Predictive profiling of gram-negative antibiotics in CagA oncoprotein inactivation: a molecular dynamics simulation approach.

Abstract

Gastric cancer (GC) is the fifth most prevalent form of cancer worldwide. CagA - positive Helicobacter pylori infects more than 60% of the human population. Moreover, chronic infection of CagA-positive H. pylori can directly affect GC incidence. In the current study, we have repurposed FDA-approved antibiotics that are viable alternatives to current regimens and can potentially be used as combination therapy against the CagA of H. pylori. The 100 FDA-approved gram negative antibiotics were screened against CagA protein using the AutoDock 4.2 tool. Further, top nine compounds were selected based on higher binding affinity with CagA. The trajectory analysis of MD simulations reflected that binding of these drugs with CagA stabilizes the system. Nonetheless, atomic density map and principal component analysis also support the notion of stable binding of antibiotics to the protein. The residues ASP96, GLN100, PRO184, and THR185 of compound cefpiramide, doxycycline, delafloxacin, metacycline, oxytetracycline, and ertapenem were involved in the binding with CagA protein. These residues are crucial for the CagA that aids in entry or pathogenesis of the bacterium. The screened FDA-approved antibiotics have a potential druggability to inhibit CagA and reduce the progression of H. pylori borne diseases.