Mechanisms predictive of Tibetan Medicine Sophora moorcroftiana alkaloids for treatment of lung cancer based on the network pharmacology and molecular docking

Abstract

Abstract Background Leguminous Sophora moorcroftiana (SM) is a genuine medicinal material in Tibet. Many research results have reveal the Sophora moorcroftiana alkaloids (SMA), as the main active substance, have a wide range of effects, such as antibacterial, antitumor and antiparasitic effects. However, there are few reports on the inhibition of lung cancer (LC) and its inhibitory mechanism, and the pharmacological mechanism of SMA is still unclear, Therefore, exploring its mechanism of action is of great significance. Methods The SMA active components were obtained from the literature database. Whereas the corresponding targets were screened from the PubChem and PharmMapper database, UniProt database were conducted the correction and transformation of UniProt ID on the obtained targets. The GeneCards and OMIM databases identified targets associated with LC. Venny tools obtained the intersection targets of SMA and LC. R language and Cytoscape software constructed the visual of SMA - intersection targets – LC disease network. The intersection targets protein-protein interaction (PPI) network were built by the STRING database. The functions and pathways of the common targets of SMA and LC were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking And A549 cells vitro experiment were performed to further validate our finding. Results We obtained six kinds of alkaloids in SM, 635 potential targets for these compounds, and 1,303 genes related to LC. SMA and LC intersection targets was 33, including ALB, CCND1, ESR1, NOTCH1 and AR. GO enrichment indicated that biological process of SMA was mainly involved in the positive regulation of transcription and nitric oxide biosynthetic process, and DNA-templated, etc. Biological functions were mainly involved in transcription factor binding and enzyme binding, etc. Cell components were mainly involved in protein complexes, extracellular exosome, cytoplasm and nuclear chromatin, etc., Which may be associated with its anti-LC effects. KEGG enrichment analysis showed that main pathways involved in the anti-LC effects of SMA, including pathway in cancer, non small-cell lung cancer, p53, PI3K-Akt and FOXO signaling pathways. Molecular docking analyses revealed that the six active compounds had a good binding activity with the main therapeutic targets 2W96, 2CCH and 1O96. Experiments in vitro proved that SMA inhibited the proliferation of LC A549 cells. Conclusions Results of the present study, we have successfully revealed the SMA compounds had a multi-target and multi-channel regulatory mechanism in treatment LC, These findings provided a solid theoretical reference of SMA in the clinical treatment of LC.