A Structural Landscape Depiction of Dynamic Stability Centers of Local Structure in Protein Thermostability Engineering

TL;DR

This paper introduces a new method to improve protein thermostability by identifying and reinforcing key structural regions.

Contribution

The novel strategy identifies and reinforces dynamic stability centers of local structure (DSCLSs) to enhance protein thermostability.

Findings

Mutants engineered using DSCLSs showed Tm increases of ~15 °C in several proteins.

The optimal EDO L1 mutant (T70Y) had 1.6-fold higher catalytic efficiency at 60 °C.

The xp-EctC mutant (I2R) exhibited a 2.1-fold increase in catalytic efficiency over the wild type.

Abstract

Engineering protein thermostability is a key aspect of rational protein design, aiming to broaden the applicability of enzymes and enhance their industrial utility. In this study, we introduce a strategy for identifying and reinforcing dynamic stability centers of local structure (DSCLSs) to improve protein thermostability. A DSCLS comprises key structural residues and their interactions, representing the structural basis of protein stability. Molecular dynamics, cross-correlation amino acid networks, and other analytical techniques were integrated into the method. This approach was initially inspired by thermostability engineering of exodiol dioxygenases (EDOs). The method was validated through mutational analyses of mesophilic EDO MT-2, CpKR (ketoreductase from Candida parapsilosis), and CaPETase (polyethylene terephthalate hydrolase from Cryptosporangium aurantiacum). Subsequently, we applied the approach to engineer thermostability in xp-EctC (ectoine synthase) from Rhodococcus and mesophilic EDO L1 from Bacillus, with the best-performing mutants showing Tm increases of ~15 °C. Notably, the catalytic efficiency of the optimal mesophilic EDO L1 mutant (T70Y) was 1.6-fold higher than that of the wild type at 60 °C, while the xp-EctC mutant (I2R) exhibited a 2.1-fold increase over the wild type. By characterizing and enhancing DSCLSs, this work presents a practical and generalizable strategy for thermostability engineering that also reduces mutational screening efforts, offering important potential for industrial applications.

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