Computational insights into the mutations of an omega-transaminase using evolutionary footprints

Transaminases have become highly remarkable enzymes for manufacturing enantiopure chiral amines. These chiral amines hold great significance as intermediates in the production of pharmaceuticals and various fine chemicals. Nonetheless, the restricted activity of transaminases frequently presents a challenge in their application for biocatalysis. Consequently, developing novel enzymes with enhanced activity and the ability to function effectively in industrial process conditions has become a crucial matter. Although a variety of studies focus on the development of new variants by mutations in the active site of the enzymes, it remains unclear how beneficial the mutations far from the active site confer improved catalytic properties. Getting an insight into this issue would aid the design of new enzymes with higher catalytic activities. Moreover, for natural evolution perspective, it is also shrouded in mystery how mutations far from the active site affect the active sites' functions and also stability. In this study, the objective is to develop an understanding on the effects of mutations realized during the natural evolution of an omega-transaminase, using computational tools. To achieve the stated purpose, a modern-day 4-aminobutyrate transaminase, and its three ancestral variants having improved catalytic activity and substrate promiscuity were chosen to study. All mutations that occurred during their evolution of this family were outside the active sites of the enzymes. Thus, effects of the mutations that occurred at the dynamic domain interfaces were put under the scope so that mutations could be classified and the important ones for the catalytic activity in addition to substrate selectivity could be identified. Functional collective motions of the variants were evaluated by using computational methods, Gaussian Network Model (GNM) and Anisotropic Network Model (ANM). It was revealed that the mutations at cross-correlation difference regions and close to hinge points have significant influence on the loop dynamics near the active sites resulting in the activity and selectivity changes. Molecular dynamic simulations results led to verification of the conservation of active site interactions in all variants, as well as understanding of the structural changes in the global behavior of the variants determining their thermotolerances.