In silico prospective analysis of the medicinal plants activity on the CagA oncoprotein from Helicobacter pylori
Authors: Vieira Rafaela Viana , Peiter Gabrielle Caroline , de Melo Fabrício Freire , Zarpelon-Schutz Ana Carla , Teixeira Kádima Nayara 
Published: May 2024

BACKGROUND
Colonization with Helicobacter pylori (H. pylori ) has a strong correlation with gastric cancer, and the virulence factor CagA is implicated in carcinogenesis. Studies have been conducted using medicinal plants with the aim of eliminating the pathogen; however, the possibility of blocking H. pylori -induced cell differentiation to prevent the onset and/or progression of tumors has not been addressed. This type of study is expensive and time-consuming, requiring in vitro and/or in vivo tests, which can be solved using bioinformatics. Therefore, prospective computational analyses were conducted to assess the feasibility of interaction between phenolic compounds from medicinal plants and the CagA oncoprotein.
AIM
To perform a computational prospecting of the interactions between phenolic compounds from medicinal plants and the CagA oncoprotein of H. pylori .
METHODS
In this in silico study, the structures of the phenolic compounds (ligands) kaempferol, myricetin, quercetin, ponciretin (flavonoids), and chlorogenic acid (phenolic acid) were selected from the PubChem database. These phenolic compounds were chosen based on previous studies that suggested medicinal plants as non-drug treatments to eliminate H. pylori infection. The three-dimensional structure model of the CagA oncoprotein of H. pylori (receptor) was obtained through molecular modeling using computational tools from the I-Tasser platform, employing the threading methodology. The primary sequence of CagA was sourced from GenBank (BAK52797.1). A screening was conducted to identify binding sites in the structure of the CagA oncoprotein that could potentially interact with the ligands, utilizing the GRaSP online platform. Both the ligands and receptor were prepared for molecular docking using AutoDock Tools 4 (ADT) software, and the simulations were carried out using a combination of ADT and AutoDock Vina v.1.2.0 software. Two sets of simulations were performed: One involving the central region of CagA with phenolic compounds, and another involving the carboxy-terminus region of CagA with phenolic compounds. The receptor-ligand complexes were then analyzed using PyMol and BIOVIA Discovery Studio software.
RESULTS
The structure model obtained for the CagA oncoprotein exhibited high quality (C-score = 0.09) and was validated using parameters from the MolProbity platform. The GRaSP online platform identified 24 residues (phenylalanine and leucine) as potential binding sites on the CagA oncoprotein. Molecular docking simulations were conducted with the three-dimensional model of the CagA oncoprotein. No complexes were observed in the simulations between the carboxy-terminus region of CagA and the phenolic compounds; however, all phenolic compounds interacted with the central region of the oncoprotein. Phenolic compounds and CagA exhibited significant affinity energy (-7.9 to -9.1 kcal/mol): CagA/kaempferol formed 28 chemical bonds, CagA/myricetin formed 18 chemical bonds, CagA/quercetin formed 16 chemical bonds, CagA/ponciretin formed 13 chemical bonds, and CagA/chlorogenic acid formed 17 chemical bonds. Although none of the phenolic compounds directly bound to the amino acid residues of the K-Xn-R-X-R membrane binding motif, all of them bound to residues, mostly positively or negatively charged, located near this region.
CONCLUSION
In silico , the tested phenolic compounds formed stable complexes with CagA. Therefore, they could be tested in vitro and/or in vivo to validate the findings, and to assess interference in CagA/cellular target interactions and in the oncogenic differentiation of gastric cells.