Computational Simulation of Phosphoacetylglucosamine Mutase (PGM3) Enzyme for the Detection and Treatment of Glioblastoma Multiforme (GBM)

Abstract

Glioblastoma (GBM) is a type of aggressive brain cancer that claims over 200,000 lives in the US alone and has the lowest survival rate of all cancers. The PGM3 protein is a recently identified potential target for treating GBM. We can use antibodies to target the PGM3 protein, which are powerful tools that can bind to and neutralize proteins. We hypothesize that antibody 1A5F will bind strongly to the PGM3 protein. We first used Uniprot to get the amino acid sequence of the PGM3 protein. Then we plugged the sequence into AlphaFold3 to model the PGM3 protein. The protein was then downloaded and converted to the PDB format using ChimeraX software. We then randomly selected antibodies due to limited information on which exhibits the strongest binding affinity. To predict whether the protein and antibody will react, we used HDOCK. We have utilized this software to predict how the PGM3 protein binds to specific antibod- ies. We used PLIP to find the number of interactions between the protein and the antibody. For a deeper analysis, we utilized Prodigy to determine the binding affinity between the two molecules. Based on the above analysis, antibody 2ULY was selected as the most appropriate antibody targeting the PGM3 protein. This research will pave the way for lab-based research, for which the antibody will most efficiently target the PGM3 protein. It can lead to new drug discoveries to treat GBM more efficiently.