摘要
在生物医学高通量数据迅速积累的背景下,突破传统药物研发技术体系,从生物医药信息的丰富数据特征出发,建立抗真菌药物的快速发现方法逐渐成为可能。从高通量组学数据出发,计算发现药物之间的相似药效关系,并应用于抗真菌新药发现。基于CMAP和LINCS数据平台,获取化合物作用下的细胞转录组数据作为生物细胞对药物效应的特征表征,采用GSEA和WTCS算法度量其特征表征之间的相似程度,通过对待筛选药物和已知抗真菌药物的相似度综合排序实现对潜在抗真菌药物的预测筛选。通过大规模计算发现,普尼拉明、伊利替康等药物有望用于抗真菌用途,部分预测结果已得到相关实验研究的支持。本研究有效利用细胞反应表征的高通量组学数据,将生物大数据应用于快速药物理性设计,为抗真菌药物重定位的理性设计提供重要的计算方法,启发并加速现有抗真菌药物发现过程。
With the rapid accumulation of high-throughput data in biomedicine,it comes to be possible to break through the traditional drug design system and establish a rapid discovery method for antifungal drugs starting from rich data characteristics of biomedical information.High-throughput omics data are to calculate similar pharmacodynamic relationships between discovered drugs,which is applied into antifungal drugs discovery.Based on the CMAP and LINCS data platforms,we obtain the cell transcriptome data under the action of the compound as characteristic characterizations of cell’s drug effects.Then we measure the similarity between the characterizations with GSEA method and WTCS algorithm.After that,we screen potential antifungal drugs by the comprehensive rank of the similarity of the drugs to be screened and known antifungal drugs.Based on the large-scale calculations of existing antifungal drugs,we found that drugs such as prenylamine and iri-notecan are expected to become antifungal drug candidates,and some of them are supported by related studies,which need to be verified by further experiments.This paper applies biological big data to quick drug rational design and provides important calculation methods for rational design of antifungal drug repositioning,and inspires and accelerates the development of existing antifungal drugs.
作者
杨浩艺
陈微
姚泽欢
谭郁松
李非
YANG Hao-yi;CHEN Wei;YAO Ze-huan;TAN Yu-song;LI Fei(College of Computer Science and Technology,National University of Defense Technology,Changsha 410073;Computer Network Information Center,Chinese Academy of Sciences,Beijing 100190,China)
出处
《计算机工程与科学》
CSCD
北大核心
2023年第2期246-251,共6页
Computer Engineering & Science
基金
国家重点研发计划(2018YFB0204301)
国家自然科学基金(81973244)。
关键词
药物重定位
生物大数据
抗真菌药物
drug repositioning
biomedical big data
antifungal drug
