QSPR study to predict some of quantum chemical properties of anticancer imidazo[4,5-b]pyridine derivatives using genetic algorithm multiple linear regression and molecular descriptors,International Journal of Quantum Chemistry

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QSPR study to predict some of quantum chemical properties of anticancer imidazo[4,5-b]pyridine derivatives using genetic algorithm multiple linear regression and molecular descriptors
International Journal of Quantum Chemistry ( IF 2.3 ) Pub Date : 2023-10-27 , DOI: 10.1002/qua.27259
Mahdi Jafari ₁ , Tahereh Momeni Isfahani ₁ , Fatemeh Shafiei ₁ , Masumeh Abdoli Senejani ₁

Affiliation

Pyridine and its derivatives have been applied clinically for the treatment of a wide range of diseases and in the synthesis of novel drugs. In the present work, imidazo[4,5-b]pyridine derivatives as anticancer drugs were exhibited to select the important descriptor for quantum chemical properties. Two of the fundamental thermodynamic properties are heat capacity (Cv) and entropy (S), which are important in the field of chemical kinetics and are key in the understanding and design of chemical processes involving chemical reactions. A Quantitative Structure–Property Relationship (QSPR) study was used to predict the quantum chemical properties like Cv and S of 105 imidazole derivatives using molecular descriptors and the genetic algorithm–multiple linear regression (GA–MLR). The best QSPR models were selected using criteria coefficients such as R², R²_adj, RMSE and Fisher ratio. Different internal and external validation metrics were adopted to evaluate the stability, fit and predictive power of the QSPR models. The validation results and statistical analysis show that the models possess good prediction power and robustness, and the total size (TS) and Sanderson electronegativity(RDF060e) and total information content index(TIC1) of imidazo[4,5-b]pyridine derivatives are increasingly related to the studied properties.

中文翻译：

使用遗传算法多元线性回归和分子描述符预测抗癌咪唑并[4,5-b]吡啶衍生物的一些量子化学性质的QSPR研究

吡啶及其衍生物在临床上已应用于多种疾病的治疗和新药的合成。在目前的工作中，展示了作为抗癌药物的咪唑并[4,5-b]吡啶衍生物，以选择量子化学性质的重要描述符。两个基本热力学性质是热容 (Cv) 和熵 (S)，它们在化学动力学领域很重要，并且是理解和设计涉及化学反应的化学过程的关键。定量结构-性质关系 (QSPR) 研究使用分子描述符和遗传算法-多元线性回归 (GA-MLR) 来预测 105 种咪唑衍生物的 Cv 和 S 等量子化学性质。使用R ²、R ²_adj、RMSE 和 Fisher 比率等标准系数选择最佳 QSPR 模型。采用不同的内部和外部验证指标来评估 QSPR 模型的稳定性、拟合度和预测能力。验证结果和统计分析表明，该模型具有良好的预测能力和鲁棒性，咪唑并[4,5-b]吡啶衍生物的总尺寸（TS）、桑德森电负性（RDF060e）和总信息含量指数（TIC1）为与所研究的特性越来越相关。

更新日期：2023-10-27

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