WITHDRAWN: Structural Enzymology, Phylogenetics, Differentiation, and Symbolic Reflexivity at the Dawn of Biology

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Abstract
The reflexive translation of symbols in one chemical language to another defined genetics. Yet, the co-linearity of codons and amino acids is so commonplace an idea that few even ask how it arose. Readout is done by two distinct sets of proteins, called aminoacyl-tRNA synthetases (AARS). AARS must enforce the rules first used to assemble themselves. The roots of translation lie in experimentally testing the structural codes that the earliest AARS•tRNA cognate pairs used to recognize both amino acid and RNA substrates. We review here new results on five different facets of that problem. (i) The surfaces of structures coded by opposite strands of the same gene have opposite polarities. The corresponding proteins then fold up “inside out” relative to one another. The inversion symmetry of base pairing thus projects into the proteome. That leads in turn to contrasting amino acid and RNA substrate binding modes. (ii) E. coli reproduces in vivo the nested hierarchy of active excerpts we had designed as models—protozymes and urzymes—for ancestral AARS. (iii) A third novel deletion produced in vivo and a new Class II urzyme suggest how to design bidirectional urzyme genes. (iv) Codon middle-base pairing provides a basis to constrain Class I and II AARS family trees. (v) AARS urzymes acylate Class-specific subsets of an RNA library, showing RNA substrate specificity for the first time. Four new phylogenetic routines augment these results to compose a viable platform for experimental study of the origins of genetic coding. Significance Statement The origin of genetic coding poses questions distinct from those faced studying the evolution of enzymes since the first cells. Modern enzymes that translate the code range in size from ∼330 to ∼970 amino acids. Ancestral forms cannot have been nearly as complex. Moreover, such primitive enzymes likely could enforce only a much-reduced coding alphabet. Structural and molecular biology data point to a broad sketch of events leading to the code. That research platform will enable us to see how Nature came to store information about the physical chemistry of amino acids in the coding table. That, in turn, allowed searching of a very broad amino acid sequence space. Selection could then learn how to assemble amino acids into functional, reflexive catalysts. Those catalysts had rates and fidelities consistent with bootstrapping the modern coding alphabet. New phylogenetic algorithms need to be developed to fully test that putative sketch experimentally.

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