The druggable genome: Twenty years later - Radoux, Chris J.; Vianello, Francesca; McGreig, Jake; Desai, Nikita; Bradley, Anthony R. (Frontiers in Bioinformatics, 2022)
The concept of the druggable genome has now been with us for twenty years. During this time, researchers have developed a number of methods and resources to help assess a target’s druggability. In parallel, evidence for target-disease associations has been collated at scale by Open Targets. More recently, the Protein Data Bank in Europe (PDBe) have built a knowledge base matching per-residue annotations with available protein structure. While each of these resources is useful in isolation, we believe that there is huge potential in bringing together all relevant data into a single knowledge graph, from gene-level to protein residue. Automation is vital for the processing and assessment of all available structures. We have developed scalable, automated workflows that provide hotspot-based druggability assessments for all available structures across large numbers of targets. Ultimately, we will run our method at a proteome scale, an ambition made more realistic by the arrival of AlphaFold 2. Bringing together annotations from the residue up to the gene level, and building connections within the graph to represent pathways or protein-protein interactions, will create complexity that mirrors the biological systems they represent. Such complexity is difficult for the human mind to utilise effectively, particularly at scale. We believe that graph-based AI methods will be able to expertly navigate such a knowledge graph, selecting the targets of the future.