Quantitative Structure-Activity Relationships of 1.2.3 Triazole Derivatives as Aromatase Inhibition Activity

Q3 Biochemistry, Genetics and Molecular Biology Turkish Computational and Theoretical Chemistry Pub Date : 2020-06-15 DOI:10.33435/tcandtc.545369
M. Ouassaf, S. Belaidi, Imane BenBrahim, H. Belaidi, Samir CHTITA
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引用次数: 3

Abstract

Aromatase is an estrogen biosynthesis enzyme belonging to the cytochrome P450 family that catalyzes the rate-limiting step of converting androgens to estrogens. As it is pertinent toward tumor cell growth promotion aromatase is a lucrative therapeutic target for breast cancer. In the pursuit of robust aromatase inhibitors, a set of thirty 1-substituted mono- and bis-benzonitrile or phenyl analogs of 1.2.3-triazole letrozole were employed in quantitative structure activity relationship (QSAR) study using multiple linear regression (MLR).The results demonstrated good predictive ability for the MLR model. After dividing the dataset into training and test set. The models were statistically robust internally (R2 = 0.982) and the model predictability was tested by several parameters, including the external criteria (R2pred = 0.851. CCC= 0.946). Insights gained from the present study are anticipated to provide pertinent information contributing to the origins of aromatase inhibitory activity and therefore aid in our on-going quest for aromatase inhibitors with robust properties.
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1.2.3三唑类衍生物芳香酶抑制活性的定量构效关系
芳香化酶是一种雌激素生物合成酶,属于细胞色素P450家族,催化雄激素转化为雌激素的限速步骤。芳香化酶与促进肿瘤细胞生长有关,是治疗乳腺癌的有利靶点。为了寻找具有鲁棒性的芳香酶抑制剂,采用多元线性回归(MLR)方法对31个1-取代的1-和2 -苯腈或苯基类似物进行了定量构效关系(QSAR)研究。结果表明,该模型具有良好的预测能力。将数据集分为训练集和测试集。模型内部具有统计稳健性(R2 = 0.982),模型的可预测性通过包括外部标准在内的多个参数进行检验(R2 = 0.851)。CCC = 0.946)。从本研究中获得的见解预计将为芳香化酶抑制活性的起源提供相关信息,因此有助于我们继续寻求具有强大性能的芳香化酶抑制剂。
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来源期刊
Turkish Computational and Theoretical Chemistry
Turkish Computational and Theoretical Chemistry Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
CiteScore
2.40
自引率
0.00%
发文量
4
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