Computer-Aided Enzyme Stability Analysis

Enzymes are biodegradable and reusable catalysts. In addition to their remarkable reaction rate, they can also work in the environment-friendly pH value and temperature range, and show the control of stereochemistry and regional selectivity, making them very suitable for many applications. But the instability often limits its application. Existing protein engineering strategies aim to construct enzymes with new or improved activity, specificity and stability, greatly benefiting from the in silico method.

Background of Enzyme Stability Analysis

Enzyme as a biocatalyst has aroused great interest, which has led to extensive research on enzyme engineering and related methodology. In particular, their excellent chemical selectivity, regioselectivity and enantioselectivity, as well as their ability to work under mild reaction conditions, are the main factors that enable enzymes to compete with catalysts even on an industrial scale. However, due to aggregation, loss of biological function, exposure to extreme conditions or small changes in temperature or pH value, it will lead to the mutation of enzyme conformation and subsequent loss of biological activity, which greatly limits its application. Therefore, it is necessary to evaluate the stability of the enzyme for improving the stability of the modified enzyme.

Fig.1 Directed evolution campaign. (Rigoldi, 2018)

Computer-Aided Enzyme Stability Analysis

Enzymes are protein molecules composed of folded amino acid polypeptide chains, which are essential for the realization of a series of biological functions. Computer-aided protein design is becoming a powerful tool to customize enzymes for specific biotechnological applications. In terms of structure- and physics-based (thermo) stability, the existing in silico methods can be used to improve our understanding and modification of enzyme stability. For example, the introduction of some mutations in the design of enzyme molecules can further stabilize proteins and increase the population of folded equilibrium. In directed evolution, it is most likely to identify mutant enzymes with improved thermal stability by introducing random mutations into coding genes and screening large result pools (usually composed of more than 105 variants) to obtain specific functions.

Recently, several different in silico methods have been developed to determine the effect of mutations on enzyme stability. Rational designs to improve enzyme stability are usually based on one or more methods, the most common strategies involve:

	The introduction of surface hydrogen bonds		The introduction of salt bridges
	The stabilization of the hydrophobic core		The introduction of disulfide bridges
	The stabilization of mobile loops using prolines		Phylogenetic analysis

The computer-aided method has been successfully applied to manganese peroxidase (MnP) engineering. First, we compare the diffusion of ligands in active and inactive enzymes by calculating the interaction energy (red and green dots, respectively) and the distance between ligands and receptors. The information on the active site environment is extracted from the active enzyme, and two specific surface mutations (blue dots) are introduced to help us redesign the active enzyme. In the second step, the activation was confirmed in silico by electron coupling calculation. The final site-specific mutation experiment confirmed the success of the new mutant, which has both stability and activity.

Fig.2 General scheme for rational MnP6 engineering. (Acebes, 2016)

With rich experience in protein/enzyme engineering, Creative Biolabs will improve the stability of enzyme through rational computer-aided design, and help each customer to customize the most appropriate method. Please contact us for more information.

References

Rigoldi, F.; et al. Engineering of thermostable enzymes for industrial applications. APL bioengineering. 2018, 2(1): 011501.
Acebes, S.; et al. Rational enzyme engineering through biophysical and biochemical modeling. ACS Catalysis. 2016, 6(3): 1624-1629.

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