title: Systems biology and the origins of life? part II. Are biochemical networks possible ancestors of living systems? networks of catalysed chemical reactions: non-equilibrium, self-organization and evolution.
abstract: The present article discusses the possibility that catalysed chemical networks can evolve. Even simple enzyme-catalysed chemical reactions can display this property. The example studied is that of a two-substrate proteinoid, or enzyme, reaction displaying random binding of its substrates A and B. The fundamental property of such a system is to display either emergence or integration depending on the respective values of the probabilities that the enzyme has bound one of its substrate regardless it has bound the other substrate, or, specifically, after it has bound the other substrate. There is emergence of information if p(A)>p(AB) and p(B)>p(BA). Conversely, if p(A)<p(AB) and p(B)<p(BA) the system is integrated. The first condition is likely to occur if the system is far from quasi-equilibrium. Moreover, in such systems, emergence results in an increase of the energy level of the ternary EAB complex that becomes closer to the transition state of the reaction, thus leading to the enhancement of catalysis. Hence a drift from quasi-equilibrium is, to a large extent, responsible for the production of information and enhancement of catalysis. Non-equilibrium of these simple systems must be an important aspect that leads to both self-organization and evolutionary processes. These conclusions can be extended to networks of catalysed chemical reactions. Such networks are, in fact, networks of networks, viz. meta-networks. In this formal representation, nodes are chemical reactions catalysed by poorly specific proteinoids, and links can be identified to the transport of metabolites from proteinoid to proteinoid. The concepts of integration and emergence can be applied to such situations and can be used to define the identity of these networks and therefore their evolution. Defined as open non-equilibrium structures, such biochemical networks possess two remarkable properties: (1) the probability of occurrence of their nodes is dependant upon the input and output of matter in, and from, the system and (2) the probability of occurrence of the nodes is strictly linked to their degree of connection. The higher this degree of connection and the higher is their probability of occurrence. These conclusions are in clear disagreement with the static descriptions of the so-called scale-free metabolic networks.
authors.affiliation: Institut Jacques-Monod, 2, place Jussieu, 75251 Paris cedex 05, France. jkricard@aol.com
authors.forename: Jacques
authors.initials: J
authors.lastname: Ricard
mesh_terms: D000465:Algorithms; D001669:Biochemical Phenomena; D005075:Biological Evolution; D002384:Catalysis; D004798:Enzymes / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D000069497:Origin of Life; D049490:Systems Biology
chemical_list: D004798:Enzymes