Identification of novel potential cyclooxygenase-2 inhibitors using ligand- and structure-based virtual screening approaches

Abstract

Cyclooxygenase 2 (COX-2) is a well-established target for the design of anti-inflammatory intermediates. Celecoxib was selected as a template molecule to perform ligand-based virtual screening, i.e. to search for structures with similarity in shape and electrostatic potential, with a gradual increase in accuracy through the combined fitting of several steps using eight commercial databases. The molecules ZINC408709 and ZINC2090319 reproduced values within the limits established in an initial study of absorption and distribution in the body. No alert was fired for possible toxic groups when these molecules were subjected to toxicity prediction. Molecular docking results with these compounds showed a higher binding affinity in comparison to rofecoxib for the COX-2 target. Additionally, ZINC408709 and ZINC2090319 were predicted to be potentially biologically active. In in silico prediction of endocrine disruption potential, it was established that the molecule ZINC2090319 binds strongly to the target related to cardiovascular risk in a desirable way as a non-steroidal antagonist and ZINC408709 binds strongly to the target that is associated with the treatment of inflammatory pathologies and similar to celecoxib. Metabolites generated from these compounds are less likely to have side effects. Simulations were used to evaluate the interaction of compounds with COX-1 and COX-2 during 200 ns. Despite the differences, ZINC408709 molecule showed better stability for COX-2 during molecular dynamics simulation. In the calculations of free energy MM/PBSA, the molecule ZINC408709 ΔGbind value has a higher affinity to celecoxib and rofecoxib COX-2. This demonstrates that the selected substances can be considered as promising COX-2 inhibitors.

Communicated by Ramaswamy H. Sarma

Keywords:

• Cyclooxygenase 2
• EON
• ROCs
• pharmacokinetics
• toxicological
• metabolism

Disclosure statement

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Additional information

Funding

We gratefully acknowledge the support provided by Laboratory of Modeling and Computational Chemistry (LMCC) of Federal University of Amapá (UNIFAP-Brazil, Macapá, Amapá, 68902-280, Brazil, Computational Laboratory of Pharmaceutical Chemistry of University of São Paulo (USP Ribeirão Preto–Brazil).