The structure-based virtual screening for natural compounds that bind with the activating receptors of natural killer cells

Abstract

The natural killer (NK) cells are responsible for immuno-surveillance against cancer and virally-infected cells. Ligand-binding with the activating receptors of the NK cells induces the tyrosine phosphorylation of the Immunoreceptor Tyrosine–based Activation Motif (ITAM) of adaptor proteins and triggers the direct cytotoxicity and the production of inflammatory cytokines through signal pathways. In this study, 1,697 natural compounds were obtained from 79 edible tropical plants through data mining. The in silico molecular docking simulations of these compounds were executed against 18 activating NK cell receptor targets using the Python Prescription (PyRx) 0.8 software incorporating both Vina and AutoDock 4.2 plug-in tools. An arbitrary docking score ≥-7.0 kcal/mol was chosen as cut-off value. Further screening for ligand efficiency, drug-likeness, Absorption Distribution Metabolism Excretion and Toxicity (ADMET) properties, Pan Assay Interference Compounds (PAIN), and possible aggregation behavior were performed. The ligand similarity analysis, phylogenetic analysis of the receptors, and binding site analysis were also performed. The results revealed 17 bioactive and non-promiscuous compounds that have good physicochemical and pharmacokinetic properties. Six of the identified compounds bound to 15 or more receptors with a free energy value ≥-7.0 kcal/mol.