A network pharmacology analysis on drug-like compounds from Ganoderma lucidum for alleviation of Atherosclerosis

Abstract

Background: Ganoderma lucidum (GL) is known as a potent alleviator against chronic inflammatory disease like atherosclerosis (AS), but its critical bioactive compounds and their mechanisms against AS have not been unveiled. This research aimed to identify the key compounds(s) and mechanism(s) of GL against AS through network pharmacology.Methods: The compounds from GL were identified by gas chromatography-mass spectrum (GC-MS), and SwissADME screened their physicochemical properties. Then, the gene(s) associated with the screened compound(s) or AS related genes were identified by public databases, and we selected the overlapping genes using a Venn diagram. The networks between overlapping genes and compounds were visualized, constructed, and analyzed by RStudio. Finally, we performed molecular docking test (MDT) to identify key gene(s), compound(s) on AutoDockVina.Results: A total of 35 compounds in GL was detected via GC-MS, and 34 compounds (accepted by the Lipinski's rule) were selected as drug-like compounds (DLCs). A total of 34 compounds were connected to the number of 785 genes and 2,606 AS-related genes were identified by DisGeNET and Online Mendelian Inheritance in Man (OMIM). The final 98 overlapping genes were extracted between the compounds-genes network and AS-related genes. On Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, the number of 27 signaling pathways were sorted out, and a hub signaling pathway (MAPK signaling pathway), a core gene (PRKCA), and a key compound (Benzamide, 4-acetyl-N-(2,6-dimethylphenyl)) were selected among the 27 signaling pathways via MDT. Conclusion: Overall, we found that the identified 3 DLCs from GL have potent anti-inflammatory efficacy, improving AS by inactivating the MAPK signaling pathway.

Network pharmacology and in silico pharmacokinetic prediction of Ozanimod in the management of ulcerative colitis: A computational study

“…OZM passes all the factors Tumorigenicity, mutagenicity, irritant, reproductive effect with green color representation 5 (Figure 1A). Overlapping Target Proteins between AID, UC, and OZM showed that 24 target proteins were overlapping between the two public databases 6 (Figure 1B). Protein-protein interaction from 24 overlapping target proteins from STRING analysis shows that 24 nodes, 123 edges, and PPI enrichment P-value was <1.0e-16.…”

Network pharmacology, molecular docking and in vivo and in vitro experiments to explore the molecular mechanism of licorice green tea beverage to scavenge oxygen free radicals

“…Network pharmacology is a branch of system biology that explores the complex relationships among drugs, constituents, diseases and targets through pharmacology and computer analysis techniques (Oh et al, 2021; Pei et al, 2022). It is used to explore the pharmacological mechanism of drug action on various diseases (Tu et al, 2022; Xu et al, 2017).…”

In Silico Identification of Protein Targets for Drug-like Compounds from Epicarp Extract of Cola rostrata K. Shum

“…The knowledge of the constituents of extracts is useful in the matching bioactive component with biomolecular targets and indirectly, the kind of diseases the extract may be potent against. In silico protein target prediction and molecular docking have been used in the selection of potential drug-like components of natural products for chemical lead discovery against many ailments and diseases (Oduselu et al, 2019;Asghar et al, 2021;Oh et al, 2021). Cola rostrata is an underutilized and uncultivated tree crop that produces crunchy tasty edible fruits; the plant belongs to the sub-family Sterculiaceae and it is one of the Cola species that are commonly called Monkey kola (Odion et al, 2013).…”