View Article and Find Full Text PDFInt J Dev Biol
September 2025
Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA.
How the dorsal thalamus of amniotes (reptiles, birds, and mammals) is organized remains an important but incompletely answered question. Identification of meaningful subdivisions would greatly aid in its understanding. Because the dorsal thalamus is more simply organized during development, studies have examined this structure during embryogenesis.
View Article and Find Full Text PDFAcc Chem Res
September 2025
Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, British Columbia V6T 1Z1, Canada.
ConspectusHydroaminoalkylation, the catalytic addition of amines to alkenes, has evolved as a powerful tool in modern synthetic chemistry, offering an atom-economic and green approach to the construction of C-C bonds. This reaction enables the direct amine functionalization of alkenes and alkynes without the need for protecting groups, directing groups, or prefunctionalization, thereby eliminating stoichiometric waste and minimizing synthetic steps. Over the past two decades, significant advances in catalyst development and mechanistic understanding have expanded the scope of hydroaminoalkylation, allowing for control over regio-, diastereo-, and enantioselectivity.
View Article and Find Full Text PDFiScience
September 2025
School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong 510006, China.
Deep learning has rapidly emerged as a promising toolkit for protein optimization, yet its success remains limited, particularly in the realm of activity. Moreover, most algorithms lack rigorous iterative evaluation, a crucial aspect of protein engineering exemplified by classical directed evolution. This study introduces DeepDE, a robust iterative deep learning-guided algorithm leveraging triple mutants as building blocks and a compact library of ∼1,000 mutants for training.
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