Platform for Analyzing the Mutations associated with Schizophrenia (PAMS) - Project Summary / Abstract Schizophrenia (SCZ) is a severe psychiatric disorder affecting millions globally, with significant economic and social impacts. Despite extensive research, the molecular mechanisms underlying SCZ remain largely elusive, particularly the role of rare genetic mutations. Recent advancements in next-generation sequencing (NGS) and machine learning (ML) offer new avenues to explore these genetic variations. Our proposal aims to develop the Platform for Analyzing Mutations associated with Schizophrenia (PAMS), a comprehensive computational tool integrating structure-based energy calculations and sequence-based ML to predict the effects of mutations in SCZ-associated genes. In Aim 1, we will investigate the impact of missense mutations on protein stability by generating computational structures for 12 SCZ risk genes using AlphaFold and the SWISS-MODEL Repository, applying computational saturation mutagenesis, and assessing the effects on protein stability through changes in folding free energy (ΔΔG). In Aim 2, we will predict the effects of mutations on protein-protein interactions by constructing complex structure models of SCZ risk genes with their interacting partners, calculating binding energy changes (ΔΔΔG), and validating these effects through co-immunoprecipitation (co-IP). In Aim 3, we will develop PAMS to analyze mutations in 921 genes identified from a meta-analysis, integrating sequence-based ML predictors and structure-based calculations to predict the consequences of mutations on protein stability and interactions. PAMS will feature a comprehensive database and user-friendly website for accessible analysis, enhancing collaboration in psychiatric genetics and bioinformatics. This platform aims to elucidate the molecular mechanisms of SCZ, providing valuable insights into the functional effects of rare mutations and offering research-intensive training opportunities for students at Howard University.
