数量结构-活动关系
分子描述符
量子化学
特征(语言学)
生物系统
人工智能
计算机科学
生化工程
机器学习
化学
数据挖掘
分子
工程类
有机化学
生物
哲学
语言学
作者
Liangliang Wang,Junjie Ding,Li Pan,Dongsheng Cao,Hui Jiang,Xiaoqin Ding
标识
DOI:10.1016/j.chemolab.2021.104384
摘要
Abstract With the accumulation of chemical and biological experimental data and the continuous development of mathematical statistical algorithms, quantitative structure–activity relationship (QSAR) models play an important role in modern chemistry research. Molecular descriptors, as the core feature parameters of QSAR models, are among the key factors in determining the model performance. With the rapid development of high-performance computers and more efficient quantum chemical (QC) methods, QC descriptors with accurate characterization of electronic structures and clear mathematical meaning are essential for the development of QSAR models. This paper systematically summarizes the advantages and basic principles of QC descriptors. In addition, it introduces the applications of QSAR models based on QC descriptors in organic, medicinal, analytical, and environmental chemistry in recent years. Finally, it discusses the existing limitations of QC descriptors and their possible future development.
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