Combined Theoretical and Experimental Study to Unravel the Differences in Promiscuous Amidase Activity of Two Nonhomologous Enzymes

Convergent evolution has resulted in nonhomologous enzymes that
contain similar active sites that catalyze the same primary and secondary
reactions. Comparing how these enzymes achieve their reaction promiscuity
can yield valuable insights to develop functions from the optimization
of latent activities. In this work, we have focused on the promiscuous
amidase activity in the esterase from Bacillus subtilis (Bs2) and compared with the same activity in the promiscuous lipase
B from Candida antarctica (CALB). The
study, combining multiscale quantum mechanics/molecular mechanics
(QM/MM) simulations, deep machine learning approaches, and experimental
characterization of Bs2 kinetics, confirms the amidase activity of
Bs2 and CALB. The computational results indicate that both enzymes
offer a slightly different reaction environment reflected by electrostatic
effects within the active site, thus resulting in a different reaction
mechanism during the acylation step. A convolutional neural network
(CNN) has been used to understand the conserved amino acids among
the evolved protein family and suggest that Bs2 provides a more robust
protein scaffold to perform future mutagenesis studies. Results derived
from this work will help reveal the origin of enzyme promiscuity,
which will find applications in enzyme (re)­design, particularly in
creating a highly active amidase.