In Silico Evaluation of Enzymatic Tunnels in the Biotransformation of α-Tocopherol Esters

Assessing the role of deep eutectic solvents in Yarrowia lipolytica inhibition

Yarrowia lipolytica has gained recognition as a microorganism with biological relevance and extensive biotechnological applications. Some of its features include a high enzyme secretion capacity and a high cell-density fermentation mode. Hexokinase (YlHxk) is a vital enzyme in Y. lipolytica growth since it catalyzes glucose metabolism through phosphorylation in the glycolytic pathway. Given the potential application of deep eutectic solvents (DES) as novel solvents in biotechnological processes, this study evaluated the influence of eighteen DES on the growth of Y. lipolytica. Furthermore, this work examined the effects of individual ions on the YlHxk enzyme by analyzing its enzymatic tunnel structure, molecule transport, and molecular docking. The results revealed a significant reduction in yeast growth in the presence of most DES compared to the control (medium without DES), with the exception of the [N8881]Cl: hexanoic acid (1:1) DES. The growth varied between 11.95 ± 0.60 and 0.68 ± 0.17 g dry cell weight L-1. According to the enzymatic tunnel analysis, DES components associated with the lowest microbial growth values were transported through tunnel 1. On the other hand, DES components had their pathway facilitated through tunnel 2 ([N8881]+ and hexanoic acid) and showed growth values close to the control. Molecular docking analysis identified a similarity between all the ligands in this tunnel (including substrate and product), presenting binding interactions with the ASN273 amino acid of the YlHxk active site. Combining experimental results with computational tools provided promising insights at the molecular level, while also potentially reducing analysis costs and time, paving the way for similar approaches in broad biocatalytic reactions.

Evaluation of lipase access tunnels and analysis of substance transport in comparison with experimental data

Lipases (E.C. 3.1.1.3) have buried active sites and used access tunnels in the transport of substrates and products for biotransformation processes. Computational methods are used to predict the trajectory and energy profile of ligands through these tunnels, and they complement the experimental methodologies because they filter data, optimizing laboratory time and experimental costs. Access tunnels of Burkholderia cepacia lipase (BCL), Candida rugosa lipase (CRL), and porcine pancreas lipase (PPL) and the transport of fatty acids, alcohols and esters through the tunnels were evaluated using the online server CaverWeb V1.0, and server calculation results were compared with experimental data (productivity). BCL showed higher productivity with palmitic acid-C16:0 (4029.95 µmol/h mg); CRL obtained productivity for oleic acid-C18:1 (380.80 µmol/h mg), and PPL achieved productivity for lauric acid-C12:0 (71.27 µmol/h mg). The highest probability of transport for BCL is through the tunnels 1 and 2, for CRL through the tunnel 1, and for PPL through the tunnels 1, 2, 3 and 4. Thus, the best in silico result was the transport of the substrates palmitic acid and ethanol and product ethyl palmitate in tunnel 1 of BCL. This result corroborates with the best result for the productivity data (higher productivity for BCL with palmitic acid-4029.95 µmol/h mg). The combination of in silico evaluation and experimental data gave similar results, demonstrating that in silico approaches are a promising alternative for reducing screening tests and minimizing laboratory time in the bio-catalysis area by identifying the lipases with the greatest reaction potential, as in the case of this proposal.