Reflexivity, coding and quantum biology.

Biosystems

Department of Physics & Te Ao Marama Centre for Fundamental Inquiry, University of Auckland, PB 92109, Auckland, 1142, Aotearoa, New Zealand; Human Biology, Institute for Biology, Free University, Königin-Luise-Str. 1-3, Berlin 14195, Germany. Electronic address:

Published: November 2019

Biological systems are fundamentally computational in that they process information in an apparently purposeful fashion rather than just transferring bits of it in a purely syntactical manner. Biological information, such has genetic information stored in DNA sequences, has semantic content. It carries meaning that is defined by the molecular context of its cellular environment. Information processing in biological systems displays an inherent reflexivity, a tendency for the computational information-processing to be "about" the behaviour of the molecules that participate in the computational process. This is most evident in the operation of the genetic code, where the specificity of the reactions catalysed by the aminoacyl-tRNA synthetase (aaRS) enzymes is required to be self-sustaining. A cell's suite of aaRS enzymes completes a reflexively autocatalytic set of molecular components capable of making themselves through the operation of the code. This set requires the existence of a body of reflexive information to be stored in an organism's genome. The genetic code is a reflexively self-organised mapping of the chemical properties of amino acid sidechains onto codon "tokens". It is a highly evolved symbolic system of chemical self-description. Although molecular biological coding is generally portrayed in terms of classical bit-transfer events, various biochemical events explicitly require quantum coherence for their occurrence. Whether the implicit transfer of quantum information, qbits, is indicative of wide-ranging quantum computation in living systems is currently the subject of extensive investigation and speculation in the field of Quantum Biology.

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Source
http://dx.doi.org/10.1016/j.biosystems.2019.104027DOI Listing

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