Extending the computational and experimental analysis of lipase active site selectivity.

Molecular docking is an important computational analysis widely used to predict the interaction of enzymes with several starting materials for developing new valuable products from several starting materials, including oils and fats. In the present study, molecular docking was used as an efficient in silico screening tool to select biocatalysts with the highest catalytic performance in butyl esters production in a solvent-free system, an eco-friendly approach, via direct esterification of free fatty acids from Licuri oil with butanol. For such purpose, three commercial lipase preparations were used to perform molecular docking studies such as Burkholderia cepacia (BCL), Porcine pancreatic (PPL), and Candida rugosa (CRL). Concurrently, the results obtained in BCL and CRL are the most efficient in the esterification process due to their higher preference for catalyzing the esterification of lauric acid, the main fatty acid found in the licuri oil composition. Meanwhile, PPL was the least efficient because it preferentially interacts with minor fatty acids. Molecular docking with the experimental results indicated the better performance in the synthesis of esters was BCL. In conclusion, experimental results analysis shows higher enzymatic productivity in esterification reactions of 1294.83 μmol/h.mg, while the CRL and PPL demonstrated the lowest performance (189.87 μmol / h.mg and 23.96 μmol / h.mg, respectively). Thus, molecular docking and experimental results indicate that BCL is a more efficient lipase to produce fatty acids and esters from licuri oil with a high content of lauric acid. In addition, this study also demonstrates the application of molecular docking as an important tool for lipase screening to achieve more sustainable production of butyl esters with a view synthesis of biolubricants.