Computational modeling is a valuable tool that allows for the design and engineering of novel enzyme catalysts. However, current methods do not consider key relationships between amino acid sequence and enzyme kinetics, as current approaches are trained on indirect measures of enzyme function. To develop tools capable of these types of predictions, a large data-base of Michaelis-Menten constants of different mutants must be collected for use in further training of computational algorithms. For this reason, a set of 129 point-mutants of β-glucosidase B (BglB) from the bacterium <i>Paenibacillus polymyxa</i> (AC: P22505) have been kinetically characterized. However, a larger library is needed to make significant improvements to the computational prediction of enzyme activity. This work reports the Michaelis-Menten kinetics and thermal stability constants for three BglB mutants (W409S, I90F, T175K) designed using FoldIt. Mutants were generated using Kunkel mutagenesis and the purified proteins were used to obtain thermal stability and kinetic activity data. All mutants studied express in <i>E. coli.</i> and have similar kinetic constants to wild type BglB, although the catalytic activity of I90F is lower than that of the wild type. Interestingly, I90F is not the least thermally stable, although melting temperature does not vary significantly between mutants and WT. Additional mutants will be developed and characterized to expand upon the current existing data set. Ultimately, this work is aimed to aid in the development of new tools for computationally designing enzymes.

Thermal stability and kinetic constants of a model enzyme to improve computational design

2019 Spring National Meeting

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