16:00 – 18:00
Lipidia: an Artificial Chemistry of Self-Replicating Assemblies of Lipid-like Molecules
Lipidia: an Artificial Chemistry of
Self-Replicating Assemblies of Lipid-like Molecules
The ``RNA World'' is possibly today's most popular theory for the origins
of life cite{Gilbert1986,Joyce2002}. Because RNA molecules can act as
catalysts in addition to acting as templates, it is hypothesized they
might have been able to do both: to store alphabet-based genetic
information emph{and} to catalyze their own creation. Life, according to
this theory, began when certain RNA molecules achieved the capability to
replicate themselves. This scenario, despite its elegance, suffers from
difficulties.
In an attempt to come up with a probable scenario, having observed that no
known bio-molecule is capable of self replication in its naked form, it
has been suggested that self replication might not have been achieved by a
single molecule, but rather by a molecular ensemble cite{Kauffman1993}.
This work is based on ``The Lipid World'' scenario cite{Segre2001a} which
follows that line of thought. The scenario assumes that self-replication
was initially achieved by non-covalent assemblies of lipid-like molecules
that contained mutually catalytic sets cite{Segre2000a}. Such
self-replication is remarkably easier to achieve. RNA according to this
scenario, while possibly playing an important role, came later.
Lipidia is a new simulation system that is related to the ``Lipid World''
scenario. Lipidia allows for conducting experiments with a population of
assemblies containing lipid-like molecules on a two dimensional grid.
The dynamics of the assemblies is modelled using the Graded Autocatalysis
Replication Domain (GARD) model. New experiments using a finite environment
model with GARD were conducted with Lipidia. The experiments show that more
self-replicating assembly species appear when using a model of finite
environment than when using a model of infinite environment. In many species
the number of individuals increases as well.
No background knowledge is required.