Proteins control a variety of intra- and extracellular biological processes and when sequenced or expressed and activated incorrectly can increase the likelihood of disease. Protein-protein interactions (PPIs) are fundamental in the stable running of cellular processes where they can alter the kinetic properties of enzymes, create new binding sites, inactivate proteins, and change the specificity of a protein. PPIs can be manipulated by small molecules that can change the outcome of a variety of different cellular processes. The inhibition of these cellular processes can prevent diseases, therefore, inhibiting PPIs is becoming increasingly attractive for novel therapeutics.
In this SelectScience® interview, we speak with Dr. David Andrews, Director of Pre-Clinical Scientific Alliances, AstraZeneca, to discuss the latest work of the Perturbation of Protein-Protein Interactions (PoPPI) program, a collaboration between the University of Leeds, University of Bristol, Northern Institute for Cancer Research, AstraZeneca and Domainex, to examine the impact of potential therapies for cancers and neurological diseases which target PPIs.
DA: The revolution in gene sequencing has led to the identification of many proteins that are mutated, deleted, or amplified in disease. In many cases, the enzyme or receptor functionality of these new proteins is modulated by their interaction with other proteins. Additionally, we are now seeing the emergence of protein targets of interest that have no known function, in which case their scaffold or other PPI functions become highly pertinent.
DA: PoPPI is applying a wide range of techniques to help better understand small molecule-PPI interactions. Of the methods being explored, I have a keen interest in computational methods, biophysics, and chemical biology.
DA: We have developed a workflow that we term ‘query-guided PPI inhibitor discovery’. This is implemented through several stages that combine established computational tools and experimental validation. Initially, a query is built that incorporates the key secondary structural motif and hot residues from the PPI. A virtual library of small molecules is then shape-matched against the query, and promising compounds docked against the target protein. Candidate inhibitors are then subjected to experimental screening and hits are selected using conventional hit-to-lead methods. We’ve just published this work in the open-access RSC journal Chemical Science1.
DA: We hope that establishing a workflow and toolkit will enable researchers to identify PPI inhibitor start points using AI and computational methods, rather than relying on ‘brute force’ high-throughput screening strategies.
DA: There can be very few, if any, therapy areas that do not exemplify protein-protein interactions as targets. In our paper, we illustrated the workflow with one PPI each from the neuroscience and oncology fields of study1. In an unrelated, late-2020 publication, the first pan-coronavirus interactome was published illustrating the wide relevance of these targets to anti-infectives2.
Discover more advancements in the field of drug discovery in our Advances in Drug Discovery Special Feature>>