Text Mining-Based Drug Discovery for Connective Tissue Disease-Associated Pulmonary Arterial Hypertension.
Text Mining-Based Drug Discovery for Connective Tissue Disease-Associated Pulmonary Arterial Hypertension.
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基于文本挖掘的结缔组织病药物发现 - 相关肺动脉高压
DOI:
10.3389/fphar.2022.743210
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发表时间:
2022
影响因子:
5.6
通讯作者:
Wang XJ
中科院分区:
文献类型:
--
作者:
Tan JS;Hu S;Guo TT;Hua L;Wang XJ
Background: The current medical treatments for connective tissue disease–associated pulmonary arterial hypertension (CTD-PAH) do not show favorable efficiency for all patients, and identification of novel drugs is desired. Methods: Text mining was performed to obtain CTD- and PAH-related gene sets, and the intersection of the two gene sets was analyzed for functional enrichment through DAVID. The protein–protein interaction network of the overlapping genes and the significant gene modules were determined using STRING. The enriched candidate genes were further analyzed by Drug Gene Interaction database to identify drugs with potential therapeutic effects on CTD-PAH. Results: Based on text mining analysis, 179 genes related to CTD and PAH were identified. Through enrichment analysis of the genes, 20 genes representing six pathways were obtained. To further narrow the scope of potential existing drugs, we selected targeted drugs with a Query Score ≥5 and Interaction Score ≥1. Finally, 13 drugs targeting the six genes were selected as candidate drugs, which were divided into four drug–gene interaction types, and 12 of them had initial drug indications approved by the FDA. The potential gene targets of the drugs on this list are IL-6 (one drug) and IL-1β (two drugs), MMP9 (one drug), VEGFA (three drugs), TGFB1 (one drug), and EGFR (five drugs). These drugs might be used to treat CTD-PAH. Conclusion: We identified 13 drugs targeting six genes that may have potential therapeutic effects on CTD-PAH.
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影响因子:
5
作者:
Liu, Ying;Zhang, Hongyue;Zhu, Daling
通讯作者:
Zhu, Daling
影响因子:
37.8
作者:
Merklinger, SL;Jones, PL;Rabinovitch, M
通讯作者:
Rabinovitch, M
影响因子:
4.9
作者:
George J;D'Armiento J
通讯作者:
D'Armiento J
影响因子:
5.8
作者:
Sakao S;Tatsumi K;Voelkel NF
通讯作者:
Voelkel NF
影响因子:
1.5
作者:
Arita, Yoh;Sakata, Yasushi;Yamauchi-Takihara, Keiko
通讯作者:
Yamauchi-Takihara, Keiko