A high-throughput library approach for minimizing peptide off-targets

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Recent breakthroughs in oral peptide delivery have vastly extended the chemical space which is available to drug protein/protein interactions and other challenging targets. In this context, high throughput techniques such as mRNA display are perfectly suited to provide clinical candidates. However, in contrast to classical approaches, these de novo peptide discovery technologies carry an increased risk of engaging off-targets, leading to less efficacious drugs and higher attrition rates due to potential adverse findings in toxicology studies. Consequently, innovative technologies to address these challenges are critically needed. In this project we will develop a streamlined mRNA-display-based approach to identify and subsequently minimize peptide off-targets using a photo-affinity labelling strategy. Complementary data from next generation sequencing and mass spectrometry will enable sophisticated in silico optimization of hit peptide sequences.