Study of enzyme-catalyzed reactions in organic solvents using multiple linear regression

Abstract

We have used multiple linear regression to predict either initial rate, log initial rate or specificity for enzyme-catalyzed reactions performed in non-aqueous solvents. The Subtilisin Carlsberg catalyzed transesterification of N-acetyl- l-phenylalanine ethyl ester by methanol, 1-propanol, and 1-butanol was assayed in 30 non-aqueous solvents, and the lipase catalyzed transesterification of methyl methacrylate in 23 non-aqueous solvents. Both sets of reactions were performed at fixed thermodynamic water activity. The lipase catalyzed reactions were also performed in water saturated solvents and in dry solvents. The report illustrates that regression analysis may provide insight into how solvents can alter the activity and specificity of enzymes suspended therein. A regression model for the subtilisin catalyzed reaction suggests that solvents which have a flat hydrophobic region inhibit by competing with the substrate for an enzyme cleft. In the lipase catalyzed reaction, tetrachloroethylene is an outlier (i.e., behaves differently to other solvents) for all the regression models. This deviation, together with an element of structural similarity to the substrate, suggests that tetrachloroethylene acts as a competitive inhibitor. Log P is an important descriptor and it, or an expression containing log P, appears in all the regression equations. Log initial rate is predicted by a two-descriptor model for either enzyme system in solvents of high log P at fixed thermodynamic water activity. Regression models with the same two descriptors predict initial rate for the lipase system over the entire log P range for solvents maintained at fixed thermodynamic water activity and for dry solvents, but not for water saturated solvents.