Directed acyclic graphical models are statistical models that use a directed acyclic graph (DAG) to represent the conditional independence structure of a set of random variables. We introduce a new class of DAG models tailored for circular variables having an Inverse Stereographic Normal distribution. We present a case study where the proposed models are employed to describe conditional independences of a sequence of angles summarising the structure of a protein.