Fig. 6

Benchmarking rBAN versus s2m. a Both software were used to validate the SMILES data by comparing the Norine monomer graphs with the SMILES-based predicted graphs. rBAN could validate more peptides than s2m and four of the entries uniquely validated by s2m turned out to be false positives of the software. The manual examination of the entries uniquely validated by rBAN revealed a better capacity of the tool to annotate large structures and peptides containing heterocycles and tautomers. b The global distribution of the correctness do not show substantial differences between the two software but it proves that rBAN does not only have more correct peptides, but also less peptides with correctness values close to zero. c The monomer database was extended with new chemical entities to evaluate its effects on the peptide mapping. The results of rBAN remained unchanged proving its robustness, while the extension of the monomer database affected mapping in s2m. d The computational performance was evaluated with different amounts of input peptides. In all cases rBAN outperformed s2m, being between four and five times faster