Potential SARS-CoV-2 RdRp inhibitors of cytidine derivatives: Molecular docking, molecular dynamic simulations, ADMET, and POM analyses for the identification of pharmacophore sites.

The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is one of the optimum targets for antiviral drug design and development. The hydroxyl groups of cytidine structures were modified with different aliphatic and aromatic groups to obtain 5´-O-acyl and 2´,3´-di-O-acyl derivatives, and then, these derivatives were employed in molecular modeling, antiviral prediction, molecular docking, molecular dynamics, pharmacological and POM studies. Density functional theory (DFT) at the B3LYP/6-31G++ level analyzed biochemical behavior and molecular electrostatic potential (MESP) of the modified cytidine derivatives. The antiviral parameters of the mutated derivatives revealed promising drug properties compared with those of standard antiviral drugs. Molecular docking has determined binding affinities and interactions between the cytidine derivatives and SARS-CoV-2 RdRp. The modified derivatives strongly interacted with prime Pro620 and Lys621 residues. The binding conformation and interactions stability were investigated by 200 ns of molecular dynamics simulations and predicted the compounds to firmly dock inside the RdRp binding pocket. Interestingly, the binding residues of the derivatives were revealed in high equilibrium showing an enhanced binding affinity for the molecules. Intermolecular interactions are dominated by both Van der Waals and electrostatic energies. Finally, the pharmacokinetic characterization of the optimized inhibitors confirmed the safety of derivatives due to their improved kinetic properties. The selected cytidine derivatives can be suggested as potential inhibitors against SARS-CoV-2. The POM Theory supports the hypothesis above by confirming the existence of an antiviral (Oδ--O'δ-) pharmacophore site of Hits.

Computational Repurposing of Mitoxantrone-Related Structures against Monkeypox Virus: A Molecular Docking and 3D Pharmacophore Study.

Monkeypox is caused by a DNA virus known as the monkeypox virus (MPXV) belonging to the Orthopoxvirus genus of the Poxviridae family. Monkeypox is a zoonotic disease where the primary significant hosts are rodents and non-human primates. There is an increasing global incidence with a 2022 outbreak that has spread to Europe in the middle of the COVID-19 pandemic. The new outbreak has novel, previously undiscovered mutations and variants. Currently, the US Food and Drug Administration (FDA) approved poxvirus treatment involving the use of tecovirimat. However, there has otherwise been limited research interest in monkeypox. Mitoxantrone (MXN), an anthracycline derivative, an FDA-approved therapeutic for treating cancer and multiple sclerosis, was previously reported to exhibit antiviral activity against the vaccinia virus and monkeypox virus. In this study, virtual screening, molecular docking analysis, and pharmacophore ligand-based modelling were employed on anthracene structures (1-13) closely related to MXN to explore the potential repurposing of multiple compounds from the PubChem library. Four chemical structures (2), (7), (10) and (12) show a predicted high binding potential to suppress viral replication.

Receptor-Based Pharmacophore Modeling in the Search for Natural Products for COVID-19 Mpro.

Considering the urgency of the COVID-19 pandemic, we developed a receptor-based pharmacophore model for identifying FDA-approved drugs and hits from natural products. The COVID-19 main protease (Mpro) was selected for the development of the pharmacophore model. The model consisted of a hydrogen bond acceptor, donor, and hydrophobic features. These features demonstrated good corroboration with a previously reported model that was used to validate the present model, showing an RMSD value of 0.32. The virtual screening was carried out using the ZINC database. A set of 208,000 hits was extracted and filtered using the ligand pharmacophore mapping, applying the lead-like properties. Lipinski's filter and the fit value filter were used to minimize hits to the top 2000. Simultaneous docking was carried out for 200 hits for natural drugs belonging to the FDA-approved drug database. The top 28 hits from these experiments, with promising predicted pharmacodynamic and pharmacokinetic properties, are reported here. To optimize these hits as Mpro inhibitors and potential treatment options for COVID-19, bench work investigations are needed.