Unveiling the multi-target compounds of Rhazya stricta: Discovery and inhibition of novel target genes for the treatment of clear cell renal cell carcinoma

• Published in: Computers in biology and medicine Vol. 165; p. 107424
• Main Authors: Rehman, Abdur, Fatima, Israr, Wang, Yinuo, Tong, Jiapei, Noor, Fatima, Qasim, Muhammad, Peng, Yuzhong, Liao, Mingzhi
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2023; Elsevier Limited
• Subjects: Biomarkers; Cancer therapies; Cell division; Clear cell renal cell carcinoma; Clear cell-type renal cell carcinoma; Data collection; Data mining; Datasets; Drug therapy; ErbB-2 protein; Flavonoids; Gelatinase B; Gene expression; Genes; Genomics; In vivo methods and tests; Investigations; Kidney cancer; Kidneys; Kinases; Malignancy; Medical innovations; Medicinal plants; Metabolites; Molecular docking; Molecular dynamic simulation; Molecular modelling; Pharmacokinetics; Pharmacology; Phytochemicals; Proteins; R&D; Research & development; Rhazya stricta; Survival analysis; Therapeutic targets; Tissue analysis; Toxicity; Clear cell renal cell carcinoma; Phytochemicals; Molecular dynamic simulation; Rhazya stricta; Molecular docking
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2023.107424

Clear cell renal cell carcinoma (ccRCC) is a prevalent kidney malignancy with a pressing need for innovative therapeutic strategies. In this context, emerging research has focused on exploring the medicinal potential of plants such as Rhazya stricta. Nevertheless, the complex molecular mechanisms underlying its potential therapeutic efficacy remain largely elusive. Our study employed an integrative approach comprising data mining,network pharmacology,tissue cell type analysis, and molecular modelling approaches to identify potent phytochemicals from R. stricta, with potential relevance for ccRCC treatments. Initially, we collected data on R. stricta's phytochemical from public databases. Subsequently, we integrated this information with differentially expressed genes (DEGs) in ccRCC, which were derived from microarray datasets(GSE16441,GSE66270, and GSE76351). We identified potential intersections between R. stricta and ccRCC targets, which enabled us to construct a compound-genes-pathway network using Cytoscape software. This helped illuminate R. stricta's multi-target pharmacological effects on ccRCC. Moreover, tissue cell type analysis added another layer of insight into the cellular specificity of potential therapeutic targets in the kidney. Through further Kaplan–Meier survival analysis, we pinpointed MMP9,ACE,ERBB2, and HSP90AA1 as prospective diagnostic and prognostic biomarkers for ccRCC. Notably, our study underscores the potential of R. stricta derived compounds-namely quebrachamine,corynan-17-ol, stemmadenine,strictanol,rhazinilam, and rhazimolare-to impede ccRCC progression by modulating the activity of MMP9,ACE,ERBB2, and HSP90AA1 genes. Further, molecular docking and dynamic simulations confirmed the plausible binding affinities of these compounds. Despite these promising findings, we recognize the need for comprehensive in vivo and in vitro studies to further investigate the pharmacokinetics and biosafety profiles of these compounds. •Network pharmacology approach was used to unravel the anti-ccRCC targets.•Network among active compounds and putative target was constructed.•Differential expression, tissue cell type and survival analysis was done against ccRCC.•Active constituents showed appreciable inhibitory effects against MMP9,ACE,ERBB2 and HSP90AA1.