Insights on Microsomal Prostaglandin E2 Synthase 1 (mPGES-1) Inhibitors using Molecular Dynamics and MM/PBSA Calculations

Abstract

Background: Despite being a normal body response against invading agents, inflammation, when exaggerated, needs to be controlled to minimize damage to the body. There are several drugs in clinical use against inflammation and other inflammatory conditions. Still, side effects often limit the use of these drugs, such as gastrointestinal effects generated by COX-1 inhibitors and cardiovascular effects by COX-2 inhibitors. Thus, exploring new targets such as mPGES-1 may lead to discovering agents that are more selective against inflammation and generate fewer side effects. Objectives: Here, docking, molecular dynamics, and MM-PBSA studies were performed on a dataset of known mPGES-1 inhibitors to identify helpful information and discover new mPGES-1 inhibitors. Methods: Molecular docking in GOLD software was used to obtain the complexes used in Molecular dynamics simulations (GROMACS software), performed to generate the RMSD, RMSF, Rg, SASA, and H-bond plots to predict the complexes' stability. The most stable conformation was analyzed regarding the most important interactions of the compounds. Finally, MM-PBSA calculations using the tool g_mmpbsa in GROMACS software were performed to determine de-binding affinity, interaction parameters, and per-residue contribution. Results: The main findings of this work were that the molecular dynamics simulation was able to find the open conformation of mPGES-1, which showed a greater preference on compounds in this region, consisting of residues known as "gateways". All compounds showed stability and stable complex formation with mPGES-1, as demonstrated by the results of RMSD, RMSF, Rg, SASA, and H-bond plots generated in a molecular dynamics simulation at 100 ns. The molecular dynamics identified three preferential sites of interaction for the compounds. Thus, the docking and dynamics protocols showed greater affinity of these compounds for cavity-02, interacting with Leu85, Pro81, Gln134, Cys137, Ala138, and Ala141. On the other hand, compound 09 preferred the cavity-03 of the protein, interacting mainly with His72 through Hbond. In addition, MM-PBSA calculations showed binding energies of up to -220,113 KJ/mol for compound 04. Furthermore, MM-PBSA could identify which electrostatic interactions are the most prevalent in the complex formation of the compounds with the highest affinity (04 and 07). Still, the van der Waals interactions are the most important for the others. Finally, the energy contribution per-residue revealed Lys120, Arg122, Arg126, and Tyr130 as the most important for the formation of the complexes. Conclusion: Design mPGES-1 inhibitors based on the residues Leu85, Pro81, Gln134, Cys137, Ala138, and Ala141, in addition to Lys120, Arg122, Arg126, and Tyr130 can provide new promising drugs useful against diseases involving inflammatory conditions.