Pharmacoinformatics-based screening of Capparis spinosa phytocompounds against pancreatic ductal adenocarcinoma by targeting TSPAN1 protein

Today, phytochemicals have garnered significant attention due to their diverse pharmacological effects against various diseases, particularly cancer. Computer-aided drug design (CADD) is a time- and cost-effective approach to drug discovery that uses computational tools to evaluate drug candidates before in vitro and in vivo testing.

This study aimed to identify potential biomarkers of pancreatic ductal adenocarcinoma (PDAC) and investigate the anticancer effects of Capparis spinosa phytocompounds against these biomarkers using in silico approaches.

A meta-analysis based on an empirical Bayesian methodology (ComBat) using two different datasets, Affymetrix and ONGene, revealed that TSPAN1, a member of the tetraspanin family, is highly expressed in malignant tumors. The phytochemical composition of Capparis spinosa was evaluated using protein-protein interaction (PPI) network analysis and comparative analysis of drug design against TSPAN1-related PDAC. 27 isolated phytochemicals from Capparis spinosa were investigated for their ability to bind the TSPAN1 protein, and four compounds were chosen for further investigation depending on their higher binding affinity.

The analysis revealed that two compounds, including apigenin (PubChemCID: 5,280443) and kaempferol (PubChemCID: 5,280863), are suitable for drug design and safe for human consumption. Regarding the anticancer potential of these phytochemicals against PDAC, further pharmacological studies are needed to verify their efficacy.