GNNs are in the suite of methods that we use and evaluate. But it’s useful to recognize that although we often draw molecules as graphs, that is not necessarily the only useful (or best) representation for molecules in machine learning. We recently published (poster and talk, paper) research using DeBERTa-style representations and self-supervision over molecular graphs, achieving SOTA results on 9/22 tasks in the Therapeutic Data Commons ADMET tasks.