Computational methods have been applied to search for parameters (e.g. residue propensity, hydrophobicity, planarity) that could distinguish glycan-binding proteins from other surface patches. For example, a model trained on 19 non-homologous carbohydrate binding structures was able to  predict carbohydrate-binding domains (CRDs) with an accuracy of 65% for non-enzymatic structures and 87% for enzymatic ones. Further studies have employed calculations of Van der Waals energies of protein-probe interactions and amino acid propensities to identify CRDs with 98% specificity at 73% sensitivity. More recent methods can predict CRDs even from protein sequences, by comparing the sequence with those for which structures are already known.