The design of bidirectional selective hydrolases for lignin, cellulose and hemicellulose through in silico methods

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Abstract

The production of methane from straw lignocellulose is limited by its structure. It is necessary to break the complex structure and prevent the loss of cellulose/hemicellulose by lignin-removing pretreatment. This paper designed bidirectional selective hydrolases based on laccase of Pleurotus ostreatus (Q6RYA4) and Bacillus subtilis (E7EDN4), established Scenario 1 (6 % H₂SO₄ and E7EDN4–2) and Scenario 2 (5 % NaOH and E7EDN4–12), significantly enhancing lignin hydrolysis while minimizing cellulose/hemicellulose hydrolysis using homology modeling, molecular docking and molecular dynamics. The suitable environmental conditions for the scenarios were determined through L₉ Taguchi orthogonal. Resveratrol was found to enhance enzyme activity in an acidic environment, while rhamnolipid in an alkaline environment. The enhanced mechanism of lignin hydrolysis was elucidated through the hotspots amino acids, root mean square fluctuation, and enzyme adsorption-desorption process. Subsequently, the deep learning algorithm was employed to conduct the enzyme turnover numbers of new hydrolases, quantifying lignin hydrolysis rate and theoretical methane yield. Compared with E7EDN4, the lignin hydrolysis rate in Scenario 1 and 2 increased by 208.16 % and 272.49 %, while the theoretical methane yields were increased by 98.23 % and 97.96 % under suitable environmental condition of appropriate concentration of exogenous substances (rhamnolipid or resveratrol). This study constituted an advanced technology for the high-efficiency utilization of cellulose/hemicellulose, which offered novel insights and approaches for the biological enhancement of the pretreatment of lignocellulose.