An engineered cellobiohydrolase I for sustainable degradation of lignocellulosic biomass

Abstract

This study provides computational‐assisted engineering of the cellobiohydrolase I (CBH‐I) from Penicillium verruculosum with simultaneous enhanced thermostability and tolerance in ionic liquids, deep eutectic solvent, and concentrated seawater without affecting its wild‐type activity. Engineered triple variant CBH‐I R1 (A65R‐G415R‐S181F) showed 2.48‐fold higher thermostability in terms of relative activity at 65°C after 1 h of incubation when compared with CBH‐I wild type. CBH‐I R1 exhibited 1.87‐fold, 1.36‐fold, and 1.57‐fold higher specific activities compared with CBH‐I wild type in [Bmim]Cl (50 g/L), [Ch]Cl (50 g/L), and two‐fold concentrated seawater, respectively. In the multicellulases mixture, CBH‐I R1 showed higher hydrolytic efficiency to hydrolyze aspen wood compared with CBH‐I wild type in the buffer, [Bmim]Cl (50 g/L), and two‐fold concentrated seawater, respectively. Structural analysis revealed a molecular basis for the higher stability of the CBH‐I structure in which A65R and G415R substitutions form salt bridges (D64 … R65, E411 … R415) and S181F forms π–π interaction (Y155 … F181), leading to stabilize surface‐exposed flexible α‐helixes and loop in the multidomain β‐jelly roll fold structure, respectively. In conclusion, the variant CBH‐I R1 could enable efficient lignocellulosic biomass degradation as a cost‐effective alternative for the sustainable production of biofuels and value‐added chemicals.

Evolving Robust and Interpretable Enzymes for the Bioethanol Industry

“…The 12 filtered beneficial substitutions were divided into two categories based on the CompassR rule: Subset 1: ΔΔ G fold ≤+0.36 kcal mol −1 , which could be predictably beneficially recombined (S12C, S12K, S12V, S12A, T77M, E85Y, G264H, G264R, D290G); Subset 2: 0.36<ΔΔ G fold ≤+7.52 kcal mol −1 , which showed unpredictable recombinants (S3T, S3P, F80Y). This general cutoff had been successfully applied to engineer the catalytic properties of several enzymes [10b, 11a, 15, 33] …”

“…Recently, several knowledge-acquiring strategies, such as KnowVolution, [11] Com-passR (Computer-assisted Recombination), [12] and 2GeReP, [13] were used to maximize the performance of evolved enzymes and minimize the experimental effort by balancing directed evolution and computational analysis. [14] Studies on numerous enzymes (e.g., Bacillus subtilis lipase A (BSLA), [10b] cellobiohydrolase I, [15] TEM-1 β-lactamase, [16] avGFP [17] and transketolase [18] ) showed that the relative folding free energy (ΔΔG fold ) is an essential factor in predicting the evolvability of proteins. Previously, the In Silico guided Recombination Process (InSiReP) adopted a computationally directed strategy applying ΔΔG fold to recombine the beneficial substitutions/recombinants based on the obtained experimental data.…”

Enhanced activity of hyperthermostable Pyrococcus horikoshii endoglucanase in superbase ionic liquids

“…These findings could assist in the planning of rational approaches to the design of new enzyme friendly ILs and to the engineering of new IL-tolerant enzymes. The success achieved to date in improving the tolerance of cellulases to ILs in some of the rational approaches is promising (Lee et al 2017 ; Pramanik et al 2021 ; Summers et al 2020 ). Important aspects to consider in planning are that enzymes differ in their response to various ILs and that different substrates may behave differently in IL solutions.…”

Oil Palm Empty Fruit Bunch Waste Pretreatment with Benzotriazolium-Based Ionic Liquids for Cellulose Conversion to Glucose: Experiments with Computational Bibliometric Analysis

“…The glucose analysis of hydrolysis samples was determined using a Somogyi-Nelson method (Pramanik et al, 2021). Measurement of glucose concentration was conducted by spectrophotometer.…”