Genome Compiler

Today we’re opening our structure-free AI drug discovery model for all to use! Ptarmigan-1 predicts which small molecules bind a protein, and where, without building a 3D protein structure. It learns from multiple kinds of data, including measurements of proteins at work inside living human cells. This is the culmination of a long and winding path to get here In my first week of grad school, I sat in a lecture hall where generations of chemists had trained and Nobel Prizes hung on display. One of the most accomplished chemists in the world introduced us to the word “undruggable,” describing targets that so many had given up on. I remember sitting there feeling so indignant. Of course all targets are impossible to drug until the right technology lets you drug it. Thankfully I found my people in @jaybradner's lab, where the T-shirts said “nothing is undruggable”, and got to work We focused on gene regulators there, proteins that control which genes turn on and off and can drive cancer. Most are poorly structured, making them difficult targets for traditional tech that focus on a well-defined binding pocket. Gene regulators are not the only disordered proteins though. Roughly 40% of the human proteome has significant disorder, and these targets remain out of reach while discovery for structured proteins gets faster every year. With Ptarmigan-1, we’re giving researchers a way to search for molecules against these targets without first having to solve their structure. I’m grateful to the team and supporters that brought us here. Now we get to see what the community does with it. Try it and tell us what you think. Link below.