A Blind Test of Computational Technique for Predicting the Likelihood of Peptide Sequences to Cyclize.

An in silico computational technique for predicting peptide sequences that can be cyclized by cyanobactin macrocyclases, e.g., PatGmac, is reported. We demonstrate that the propensity for PatGmac-mediated cyclization correlates strongly with the free energy of the so-called pre-cyclization conformation (PCC), which is a fold where the cyclizing sequence C and N termini are in close proximity. This conclusion is driven by comparison of the predictions of boxed molecular dynamics (BXD) with experimental data, which have achieved an accuracy of 84%. A true blind test rather than training of the model is reported here as the in silico tool was developed before any experimental data was given, and no parameters of computations were adjusted to fit the data. The success of the blind test provides fundamental understanding of the molecular mechanism of cyclization by cyanobactin macrocyclases, suggesting that formation of PCC is the rate-determining step. PCC formation might also play a part in other processes of cyclic peptides production and on the practical side the suggested tool might become useful for finding cyclizable peptide sequences in general.

The mechanism of patellamide macrocyclization revealed by the characterization of the PatG macrocyclase domain.

Peptide macrocycles are found in many biologically active natural products. Their versatility, resistance to proteolysis and ability to traverse membranes has made them desirable molecules. Although technologies exist to synthesize such compounds, the full extent of diversity found among natural macrocycles has yet to be achieved synthetically. Cyanobactins are ribosomal peptide macrocycles encompassing an extraordinarily diverse range of ring sizes, amino acids and chemical modifications. We report the structure, biochemical characterization and initial engineering of the PatG macrocyclase domain of Prochloron sp. from the patellamide pathway that catalyzes the macrocyclization of linear peptides. The enzyme contains insertions in the subtilisin fold to allow it to recognize a three-residue signature, bind substrate in a preorganized and unusual conformation, shield an acyl-enzyme intermediate from water and catalyze peptide bond formation. The ability to macrocyclize a broad range of nonactivated substrates has wide biotechnology applications.