Pharmacophore based virtual screening for identification of effective inhibitors to compact HPV 16 E6 a triggered cervical cancer

Abstract

Cervical cancer, one of the most common causes of cancer-related death among women in the world, has been linked to the presence of a particular oncoprotein that is predominantly transferred through sexual contact with an infected host. In 90% of cervical cancer deaths, a correlation has been found with the expression of the viral genome of HPV16 E6. As a result, HPV16 E6 has emerged as an optimistic therapeutic drug target for the treatment of cervical cancer. In order to develop a drug that is capable of disturbing the genome expression activity of HPV16 E6, it is imperative to identify the key chemical features of its known inhibitors. In this study, we present an investigationon identifying potential inhibitors of HPV16 E6 by utilizing pharmacophore-based virtual screening, molecular docking, ADME prediction, and molecular dynamics simulation. In the initial stage, we generated a ligand-based pharmacophore model based on the features of four known HPV16 E6 inhibitors (CA24, CA25, CA26, and CA27)via the PHASE module implanted in the Schrödinger suite. We constructedfour-point pharmacophore features, which consists of three hydrogen bond acceptors (A) and one aromatic ring (R). The common pharmacophore features further employed as a query for virtual screening against the ASINEX database via the Schrödinger suite. The pharmacophore-based virtual screening filtered out top 2000 hits, based on the fitness score. We applied the molecular docking studies for further compound filtration using Glide which provide three ligand filtering phases, namely HTVS, SP, XP. Initially, 1000 compounds were obtained from HTVS docking. Based on the glide score, they were further filtered to 500 hits by employing docking in standard precision mode. Finally, the best four hits were identified using docking in XP mode. The four compounds were then further subjected to ADME profile prediction by engaging the Qikprop module. The ADME properties of the four fell within a satisfactory range and the compounds exhibited anticipated pharmacokinetic properties. These compounds were further investigated to determine the binding stability of the protein-ligand complex at a different time scale (100 ns) by using the desmond package for a molecular dynamics simulation. These molecular dynamics simulation studies revealed that theCYS 51 and GLN 107 proteins are residues of HPV 16 E6 binding sites, and the root mean square deviation (RMSD) and root mean square fluctuations (RMSF) values for these residues were also found to be within satisfactory ranges and suggest a crucial role in enhancing the stability of the protein-ligand complex during the simulation. From these computational investigations, we concluded that the four potential compounds are appropriate for further study, and potential clinical investigation, as HPV16 E6 inhibitors.

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“…13 A small ΔGbind value indicates a more stable conformation, 14 while a large ΔGbind value indicates a less stable complex. 15 The RMSD value is used to determine whether the binding mode prediction is successful and it is important for docking program validation. 16 In general, the RMSD value is said to be good if it is < 2 Å.…”

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