High Schooler Tackles Computational Drug Discovery

Research experiences can be lifechanging for young people, informing their education and career decisions before they even complete high school. For rising high school senior Pavan Subramani from Morgantown High School, this scientific exploration started in his sophomore year when he read that a promising drug against a protein involved in many inflammatory diseases failed in its clinical trial; he wanted to understand how to improve such a drug. This simple question culminated in an invaluable research experience that solidified Subramani’s interest in computational drug discovery.

How did you get involved with research?

I started by reading scientific studies about this protein, receptor for advanced glycan end products (RAGE), and the small molecule that was developed against it. I took online courses to learn Python so that I could screen potential drugs from a database for their binding and then explore how these could be optimized to recognize RAGE.

From this work, I identified a candidate that was predicted to perform better than currently existing drugs. At this time, I thought that I could benefit from having a formal mentor to explore more complicated questions, so I looked up research programs and found the Open Bio Student Research Institute. After applying to and being selected for this program, I worked with a graduate student researcher, Joseph Torsiello from Temple University, to develop a preliminary technique to determine protein conformations in molecular dynamic simulations. These studies aim to predict how proteins move over time, which is important in developing drugs. As part of this work, I got the opportunity to publish my findings, which was a really interesting experience.¹ Writing a research article for a journal involves a lot more detail than the papers I wrote for high school assignments, and I really appreciated the feedback from peer reviewers about how to improve the paper and the project overall.

After this program, I wanted to continue my research project, so I looked online for experts and found computational scientist David Mobley at the University of California, Irvine. I reached out to him directly about working under him to further develop the technique I created and to expand it to study protein-drug interactions. One of the limitations in molecular dynamic simulations is that these predictions take a lot of time to generate, delaying drug discovery pipelines. My approach used machine learning to predict important protein-ligand conformations and, instead of modeling the entire transition, “jump” between these two configurations and estimate the energy differences between them. Mobley helped me improve my technique’s accuracy in evaluating the thermodynamics of these molecules and deciding on the best target system to validate my method. I feel like the advice I got from my mentor strengthened my project and also greatly exceeded my expectations. I’ll continue working with Mobley, shifting to studying the ligand conformations within a protein binding pocket. This new technique could expedite drug discovery pipelines.

How have these research experiences affected your career goals?

Before conducting any research, I was interested in chemistry and physics and ways to apply them to human health, like through drug discovery. My student research experiences gave me the chance to determine if I actually really liked this type of work, and they definitely confirmed for me that I want to work in computational drug discovery and biophysics. Finding a mentor in this field was also very helpful because working independently, I had to conduct the literature review and interpret the findings on my own, so I could miss important information and spend a lot of time trying something that wasn’t going to succeed. Working with an expert helped me avoid a lot of those pitfalls.

What advice do you have for your peers interested in research?

I think that a lot of times people get overwhelmed because they assume that research is going to be too complicated to do, but I think that the hardest part is really just getting started. I think that my research experiences were very helpful in influencing my career decisions, and I would recommend any student interested in STEM to find and join a research project. The first step really is the hardest, but it only gets easier from there.

This interview has been edited for length and clarity.