Presenter(s)
Clinton Belott
Files
Download Project (4.6 MB)
Description
“Bioinformatics” utilizes computer scripts and some degree of artificial intelligence (AI) to constructively break down and process large sets of biological data into tangible results. Using bioinformatics programs like Alphafold3 and AIUPred, it is possible to break down and understand the complex interactions between transcription factors and potential repressors, activators; and the competitive nature between repressors and activators. Alphafold3 predicts three-dimensional protein confirmation and binding between or among proteins all in a probabilistic manner. AIUPred was then used to predict areas of protein-protein binding, motifs, and redox sensitivity. The resulting synergy between Alphafold3 and AIUPred was capable of correctly predicting protein interactions that have been previously empirically demonstrated. Therefore, we sought to leverage these bioinformatic programs to discover novel interactions between transcription factors like Drosophila Scalloped (TEAD in mammals), which forms activator- and repressor-complexes depending on its binding partners that play a major role in growth, development, and cancer. For proteins that are already known to interact, Alphafold3 and AIUPred provided insights at a motif- and/or residue-level, which can be corroborated with molecular level interactions amongst proteins. Furthermore, our results predicted several novel protein interactions, including cross-talk interactions between proteins belonging to two different canonical pathways involved with growth, development, and cancer. Excitingly, we hypothesize that this may shed light on the enigmatic nature of some proteins to act as a repressor in some experimental conditions, or as an activator in others. Lastly, we are currently in the process of experimentally testing these predictions using in cellulo models.
Publication Date
4-23-2025
Project Designation
Graduate Research
Primary Advisor
Madhuri Kango-Singh
Primary Advisor's Department
Biology
Keywords
Stander Symposium, College of Arts and Sciences
Institutional Learning Goals
Scholarship; Practical Wisdom; Vocation
Recommended Citation
"Using Bioinformatics to Discover Novel Interactions Regulating Growth, Development, and Cancer" (2025). Stander Symposium Projects. 4098.
https://ecommons.udayton.edu/stander_posters/4098

Comments
3:00-4:15, Kennedy Union Ballroom