Peptide nucleic acid-encoded libraries for microarray-based enzymatic high-throughput screening

Abstract

Protein kinases represent one of the largest families of enzymes. Due to their crucial roles in many cellular processes, protein kinases have become one of the major drug targets for pharmaceutical companies. In order to be able to determine selective substrates, elucidate pathway functionality and design potential kinase inhibitors, it is important to determine kinase substrate specificity. A 10,000-member split and mix peptide nucleic acid (PNA)-encoded peptide library was used to establish the substrate specificity of three different protein tyrosine kinases, using a DNA microarray and a Cy3-fluorescently labelled secondary anti-phosphotyrosine antibody. This approach was proven to be a powerful tool as several peptides (“hits”) were rapidly identified as good substrates for the three kinases. Split and mix combinatorial libraries can generate large peptide libraries consisting of potentially millions of compounds, but the main disadvantage is the deconvolution process required to identify active individual peptides from mixtures. The aim of the second part of the project was to build a PNA-encoded positional scanning library of FRET-based tetrapeptides to carry out microarray-based proteolytic profiling. As proof-of-principle, a 625-member library was first synthesised on solid phase using a split and mix methodology, and successfully used to profile three different proteases. The concept was then extended to the synthesis of a larger positional scanning library containing 50,625 different tetrapeptides encoded for by just 60 PNA tags.