Effects of Missense Mutations on Proteins and Protein-Protein Interactions "A Machine Learning Perspective"

Proteins are fundamental molecules that are responsible for most biological functions. Mutations in these proteins can cause malfunction and affect protein-protein interactions, leading to drug resistance and diseases such as cancer and diabetes. Understanding the effects of these mutations is crucial for creating treatments and engineering drugs. While mutation’s effect can be estimated using experimental technologies such as mass spectrometry, these are often expensive and time-intensive. It is highly desirable to have computational predictors to predict mutation’s effect accurately. This dissertation presents machine-learning approaches to predict and visualize the effect of mutations on proteins and protein-protein interactions.