UCLA PI Name: Hosein Mohimani
E-Mail: hmohimani@g.ucla.edu
Division/Department: School of Medicine, Computational Medicine Department
Expected Weekly Time Commitment: 10-20 hours

Project description: Enzymes chemically transform small molecules. Understanding these transformations can help us figure out why some small molecule drugs are active in some patients, but inactive in others. Additionally, these reactions explain why people digest dietary molecules from food differently. Finally, knowledge of how enzymes change molecules can help us to optimize drug leads for the highest activity and least toxicity.

Recent methodological advances in machine learning have enabled predicting which enzymes react on small molecules and identifying the product of these reactions. However, currently, these methods have poor performance outside their training data. The major obstacle is that training data on the reaction of enzymes on small molecules is limited and non-homogenous. The goal of this project is to collect data on the reaction of hundreds of enzymes on thousands of small molecules using high-throughput mass spectrometry. The next step will be development of machine learning models based in this dataset to predict how enzymes modify small molecules.

Qualifications or skill required: 

Senior in Chemistry or Biochemistry

Application instructions:

To apply, please send a resume to hmohimani@g.ucla.edu.