Properties of an optimally evolved metabolic network

by Prof. Daniel Segre'

Thursday 18 Jun 2009, 15:00 → 17:00 Europe/Rome

Aula Conversi (Dip di Fisica - Edificio G. Marconi)

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. A fundamental unanswered question is whether the topology of metabolic networks is the unpredictable result of historical accidents, or if it can be partially explained by yet unknown properties of adaptive processes in complex biochemical networks. Towards uncovering potential network attributes of an optimally evolved metabolic system, we build an artificial chemistry and exhaustively search for pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles, a modular organization of simple tasks into more complex ones, and a logarithmic trend of pathway length as a function of input/output molecule size. By mapping real metabolic networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the model seem to hold for real biochemistry, offering possible insight on the laws and accidents involved in biochemical adaptation.