A Combination of Pharmacophore Generation, Ligand-based Virtual Screening, Atom-based 3D-QSAR, and Molecular Docking Studies on Febuxostat-based Amides Analogues as Anti-inflammatory Agents

Abstract

Background: A defence mechanism of the body includes inflammation. It is a process through which the immune system identifies, rejects, and starts to repair foreign and damaging stimuli. In the world, chronic inflammatory disorders are the leading cause of death.

Material and methods: To obtain optimized pharmacophore, previously reported febuxostat- based anti-inflammatory amide derivatives series were subjected to pharmacophore hypothesis, ligand-based virtual screening, and 3D-QSAR studies in the present work using Schrodinger suite 2022-4. QuikProp module of Schrodinger was used for ADMET prediction, and HTVS, SP, and XP protocols of GLIDE modules were used for molecular docking on target protein (PDB ID:3LN1).

Result: Utilising 29 compounds, a five-point model of common pharmacophore hypotheses was created, having pIC50 ranging between 5.34 and 4.871. The top pharmacophore hypothesis AHHRR_ 1 model consists of one hydrogen bond acceptor, two hydrophobic groups and two ring substitution features. The hypothesis model AHHRR_1 underwent ligand-based virtual screening using the molecules from Asinex. Additionally, a 3D-QSAR study based on individual atoms was performed to assess their contributions to model development. The top QSAR model was chosen based on the values of R2 (0.9531) and Q2 (0.9424). Finally, four potential hits were obtained by molecular docking based on virtual screening.

Conclusion: The virtual screen compounds have shown similar docking interaction with amino acid residues as shown by standard diclofenac sodium drugs. Therefore, the findings in the present study can be explored in the development of potent anti-inflammatory agents.

Keywords: 3D-QSAR; Asinex database; Febuxostat; Ligand-based virtual screening; Schrodinger.; anti-inflammatory; common pharmacophore hypothesis.