定量构效关系方法学习探索：以钴卟啉活化氧气为例

doi:10.12461/PKU.DXHX202410107

摘要/Abstract

摘要： 金属卟啉配合物由于在氧气还原反应中具有优异的催化活性以及良好的反应选择性，受到了人们的广泛关注。但是，常规的实验合成表征或高精度量化计算较难大批量研究其取代基效应。为此，本文基于定量构效关系(QSAR)方法，利用Chem3D、Gaussian等软件计算了不同取代基钴卟啉配合物的拓扑参数、量化参数，并结合现有物化参数用SPSS进行相关性分析，可以快速筛选出影响钴卟啉活化氧气分子的特征描述符。并且，本文进一步采用逐步回归分析得到了多元回归方程，其具有较好的拟合优度以及泛化能力。本文详细阐述了QSAR中代表性描述符的计算与采集，并展示了常用的相关性分析与回归分析过程，旨在帮助学生自学Chem3D、Gaussian、SPSS等软件，且可以有效提高学生在分子建模、计算化学、统计学软件等方面的实际操作能力以及数据分析和处理能力。

关键词: 钴卟啉, 氧气结合能, 定量构效关系, 相关性分析, 逐步回归分析

Abstract: Metalloporphyrin complexes have attracted much attention because of their excellent catalytic performance and good selectivity in oxygen reduction reactions (ORR). However, massive investigations on substituent effects with conventional experimental synthetic approaches as well as high accuracy quantum chemistry computations would be difficult. Herein, quantitative structure-activity relationship (QSAR) methods were utilized. Based on collected physicochemical parameters, calculated topological parameters and quantum-chemical parameters of cobalt porphyrins with various substituents by Chem3D and Gaussian, the correlation analysis was performed by SPSS program, which enables quick screening of feature descriptors on dioxygen activation mediated by cobalt porphyrins. Subsequently, a stepwise regression analysis was performed, which outputs a multi-variant regression equation with acceptable goodness-of-fit and generalization ability. Our work systematically demonstrated the calculation and collection of representative descriptors in QSAR, and the detailed process of correlation analysis and regression analysis were shown. This work can assist in self-learning the relevant functions of Chem3D, Gaussian, and SPSS software, enhancing practical abilities in molecular modeling, computational chemistry and statistical software, as well as data analysis and processing skills.

Key words: Cobalt porphyrin, Oxygen binding energy, QSAR, Correlation analysis, Stepwise regression analysis

张学鹏, 龙宇驰, 潘禹澍, 王继顶, 白宝钰, 丁瑞. 定量构效关系方法学习探索：以钴卟啉活化氧气为例[J]. 大学化学, 2025, 40(8): 345-359.

Xue-Peng Zhang, Yuchi Long, Yushu Pan, Jiding Wang, Baoyu Bai, Rui Ding. Exploring Quantitative Structure-Activity Relationship Methods: A Case Study on Oxygen Activation by Cobalt Porphyrins[J]. University Chemistry, 2025, 40(8): 345-359.

链接本文: https://www.dxhx.pku.edu.cn/CN/10.12461/PKU.DXHX202410107

https://www.dxhx.pku.edu.cn/CN/Y2025/V40/I8/345

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