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靶向核DNA的新型1,8-萘二甲酰亚胺衍生物的定量构效关系研究

QSAR Study of Novel 1, 8-Naphthimide Derivatives Targeting Nuclear DNA.

作者信息

Lian Zheng, Tai Yunheng, Xia Huanling, Zhai Honglin

机构信息

Department of Orthopedics, Weifang Medical University, Weifang, China.

Department of Orthopedics, The 960th Hospital of the Chinese People's Liberation Army, Beijing, China.

出版信息

Anticancer Agents Med Chem. 2023;23(6):726-733. doi: 10.2174/1871520622666220822010953.

Abstract

BACKGROUND

1, 8-naphthimide is a novel tumor inhibitor targeting nuclear DNA, which can be used to design and develop anti-osteosarcoma drugs.

OBJECTIVE

Quantitative structure-activity relationship (QSAR) model was established to predict the physical properties of compounds.

METHODS

In this study, gene expression programming (GEP) was used to build a nonlinear quantitative structureactivity relationship (QSAR) model with descriptors and to predict the activity of a serials novel DNA-targeted chemotherapeutic agents. These descriptors were calculated in CODESSA software and selected from the descriptor pool based on heuristics. Three descriptors were selected to establish a multiple linear regression model. The best nonlinear QSAR model with a correlation coefficient of 0.89 and 0.82 and mean error of 0.02 and 0.06 for the training and test sets were obtained.

RESULTS

The results showed that the model established by GEP had better stability and predictive ability. The small molecular docking experiment of 32 compounds was carried out in SYBYL software, and it was found that compound 7A had reliable molecular docking ability.

CONCLUSION

The established model reveals the factors affecting the activity of DNA inhibitors and provides direction and guidance for the further design of highly effective DNA-targeting drugs for osteosarcoma.

摘要

背景

1,8-萘二甲酰亚胺是一种新型的靶向核DNA的肿瘤抑制剂,可用于设计和开发抗骨肉瘤药物。

目的

建立定量构效关系(QSAR)模型以预测化合物的物理性质。

方法

在本研究中,基因表达式编程(GEP)被用于构建一个带有描述符的非线性定量构效关系(QSAR)模型,并预测一系列新型DNA靶向化疗药物的活性。这些描述符在CODESSA软件中计算,并基于启发式方法从描述符库中选择。选择三个描述符建立多元线性回归模型。获得了最佳非线性QSAR模型,训练集和测试集的相关系数分别为0.89和0.82,平均误差分别为0.02和0.06。

结果

结果表明,由GEP建立的模型具有更好的稳定性和预测能力。在SYBYL软件中对32种化合物进行了小分子对接实验,发现化合物7A具有可靠的分子对接能力。

结论

所建立的模型揭示了影响DNA抑制剂活性的因素,为进一步设计高效的骨肉瘤DNA靶向药物提供了方向和指导。

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