Exploring sequence- and structure-based fitness landscapes to enhance thermal resistance and activity of endoglucanase II with minimal experimental effort

Abstract

Enhancing the performance of cellulases at high temperatures is crucial for efficient biomass hydrolysis—a fundamental process in biorefineries. Traditional protein engineering methods, while effective, are time-consuming and labour-intensive, limiting rapid advancements. To streamline the engineering process, we tested two distinct in silico methods for predicting thermally resistant and highly active variants of Penicillium verruculosum endoglucanase II. Specifically, we used FoldX to pinpoint structure-stabilizing substitutions (ΔΔG < 0) and applied the sequence-based method EVmutation to identify evolutionarily favorable substitutions (ΔE > 0). Experimental validation of the top 20 ranked single-substituted variants from both methods showed that EVmutation outperformed FoldX, identifying variants with enhanced enzyme activity after one-hour incubation at 75 °C (up to 3.6-fold increase), increased melting temperature (ΔT_m of 2.8 °C), and longer half-lives at 75 °C (up to 104 minutes vs. 40 minutes for the wild type). Building upon these results, EVmutation was used to predict variants with two amino acid substitutions. These double-substituted endoglucanase variants showed further improvements—up to a 4.4-fold increase in activity, ΔT_m gains of 3.7 °C, and half-life extensions up to 82 minutes. This study highlights EVmutation's potential for accelerating protein engineering campaigns and enhancing enzyme properties while reducing experimental efforts, thereby contributing to more efficient and sustainable bioprocesses.