Network pharmacology and pharmacophore modelling of aniline-containing natural products for anticancer drug discovery

Abstract

Abstract Network pharmacology could revolutionise the study of pharmaceuticals and natural products research. A compilation of 100 aniline-containing compounds was used for this study. Further filtering yielded 56 aniline-containing NPs that contain heavy atom count (HAC) <10; besides these, para-aminobenzoic acid (HAC = 10) was included from food sources. The network topological parameters were calculated. The overall network is comprised of 177 nodes and 809 edges with an average number of 7.051 neighbours. The monoamine oxidases B node has the highest degree, 117, and the clustering coefficient is 0.454, providing high connectivity to the network. A structure-based pharmacophore modelling approach was employed for the screening of lead compounds, and they were docked against the specified targets. The average binding energies of the complexes were −8.88, −7.98, and −6.11 kcal/mol, respectively. All filtered compounds exhibited the capacity to inhibit the targets. Furthermore, optimisation through the targeted chemical alteration of ligands may improve binding affinity and offer a promising approach for anticancer drug development.