Xin Yijing, Chen Shubing, Tang Ke, Wu You, Guo Ying
Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
Int J Mol Sci. 2022 Feb 21;23(4):2372. doi: 10.3390/ijms23042372.
The rapid development in the field of transcriptomics provides remarkable biomedical insights for drug discovery. In this study, a transcriptome signature reversal approach was conducted to identify the agents against influenza A virus (IAV) infection through dissecting gene expression changes in response to disease or compounds' perturbations. Two compounds, nifurtimox and chrysin, were identified by a modified Kolmogorov-Smirnov test statistic based on the transcriptional signatures from 81 IAV-infected patients and the gene expression profiles of 1309 compounds. Their activities were verified in vitro with half maximal effective concentrations (ECs) from 9.1 to 19.1 μM against H1N1 or H3N2. It also suggested that the two compounds interfered with multiple sessions in IAV infection by reversing the expression of 28 IAV informative genes. Through network-based analysis of the 28 reversed IAV informative genes, a strong synergistic effect of the two compounds was revealed, which was confirmed in vitro. By using the transcriptome signature reversion (TSR) on clinical datasets, this study provides an efficient scheme for the discovery of drugs targeting multiple host factors regarding clinical signs and symptoms, which may also confer an opportunity for decelerating drug-resistant variant emergence.
转录组学领域的快速发展为药物发现提供了卓越的生物医学见解。在本研究中,开展了一种转录组特征逆转方法,通过剖析因疾病或化合物扰动而产生的基因表达变化,来识别抗甲型流感病毒(IAV)感染的药物。基于81名IAV感染患者的转录特征和1309种化合物的基因表达谱,通过改进的柯尔莫哥洛夫-斯米尔诺夫检验统计量,鉴定出两种化合物,硝呋替莫和白杨素。它们在体外对H1N1或H3N2的半数最大有效浓度(EC)为9.1至19.1μM,从而验证了其活性。这还表明这两种化合物通过逆转28个IAV信息基因的表达,干扰了IAV感染的多个环节。通过对28个逆转的IAV信息基因进行基于网络的分析,揭示了这两种化合物的强协同效应,并在体外得到了证实。通过对临床数据集使用转录组特征逆转(TSR),本研究为发现针对多种与临床体征和症状相关宿主因子的药物提供了一种有效方案,这也可能为延缓耐药变体的出现带来契机。