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基于系统化学遗传学的药物发现:将靶向多个/可靠疾病相关基因的药物作为候选药物进行优先级排序。

Systems Chemical Genetics-Based Drug Discovery: Prioritizing Agents Targeting Multiple/Reliable Disease-Associated Genes as Drug Candidates.

作者信息

Quan Yuan, Luo Zhi-Hui, Yang Qing-Yong, Li Jiang, Zhu Qiang, Liu Ye-Mao, Lv Bo-Min, Cui Ze-Jia, Qin Xuan, Xu Yan-Hua, Zhu Li-Da, Zhang Hong-Yu

机构信息

Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China.

College of Life Sciences and Technology, Huazhong Agricultural University, Wuhan, China.

出版信息

Front Genet. 2019 May 29;10:474. doi: 10.3389/fgene.2019.00474. eCollection 2019.

Abstract

Genetic disease genes are considered a promising source of drug targets. Most diseases are caused by more than one pathogenic factor; thus, it is reasonable to consider that chemical agents targeting multiple disease genes are more likely to have desired activities. This is supported by a comprehensive analysis on the relationships between agent activity/druggability and target genetic characteristics. The therapeutic potential of agents increases steadily with increasing number of targeted disease genes, and can be further enhanced by strengthened genetic links between targets and diseases. By using the multi-label classification models for genetics-based drug activity prediction, we provide universal tools for prioritizing drug candidates. All of the documented data and the machine-learning prediction service are available at SCG-Drug (http://zhanglab.hzau.edu.cn/scgdrug).

摘要

遗传疾病基因被认为是药物靶点的一个有前景的来源。大多数疾病是由多种致病因素引起的;因此,有理由认为靶向多个疾病基因的化学药剂更有可能具有预期的活性。这得到了对药剂活性/成药可能性与靶点遗传特征之间关系的全面分析的支持。药剂的治疗潜力随着靶向疾病基因数量的增加而稳步提高,并且可以通过加强靶点与疾病之间的遗传联系而进一步增强。通过使用基于遗传学的药物活性预测的多标签分类模型,我们提供了用于对候选药物进行优先级排序的通用工具。所有记录的数据和机器学习预测服务都可在SCG-Drug(http://zhanglab.hzau.edu.cn/scgdrug)上获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81a6/6549477/051d8ca77855/fgene-10-00474-g0001.jpg

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