Answers are grounded in this paper and cite their sources.
Thermostability is critical yet challenging to engineer in industrial enzymes. Here, we present an integrated workflow for enhancing the thermostability of GH11 xylanases through systematic Ser/Thr optimization. Gibbs free energy calculations on XynCDBFV identified 169 stabilizing single-site mutations involving Ser/Thr residues, which were combinatorially integrated via rational design and a machine-learning model (ESM2-RF). Both strategies generated multisite variants with superior thermal tolerance. Top performers included RD-4M3 (ΔTm = 7.10 °C) and ER-4M6 (+56.19% residual activity). Molecular dynamics simulations revealed that R148-D57 competition in the WT at high temperature disrupts the R148-E109 interaction, and its elimination in Ser/Thr variants induces 150-loop rigidification, thereby enhancing thermostability. This finding was validated by transplanting two Ser/Thr substituted combinations to a second GH11 xylanase, PjxA. This work establishes a systematic Ser/Thr optimization strategy for engineering thermostable xylanases and underscores the efficiency of multisite combinatorial design.
No takes yet. Share an insight, caveat, or question.
Zhe et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: