Computational and experimental analysis on the preferential selectivity of lipases for triglycerides in Licuri oil.

In the present study, we demonstrated the use of molecular docking as an efficient in silico screening tool for lipase-triglyceride interactions. Computational simulations using the crystal structures from Burkholderia cepacia lipase (BCL), Thermomyces lanuginosus lipase (TLL), and pancreatic porcine lipase (PPL) were performed to elucidate the catalytic behavior with the majority triglycerides present in Licuri oil, as follows: caprilyl-dilauryl-glycerol (CyLaLa), capryl-dilauryl-glycerol (CaLaLa), capryl-lauryl-myristoyl-glycerol (CaLaM), and dilauryl-myristoyl-glycerol (LaLaM). The computational simulation results showed that BCL has the potential to preferentially catalyze the major triglycerides present in Licuri oil, demonstrating that CyLaLa, (≈25.75% oil composition) interacts directly with two of the three amino acid residues in its catalytic triad (Ser87 and His286) with the lowest energy (-5.9 kcal/mol), while other triglycerides (CaLaLa, CaLaM, and LaLaM) interact with only one amino acid (His286). In one hard, TLL showed a preference for catalyzing the triglyceride CaLaLa also interacting with His286 residue, but, achieving higher binding energies (-5.3 kcal/mol) than found in BCL (-5.7 kcal/mol). On the other hand, PPL prefers to catalyze only with LaLaM triglyceride by His264 residue interaction. When comparing the computational simulations with the experimental results, it was possible to understand how BCL and TLL display more stable binding with the majority triglycerides present in the Licuri oil, achieving conversions of 50.86 and 49.01%, respectively. These results indicate the production of fatty acid concentrates from Licuri oil with high lauric acid content. Meanwhile, this study also demonstrates the application of molecular docking as an important tool for lipase screening to reach a more sustainable production of fatty acid concentrates from vegetable oils.