Special Seminar in Computing & Mathematical Sciences
Moore B280
Exploring chemical reaction spaces using a graph grammar approach.
Christoph Flamm,
Professor,
Theoretical Chemistry,
University of Vienna,
During chemical transformations molecular entities can change their
quantitative physico-chemical properties while atom types or mass is
conserved. Furthermore, upon interaction, novel molecular species with
hitherto unknown physico-chemical properties may arise. Hence a formalism
for chemistry must be capable of capturing the algebraic and thermodynamic
structure of chemical processes. The formalization of chemical
transformation (reactions) as graph grammers shows the right level of
abstraction for the analysis of large and complex reaction networks. The
used double pushout formalism (DPO) guarantees important intrinsic
properties of chemical reaction systems such as mass conservation or
atom-to-atom mappings from educts to products. A graph grammar provides a
set of production rules (reactions) describing all possible graphs of the
given formal language and thuse is a compact representation of a chemical
reaction space. Iterative application of the production rules to a set of
starting graphs constructs a chemical reaction network that organizes the
molecular graphs in a hypergraph. Important questions such as the existance
and topology of complex reaction patterns, such as auto-catalysis, in large
reaction networks can be investigated in a systematic manner. The basic
idea here is to reformulate the chemical question as hyperflow problem and
to use optimization techniques such es integer linear programming (ILP) to
calculate solutions. Metabolic engineering, a sub-field of Synthetic
Biology, investigates the de-novo construction and design of enzyme
catalysed reaction networks for in vitro and/or in vivo production of
commodity chemicals. Since for many target molecules no natural pathways
are known, recombination of enzyme functionality under optimality criteria
becomes important to guide the design efforts. I illustrate how the
presented framework can be used in this research area to explore and rank
the entire network design space spanned by a set of enzymes, starting
and target compounds, and some measure of optimality.
Host: Stefan Badelt. Please contact me ([email protected]) if you would like to meet with Christoph during his visit on Nov 21.
For more information, please contact Lucinda Acosta by phone at 626 395 4843/626 395 5707 or by email at [email protected].
Event Series
Computing + Mathematical Sciences Lecture Series