基于结构信息的MHET降解酶挖掘及温和温度下的酶级联塑料降解

Structure motif guided mining of MHET hydrolase and development of a two-enzyme cascade for plastics depolymerization at mild temperature

聚对苯二甲酸乙二醇酯(polyethylene terephthalate,PET)的不规范使用和处置造成了严重的生态污染。酶法降解是一种环境友好的解决PET污染的方法。对苯二甲酸单(2-羟乙基)酯[mono(2-hydroxyethyl)terephthalate,MHET]是PET降解过程中的具有竞争性抑制效果的中间产物,可由MHET降解酶催化水解。本研究采用生物信息学方法,结合序列和结构信息,发现了一种MHET水解酶,BurkMHETase。酶学性质研究表明该酶的最适pH和最适温度分别为7.5和40℃,在pH 7.5−10.0、30−45℃条件下相对稳定;以MHET为底物测定动力学参数kcat为(24.2±0.5)s^(-1),Km为(1.8±0.2)μmol/L,具有与目前最高效的IsMHETase相似的kcat值和更高的底物亲和力。BurkMHETase与PET降解酶IsPETase联用能够改善PET薄膜的降解效果。结构分析和突变实验表明,BurkMHETase可能已经进化出特定的结构特征来催化MHET的水解。对于MHET降解酶,在495位为芳香族氨基酸以及活性部位或远端氨基酸间的协同相互作用对于MHET水解活性似乎是必需的。因此,BurkMHETase有潜力应用于PET双酶降解系统,而所使用的生物信息学方法可以用来高效挖掘新的MHET降解酶。

The utilization of polyethylene terephthalate(PET)has caused significant and prolonged ecological repercussions.Enzymatic degradation is an environmentally friendly approach to addressing PET contamination.Hydrolysis of mono(2-hydroxyethyl)terephthalate(MHET),a competitively inhibited intermediate in PET degradation,is catalyzed by MHET degrading enzymes.Herein,we employed bioinformatic methods that combined with sequence and structural information to discover an MHET hydrolase,BurkMHETase.Enzymatic characterization showed that the enzyme was relatively stable at pH 7.5−10.0 and 30−45°C.The kinetic parameters kcat and Km on MHET were(24.2±0.5)/s and(1.8±0.2)μmol/L,respectively,which were similar to that of the well-known IsMHETase with higher substrate affinity.BurkMHETase coupled with PET degradation enzymes improved the degradation of PET films.Structural analysis and mutation experiments indicated that BurkMHETase may have evolved specific structural features to hydrolyze MHET.For MHET degrading enzymes,aromatic amino acids at position 495 and the synergistic interactions between active sites or distal amino acids appear to be required for MHET hydrolytic activity.Therefore,BurkMHETase may have substantial potential in a dual-enzyme PET degradation system while the bioinformatic methods can be used to broaden the scope of applicable MHETase enzymes.