Event Title

Computational Prediction of Mutagenesis in Soybean Rubisco Activase Monomer for Increased Thermal Stability

Advisor(s)

Dr. Sarah Stainbrook; Washington University of St. Louis

Dr. Angela Ahrendt; Illinois Mathematics and Science Academy

Discipline

Biology

Start Date

21-4-2021 10:25 AM

End Date

21-4-2021 10:40 AM

Abstract

Due to the onset of climate change, measures must be taken to circumvent the decreased rate of net photosynthesis of Glycine max (soybean) under high temperatures. Although the decreased rate is due to a myriad of factors, one promising avenue to a solution is the enzyme rubisco activase (RCA). At higher temperatures, RCA is unable to activate Rubisco to fix carbon dioxide as quickly, leading to a decreased rate of net photosynthesis. We have attempted to improve the thermostability of RCA through computationally predicting the effects of single point mutations. Several computational tools were tested for accuracy utilizing experimental data previously obtained from Argonne National Laboratory. The tool PremPS was eventually selected since it was most accurate. Through PremPS, we tested a total of 399 mutations, of which 32.33% were predicted to be stabilizing. Mutagenic primer designs will allow the most successful theoretical mutations to be evaluated in vitro. Using the strategies of mutating non-conserved residues, hexamer formation, monomer interaction, intramolecular bonds, Pymol location and bond identification, and hydrophobic properties in conjunction with single-point mutagenesis led to promising theoretical results of a more thermally stable RCA.

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Apr 21st, 10:25 AM Apr 21st, 10:40 AM

Computational Prediction of Mutagenesis in Soybean Rubisco Activase Monomer for Increased Thermal Stability

Due to the onset of climate change, measures must be taken to circumvent the decreased rate of net photosynthesis of Glycine max (soybean) under high temperatures. Although the decreased rate is due to a myriad of factors, one promising avenue to a solution is the enzyme rubisco activase (RCA). At higher temperatures, RCA is unable to activate Rubisco to fix carbon dioxide as quickly, leading to a decreased rate of net photosynthesis. We have attempted to improve the thermostability of RCA through computationally predicting the effects of single point mutations. Several computational tools were tested for accuracy utilizing experimental data previously obtained from Argonne National Laboratory. The tool PremPS was eventually selected since it was most accurate. Through PremPS, we tested a total of 399 mutations, of which 32.33% were predicted to be stabilizing. Mutagenic primer designs will allow the most successful theoretical mutations to be evaluated in vitro. Using the strategies of mutating non-conserved residues, hexamer formation, monomer interaction, intramolecular bonds, Pymol location and bond identification, and hydrophobic properties in conjunction with single-point mutagenesis led to promising theoretical results of a more thermally stable RCA.