β-Glucosidases (βgls) primarily catalyze the hydrolysis of the terminal glycosidic bond at the non-reducing end of β-glucosides, although glycosidic bond synthesis (called transglycosylation) can also occur in the presence of another acceptor. In the final reaction step, the glucose product or another substrate competes with water for transfer to the glycosyl-enzyme intermediate. The factors governing the balance between the two pathways are not fully known; however, the involvement of ionizable residues in binding and catalysis suggests that their pKa may play a role. Through constant pH molecular dynamics simulations of a glycoside hydrolase Family 3 (GH3) βgl, we showed that the pKa of the catalytic acid/base residue, E441, is low (∼2) during either reaction due to E441–R125–E128 and E441–R125–E166 hydrogen bond networks. The low basicity of E441 would reduce its ability to deprotonate the acceptor. This may be less critical for transglycosylation because sugars have a lower deprotonation enthalpy than water. Moreover, their acidity would be increased by hydrogen bonding with R169 at the acceptor binding site. In contrast, no such interaction was observed for catalytic water. The results are likely applicable to other GH3 βgls because R125, E128, E166, and R169 are conserved. As these enzymes are commonly used in biomass degradation, there is interest in developing variants with enhanced hydrolytic activity. This may be accomplished by elevating the acid/base residue pKa by disrupting its hydrogen bond networks and reducing the affinity and reactivity of a sugar acceptor by mutating R169.

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Published in Organic & Biomolecular Chemistry, v. 16, issue 2, p. 316-324.

This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence. Material from this article can be used in other publications provided that the correct acknowledgement is given with the reproduced material and it is not used for commercial purposes.

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Acknowledgement is made to the Swedish Governmental Agency for Innovation Systems (VINNOVA, Grant No. 2015-04835) for support of this research. Simulations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at High Performance Computing Center North (HPC2N) and National Science Foundation (NSF) Extreme Science and Engineering Discovery Environment (XSEDE). XSEDE is supported by NSF Grant No. ACI-1548562 (Gordon cluster under allocation MCB090159).

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Electronic supplementary information (ESI) available: Details of computational method, glycosyl-enzyme intermediate force field parameters, simulation analyses, and movies of trajectories. See DOI: 10.1039/c7ob02558k

c7ob02558k1.txt (2 kB)
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Supplementary Information: S1-S24