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.

Computational basis of SARS-CoV 2 main protease inhibition: an insight from molecular dynamics simulation based findings.

The coronavirus disease 2019 (COVID-19) pandemic is caused by newly discovered severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). One of the striking targets amongst all the proteins in coronavirus is the main protease (Mpro), as it plays vital biological roles in replication and maturation of the virus, and hence the potential target. The aim of this study is to repurpose the Food and Drug Administration (FDA) approved molecules via computer-aided drug designing against Mpro (PDB ID: 6Y2F) of SARS CoV-2 due to its high x-ray resolution of 1.95 Å as compared to other published Mprostructures. High Through Virtual Screening (HTVS) of 2456 FDA approved drugs using structure-based docking were analyzed. Molecular Dynamics simulations were performed to check the overall structural stability (RMSD), Cα fluctuations (RMSF) and protein-ligand interactions. Further, trajectory analysis was performed to assess the binding quality by exploiting the protein-residue motion cross correlation (DCCM) and binding free energy (MM/GBSA). Tenofovir, an antiretroviral for HIV-proteases and Terlipressin, a vasoconstrictor show stable RMSD, RMSF, better MM/GBSA with good cross correlation as compared to the Apo and O6K. Moreover, the results show concurrence with Nelfinavir, Lopinavir and Ritonavir which have shown significant inhibition in in vitro studies. Therefore, we conclude that Tenofovir and Terlipresssin might also show protease inhibition but are still open to clinical validation in case of SARS-CoV 2 treatment.Communicated by Ramaswamy H. Sarma.

Exploiting the co-crystal ligands shape, features and structure-based approaches for identification of SARS-CoV-2 Mpro inhibitors.

SARS-CoV-2 enters the host cell through the ACE2 receptor and replicates its genome using an RNA-Dependent RNA Polymerase (RDRP). The functional RDRP is released from pro-protein pp1ab by the proteolytic activity of Main protease (Mpro) which is encoded within the viral genome. Due to its vital role in proteolysis of viral polyprotein chains, it has become an attractive potential drug target. We employed a hierarchical virtual screening approach to identify small synthetic protease inhibitors. Statistically optimized molecular shape and color-based features (various functional groups) from co-crystal ligands were used to screen different databases through various scoring schemes. Then, the electrostatic complementarity of screened compounds was matched with the most active molecule to further reduce the hit molecules' size. Finally, five hundred eighty-seven molecules were docked in Mpro catalytic binding site, out of which 29 common best hits were selected based on Glide and FRED scores. Five best-fitting compounds in complex with Mpro were subjected to MD simulations to analyze their structural stability and binding affinities with Mpro using MM/GB(PB)SA models. Modeling results suggest that identified hits can act as the lead compounds for designing better active Mpro inhibitors to enhance the chemical space to combat COVID-19.Communicated by Ramaswamy H. Sarma.

Pharmacophore model-aided virtual screening combined with comparative molecular docking and molecular dynamics for identification of marine natural products as SARS-CoV-2 papain-like protease inhibitors.

Targeting SARS-CoV-2 papain-like protease using inhibitors is a suitable approach for inhibition of virus replication and dysregulation of host anti-viral immunity. Engaging all five binding sites far from the catalytic site of PLpro is essential for developing a potent inhibitor. We developed and validated a structure-based pharmacophore model with 9 features of a potent PLpro inhibitor. The pharmacophore model-aided virtual screening of the comprehensive marine natural product database predicted 66 initial hits. This hit library was downsized by filtration through a molecular weight filter of ≤ 500 g/mol. The 50 resultant hits were screened by comparative molecular docking using AutoDock and AutoDock Vina. Comparative molecular docking enables benchmarking docking and relieves the disparities in the search and scoring functions of docking engines. Both docking engines retrieved 3 same compounds at different positions in the top 1 % rank, hence consensus scoring was applied, through which CMNPD28766, aspergillipeptide F emerged as the best PLpro inhibitor. Aspergillipeptide F topped the 50-hit library with a pharmacophore-fit score of 75.916. Favorable binding interactions were predicted between aspergillipeptide F and PLpro similar to the native ligand XR8-24. Aspergillipeptide F was able to engage all the 5 binding sites including the newly discovered BL2 groove, site V. Molecular dynamics for quantification of Cα-atom movements of PLpro after ligand binding indicated that it exhibits highly correlated domain movements contributing to the low free energy of binding and a stable conformation. Thus, aspergillipeptide F is a promising candidate for pharmaceutical and clinical development as a potent SARS-CoV-2 PLpro inhibitor.

Nature's therapy for COVID-19: Targeting the vital non-structural proteins (NSP) from SARS-CoV-2 with phytochemicals from Indian medicinal plants.

Background: Containing COVID-19 is still a global challenge. It has affected the "normal" world by targeting its economy and health sector. The effect is shifting of focus of research from life threatening diseases like cancer. Thus, we need to develop a medical solution at the earliest. The purpose of this present work was to understand the efficacy of 22 rationally screened phytochemicals from Indian medicinal plants obtained from our previous work, following drug-likeness properties, against 6 non-structural-proteins (NSP) from SARS-CoV-2. Methods: 100 ns molecular dynamics simulations were performed, and relative binding free energies were computed by MM/PBSA. Further, principal component analysis, dynamic cross correlation and hydrogen bond occupancy were analyzed to characterize protein-ligand interactions. Biological pathway enrichment analysis was also carried out to elucidate the therapeutic targets of the phytochemicals in comparison to SARS-CoV-2. Results: The potential binding modes and favourable molecular interaction profile of 9 phytochemicals, majorly from Withania somnifera with lowest free binding energies, against the SARS-CoV-2 NSP targets were identified. It was understood that phytochemicals and 2 repurposed drugs with steroidal moieties in their chemical structures formed stable interactions with the NSPs. Additionally, human target pathway analysis for SARS-CoV-2 and phytochemicals showed that cytokine mediated pathway and phosphorylation pathways were with the most significant p-value. Conclusions: To summarize this work, we suggest a global approach of targeting multiple proteins of SARS-CoV-2 with phytochemicals as a natural alternative therapy for COVID-19. We also suggest that these phytochemicals need to be tested experimentally to confirm their efficacy.

The SARS-Cov-2 Proliferation Blocked by a Novel and Potent Main Protease Inhibitor via Computer-aided Drug Design.

The recent prevalence of novel "coronavirus disease 2019" has expanded quickly globally, causing a universal pandemic. Herein, an effort was constructed to design a potent drug to inhibit the main protease of SARS-Cov-2 (3CLp) by means of structure-based drug design. A large library of the compounds was used for virtual screening. After molecular docking and ADME studies, we selected a compound with a better binding affinity to the 3CLp active site and acceptable ADME properties compared to the selected positive control drug. Molecular dynamic (MD) simulation (200 ns) and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) were used for further analysis. MD simulation outcomes have proved that the 3CLp-ZINC31157475 complex possesses a considerable value of dynamic properties such as flexibility, stability, compactness, and binding energy. Our MM-PBSA computation illustrates that ZINC31157475 is more potent (-88.03 kcal mol-1) than nelfinavir (-19.54 kcal mol-1) against COVID-19 3CLp. Further, we have determined that the main residues of the 3CLp interact with ligands from per-residue binding energy. In conclusion, we suggest that ZINC31157475 can potentially treat COVID-19 by inhibition of the 3CLp. However, in-vitro and in-vivo study is essential for approval of this suggestion.

Structural and conformational analysis of SARS CoV 2 N-CTD revealing monomeric and dimeric active sites during the RNA-binding and stabilization: Insights towards potential inhibitors for N-CTD.

The advent of SARS-CoV-2 has become a universal health issue with no appropriate cure available to date. The coronavirus nucleocapsid (N) protein combines viral genomic RNA into a ribonucleoprotein and protects the viral genome from the host's nucleases. Structurally, the N protein comprises two independent domains: the N-terminal domain (NTD) for RNA-binding and C-terminal domain (CTD) involved in RNA-binding, protein dimerization, and nucleocapsid stabilization. The present study explains the structural aspects associated with the involvement of nucleocapsid C-terminal domain in the subunit assembly that helps the RNA binding and further stabilizing the virus assembly by protecting RNA from the hosts exonucleases degradation. The molecular dynamics (MD) simulations of the N-CTD and RNA complex suggests two active sites (site I: a monomer) and (site II: a dimer) with structural stability (RMSD: ~2 Å), Cα fluctuations (RMSF: ~3 Å) and strong protein-ligand interactions were estimated through the SiteMap module of Schrodinger. Virtual screening of 2456 FDA-approved drugs using structure-based docking identified top two leads distinctively against Site-I (monomer): Ceftaroline fosamil (MM-GBSA = -47.12 kcal/mol) and Cefoperazone (-45.84 kcal/mol); and against Site-II (dimer): Boceprevir, (an antiviral protease inhibitor, -106.78 kcal/mol) and Ceftaroline fosamil (-99.55 kcal/mol). The DCCM and PCA of drugs Ceftaroline fosamil (PC1+PC2 = 71.9%) and Boceprevir (PC1 +PC2 = 61.6%) show significant correlated residue motions which suggests highly induced conformational changes in the N-CTD dimer. Therefore, we propose N-CTD as a druggable target with two active binding sites (monomer and dimer) involved in specific RNA binding and stability. The RNA binding site with Ceftaroline fosamil binding can prevent viral assembly and can act as an antiviral for coronavirus.

Structural insights into the mechanism of RNA recognition by the N-terminal RNA-binding domain of the SARS-CoV-2 nucleocapsid phosphoprotein.

The emergence of recent SARS-CoV-2 has become a global health issue. This single-stranded positive-sense RNA virus is continuously spreading with increasing morbidities and mortalities. The proteome of this virus contains four structural and sixteen nonstructural proteins that ensure the replication of the virus in the host cell. However, the role of phosphoprotein (N) in RNA recognition, replicating, transcribing the viral genome, and modulating the host immune response is indispensable. Recently, the NMR structure of the N-terminal domain of the Nucleocapsid Phosphoprotein has been reported, but its precise structural mechanism of how the ssRNA interacts with it is not reported yet. Therefore, here, we have used an integrated computational pipeline to identify the key residues, which play an essential role in RNA recognition. We generated multiple variants by using an alanine scanning strategy and performed an extensive simulation for each system to signify the role of each interfacial residue. Our analyses suggest that residues T57A, H59A, S105A, R107A, F171A, and Y172A significantly affected the dynamics and binding of RNA. Furthermore, per-residue energy decomposition analysis suggests that residues T57, H59, S105 and R107 are the key hotspots for drug discovery. Thus, these residues may be useful as potential pharmacophores in drug designing.