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There is a high level of conservation of tryptophans within the active site architecture of the cellulase family, whereas the function of the four tryptophans in the catalytic domain of Cel7A is unclear. By mutating four tryptophan residues in the catalytic domain of Cel7A from Penicillium piceum (PpCel7A), the binding affinity between PpCel7A and p‐nitrophenol‐d‐cellobioside (pNPC) was reduced as determined by Michaelis–Menten constants, molecular dynamics simulations, and fluorescence spectroscopy. Furthermore, PpCel7A variants showed a reduced level of cellobiohydrolase (CBH) activity against cellulose analogs or natural cellulose. Therefore, it could be concluded four tryptophan residues in Cel7A played a critical role in substrate binding. Mutagenesis results indicated that the W390 stacking interactions at the −2 site played an essential role in facilitating substrate distortion to the −1 site. As soon as the function was altered, the mutation would inevitably affect the catalytic activity against the natural substrate. Interestingly, no clear relationship was found between the CBH activity of PpCel7A variants against pNPC and Avicel. p‐Nitrophenol contains many electrophilic groups that may result in overestimation of the binding constant between tryptophan residues and pNPC in comparison with the natural substrate. Consequently, screening improved cellulase using cellulose analogs would divert attention from the target direction for lignocellulose biorefinery. Clarifying mechanism of catalytic diversity on the natural cellulose or cellulose analogs may give better insight into cellulase screening and selecting strategy. [ABSTRACT FROM AUTHOR]

Trichoderma reesei endoglucanases (EGs) have limited industrial applications due to its low thermostability and activity. Here, we aimed to improve the thermostability of EGs from T. reesei without reducing its activity counteracting the activity–stability trade‐off. A cross‐strategy combination of machine learning and B‐factor analysis was used to predict beneficial amino acid substitution in EG loop optimization. Experimental validation showed single‐site mutated EG concomitantly improved enzymatic activity and thermal properties by 17.21%–18.06% and 49.85%–62.90%, respectively, compared with wild‐type EGs. Furthermore, the mechanism explained mutant variants had lower root mean square deviation values and a more stable overall structure than the wild type. According to this study, EGs loop optimization is crucial for balancing the activity–stability trade‐off, which may provide new insights into how loop region function interacts with enzymatic characteristics. Moreover, the cross‐strategy between machine learning and B‐factor analysis improved superior enzyme activity–stability performance, which integrated structure‐dependent and sequence‐dependent information. [ABSTRACT FROM AUTHOR]