Abstract
Protein modeling aids in developing novel protein configurations that are critical in, for example, the pharmaceutical and environmental industries. However, the predictive capabilities of the protein modeling algorithms are limited due to a lack of experimental data on structure and function. To bridge this gap, Seigel Lab at UC Davis developed the Design to Data (D2D) program to catalog thermal stability and catalytic efficiency data sets on β-glucosidase B (BglB) variants. Over 300 BglB variants have been characterized. However, there are over 8400 possible BglB single-point mutations. We utilized Foldit software to design BglB mutants E26K, I170Y, and V398N. The variants were tested for catalytic efficiency and thermal stability using a calorimetric assay. Our results show that the mutants exhibited a decrease in thermal stability and catalytic efficiency. These data were uploaded to the D2D database, increasing the BglB data sets.
Recommended Citation
Ahlstedt, Carter; Bennett, Annika; and Kaluka, Daniel
(2024)
"Design to Data for mutants of β-glucosidase B from Paenibacillus polymyxa: E26K, I170Y, and V398N,"
Lux et Fides: A Journal for Undergraduate Christian Scholars: Vol. 2, Article 3.
Available at:
https://pillars.taylor.edu/luxetfidesjournal/vol2/iss1/3