Active Cells, Biochemistry & Physiology Genetics & Molecular Biology

Cyclic Peptide Platform as an Approach to Target Validation

Summary

Original abstract (not yet simplified)

The current ‘genomics’ era is an exciting time for drug target discovery with considerable opportunities for therapeutic intervention. Whilst classical small molecules remain the reagents of choice as chemical probes for target validation, not all targets are tractable with small molecules. There is thus an urgent need to develop methods for more efficient target validation, not only of individual proteins...

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The current ‘genomics’ era is an exciting time for drug target discovery with considerable opportunities for therapeutic intervention. Whilst classical small molecules remain the reagents of choice as chemical probes for target validation, not all targets are tractable with small molecules. There is thus an urgent need to develop methods for more efficient target validation, not only of individual proteins but also of protein-protein and other complexes. Natural product like cyclic peptides have enormous potential as a chemical platform for target validation. Recent technological advances have enabled the efficient production and screening of large libraries containing non-proteinogenic residues. De novo cyclic peptides with high affinity and selectivity for target proteins can be readily generated, even for protein-protein interaction targets perceived as challenging. Development of this technology and their innovative applications as outlined in our proposal will provide a step-change in methodology, and transform the current approach for studying the biological function of the target / pathways, enabling new ways to investigate potential targets.We aim to develop innovative chemical and molecular techniques to explore the applications of natural product-like cyclic peptides in target validation for very challenging targets. Ultimately the work aims to enable the development of new therapeutic agents targeting multiple diseases.

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Original classification

H2020

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