Abstract. A standard representation of molecules is based on graphs where atoms correspond to vertices and covalent bonds are represented by a number of edges according to the bond order. This depiction reaches its limitations for aromatic molecules where the aromatic ring can be encoded by different bond order layouts, i.e. Kekule ́ structures, since electrons are shared within the ring rather than fixed to a specific bond. Thus, several Kekule ́ structures are possible for aromatic molecules. Here, we propose a new constraint programming based approach to enumerate all Kekule ́ structures for a given molecule. Furthermore, the ambiguity information derived is used to enable a unique Kekulé-based SMILES encoding of the molecule independent of any aromaticity detection al-gorithm. This is of importance, since there is no generally accepted aro-maticity definition available that covers all cases. 1

A chemical reaction is a process of transforming one set of molecules (educts) into another set (products). In the course of a reaction, chemical bonds which hold the atoms together are redistributed, so that each atom in a reaction educt appears in a specific position of a reaction product. Tracing atoms between educts and products refers to a non-trivial problem in computational chemistry and system biology, namely the “Atom Mapping Problem”. Our determination of atom mappings relies on the existence of an imaginary transition state (ITS), in which reacting bonds (formed, broken) are arranged in a cyclic topology. Cyclic mechanisms are very common in chemistry and almost all elementary homovalent and ambivalent reactions feature a cyclic ITS. The used approach aims at the identification of the cyclic ITS, that imposes additional restrictions on the bijection between educt and product atoms. Once the cyclic ITS is fixed, the overall mapping is easily derived. For this purpose we use Constraint Programming and we show that it is a very promising approach to solve the atom mapping task. The constraint-based model enables the enumeration of

Graph kernel based aromaticity prediction thesis submitted in fulfilment of the requirements