吡唑氮杂环[3.2.1]辛烷磺酰胺类n -酰基乙醇胺水解酸酰胺酶抑制剂的QSAR研究

Huan Wang, Shengnan Ren, Liyang Sun, H. Si, Zhuang Yu
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引用次数: 0

摘要

炎症是人类常见的顽固性疾病。目前的消炎药有很多副作用,会对身体造成不可逆的损害。我们预测了n -酰基乙醇胺水解酸酰胺酶(NAAA)抑制剂的活性,以寻找更有效的化合物。通过基因表达编程建立定量构效关系(QSAR)模型,预测天然化合物的IC50值。NAAA抑制剂作为一种半胱氨酸酶,在疼痛的治疗、抗炎作用以及其他疾病的应用中发挥着重要作用。在CODESSA程序中,采用启发式方法对36个NAAA抑制剂进行优化,建立线性模型。27个化合物和9个化合物在训练和测试集上。在此基础上,我们选择了三个描述符,并利用它们建立了基因表达式编程中的非线性模型。在基因表达编程方法中找到了最佳模型,训练集R2相关系数的平方和均方误差分别为0.79和0.14,测试集为0.78和0.20。利用该方法可以预测分子的活性,并找到了最佳的方法。因此,该模型对开发NAAA抑制剂具有较强的预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
QSAR Studies on a Series of Pyrazole Azabicyclo [3.2.1] Octane Sulfonamides N-Acylethanolamine-Hydrolyzing Acid Amidase Inhibitors
Inflammation is a common and intractable disease for humans. Current anti-inflammatory drugs have a lot of side effects, which cause irreversible damage to the body. We predict the activity of the N-acylethanolamine-hydrolyzing acid amidase (NAAA) inhibitor to find more effective compounds. we established a quantitative structure-activity relationship (QSAR) model by gene expression programming to predict the IC50 values of natural compounds. The NAAA inhibitor, as a cysteine enzyme, plays an important role in the therapy of pain, anti-inflammatory effects and application of other diseases. A total of 36 NAAA inhibitors were optimized by the heuristic method in the CODESSA program to build a linear model. The 27 compounds and 9 compounds were in train and test sets. On this basis, we selected three descriptors and used them to build nonlinear models in gene expression programming. The best model in the gene expression programming method was found, the square of correlation coefficients of R2 and mean square error for the training set were 0.79 and 0.14, testing set was 0.78 and 0.20, respectively. From this method, the activity of molecules could be predicted, and the best method was found. Therefore, this model has a stronger predictive ability to develop NAAA inhibitors.
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