A key benchmark in our understanding of evolutionary self-organization
is formed by the origin of encoded construction systems. In contrast with
simple self-replication, where the construction principle leading to replication
is a special property of the molecules involved, encoded construction allows
different functional molecules to be constructed using a common construction
machinery. The evolution of such systems provides a testing example
of the evolution of altruism which can only be addressed within a stochastic
individual-based kinetic framework. Such a framework is computationally
extremely intensive, but can now be handled on evolutionary time scales
using dedicated reconfigurable digital hardware. Spatial correlations between
different individual sequences play a major role in the non-equilibrium
statistical mechanics of such evolving populations. The emphasis
of the work is not on the molecular details of the current genetic code
but on the informational dynamics of the cooperative processes necessary
to stabilize such task-diversified multi-component construction systems.
It is aimed at providing a basis for both understanding and generating
functionally diversified evolving molecular systems.
A hierarchy of model systems and examples of their simulation are presented,
leading up to evolutionary stable encoded construction systems in continuously
distributed space. In particular it is shown how a universal replicase
molecule can be stably evolved, with a second level error threshold. The
influence of partial molecular recognition of templates is evaluated within
the context of replicase exploitation. The relation of this work with experimental
in vitro model systems is discussed. Finally, the extension to fully encoded
replication and to encoded translation (the GRT model) will be presented.
In particular, the GRT model is contrasted with the radical mean-field
assumptions made in Dyson's model.
The seminar reports on original research by the speaker, together with
students S. Altmeyer, J. Breyer and Dr. R. Füchslin.