[1]赵言龙,郑浩然.基于代谢分析的SARS-CoV-2药物靶点预测方法[J].中国医学物理学杂志,2023,40(11):1433-1440.[doi:DOI:10.3969/j.issn.1005-202X.2023.11.019]
　ZHAO Yanlong,ZHENG Haoran.Drug target prediction approach for SARS-CoV-2 based on metabolic analysis[J].Chinese Journal of Medical Physics,2023,40(11):1433-1440.[doi:DOI:10.3969/j.issn.1005-202X.2023.11.019]
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基于代谢分析的SARS-CoV-2药物靶点预测方法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
40卷
期数:
2023年第11期
页码:
1433-1440
栏目:
其他（激光医学等）
出版日期:
2023-11-24

文章信息/Info

Title:
Drug target prediction approach for SARS-CoV-2 based on metabolic analysis
文章编号:
1005-202X（2023）11-1433-08
作者:
赵言龙; 郑浩然
中国科学技术大学计算机科学与技术学院， 安徽 合肥 230027
Author(s):
ZHAO Yanlong;  ZHENG Haoran
School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China
关键词:
SARS-CoV-2; 药物靶点; 代谢网络模型; 显著高表达基因
Keywords:
SARS-CoV-2 drug target metabolic network model highly expressed gene
分类号:
R318.04
DOI:
DOI:10.3969/j.issn.1005-202X.2023.11.019
文献标志码:
A
摘要:
提出一种基于代谢分析的抑制SARS-CoV-2复制的药物靶点预测方法。使用5组基因表达综合数据库（GEO）的人类肺部组织细胞的转录组学数据，提取出SARS-CoV-2入侵宿主细胞后显著高表达的基因，进而重构出病毒入侵肺部组织细胞后的代谢网络模型；之后采用基因敲除、毒性测试等系统生物学分析方法来预测药物靶点。对GEO中5个数据集的样本进行分析，结果显示各数据集预测的靶点基因具有一定的一致性。其中，PLPBP是5个数据集中预测的共有靶点基因，说明它对于SARS-CoV-2代谢活动具有重要作用，可作为治疗该疾病的潜在药物靶点；另外，BCAT1、BCAT2、ADI1也具有一定的研究价值。提出的方法为预测SARS-CoV-2的药物靶点提供一种新的思路，预测的药物靶点也具有进一步临床研究的潜力。
Abstract:
A metabolic profiling-based method for predicting the drug targets that inhibit SARS-CoV-2 replication is presented. Five sets of the transcriptomic data of human lung histiocytes from the Gene Expression Omnibus (GEO) database are used in the study. The highly expressed genes after SARS-CoV-2 invaded the host cells are extracted, and a metabolic network model after the virus invasion is reconstructed. Some systems biology approaches such as gene knockout and cytotoxicity test are adopted to discover the drug targets. The analysis on the samples from 5 datasets in GEO shows that the target genes predicted in each dataset has certain consistency. PLPBP is the common target gene predicted in the 5 datasets, indicating that it plays an important role in the metabolic activities of SARS-CoV-2 and can be served as a potential drug target. In addition, BCAT1, BCAT2, ADI1 are also worth further exploring. The proposed method provides a new idea for predicting the drug targets for SARS-CoV-2, and the predicted drug targets are potential for further clinical research.

相似文献/References:

[1]齐瑜鹏,赵言龙,郑浩然.一种通过代谢差异分析抑制SARS-CoV-2复制的靶点预测方法[J].中国医学物理学杂志,2023,40(12):1577.[doi:DOI:10.3969/j.issn.1005-202X.2023.12.019]
　QI Yupeng,ZHAO Yanlong,ZHENG Haoran.Target prediction approach to inhibit SARS-CoV-2 replication based on metabolic difference analysis[J].Chinese Journal of Medical Physics,2023,40(11):1577.[doi:DOI:10.3969/j.issn.1005-202X.2023.12.019]

备注/Memo

备注/Memo:
【收稿日期】2023-07-16 【基金项目】国家重点基础研究发展计划（2017YFA0505502）；中国科学院战略性先导科技专项（XDB38000000） 【作者简介】赵言龙，硕士研究生，研究方向：生物信息学，E-mail: zhaoyanlong_ouc@163.com 【通信作者】郑浩然，副教授，研究方向：生物信息学，E-mail: hrzheng@ustc.edu.cn
更新日期/Last Update: 2023-11-24