The Mg-dechelatase enzyme encoded by the Stay-Green (SGR) gene catalyzes Mg²⁺ dechelation from chlorophyll a. This reaction is the first committed step of chlorophyll degradation pathway in plants and is thus indispensable for the process of leaf senescence. There is no structural information available for this or its related enzymes. This study aims to provide insights into the structure and reaction mechanism of the enzyme through biochemical and computational analysis of an SGR homolog from the Chloroflexi Anaerolineae (AbSGR-h). Recombinant AbSGR-h with its intact sequence and those with mutations were overexpressed in Escherichia coli and their Mg-dechelatase activity were compared. Two aspartates – D34 and D62 were found to be essential for catalysis, while R26, Y28, T29 and D114 were responsible for structural maintenance. Gel filtration analysis of the recombinant AbSGR-h indicates that it forms a homo-oligomer. The three-dimensional structure of AbSGR-h was predicted by a deep learning-based method, which was evaluated by protein structure quality evaluation programs while structural stability of wild-type and mutant forms were investigated through molecular dynamics simulations. Furthermore, in concordance with the results of enzyme assay, molecular docking concluded the significance of D34 in ligand interaction. By combining biochemical analysis and computational prediction, this study unveils the detailed structural characteristics of the enzyme, including the probable pocket of interaction and the residues of structural and functional importance. It also serves as a basis for further studies on Mg-dechelatase such as elucidation of its reaction mechanism or inhibitor screening.

由Stay-Green ( SGR ) 基因编码的镁去螯合酶催化叶绿素a 的镁^{2+ 去}螯合。该反应是植物叶绿素降解途径的第一个关键步骤，因此对于叶片衰老过程是必不可少的。没有可用于此或其相关酶的结构信息。本研究旨在通过对来自 Chloroflexi Anaerolineae (AbSGR-h)的 SGR 同源物的生化和计算分析，深入了解该酶的结构和反应机制。具有完整序列和突变序列的重组 AbSGR-h 在大肠杆菌中过表达并比较了它们的镁去螯合酶活性。发现两种天冬氨酸——D34 和 D62 对催化至关重要，而 R26、Y28、T29 和 D114 负责结构维护。重组 AbSGR-h 的凝胶过滤分析表明它形成了同源寡聚体。AbSGR-h 的三维结构通过基于深度学习的方法进行预测，通过蛋白质结构质量评估程序进行评估，同时通过分子动力学模拟研究野生型和突变体的结构稳定性。此外，与酶分析的结果一致，分子对接得出了 D34 在配体相互作用中的重要性。通过结合生化分析和计算预测，这项研究揭示了酶的详细结构特征，包括可能的相互作用口袋以及具有结构和功能重要性的残基。它还可以作为进一步研究镁脱螯合酶的基础，例如阐明其反应机制或筛选抑制剂。