Zinc N,N-bis(2-picolyl)amine Chelates Show Substitution-Dependent Cleavage of Phosphodiesters in Models as Well as of PNAzyme-RNA Bulges.

PNAzymes are a group of artificial enzymes which show promising results in selective and efficient cleavage of RNA targets. In the present study, we introduce a series of metal chelating groups based on N,N-bis(2-picolyl) groups (parent, 6-methyl and 6-amino substituted) as the active sites of novel PNAzymes. An improved synthetic route for the 6-amino analogues is described. The catalytic activity of the chelating groups for cleaving phosphodiesters were assessed with the model substrate 2-hydroxypropyl p-nitrophenyl phosphate (HPNPP), confirming that the zinc complexes have the reactivity order of parent < 2-methyl < 2-amino. The three ligands were conjugated to a PNA oligomer to form three PNAzymes which showed the same order of reactivity and some sensitivity to the size of the RNA bulge designed into the catalyst-substrate complex. This work demonstrates that the kinetic activity observed for the model substrate HPNPP could be translated onto the PNAzymes, but that more reactive Zn complexes are required for such PNAzymes to be viable therapeutic agents.

pIChemiSt ─ Free Tool for the Calculation of Isoelectric Points of Modified Peptides.

The isoelectric point (pI) is a fundamental physicochemical property of peptides and proteins. It is widely used to steer design away from low solubility and aggregation and guide peptide separation and purification. Experimental measurements of pI can be replaced by calculations knowing the ionizable groups of peptides and their corresponding pKa values. Different pKa sets are published in the literature for natural amino acids, however, they are insufficient to describe synthetically modified peptides, complex peptides of natural origin, and peptides conjugated with structures of other modalities. Noncanonical modifications (nCAAs) are ignored in the conventional sequence-based pI calculations, therefore producing large errors in their pI predictions. In this work, we describe a pI calculation method that uses the chemical structure as an input, automatically identifies ionizable groups of nCAAs and other fragments, and performs pKa predictions for them. The method is validated on a curated set of experimental measures on 29 modified and 119093 natural peptides, providing an improvement of R2 from 0.74 to 0.95 and 0.96 against the conventional sequence-based approach for modified peptides for the two studied pKa prediction tools, ACDlabs and pKaMatcher, correspondingly. The method is available in the form of an open source Python library at https://github.com/AstraZeneca/peptide-tools, which can be integrated into other proprietary and free software packages. We anticipate that the pI calculation tool may facilitate optimization and purification activities across various application domains of peptides, including the development of biopharmaceuticals.