Miranda Baumbick
Pronouns: She/Her
Research Mentor(s): Jaie Woodard, Postdoctoral Fellow
Research Mentor School/College/Department: Computational Medicine and Bioinformatics, Michigan Medicine
Presentation Date: Thursday, April 22, 2021
Session: Session 4 (2pm-2:50pm)
Breakout Room: Room 8
Presenter: 2
Abstract
Missense single nucleotide polymorphisms (SNPs) are single point mutations that alter the amino acid produced. By changing the amino acid, protein stability, pathogenicity, or chemical properties of the protein can change. These mutations can also cause various diseases, specifically diabetes, intellectual disability, and speech-language disorder. However, not all mutations are pathogenic. This study’s objective is to research the properties of these mutations by looking at the change in free energy, amino acid change, and pathogenicity and to determine whether or not it’s harmful to humans. The study specifically focused on the forkhead transcription factors, a set of DNA-binding proteins involved in regulating gene expression. Data was gathered from the Uniprot database, and PyMOL was used to determine protein to DNA contact. EvoEF was used to calculate the change in free energy, and SIFT and Polyphen-2 were used to predict pathogenicity. The results showed common trends among most pathogenic mutations such as high ??G values, no DNA contact, and a high damaging score. Therefore, the data collected is useful for making predictions about mutations.
Authors: Miranda Baumbick
Research Method: Computer Programming
