Chemical Graph Transformation and Applications
Any computational method in chemistry must choose some level of precision in the modeling. One choice is made in the methods of quantum chemistry based on quantum field theory. While highly accurate, the methods are computationally very demanding, which restricts their practical use to single reactions of molecules of moderate size even when run on supercomputers. At the same time, most existing computational methods for systems chemistry and biology are formulated at the other abstraction extreme, in which the structure of molecules is represented either not at all or in a very rudimentary fashion that does not permit the tracking of individual atoms across a series of reactions.
In this talk, we present our on-going work on creating a practical modelling framework for chemistry based on Double Pushout graph transformation, and how it can be applied to analyse chemical systems. We will address important technical design decisions as well as the importance of methods inspired from Algorithm Engineering in order to reach the required efficiency of our implementation. We will present chemically relevant features that our framework provides (e.g. automatic atom tracing) as well as a set of chemical systems we investigated are currently investigating. If time allows we will discuss variations of graph transformation rule compositions and their chemical validity.