基于机器学习方法虚拟筛选Syk的抑制剂

被引：3

作者：

王洁雪

李瑶

杨敏

王琪慧

邓国伟

杨帆

李秉轲

机构：

[1] 成都师范学院化学与生命科学学院功能分子研究所

来源：

化学研究与应用 | 2019年 / 31卷 / 07期

关键词：

Syk; 虚拟筛选; 分子描述符; 机器学习方法; C4.5决策树; 随机森林;

D O I：

暂无

中图分类号：

TQ460 [一般性问题];

学科分类号：

1007 ;

摘要：

脾酪氨酸激酶(Syk)是一种细胞内的酪氨酸激酶细胞质受体,在类风湿性关节炎(RA)的发病过程中起着至关重要的作用。筛选Syk抑制剂对RA的治疗有着重要的意义。采用C4.5决策树与随机森林(RF)两种机器学习方法分别对Syk抑制剂与非抑制剂建立模型,经过对比,RF具有更好的预测精度。采用RF模型对Syk抑制剂进行虚拟筛选,从ZINC数据库筛选得到潜在的Syk抑制剂分子。研究结果表明,机器学习方法对于虚拟筛选和发现潜在的Syk抑制剂十分有效。

引用

页码：1313 / 1320

页数：8

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