Computational repurposing approach for targeting the critical spike mutations in B.1.617.2 (delta), AY.1 (delta plus) and C.37 (lambda) SARS-CoV-2 variants using exhaustive structure-based virtual screening, molecular dynamic simulations and MM-PBSA methods.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the contagious coronavirus disease 2019 (COVID-19) which was first identified in Wuhan, China, in December 2019. Around the world, many researchers focused their research on identifying inhibitors against the druggable SARS-CoV-2 targets. The reported genomic mutations have a direct effect on the receptor-binding domain (RBD), which interacts with host angiotensin-converting enzyme 2 (ACE-2) for viral cell entry. These mutations, some of which are variants of concern (VOC), lead to increased morbidity and mortality rates. The newest variants including B.1.617.2 (Delta), AY.1 (Delta plus), and C.37 (Lambda) were considered in this study. Thus, an exhaustive structure-based virtual screening of a ligand library (in which FDA approved drugs are also present) using the drug-likeness screening, molecular docking, ADMET profiling was performed followed by molecular dynamics (MD) simulation, and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculation to identify compounds or drugs can be repurposed for inhibiting the wild type, Delta, Delta plus and Lambda variants of RBD of the spike protein. Based on the virtual screening steps, two FDA approved drugs, Atovaquone (atv) and Praziquantel (prz), were selected and repurposed as the best candidates of SARS-CoV-2 RBD inhibitors. Molecular docking results display that both atv and prz contribute in different interaction with binding site residues (Gln493, Asn501 and Gly502 in the hydrogen bond formation, Phe490 and Tyr505 in the π- π stacking and Tyr449, Ser494, and Phe497 in the vdW interactions) in the wild type, Delta, Delta plus and Lambda variants of RBD of the spike protein. MD simulations revealed that among the eight studied complexes, the wild type-atv and Delta-prz complexes have the most structural stability over the simulation time. Furthermore, MM-PBSA calculation showed that in the atv containing complexes, highest binding affinity is related to the wild type-atv complex and in the prz containing complexes, it is related to the Delta-prz complex. The validation of docking results was done by comparing with experimental data (heparin in complex with wild type and Delta variants). Also, comparison of the obtained results with the result of simulation of the k22 with the studied proteins showed that atv and prz are suitable inhibitors for these proteins, especially wild type t and Delta variant, respectively. Thus, we found that atv and prz are the best candidate for inhibition of wild type and Delta variant of the spike protein. Also, atv can be an appropriate inhibitor for the Lambda variant. Obtained in silico results may help the development of new anti-COVID-19 drugs.

Computational prediction of potential inhibitors for SARS-COV-2 main protease based on machine learning, docking, MM-PBSA calculations, and metadynamics.

The development of new drugs is a very complex and time-consuming process, and for this reason, researchers have been resorting heavily to drug repurposing techniques as an alternative for the treatment of various diseases. This approach is especially interesting when it comes to emerging diseases with high rates of infection, because the lack of a quickly cure brings many human losses until the mitigation of the epidemic, as is the case of COVID-19. In this work, we combine an in-house developed machine learning strategy with docking, MM-PBSA calculations, and metadynamics to detect potential inhibitors for SARS-COV-2 main protease among FDA approved compounds. To assess the ability of our machine learning strategy to retrieve potential compounds we calculated the Enrichment Factor of compound datasets for three well known protein targets: HIV-1 reverse transcriptase (PDB 4B3P), 5-HT2A serotonin receptor (PDB 6A94), and H1 histamine receptor (PDB 3RZE). The Enrichment Factor for each target was, respectively, 102.5, 12.4, 10.6, which are considered significant values. Regarding the identification of molecules that can potentially inhibit the main protease of SARS-COV-2, compounds output by the machine learning step went through a docking experiment against SARS-COV-2 Mpro. The best scored poses were the input for MM-PBSA calculations and metadynamics using CHARMM and AMBER force fields to predict the binding energy for each complex. Our work points out six molecules, highlighting the strong interaction obtained for Mpro-mirabegron complex. Among these six, to the best of our knowledge, ambenonium has not yet been described in the literature as a candidate inhibitor for the SARS-COV-2 main protease in its active pocket.

A proteomics-MM/PBSA dual approach for the analysis of SARS-CoV-2 main protease substrate peptide specificity.

The main protease Mpro of SARS-CoV-2 is a well-studied major drug target. Additionally, it has been linked to this virus' pathogenicity, possibly through off-target effects. It is also an interesting diagnostic target. To obtain more data on possible substrates as well as to assess the enzyme's primary specificity a two-step approach was introduced. First, Terminal Amine Isobaric Labeling of Substrates (TAILS) was employed to identify novel Mpro cleavage sites in a mouse lung proteome library. In a second step, using a structural homology model, the MM/PBSA variant MM/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized Born Surface Area) free binding energy calculations were carried out to determine relevant interacting amino acids. As a result, 58 unique cleavage sites were detected, including six that displayed glutamine at the P1 position. Furthermore, modeling results indicated that Mpro has a far higher potential promiscuity towards substrates than expected. The combination of proteomics and MM/PBSA modeling analysis can thus be useful for elucidating the specificity of Mpro, and thus open novel perspectives for the development of future peptidomimetic drugs against COVID-19, as well as diagnostic tools.

Identification of Natural Inhibitors Against SARS-CoV-2 Drugable Targets Using Molecular Docking, Molecular Dynamics Simulation, and MM-PBSA Approach.

The present study explores the SARS-CoV-2 drugable target inhibition efficacy of phytochemicals from Indian medicinal plants using molecular docking, molecular dynamics (MD) simulation, and MM-PBSA analysis. A total of 130 phytochemicals were screened against SARS-CoV-2 Spike (S)-protein, RNA-dependent RNA polymerase (RdRp), and Main protease (Mpro). Result of molecular docking showed that Isoquercetin potentially binds with the active site/protein binding site of the Spike, RdRP, and Mpro targets with a docking score of -8.22, -6.86, and -9.73 kcal/mole, respectively. Further, MS 3, 7-Hydroxyaloin B, 10-Hydroxyaloin A, showed -9.57, -7.07, -8.57 kcal/mole docking score against Spike, RdRP, and Mpro targets respectively. The MD simulation was performed to study the favorable confirmation and energetically stable complex formation ability of Isoquercetin and 10-Hydroxyaloin A phytochemicals in Mpro-unbound/ligand bound/standard inhibitor bound system. The parameters such as RMSD, RMSF, Rg, SASA, Hydrogen-bond formation, energy landscape, principal component analysis showed that the lead phytochemicals form stable and energetically stabilized complex with the target protein. Further, MM-PBSA analysis was performed to compare the Gibbs free energy of the Mpro-ligand bound and standard inhibitor bound complexes. The analysis revealed that the His-41, Cys145, Met49, and Leu27 amino acid residues were majorly responsible for the lower free energy of the complex. Drug likeness and physiochemical properties of the test compounds showed satisfactory results. Taken together, the study concludes that that the Isoquercetin and 10-Hydroxyaloin A phytochemical possess significant efficacy to bind SARS-Cov-2 Mpro active site. The study necessitates further in vitro and in vivo experimental validation of these lead phytochemicals to assess their anti-SARS-CoV-2 potential.

Multifunctional inhibitors of SARS-CoV-2 by MM/PBSA, essential dynamics, and molecular dynamic investigations.

The ongoing COVID-19 pandemic demands a novel approach to combat and identify potential therapeutic targets. The SARS-CoV-2 infection causes a hyperimmune response followed by a spectrum of diseases. Limonoids are a class of triterpenoids known to prevent the release of IL-6, IL-15, IL-1α, IL-1ß via TNF and are also known to modulate PI3K/Akt/GSK-3ß, JNK1/2, MAPKp38, ERK1/2, and PI3K/Akt/mTOR signaling pathways and could help to avoid viral infection, persistence, and pathogenesis. The present study employs a computational approach of virtual screening and molecular dynamic (MD) simulations of such compounds against RNA-dependent RNA polymerase (RdRp), Main protease (Mpro), and Papain-like protease (PLpro) of SARS-CoV-2. MD simulation, Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA), and Essential dynamics revealed that the macromolecule-ligand complexes are stable with very low free energy of binding. Such compounds that could modulate both host responses and inhibit viral machinery could be beneficial in effectively controlling the global pandemic.

Molecular docking, simulation and MM-PBSA studies of nigella sativa compounds: a computational quest to identify potential natural antiviral for COVID-19 treatment.

Nigella sativa or black seed is used as a medicinal plant around the globe. Oil and seeds have a long tradition of folklore use in various medicinal and food systems. The conventional therapeutic use of Nigella sativa, in different ways, has been reported in several studies to treat different diseases including influenza, headache, hypertension, diabetes, inflammation, eczema, fever, cough, asthma, bronchitis, and fever. Based on previously reported potential therapeutic uses of N. sativa compounds, and keeping in mind the dire need of time for the development of potent antiviral, a combined docking, ADMET properties calculation, molecular dynamics, and MM-PBSA approaches were applied in the current study to check the therapeutic potentials of N. sativa chief constituents against COVID-19. Among the studied compounds, we found that dithymoquinone (DTQ), with binding affinity of -8.6 kcal/mol compared to a positive control (chloroquine, -7.2 kcal/mol) , has the high potential of binding at SARS-CoV-2:ACE2 interface and thus could be predicted as a plausible inhibitor to disrupt viral-host interactions. Molecular dynamics simulation of 100 ns well complemented binding affinity of the compound and revealed strong stability of DTQ at the docked site. Additionally, MM-PBSA also affirms the docking results. Compound DTQ of the present study, if validated in wet lab experiments, could be used to treat COVID-19 and could serve as a lead in the future for development of more effective natural antivirals against COVID-19. Communicated by Ramaswamy H. Sarma.

Isatin-based virtual high throughput screening, molecular docking, DFT, QM/MM, MD and MM-PBSA study of novel inhibitors of SARS-CoV-2 main protease.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a rapidly growing health care emergency across the world. One of the viral proteases called main protease or Mpro, plays a crucial role in the replication of SARS-CoV-2. As the structure of Mpro of SARS-CoV-2 is similar to the Mpro of SARS-CoV-1 (responsible for SARS outbreak between 2002 and 2004), we hypothesize that the inhibitors of SARS-CoV-1 Mpro can also inhibit the Mpro of SARS-CoV-2. To test this hypothesis, a total of 79 isatin derivatives, which inhibited Mpro activity under in vitro conditions, were selected from the literature, and then screened through AutoDock Vina. The chemical features of the top 5 isatin derivatives with low binding energies (-8.5 to -8.2 kcal/mol) were used to screen similar types of compounds from several small-molecule libraries containing 15856508 compounds. A total of 1,609 compounds with similarity score ≥ 6 were screened and then subjected to docking as well as ADME analysis. Among the compounds screened, 4 ligands form Zinc drug-like library (ZINC000008848565, ZINC000009513563, ZINC000036759789 and ZINC000046053855) showed good ADMET properties, low binding energy (-8.4 to -8.6 kcal/mol), low interaction energy (-72.62 to -50.01 kcal/mol) and high structural stability with Mpro. Hence, the selected ligands might serve as the lead candidates for further wet laboratory validation, optimization and development.Communicated by Ramaswamy H. Sarma.

Binding and inhibitory effect of ravidasvir on 3CLpro of SARS-CoV-2: a molecular docking, molecular dynamics and MM/PBSA approach.

Drug repurposing requires a limited resource, cost-effective and faster method to combat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, this in silico studies attempts to identify the drug-likeness properties of ravidasvir, an II/III phase clinical trial chronic hepatitis C drug against 3-Chymotrypsin-like protease (3CLpro) of SARS-CoV-2 to combat the ongoing coronavirus disease 2019 (COVID-19) pandemic. This protease is predominantly involved in virus replication cycle; hence it is considered as a potent drug target. The molecular docking results showed that ravidasvir was found to be potent inhibitors of 3CLpro with scoring function based binding energy is -26.7 kJ/mol. Further dynamic behaviour of apo form and complex form of ravidasvir with 3CLpro were studied using molecular dynamics (MD) simulations over 500 ns each, total 2 µs time scale. The motion of the protein was studied using principal component analysis of the MD simulation trajectories. The binding free energy calculated using MM/PBSA method from the MD simulation trajectory was -190.3 ± 70.2 kJ/mol and -106.0 ± 26.7 kJ/mol for GROMOS96 54A7 and AMBER99SB-ILDN force field, respectively. This in silico studies suggesting ravidasvir might be a potential lead molecule against SARS-CoV-2 for further optimization and drug development to combat the life-threatening COVID-19 pandemic.Communicated by Ramaswamy H. Sarma.

Investigation of the inhibitory activity of some dietary bioactive flavonoids against SARS-CoV-2 using molecular dynamics simulations and MM-PBSA calculations.

Eventhough the development of vaccine against COVID-19 pandemic is progressing in different part of the world a well-defined treatment plan is not yet developed. Therefore, we investigate the inhibitory activity of a group of dietary bioactive flavonoids against SARS-CoV-2 main protease (Mpro), which are identified as one of the potential targets in the drug discovery process of COVID-19. After the initial virtual screening of a number of bioactive flavonoids, the binding affinity of three compounds - Naringin, Naringenin and Amentoflavone - at the active site of Mpro was investigated through MD Simulations, MM-PBSA and DFT Binding Energy calculations. From the MD trajectory analysis, Amentoflavone and Naringin showed consistent protein-ligand interactions with the aminoacid residues of the active site domains of Mpro. The excellent inhibitory activity of Amentoflavone and Naringin was established from its MM-PBSA binding energy values of -190.50 and -129.87 kJ/mol respectively. The MET165 residue of Mpro is identified as one of the key residue which contributed significantly to MM-PBSA binding energy through hydrophobic interactions. Furthermore, the DFT binding energy values of Amentoflavone (-182.92 kJ/mol) and Naringin (-160.67 kJ/mol) in active site molecular clusters with hydrogen bonds confirmed their potential inhibitory activity. These compounds are of high interest because of their wide availability, low cost, no side effects, and long history of use. We can prevent the severity of this disease for home care patients using these effective dietary supplements. We are hopeful that our results have implications for the development of prophylaxis of COVID-19.Communicated by Ramaswamy H. Sarma.

Combination of QSAR, molecular docking, molecular dynamic simulation and MM-PBSA: analogues of lopinavir and favipiravir as potential drug candidates against COVID-19.

Pandemic COVID-19 infections have spread throughout the world. There is no effective treatment against this disease. Viral RNA-dependent RNA polymerase (RdRp) catalyzes the replication of RNA from RNA and the main protease (Mpro) has a role in the processing of polyproteins that are translated from the RNA of SARS-CoV-2, and thus these two enzymes are strong candidates for targeting by anti-viral drugs. Small molecules such as lopinavir and favipiravir significantly inhibit the activity of Mpro and RdRp in vitro. Studies have shown that structurally modified lopinavir, favipiravir, and other similar compounds can inhibit COVID-19 main protease (Mpro) and RNA-dependent RNA polymerase (RdRp). In this study, lopinavir and its structurally similar compounds were chosen to bind the main protease, and favipiravir was chosen to target RNA-dependent RNA polymerase. Molecular docking and the quantitative structure-activity relationships (QSAR) study revealed that the selected candidates have favorable binding affinity but less druggable properties. To improve the druggability, four structural analogues of lopinavir and one structural analogue of favipiravir was designed by structural modification. Molecular interaction analyses have displayed that lopinavir and favipiravir analogues interact with the active site residues of Mpro and RdRp, respectively. Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, medicinal chemistry profile, and physicochemical features were shown that all structurally modified analogues are less toxic and contain high druggable properties than the selected candidates. Subsequently, 50 ns molecular dynamics simulation of the top four docked complexes demonstrated that CID44271905, a lopinavir analogue, forms the most stable complex with the Mpro. Further MMPBSA analyses using the MD trajectories also confirmed the higher binding affinity of CID44271905 towards Mpro. In summary, this study demonstrates a new way to identify leads for novel anti-viral drugs against COVID-19. Communicated by Ramaswamy H. Sarma.

Identification of natural inhibitors against prime targets of SARS-CoV-2 using molecular docking, molecular dynamics simulation and MM-PBSA approaches.

The recently emerged COVID-19 has been declared a pandemic by the World Health Organization as to date; no therapeutic drug/vaccine is available for the treatment. Due to the lack of time and the urgency to contain the pandemic, computational screening appears to be the best tool to find a therapeutic solution. Accumulated evidence suggests that many phyto-compounds possess anti-viral activity. Therefore, we identified possible phyto-compounds that could be developed and used for COVID-19 treatment. In particular, molecular docking was used to prioritize the possible active phyto-compounds against two key targets namely RNA dependent RNA polymerase (RdRp) and main protease (Mpro) of SARS-CoV-2. In this study, an antiviral drug- Remdesivir (RdRp inhibitor) and Darunavir (Mpro inhibitor) are used as reference drugs. This study revealed that phyto-molecules- Mulberroside-A/C/E/F, Emblicanin A, Nimbolide, and Punigluconin showed high binding affinity against RdRp while Andrographolides, Mulberrosides, Anolignans, Chebulic acid, Mimusopic acid, and Punigluconin showed better binding affinity against Mpro as compared with the reference drug. Furthermore, ADME profiles validated the drug-likeness properties of prioritized phyto-compounds. Besides, to assess the stability, MD simulations studies were performed along with reference inhibitors for Mpro (Darunavir) and RdRp (Remdesivir). Binding free energy calculations (MM-PBSA) revealed the estimated value (ΔG) of Mpro_Darunavir; Mpro_Mulberroside E; RdRp_Remdesivir and RdRp_Emblicanin A were -111.62 ± 6.788, -141.443 ± 9.313, 30.782 ± 5.85 and -89.424 ± 3.130 kJmol-1, respectively. Taken together, the study revealed the potential of these phyto-compounds as inhibitors of RdRp and Mpro inhibitor that could be further validated against SARS-CoV-2 for clinical benefits.Communicated by Ramaswamy H. Sarma.

Identification of natural inhibitors against Mpro of SARS-CoV-2 by molecular docking, molecular dynamics simulation, and MM/PBSA methods.

The recent outbreak of SARS-CoV-2 disease, also known as COVID-19, has emerged as a pandemic. The unavailability of specific therapeutic drugs and vaccines urgently demands sincere efforts for drug discovery against COVID-19. The main protease (Mpro) of SARS-CoV-2 is a critical drug target as it plays an essential role in virus replication. Therefore for the identification of potential inhibitors of SARS-CoV-2 Mpro, we applied a structure-based virtual screening approach followed by molecular dynamics (MD) study. A library of 686 phytochemicals was subjected to virtual screening which resulted in 28 phytochemicals based on binding energy. These phytochemicals were further subjected to drug-likeness and toxicity analysis, which resulted in seven drug-like hits. Out of seven, five phytochemicals viz., Mpro-Dehydrtectol (-10.3 kcal/mol), Epsilon-viniferin (-8.6 kcal/mol), Peimisine (-8.6 kcal/mol), Gmelanone (-8.4 kcal/mol), and Isocolumbin (-8.4 kcal/mol) were non-toxic. Consequently, these phytochemicals are subjected to MD, post MD analysis, and MM/PBSA calculations. The results of 100 ns MD simulation, RMSF, SASA, Rg, and MM/PBSA show that Epsilon-viniferin (-29.240 kJ/mol), Mpro-Peimisine (-43.031 kJ/mol) and Gmelanone (-13.093 kJ/mol) form a stable complex with Mpro and could be used as potential inhibitors of SARS-CoV-2 Mpro. However, further investigation of these inhibitors against Mpro receptor of COVID-19 is needed to validate their candidacy for clinical trials. Communicated by Ramaswamy H. Sarma.

Tackling COVID-19: identification of potential main protease inhibitors via structural analysis, virtual screening, molecular docking and MM-PBSA calculations.

The widespread of the COVID-19 disease, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), had severely affected the entire world. Unfortunately, no successful vaccines or antiviral drugs are currently available which leaves the scientific community under huge pressure to tackle this pandemic. Among the identified promising druggable targets, specific to this virus, is the main protease (Mpro) enzyme, which is vital for viral replication, transcription and packaging within the host cells. In this study, selective inhibition of the Mpro was sought via thorough analysis of its available structural data in the Protein Data Bank. To this end, COVID-19 Mpro crystal complexes were explored and the key interacting residues (KIRs) within its active site, that are expected to be vital for effective ligand binding, were identified. Based on these KIRs, 3D pharmacophore models were generated and used in virtual screening of different databases. Retrieved hits were docked into the active site of the enzyme and their MM-PBSA based free binding energies were calculated. Finally, ADMET descriptors were calculated to aid the selection of top scoring hits with best ADMET properties. Nine compounds with different chemotypes were identified as potential Mpro inhibitors. Further, MD simulations of a virtual complex of Mpro with one of the promising hits revealed stable binding which is indicative of good inhibitory potential. The identified compounds in this study are expected to support the global drug discovery efforts in fighting against this highly contagious virus by narrowing the searchable chemical space for potential effective therapeutics.

Potential inhibitors of SARS-cov-2 RNA dependent RNA polymerase protein: molecular docking, molecular dynamics simulations and MM-PBSA analyses.

The SARS-cov-2 RNA dependent RNA polymerase (nsp12) is a crucial viral enzyme that catalyzes the replication of RNA from RNA templates. The fixation of some ligands in the active site may alter the viral life cycle. The aim of the present study is to identify the conservation level of nsp12 motifs (A-G), using consurf server, and discover their interactions with rifabutin, rifampicin, rifapentin, sorangicin A, streptolydigin, myxopyronin B, VXR and VRX using AutoDockTools-1.5.6, Gromacs 2018.2 and g-mmpbsa. Thus, the most of amino acids residues located in nsp12 protein Motifs (A-G) were predicted as highly conserved. The binding energies of streptolydigin, VXR, rifabutin, rifapentine, VRX, sorangicin A, myxopyronin B and rifampicin with nsp12 protein are -8.11, -8.23, -7.14, -6.94, -6.55, -5.46, -5.33 and -5.26 kcal/mol, respectively. In the other hand, the binding energies of ligand in the same order with nsp7-nsp8-nsp12 complex are -7.23, -7.08, -7.21, -7, -6.59, -8.73, -5.52, -5.87 kcal/mol, respectively. All ligands interact with at least two nsp12 motifs. The molecular dynamics simulation of nsp12-streptolydigin and nsp12-VXR complexes shows that these two complexes are stable and the number of hydrogen bonds as a function of time, after 30 ns of simulation, varies between 0 and 6 for nsp12-streptolydigin complex and between 0 and 4 for nsp12-VXR complex. The average of free binding energies obtained using g_mmpbsa, after 30 ns of simulation, is -191.982 Kj/mol for nsp12-streptolydigin complex and -153.583 Kj/mol for nsp12-VXR complex. Our results suggest that these ligands may be used as inhibitors of SARS-cov-2 nsp12 protein.Communicated by Ramaswamy H. Sarma.