Identification of novel inhibitor against endonuclease subunit of Influenza pH1N1 polymerase: A combined molecular docking, molecular dynamics, MMPBSA, QMMM and ADME studies to combat influenza A viruses

Targeting Metalloenzymes: The "Achilles' Heel" of Viruses and Parasites

Metalloenzymes are central to the regulation of a wide range of essential viral and parasitic functions, including protein degradation, nucleic acid modification, and many others. Given the impact of infectious diseases on human health, inhibiting metalloenzymes offers an attractive approach to disease therapy. Metal-chelating agents have been expansively studied as antivirals and antiparasitics, resulting in important classes of metal-dependent enzyme inhibitors. This review provides the recent advances in targeting the metalloenzymes of viruses and parasites that impose a significant burden on global public health, including influenza A and B, hepatitis B and C, and human immunodeficiency viruses as well as Trypanosoma brucei and Trypanosoma cruzi.

Structural screening into the recognition of a potent inhibitor against non-structural protein 16: a molecular simulation to inhibit SARS-CoV-2 infection

COVID-19 infection is caused by endemic crown infection (SARS-CoV-2) and is associated with lung damage and severe immune response. Non-Structural Proteins are the central components of coronaviral transcription and replication machinery in SARS-CoV-2 and also stimulate mRNA cap methylation to avoid the immune response. Non-Structural Protein 16 (NSP16) is one of the primary targets for the drug discovery of coronaviruses. Discovering an effective inhibitor against the NSP16 in comparison with Sinefungin was the main purpose of this investigation. Binding free-energy calculations, computational methods of molecular dynamics, docking, and virtual screening were utilized in this study. The ZINC and PubChem databases were applied to screen some chemical compounds regarding Sinefungin as a control inhibitor. Based on structural similarity to Sinefungin, 355 structures were obtained from the mentioned databases. Subsequently, this set of compounds were monitored by AutoDock Vina software, and ultimately the potent inhibitor (PUBCHEM512713) was chosen. At the next stage, molecular dynamics were carried out by GROMACS software to evaluate the potential elected compounds in a simulated environment and in a timescale of 100 nanoseconds. MM-PBSA investigation exhibited that the value of binding free energy for PUBCHEM512713 (-30.829 kJ.mol^-1) is more potent than Sinefungin (-11.941 kJ.mol^-1). Furthermore, the results of ADME analysis illustrated that the pharmacokinetics, drug-likeness, and lipophilicity parameters of PUBCHEM512713 are admissible for human utilization. Finally, our data suggested that PUBCHEM512713 is an effective drug candidate for inhibiting the NSP16 and is suitable for in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

Identification of the SARS-CoV-2 surface therapeutic targets and drugs using molecular modeling methods for inhibition the virus entry

Although COVID-19 emerged as a major concern to public health around the world, no licensed medication has been found as of yet to efficiently stop the virus spread and treat the infection. The SARS-CoV-2 entry into the host cell is driven by the direct interaction of the S1 domain with the ACE-2 receptor followed by conformational changes in the S2 domain, as a result of which fusion peptide is inserted into the target cell membrane, and the fusion process is mediated by the specific interactions between the heptad repeats 1 and 2 (HR1 and HR2) that form the six-helical bundle. Since blocking this interaction between HRs stops virus fusion and prevents its subsequent replication, the HRs inhibitors can be used as anti-COVID drugs. The initial drug selection is based on existing molecular databases to screen for molecules that may have a therapeutic effect on coronavirus. Based on these premises, we chose two approved drugs to investigate their interactions with the HRs (based on docking methods). To this end, molecular dynamics simulations and molecular docking were carried out to investigate the changes in the structure of the SARS-CoV-2 spike protein. Our results revealed, cefpiramide has the highest affinity to S protein, thereby revealing its potential to become an anti-COVID-19 clinical medicine. Therefore, this study offers new ways to re-use existing drugs to combat SARS-CoV-2 infection.

Prevention of SARS-CoV-2 Proliferation with a Novel and Potent Main Protease Inhibitor by Docking, ADMET, MM-PBSA, and Molecular Dynamics Simulation

COVID-19 is the last disease caused by SARS-CoV-2 associated with a severe immune response and lung damage. The main protease (Mpro) has a vital role in SARS-CoV-2 proliferation. Moreover, humans lack homologous Mpro, which makes the Mpro a suitable drug target for the development of SARS-CoV-2 drugs. The purchasable L5000 library (Selleckchem Inc) includes 99,040 compounds that were used for virtual screening. After molecular docking and ADME studies, we selected a compound (WAY-604395) with a potent binding affinity to the Mpro active site and acceptable ADME properties compared to the reference drug (nelfinavir). Molecular dynamics (MD) simulation outcomes have proved that the Mpro-WAY604395 complex possesses a considerable value of flexibility, stability, compactness and binding energy. Our Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculation demonstrates that WAY-604395 is more potent ([Formula: see text]272.19[Formula: see text]kcal mol[Formula: see text]) in comparison with nelfinavir ([Formula: see text]173.39[Formula: see text]kcal[Formula: see text]mol[Formula: see text]) against SARS-CoV-2 Mpro. In conclusion, we suggest that WAY-604395 has the potential for the treatment of SARS-CoV-2 by inhibition of the Mpro.

The identification of novel inhibitors of human angiotensin-converting enzyme 2 and main protease of Sars-Cov-2: A combination of in silico methods for treatment of COVID-19

The angiotensin-converting enzyme 2 (ACE2) and main protease (MPro), are the putative drug candidates for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we performed 3D-QSAR pharmacophore modeling and screened 1,264,479 ligands gathered from Pubchem and Zinc databases. Following the calculation of the ADMET properties, molecular docking was carried out. Moreover, the de novo ligand design was performed. MD simulation was then applied to survey the behavior of the ligand-protein complexes. Furthermore, MMPBSA has utilized to re-estimate the binding affinities. Then, a free energy landscape was used to find the most stable conformation of the complexes. Finally, the hybrid QM-MM method was carried out for the precise calculation of the energies.

The Hypo1 pharmacophore model was selected as the best model. Our docking results indicate that the compounds ZINC12562757 and 112,260,215 were the best potential inhibitors of the ACE2 and MPro, respectively. Furthermore, the Evo_1 compound enjoys the highest docking energy among the designed de novo ligands. Results of RMSD, RMSF, H-bond, and DSSP analyses have demonstrated that the lead compounds preserve the stability of the complexes’ conformation during the MD simulation. MMPBSA data confirmed the molecular docking results. The results of QM-MM showed that Evo_1 has a stronger potential for specific inhibition of MPro, as compared to the 112,260,215 compound.

A model for phthalic acid esters' biodegradability and biotoxicity multi-effect pharmacophore and its application in molecular modification

The objective of this study was to investigate 13 phthalic acid esters (PAEs) with medium or long straight-alkyl-chain, branching or unsaturated side chains, because their structural characteristics make them difficult to biodegrade or highly toxic. A biodegradability and biotoxicity multi-effect pharmacophore model was built using comprehensive evaluation method. The results suggested that introducing hydrophobic groups to the side chains of the PAEs could improve the molecules' biodegradability and biotoxicity effects simultaneously. Thus, 40 target PAE (HEHP, DNOP, DUP) derivatives were designed. Two environmentally friendly PAE derivatives (HEHP-Anthryl and HEHP-Naphthyl) were screened via the test of environmental friendliness and functionality. In addition, the biodegradation and biotoxicity of derivatives were found to have improved as a result of the change in van der Waals forces between molecules and their corresponding proteins. Moreover, the environmental safety of the screened PAE derivatives was confirmed by predicting the toxicity of their intermediates and calculating the energy barrier values for biodegradation and metabolic pathways. This study could provide theoretical guidance for the practical development of environmentally friendly plasticizer.

Effective prediction model and determination of binding residues influential for inhibitors targeting HIV-1 integrase-LEDGF/p75 interface by employing solvent accessible surface area energy as key determinant

Development of a highly accurate prediction model for protein-ligand inhibition has been a major challenge in drug discovery. Herein, we describe a novel predictive model for the inhibition of HIV-1 integrase (IN)-LEDGF/p75 protein-protein interaction. The model was constructed using energy parameters approximated from molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. Chemometric analysis using partial least squares (PLS) regression revealed that solvent accessible surface area energy (ΔG_SASA) is the major determinant parameter contributing greatly to the prediction accuracy. PLS prediction model on the ΔG_SASA values collected from 41 complexes yielded a strong correlation between the predicted and the actual inhibitory activities (R² = 0.9666, RMSEC of pIC₅₀ values = 0.0890). Additionally, for the test set of 14 complexes, the model performed satisfactorily with very low pIC₅₀ errors (Q² = 0.5168, RMSEP = 0.3325). A strong correlation between the buried surface areas on the IN protein, when bound with IN-LEDGF/p75 inhibitors, and the respective ΔG_SASA values was also obtained. Furthermore, the current method could identify 'hot spots'of amino acid residues highly influential to the inhibitory activity prediction. This could present fruitful implications in binding site determination and future inhibitor developments targeting protein-protein interactions.Communicated by Ramaswamy H. Sarma.