Abstract
Alkaline hydrothermal vents have long been proposed as a cradle for the origin of cellular life because they provide continuous chemical gradients and catalytic mineral surfaces capable of promoting redox reactions. These environments could have fostered a transition from inorganic electron transfer catalyzed by geochemical surfaces to organic electron transfer mediated by small, metal-binding peptides. Ferredoxin, a small iron-sulfur protein central to respiration, photosynthesis, and nitrogen fixation, is thought to represent one of the earliest proteins to evolve and to bridge inorganic minerals with the emergence of biological energy. Since only a limited set of amino acids is believed to have been available on the prebiotic Earth, ancestral ferredoxins likely arose from these prebiotic amino acids. To explore this hypothesis, the AI deep learning algorithm ProteinMPNN was used to redesign extant ferredoxins composed of only prebiotic amino acids plus cysteine for FeS cluster coordination. AlphaFold3 was then used to assess foldability, yielding multiple candidate sequences predicted to adopt ferredoxin folds. Confirmed sequences were then analyzed to select both consensus-based and diversity-based prebiotic sequences for experimental testing. Plasmids containing these prebiotic sequences were transformed into E. coli and prebiotic ferredoxins were expressed and characterized, including from both soluble and inclusion body fractions. In favorable cases, expression of some sequences was scaled up to purify larger quantities of protein using metal affinity FPLC.