AUTHOR=Zhou Yehong , Shu Fuxing , Sarsaiya Surendra , Jiang Hu , Jiang Chengyan , Qu Tingnian , Wang Ruixia TITLE=Network pharmacology and molecular docking to explore Siraitia grosvenorii’s potential mechanism in preventing and treating proliferative diabetic retinopathy JOURNAL=Frontiers in Drug Discovery VOLUME=2 YEAR=2022 URL=https://www.frontiersin.org/journals/drug-discovery/articles/10.3389/fddsv.2022.1038224 DOI=10.3389/fddsv.2022.1038224 ISSN=2674-0338 ABSTRACT=

Although Siraitia grosvenorii (abbreviated as S.g.) is frequently used to prevent and cure diabetes problems, the precise mechanism underlying its ability to do so remains unknown. Through network pharmacology and molecular docking techniques, we studied the early molecular mechanisms of S.g in the treating of proliferative diabetic retinopathy (PDR) in this study. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to screen the active compounds and related targets of S.g. Oral bioavailability (OB) 30% and drug likeness (DL) 0.18 were used as screening criteria. The active compounds without knowledge of a probable target were excluded. The Uniprot database included converted symbols for the associated targets. GEO2R was used to explore several genes related to PDR. Using jvenn web service to intersect targets of S.g and PDR. The Xiantao Academic Online website was used to examine the expression patterns of intersect targets in PDR samples. The STRING database was used to create a protein-protein interaction (PPI) network of intersecting targets. Cytoscape software was used to show the PPI network, MCODE software was used to evaluate the network’s core proteins, and CytoHubba software was used to extract the important networks of the top three targets. Omicshare platform carried a functional analysis using the Gene Ontology (GO) and pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Pymol, AutoDock Vina software, Schrödinger Software were used to conduct molecular docking experiments or pockets search on the top three targets. The results showed that 85 targets were matched to six active compounds of S.g. 18 intersect targets were found. Seven DEGs were up-regulated and eleven genes were down-regulated when these targets were divided into two groups. TNF, PTGS2, and CASP3 were the main targets, according to the PPI network. The intersect targets were mostly related to angiogenesis, cell proliferation, oxidative stress, inflammatory response, and metabolism. It was discovered that the core targets TNF, PTGS2, and CASP3 had various levels of affinity for their respective compounds. Interestingly, multiple good drug-forming pockets for CASP3 and PTGS2 targets were identified through Schrödinger software. In particular, six compounds bind to the top three core targets to inhibit IL-17 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, Pathways in cancer and 14 other signaling pathways to inhibit inflammation, apoptosis, oxidative stress, arachidonic acid metabolism, and angiogenesis to prevent and treat PDR. The study’s findings, which served as a guide for the widespread use of S.g in PDR clinical practise, included multi-substances and targets of S.g to prevent and cure PDR.