Shana Sara Luke, M Naveen Raj, Suraj Ramesh, N Prasanth Bhatt
{"title":"基于网络药理学预测和分子对接策略探索角鲨烯抗炎的潜在机制。","authors":"Shana Sara Luke, M Naveen Raj, Suraj Ramesh, N Prasanth Bhatt","doi":"10.1007/s40203-024-00217-0","DOIUrl":null,"url":null,"abstract":"<p><p>Squalene (SQ) has been documented in the past for its ability to reduce inflammation, but its mechanism needs more information. In this study, we investigated squalene as an anti-inflammatory drug candidate and the framework involved in treating inflammation (INF) using the network pharmacology concept. The molecular targets of SQ and INF that are available in databases and the overlaps between these targets were demonstrated using InteractiVenn. The protein-protein networks were generated that in turn revealed several key targets and were further processed with Cytoscape. The gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) studies were performed. We also performed molecular docking tests that validated the binding affinity of molecular targets and drugs. A total of 100 SQ targets and 11,417 INF-related targets yielded 93 overlapping targets. Seven core targets, CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R were found to be relevant with respective to SQ's anti-inflammatory activity. The underlying mechanism of SQ with regard to INF was interpreted by analyzing various enrichment analyses along with the KEGG pathway. In conclusion, SQ played a vital role in the management of INF by regulating CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R. The research outcomes are crucial as they offer significant insights into the use of SQ for combating inflammation.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00217-0.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"12 1","pages":"44"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11093945/pdf/","citationCount":"0","resultStr":"{\"title\":\"Network pharmacology prediction and molecular docking-based strategy to explore the potential mechanism of squalene against inflammation.\",\"authors\":\"Shana Sara Luke, M Naveen Raj, Suraj Ramesh, N Prasanth Bhatt\",\"doi\":\"10.1007/s40203-024-00217-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Squalene (SQ) has been documented in the past for its ability to reduce inflammation, but its mechanism needs more information. In this study, we investigated squalene as an anti-inflammatory drug candidate and the framework involved in treating inflammation (INF) using the network pharmacology concept. The molecular targets of SQ and INF that are available in databases and the overlaps between these targets were demonstrated using InteractiVenn. The protein-protein networks were generated that in turn revealed several key targets and were further processed with Cytoscape. The gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) studies were performed. We also performed molecular docking tests that validated the binding affinity of molecular targets and drugs. A total of 100 SQ targets and 11,417 INF-related targets yielded 93 overlapping targets. Seven core targets, CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R were found to be relevant with respective to SQ's anti-inflammatory activity. The underlying mechanism of SQ with regard to INF was interpreted by analyzing various enrichment analyses along with the KEGG pathway. In conclusion, SQ played a vital role in the management of INF by regulating CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R. The research outcomes are crucial as they offer significant insights into the use of SQ for combating inflammation.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-024-00217-0.</p>\",\"PeriodicalId\":94038,\"journal\":{\"name\":\"In silico pharmacology\",\"volume\":\"12 1\",\"pages\":\"44\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11093945/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"In silico pharmacology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40203-024-00217-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"In silico pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40203-024-00217-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Network pharmacology prediction and molecular docking-based strategy to explore the potential mechanism of squalene against inflammation.
Squalene (SQ) has been documented in the past for its ability to reduce inflammation, but its mechanism needs more information. In this study, we investigated squalene as an anti-inflammatory drug candidate and the framework involved in treating inflammation (INF) using the network pharmacology concept. The molecular targets of SQ and INF that are available in databases and the overlaps between these targets were demonstrated using InteractiVenn. The protein-protein networks were generated that in turn revealed several key targets and were further processed with Cytoscape. The gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) studies were performed. We also performed molecular docking tests that validated the binding affinity of molecular targets and drugs. A total of 100 SQ targets and 11,417 INF-related targets yielded 93 overlapping targets. Seven core targets, CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R were found to be relevant with respective to SQ's anti-inflammatory activity. The underlying mechanism of SQ with regard to INF was interpreted by analyzing various enrichment analyses along with the KEGG pathway. In conclusion, SQ played a vital role in the management of INF by regulating CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R. The research outcomes are crucial as they offer significant insights into the use of SQ for combating inflammation.
Graphical abstract:
Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00217-0.