  This paper shows how one can directly apply natural language processing (NLP)
methods to classification problems in cheminformatics. Connection between these
seemingly separate fields is shown by considering standard textual
representation of compound, SMILES. The problem of activity prediction against
a target protein is considered, which is a crucial part of computer aided drug
design process. Conducted experiments show that this way one can not only
outrank state of the art results of hand crafted representations but also gets
direct structural insights into the way decisions are made.
