From molecular serendipity to design blueprints: learning the rules for new degrader drugs

Katelyn Randal is a Chemistry PhD student at Stanford and part of the Chemistry/Biology Interface (CBI) Training Program at Sarafan ChEM-H. CBI is an interdisciplinary training program that supplements traditional degree-granting PhD programs at Stanford. The program aims to help scientists speak multiple scientific languages spanning chemistry, biology, engineering, and medicine, and enable them to tackle the most challenging and important problems facing human health. Randal sat down to talk with us about her work to broaden the molecular toolbox for drug discovery.

What research area do you work in, and what problem are you trying to solve?

I work in Steven Banik’s lab in the chemistry department, where we design methods to study changes in cellular protein abundance. Specifically, I use our methods to study the application of chemical tools targeting E3 ligases, which are part of the native machinery that a cell uses to dispose of proteins that are old, damaged,  or otherwise no longer performing the functions that cells need. 

In the last 20 years, scientists have found that they can use specific drug molecules to hijack these natural degradation pathways to degrade proteins that are driving cancer, neurodegeneration, or other diseases. We are interested in using rational design and machine learning to generate molecules that can recruit an E3 ligase to degrade specific disease-causing proteins, with the goal of being able to develop new types of therapeutics that could, for example, provide more options for treating cancers that have become resistant to chemotherapies.  

Why has it been a challenge to design these types of degrader drugs?

Up to this point, discovery of these protein degraders has been mostly serendipitous, meaning there is no blueprint for targeting new proteins of interest. This is largely because these molecules do not target classic druggable pockets on proteins and instead rely on the slight alteration of protein surfaces to induce E3 recruitment. If we can piece together exactly what molecular motifs enable degradation of specific proteins, as well as what types of proteins can be degraded and to what extent, then we can start to see trends that will allow us to design or predict potential new drugs, instead of relying on luck to find them.

One thing that we’re really good at in the Banik lab is developing tools to look at minute changes in protein abundance in a cell. With these tools, we can measure whether a particular protein is depleted by a small, medium, or large amount. By screening many degrader molecules against many proteins, we are working towards generating a powerful dataset that will allow us to understand the underlying molecular principles behind how different degrader drugs work. We hope to use these data to identify trends and train a machine learning model that could help us develop drugs for proteins that are traditionally difficult to target.

What are you most excited about with your project?

With my project, and science in general, sometimes we think we are seeing the whole picture, but then a new paper comes out, or we find a new piece of evidence, and we have to expand our way of thinking. We have just started to get data that are providing another layer to the picture of how molecular glue degrader drugs work. Over the next six months, I’m really excited about picking different proteins and molecules that fit into the trends that we’re observing to see if they continue to match our model. We’ve also found some surprising outliers, where we seem to be recruiting native cellular machinery that we didn’t expect. I think that’s where some of the most interesting science happens—when you think you know the whole picture but then something totally different happens, and you get to go down a rabbit hole to see what’s at the bottom!

How did you become interested in the CBI program at Sarafan ChEM-H?

My undergrad degree was in chemical biology, so when I was looking at grad schools, I was thinking about labs where I could still sit at the intersection of chemistry and biology. I also found that there were many labs collaborating with other fields I hadn’t considered as a path for me before—like computer science, biophysics, and structural biology—and they were doing amazing things. The CBI program really spoke to me because, even if I joined a lab doing only chemistry or biology, I’d be able to talk to people in a close interdisciplinary community where I could ask for advice from my peers and stay up-to-date on all the interesting things that are going on in the rest of the science world. It’s nice to be able to go to people who are my friends and peers to discuss new ideas in an approachable and collaborative atmosphere.

Do you have any advice for incoming students?

Meet people. Take advantage of the connections in your CBI cohort and the generational knowledge of the cohorts above you. The CBI community has been a really important part of my PhD, as nearly all of my research collaborations have involved people from ChEM-H.

Also, try to learn about the science being conducted by your peers. It can be hard to look up from your own project, but I’ve recently started to more deeply consider the projects of my lab peers—seeing what is inspiring them, what they’re struggling with, and seeing how their projects fit into the larger scientific picture. That has provided a lot of insight into how to direct my project beyond just the very next step.

My last piece of advice is to take care of yourself outside of the lab and take advantage of being in the Bay Area—Yosemite is not that far away, the beach is not that far away, San Francisco is not that far away. I like to hike and go to the beach and go tide-pooling, and I’ve recently been getting into triathlons, which has been fun!  You never know where you might get scientific inspiration from!

Steven Banik is an assistant professor of chemistry in the School of Humanities and Sciences and an Institute scholar at Sarafan ChEM-H. He is also a member of Bio-X, the Wu Tsai Human Performance Alliance, and the Wu Tsai Neurosciences Institute.