Working with Protein Models

This is part of a series of posts by recipients of the 2021 Career Services Summer Funding Grant. We’ve asked funding recipients to reflect on their summer experiences and talk about the industries in which they spent their summer. You can read the entire series here.

This entry is by Sagar Gupta, COL ’24

This summer, I continued working in the protein modeling lab I joined last fall. My experience working in Dr. Nikolaos Sgourakis’s lab at the Children’s Hospital of Philadelphia has been truly memorable and thought-provoking. With support from Career Services, I was able to help develop a protein homology modeling software relevant to human immunological diseases.

The protein that I was tasked with modeling, major histocompatibility complex class I (MHC I), exhibits extreme polymorphism in that there are over 10,000 alleles of this protein across the human population. MHC I is crucial to the antigen processing pathway since it presents peptide antigens derived from proteins in the cytosol onto the cell surface for T cell surveillance. Essentially, MHC I informs the immune system whether a given cell is healthy or has been compromised. Given that each of the thousands of MHC alleles can bind thousands of peptides, this presents a pertinent modeling problem that cannot be solved with experimental, time-consuming methods like X-ray crystallography and NMR.

To address this issue, I utilized the Rosetta software suite and wrote code in Python and R. Throughout the development of our software, I helped develop and optimize a feed-forward neural network which would assist in selecting accurate structures. My responsibilities included writing and troubleshooting scripts, analyzing structures in a tool called PyMOL, and benchmarking different variations of the neural network. I was exposed to key ideas in biochemistry and biophysics such as the dihedral angles of amino acid residues and became more confident in my programming skills.

At the end of the summer, I got the opportunity to present my work to the scientific community at RosettaCon, a protein modeling software conference. There, I explained how this project has clear applications to the ongoing pandemic. Scientists can model peptides derived from SARS-CoV-2 proteins and determine how to induce an effective immune response. By participating in this conference, I met leaders in the field of protein modeling and garnered information from other projects which could inform my work going forward.

Not only did I gain an immense amount of scientific knowledge by working on this project, but I also was constantly stimulated because the lab environment was filled with curious and intelligent minds. I learned about many postgraduate opportunities and made valuable connections with lab members which will help me pursue my career goal of becoming an academic researcher. Thanks to a generous grant from Career Services, I was able to pursue this opportunity and not worry about other financial issues. I look forward to applying what I have learned this summer to further research this topic during the school year.

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