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Ancestral metabolic processes involve the reversible oxidation of molecular hydrogen by hydrogenase. Extant hydrogenase enzymes are complex, comprising hundreds of amino acids and multiple cofactors. We designed a 13–amino acid nickel-binding peptide capable of robustly producing molecular hydrogen from protons under a wide variety of conditions. The peptide forms a di-nickel cluster structurally analogous to a Ni-Fe cluster in [NiFe] hydrogenase and the Ni-Ni cluster in acetyl-CoA synthase, two ancient, extant proteins central to metabolism. These experimental results demonstrate that modern enzymes, despite their enormous complexity, likely evolved from simple peptide precursors on early Earth. 

Computational exploration of similarities among metal-binding protein structural motifs elucidates the origins of life. 

Harnessing the self-assembly of peptide sequences has demonstrated great promise in the domain of creating high precision shape-tunable biomaterials. The unique properties of peptides allow for a building block approach to material design. In this study, self-assembly of mixed systems encompassing two peptide sequences with identical hydrophobic regions and distinct polar segments is investigated. The two peptide sequences are diphenylalanine and phenylalanine-asparagine-phenylalanine. The study examines the impact of molecular composition (namely, the total peptide concentration and the relative tripeptide concentration) on the morphology of the self-assembled hybrid biological material. We report a rich polymorphism in the assemblies of these peptides and explain the relationship between the peptide sequence, concentration and the morphology of the supramolecular assembly. 

Abstract The core metabolic reactions of life drive electrons through a class of redox protein enzymes, the oxidoreductases. The energetics of electron flow is determined by the redox potentials of organic and inorganic cofactors as tuned by the protein environment. Understanding how protein structure affects oxidation–reduction energetics is crucial for studying metabolism, creating bioelectronic systems, and tracing the history of biological energy utilization on Earth. We constructed ProtReDox (https://protein-redox-potential.web.app), a manually curated database of experimentally determined redox potentials. With over 500 measurements, we can begin to identify how proteins modulate oxidation–reduction energetics across the tree of life. By mapping redox potentials onto networks of oxidoreductase fold evolution, we can infer the evolution of electron transfer energetics over deep time. ProtReDox is designed to include user‐contributed submissions with the intention of making it a valuable resource for researchers in this field.