Enzymatic activity is crucial for various technological applications, yet the complex structures and limited stability of enzymes often hinder their use. Hence, de novo design of robust biocatalysts that are much simpler than their natural counterparts and possess enhanced catalytic activity has long been a goal in biotechnology. Here, we present evidence for the ability of a single amino acid to self-assemble into a potent and stable catalytic structural entity. Spontaneously, phenylalanine (F) molecules coordinate with zinc ions to form a robust, layered, supramolecular amyloid-like ordered architecture (F-Zn(ii)) and exhibit remarkable carbonic anhydrase-like catalytic activity. Notably, amongst the reported artificial biomolecular hydrolases, F-Zn(ii) displays the lowest molecular mass and highest catalytic efficiency, in addition to reusability, thermal stability, substrate specificity, stereoselectivity and rapid catalytic CO₂ hydration ability. Thus, this report provides a rational path towards future de novo design of minimalistic biocatalysts for biotechnological and industrial applications.

The variety and complexity of DNA-based structures make them attractive candidates for nanotechnology, yet insufficient stability and mechanical rigidity, compared to polyamide-based molecules, limit their application. Here, we combine the advantages of polyamide materials and the structural patterns inspired by nucleic-acids to generate a mechanically rigid fluorenylmethyloxycarbonyl (Fmoc)-guanine peptide nucleic acid (PNA) conjugate with diverse morphology and photoluminescent properties. The assembly possesses a unique atomic structure, with each guanine head of one molecule hydrogen bonded to the Fmoc carbonyl tail of another molecule, generating a non-planar cyclic quartet arrangement. This structure exhibits an average stiffness of 69.6 ± 6.8 N m^-1 and Young's modulus of 17.8 ± 2.5 GPa, higher than any previously reported nucleic acid derived structure. This data suggests that the unique cation-free "basket" formed by the Fmoc-G-PNA conjugate can serve as an attractive component for the design of new materials based on PNA self-assembly for nanotechnology applications.

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges—how to comprehensively map such systems and how to identify which are under mutational selection—have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.