In silico predictions of 3D structures of linear and cyclic peptides with natural and non-proteinogenic residues

Abstract

We extended the use of Peplook, an in silico procedure for the prediction of three-dimensional (3D) models of linear peptides to the prediction of 3D models of cyclic peptides and thanks to the ab initio calculation procedure, to the calculation of peptides with non-proteinogenic amino acids. Indeed, such peptides cannot be predicted by homology or threading. We compare the calculated models with NMR and X-ray models and for the cyclic peptides, with models predicted by other in silico procedures (Pep-Fold and I-Tasser). For cyclic peptides, on a set of 38 peptides, average root mean square deviation of backbone atoms (BB-RMSD) was 3.8 and 4.1 Å for Peplook and Pep-Fold, respectively. The best results are obtained with I-Tasser (2.5 Å) although evaluations were biased by the fact that the resolved Protein Data Bank models could be used as template by the server. Peplook and Pep-Fold give similar results, better for short (up to 20 residues) than for longer peptides. For peptides with non-proteinogenic residues, performances of Peplook are sound with an average BB-RMSD of 3.6 Å for 'non-natural peptides' and 3.4 Å for peptides combining non-proteinogenic residues and cyclic structure. These results open interesting possibilities for the design of peptidic drugs.