GC–MS and Network Pharmacology Analysis of the Ayurvedic Fermented Medicine, Chandanasava, Against Chronic Kidney and Cardiovascular Diseases

Abstract

Chandanasava is an Ayurvedic polyherbal fermented traditional medicine (FTM) used by traditional practitioners for millennia . Nevertheless, the mode of action and functional targets are still unknown. The current study includes a pharmacological network analysis to identify the Chandanasava compounds interacting with target proteins involved in chronic kidney disease (CKD) and cardiovascular disease (CVD). Sixty-one Chandanasava phytochemicals were obtained by GC–MS and screened using the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The disease target genes were obtained from DisGeNET and GeneCards databases. Forty-five phytocompounds and 135 potential targets were screened for CKD and CVD target proteins and protein interaction networks were constructed. The pharmacological network was deciphered employing target proteins involved in the mechanical action of Chandanasava . The results indicated that 10 bioactive compounds exhibited higher binding affinity patterns with the screened 42 CKD and CVD target proteins. Gene Ontology and KEGG analysis revealed target pathways involved in CKD and CVD, which were further explored by detailed analysis and network-coupled drug profile screening. The molecular docking results showed piperine and melatonin as effective inhibitors/regulators of the hub genes of CKD and CVD. The current study establishing authentic bioactive compounds in FTM is based on deeper insights into recognized Ayurvedic medicines. Graphical Abstract Representing the workflow of the network pharmacological analysis Supplementary Information The online version contains supplementary material available at 10.1007/s12010-022-04242-7.

Untargeted metabolomics-based network pharmacology reveals fermented brown rice towards anti-obesity efficacy

“…The resultant metabolites were subsequently assessed by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database for assimilatory characteristics according to drug-selection criteria such as oral bioavailability (OB) and drug-likeness (DL). Oral bioavailability summarizes medicines’ attributes of absorption, distribution, metabolism, and excretion (ADME) and their consumption in the blood flow 50 . The chemical data for each ingredient, including their chemical structures, molecular formula, and biological information, were acquired using the Pub Chem and Drug Bank databases.…”

“…Obesity-related gene target data were obtained from TCMSP, DisGeNET, and GeneCards 50 . In addition, the aforementioned electronic databases were explored using the search term “obesity” to find the disease of interest and its associated genes.…”

“…The network of protein‒protein interactions (PPI) was constructed using STRING 11.0 and was estimated toward a high confidence level of 70% identity (0.700). The enrichment analyses, Gene Ontology (GO), and KEGG Pathway were performed to develop the biological process (BP), molecular function (MF), and cellular components (CC) of disease target proteins 50 , 51 . Moreover, networks of hub-gene-associated targets, pathway interactions, and target‒gene interactions with potential compounds were constructed using the Cystoscope tool 50 .…”

“…The Discovery Studio software was used to determine the molecular binding from a two-and three-dimensional viewpoint. The docking scores, bond lengths, and all interactions were recorded 50 .…”

Secondary metabolite profiling using HR-LCMS, antioxidant and anticancer activity of Bacillus cereus PSMS6 methanolic extract: In silico and in vitro study

“…The network consists of 18 nodes and 82 edges, as represented in Supplementary Table S6, S7. Interestingly, we identified the top three hub genes that control an entire PPIN [ [35] , [36] , [37] , [38] , [39] , [40] , [41] ] in the biological and molecular mechanisms of the ERBB2 signalling pathway. Such genes are erbB-2, EGFR, and pro-epidermal growth factor (GRB2), as depicted in ( Fig.…”