Candida antarctica lipase B performance in organic solvent at varying water activities studied by molecular dynamics simulations

• Published in: Computational and Structural Biotechnology Journal
• Main Authors: Helena D. Tjørnelund, Jesper Vind, Jesper Brask, John M. Woodley, Günther H.J. Peters
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2023
• Subjects: Biocatalysis; Candida antarctica lipase B (CALB); Esterification; Protein engineering; Organic solvent; Water activity; Biotechnology; TP248.13-248.65; Antarc*; Antarctica
• Online Access: https://doi.org/10.1016/j.csbj.2023.10.049; https://doaj.org/article/be0903e15e434dc0849ff019a95073f8

Applications of lipases in low-water environments are found across a broad range of industries, including the pharmaceutical and oleochemical sectors. This includes condensation reactions in organic solvents where the enzyme activity has been found to depend strongly on both the solvent and the water activity (aw). Despite several experimental and computational studies, knowledge is largely empirical, and a general predictive approach is much needed. To close this gap, we chose native Candida antarctica lipase B (CALB) and two mutants thereof and used molecular dynamics (MD) simulations to gain a molecular understanding of the effect of aw on the specific activity of CALB in hexane. Based on the simulations, we propose four criteria to understand the performance of CALB in organic media, which is supported by enzyme kinetics experiments. First, the lipase must be stable in the organic solvent, which was the case for native CALB and the two mutants studied here. Secondly, water clusters that form and grow close to the active site must not block the path of substrate molecules into the active site. Thirdly, the lipase’s lid must not cover the active site. Finally, mutations and changes in aw must not disrupt the geometry of the active site. We show that mutating specific residues close to the active site can hinder water cluster formation and growth, making the lipase resistant to changes in aw. Our computational screening criteria could potentially be used to screen in-silico designed variants, so only promising candidates could be pushed forward to characterisation.