Substrate structure and computation guided engineering of a Lipase for Omega-3 fatty acid selectivity

Abstract

AbstractOptimum health benefits of omega-3 fatty acids (ω-3 FAs) require it to be concentrated in its natural sources. Fatty acid selectivity of lipase governs the efficacy of the production of lipase-mediated ω-3 FAs concentrates. We attempted to improve the fatty acid selectivity of a lipase from thermophilic bacteriumGeobacillus thermoleovorans(GTL) by two approaches. In a semi-rational approach, six amino acid positions of GTL interacting with the substrate, were identified by docking and were subjected to site-saturation mutagenesis. Three best substitutions were incorporated into GTL(CM-GTL). Hydrolysis of oil by lipase was monitored in a pH-Stat and the fatty acids released at various time points were analyzed by GC-MS.CM-GTL showed a significant improvement in discrimination against DHA during hydrolysis. In the second approach based on rational design, the active site was narrowed by incorporating heavier amino acids in the lining of acyl-binding pocket to hinder access to bulky ω-3 FAs. For this purpose, two amino acids surrounding the opening of the acyl pocket were replaced with the next heavier amino acids and the affinities were evaluatedin silico.The double mutant, thus deigned, was found to be excellent in discriminating the ω-3 FAs during hydrolysis of triglycerides. Engineering the binding pocket of a complex substrate, such as a triglyceride, with the supportive information on substrate structure and its binding modes with the enzyme provided by computational methods, has resulted in designing two efficient lipase variants with improved substrate selectivity.