卟啉和金属卟啉产生单线态氧的重新研究：定量结构

卟啉和金属卟啉在光催化，光动力疗法（PDT），消毒，持久性污染物的降解和其他应用中用作光敏剂。它们的作用机理涉及系统间交叉到三重激发态，然后形成单重态氧（1 O 2），这是一种高反应性物质，可介导各种氧化过程。近年来，基于卟啉化合物的高级敏化剂的设计引起了极大的关注。然而，仍然难以预测给定结构的单线态氧产生效率。我们的目标是开发一种定量结构-性质关系（QSPR）模型，用于快速虚拟筛选和预测Pophyrin和Metalloporphyrin的单重态氧量子产率。我们对包含32种化合物的数据集进行了QSPR分析，其中包括各种卟啉及其类似物（二氢卟酚和细菌绿素）。使用密度泛函理论（DFT），即B3LYP和M062X泛函来计算量子化学描述符。三种不同的机器学习方法用于开发QSPR模型：随机森林回归（RFR），支持向量回归（SVR）和多元线性回归（MLR）。使用RFR方法获得的最佳QSPR模型《结构-单重态氧生成量子产率》证明了训练集的高确定系数（R2 = 0.949）和测试集的最高预测能力（pred_R 2 = 0.875）。这证明了开发的QSPR方法是可行的，可以直接用于研究游离碱卟啉及其金属配合物的单线态氧的生成。我们认为，本研究中开发的QSPR方法可用于寻找具有增强的单线态氧生成能力的新型Poprhyrin光敏剂。

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Singlet oxygen generation by porphyrins and metalloporphyrins revisited: A quantitative structure-property relationship (QSPR) study

Porphyrins and metalloporphyrins are used as photosensitizers in photocatalysis, photodynamic therapy (PDT), disinfection, degradation of persistent pollutants and other applications. Their mechanism of action involves intersystem crossing to triplet excited state followed by formation of singlet oxygen (1O2), which is a highly reactive species and mediates various oxidative processes. The design of advanced sensitizers based on porphyrin compounds have attracted significant attention in recent years. However, it is still difficult to predict the efficiency of singlet oxygen generation for a given structure. Our goal was to develop a quantitative structure-property relationship (QSPR) model for the fast virtual screening and prediction of singlet oxygen quantum yields for pophyrins and metalloporphyrins. We performed QSPR analysis of a dataset containing 32 compounds, including various porphyrins and their analogues (chlorins and bacteriochlorins). Quantum-chemical descriptors were calculated using Density Functional Theory (DFT), namely B3LYP and M062X functionals. Three different machine learning methods were used to develop QSPR models: random forest regression (RFR), support vector regression (SVR), and multiple linear regression (MLR). The optimal QSPR model «structure – singlet oxygen generation quantum yield» obtained using RFR method demonstrated high determination coefficient for the training set (R2 = 0.949) and the highest predicting ability for the test set (pred_R2 = 0.875). This proves that the developed QSPR method is realiable and can be directly applied in the studies of singlet oxygen generation both for free base porphyrins and their metal complexes. We believe that QSPR approach developed in this study can be useful for the search of new poprhyrin photosensitizers with enhanced singlet oxygen generation ability.