Session # P690

Integration of protein stability and structural context scores improves bioinformatics predictions for BRCA1 and TP53 gene variants

Presenting Author: Matthew J. Varga, PhD

Take home points: 

1. Structural information is a useful tool in variant interpretation but until recently has not been available in a user-friendly format for non-experts.
2. This work obtained structural data from accessible sources and compared outputs to rich functional datasets for BRCA1 and TP53.
3. Results show that using these structural metrics improved predictions, particularly when combined with data from other bioinformatics predictors like AlphaMissense.

• Title: Integration of protein stability and structural context scores improves bioinformatics predictions for BRCA1 and TP53 gene variants
• Authors: Matthew J. Varga; Nitsan Rotenberg; Lobna Ramadane-Morchadi; Adam Chamberlin; Marcy E. Richardson; Cristina Fortuno; Miguel de la Hoya; Amanda B. Spurdle
• Collaborators: QIMR Berghofer Medical Research Institute; The University of Queensland
• Conference: ACMG 2024
• Date: Friday, Mar 15, 2024 10:30am - 12:00pm