Instruction set and language for chemical nomenclature

Processing of chemical information by computational intelligence methods faces the challenge of the structural complexity of molecular graphs. These graphs are not amenable to being represented in a suitable way for such methods. The most popular representation is the SMILES notation standard. However, it comes with some limitations such as the abundance of non-valid strings and the fact that similar strings often represent very different molecules. In this work, a completely different approach to chemical nomenclature is presented. A reduced instruction set is defined, and the language of all strings that are sequences of such instructions is considered. All strings of this language are valid, i.e., each string represents a molecule. Moreover, slight changes in a string usually correspond to small modifications in the represented molecule. Therefore, this approach is appropriate for its use if state-of-the-art computational intelligence systems for chemical information processing, including deep learning models.