Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

Abstract

Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson's correlation for the construction of quantitative structure-activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R² = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, Z-964, Z-627, and Z-814, with their predicted pIC₅₀ (-log IC₅₀) values, Z-814 = 7.9484, Z-627 = 9.3458, and Z-964 = 9.5272. All candidates inhibitors complied with Lipinski's rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.

Keywords: COX-2 inhibitors; in silico; molecular modeling.

Figure 1

Cascade of arachidonic acid.

Figure 2

General scheme summarizing of the methodological steps.

Figure 3

The most active molecules.

Figure 4

Linear correlation graph of the tetra-parametric model.

Figure 5

Selected inhibitors with Tanimoto index. (A) Z-814; (B) Z-964; (C) Z-627.

Figure 6

Overlapping poses of the crystallographic complexes (in green) with calculated poses (in red): (a) rofecoxib (RCX) for Homo sapiens (PDB 5KIR), (b) celecoxib (CEL) for Mus musculus (PDB 3LN1) and (c) indomethacin (IMS) Ovis aries (PDB 2OYE).

Figure 7

Interactions of the inhibitors (a) rofecoxib, (b) Z-627, (c) Z-964, and (d) Z-814 with the active site of the structure of the Vioxx bound to the Homo sapiens cyclooxygenase-2 (COX-2, PDB 5KIR).

Figure 8

Interactions of inhibitors (a) celecoxib, (b) Z-627, (c) Z-964, and (d) Z-814 with the active site of the Mus musculus COX-2 (PDB 3LN1).

Figure 9

Interactions of the inhibitors (a) indomethacin, (b) Z-627, (c) Z-964, and (d) Z-814 with the active site of the structure of the indomethacin complex to the Ovis aries COX-1 (PDB 2OYE).

Figure 10

Binding affinity ratio of the selected structures.

Figure 11

Root mean square deviations (RMSD) plot of complexes established with Homo sapiens COX-2. The protein backbone plot is colored black, but the ligand plots are colored in different ways. (A) RMSDs of the COX-2-rofecoxib system, (B) RMSDs of the COX-2-Z627 system, and (C) RMSDs of the COX-2-Z814 system.

Figure 12

RMSD plot of complexes established with Mus musculus COX-2. The protein backbone plot is colored black, but the ligand plots are colored in different ways. (A) RMSDs of the COX-2-celecoxib system, (B) RMSDs of the COX-2-Z627 system, and (C) RMSDs of the COX-2-Z814 system.

Figure 13

Root mean square fluctuations (RMSF) plot of the backbone of the proteins that established complexes with the compounds obtained by virtual screening. (A) RMSF for the COX-2 Homo sapiens; (B) RMSF for the COX-2 Mus musculus. (C) The region of the protein that has undergone the greatest fluctuations is highlighted in red.