title: Basic statistical recipes for the emergence of biochemical discernment.
abstract: An essential step towards understanding life would be to identify the very basic mechanisms responsible for the discerning behaviour of living biochemical systems, absent from randomly reacting chemical soups. One intuitively feels that this question goes beyond the particular nature of the biological molecules and should relate to general physical principles. The pre-eminent physicist Ludwig Boltzmann early envisioned life as a struggle for entropy, in concordance with the subsequent principle of self-organization out of equilibrium. Re-examination of elementary steady state biochemical systems from a statistical perspective supports this view and shows that sigmoidal responses arising from microstates elimination, are sufficient to explain innermost characteristics of life, including its capacity to convert random molecular interactions into accurate biological reactions. A primary operating strategy to achieve this goal is the introduction of time-irreversible transitions in molecular state conversion cycles by injection of free energy, which confers decisional capacity to single macromolecules. Selected examples from various fields of molecular biology such as enzymology and gene expression, are provided to show that these non-equilibrium steady state mechanisms remain important in contemporary biochemical systems. But in addition, information archiving allowed the emergence of the time-reversible counterparts of these mechanisms, mediated by evolutionary pre-organized macromolecular complexes capable of generating discernment in a non-dissipative manner.
authors.affiliation: Université de Rennes1, Molecular and Cellular Interactions UMR6026, Irset. IFR140GFAS, Bat. 13, Campus de Beaulieu, 35042 Rennes Cedex, France. denis.michel@live.fr
authors.forename: Denis
authors.initials: D
authors.lastname: Michel
mesh_terms: D000818:Animals; D001669:Biochemical Phenomena; D005075:Biological Evolution; D001699:Biometry / Q000379:methods*; D019277:Entropy; D006801:Humans; D008956:Models, Chemical; D049490:Systems Biology