1. Introduction
Natural enzymes usually only evolve relevant catalytic performance
according to their own needs. When enzymes are used in industry, methods
are needed to be explored to tailor their activity towards industrially
relevant substrates, and these enzymes should also be optimized towards
industrial reaction conditions.1 To improve the
production in industry which involves biocatalysts, increasing activity
of enzymes for specific substrates is the key.2Besides, given that high temperatures in industrial processes including
reaction, purification, packaging etc. provide benefits such as
increased substrate solubility, improved diffusivity, decreased
viscosity of the medium, and a lower risk of microbial contamination,
thermostability of enzymes is another important
property.3, 4
Enzymes obtained from natural recruitment and protein engineering have
greatly contributed in various sets of applications. Over recent
decades, the newly developed methods in the protein engineering,
including directed evolution, semi-rational design, and de novodesign, have enabled to obtain numerous better enzymes for the
industrial application.5-7 The catalytic activity and
thermostability of many enzymes has been improved by directed evolution.
By screening the triple mutant C168T/Q192H/Y7L with error-prone PCR and
site-saturation, the thermostability and enzyme activity of GH11
xylanase from Aspergillus fumigatus RT-1 were
improved.8 Lin et al. identified a N255D mutant by
random mutagenesis with 14-fold higher activity than the wild type
Horseradish Peroxidase.9 Yin et al. also constructed a
mutation library with error-prone PCR. In this library, three
five-linked mutants Bgl1D2, Bgl1D6 and Bgl1D20 stands out to have
2.3-2.6 times higher hydrolytic activity, while only Bgl1D2 becomes more
stable. It has seven times higher thermostability, whereas Bgl1D6,
Bgl1D20 shows no significant change in thermostability compared with the
wild type.10
Despite of the success of the above trials, directed evolution is
unfavorable when one considers the experimental resources it requires
for mutants in a large library. Semi-rational design of proteins deals
with this problem by introducing bioinformatics to rationally reduce the
size of the mutant’s library. At present, the catalytic activity and
thermostability of enzyme are mainly improved by semi-rational design.
Generally, the non-conservative amino acids around the active site may
be related to the catalytic performance of the enzyme, and hence the
catalytic activity of enzymes can be improved by changing the
non-conservative amino acids.11 Moreover, based on the
correlation between thermostability of proteins and factors such as
hydrophobicity, packing density,12, 13 number of
disulfide bonds,14 strength of electrostatic
interactions,15, 16 length of surface
loops,13 conformational rigidity,17,
18 amino acid coupling patterns,19 and local
structural entrop,20 bioinformatics software is
generally developed to design proteins with good thermostability using
proline theory,21 B-fitter,18Rosetta,22 molecular dynamics
simulations23 and disulfide by design et
al24.
Notably, among these semi-rational methods, mutants which have been
designed to show improved thermostability, all display lower enzyme
activity,25, 26 and vice versa.11 It
is reasonable when we noticed the contradiction in the adjustment of
protein structures between the two design strategies. Specifically, high
catalytic activity was often obtained by reducing their surface
hydrophobicity and hence increasing the flexibility of the
structure,27-29 while enzymes with good stability were
designed by making the structure more rigid, which involves enhancing
their surface hydrophobicity.30-31 Thus, it is
impossible to simply combine these strategies to design enzymes with
both properties improved. Given that the high catalytic activity and
good thermostability are both related to reduced costs, and vice versa,
when one considers to optimize the total costs, which is often the case
in the industry, new effective semi-rational design method is needed to
be developed to simultaneously improve the catalytic activity and
thermostability of enzymes.
To fill this need, here we proposed a double-screening strategy to
obtain mutants with both properties improved based on compactional
analysis and prediction of enzyme properties. Firstly, given that the
non-conservative amino acids around the active site is related to the
catalytic performance of the enzyme, mutation on the non-conserved
residues in the catalytic region could bring potential higher activity.
These mutants could be further screened virtually to select mutants with
favorable heat stability. In this way, a relatively small library of
mutants of potential simultaneous higher activity and thermostability
could be further constructed and tested experimentally. Thus, not only
does this strategy overcome the disadvantages of directed evolution,
i.e. too large a library to do experiments, but also consider the
shortcoming of the current semi-rational methods, i.e. limit the design
too much on the local structure without considering the global effect.
We tested this strategy on an extensively investigated enzyme in our
lab, α-L-rhamnosidase.
α-L-Rhamnosidase is a glycoside hydrolase, which can effectively
hydrolyze the rhamnose group at the end of most glycosides. It is widely
used in the debittering of citrus juices,32, 33improving the aroma components of beverages.34, 35 To
date, only 29 α-L-rhamnosidases have been biochemically characterized,
and six of them, namely Bs RhaB (PDB entry 2OKX), Bt 1001
(PDB entry 3CIH), Sa Rha78A (PDB entry 3W5M), Ko Rha (PDB
entry 4XHC), At Rha (PDB entry 6GSZ), and Dt Rha (PDB entry
6I60) have been illustrated in crystal structures in GH78
family.36-40 In previous studies, we cloned and
expressed α-L-rhamnosidase (Rha1) from Aspergillus nigerJMU-TS528,41 which belongs to the GH78 family in the
CAZy database. Simultaneously, we applied semi-conservative
site-directed mutagenesis on the catalytic domain to increase the enzyme
activity of Rha1.42 We also used two different methods
to improve thermostability of Rha1, PoPMuSiC algorithm and
lysine-arginine mutation on the surface of rRha1.43,
44 In this study, we applied the strategy mentioned above to improve
the catalysis efficiency and thermostability simultaneously.
Specifically, we computationally predicted the mutation in the catalytic
region of Rha1 with the potential to improve the catalysis efficiency
and thermostability by the aid of molecular docking and conservation
degree and energy variation analysis. The predicted mutants were then
expressed and validated in the enzymatic activity and thermostability.
This is the first semi-rational design to improve catalysis efficiency
and thermostability simultaneously of enzymes, which could be helpful to
effective design α-L-rhamnosidases and other important enzymes in the
industry.