Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase

Dynamics and binding affinity of nucleoside and non-nucleoside inhibitors with RdRp of SARS-CoV-2: a molecular screening, docking, and molecular dynamics simulation study

In this COVID-19 pandemic situation, an appropriate drug is urgent to fight against this infectious disease to save lives and prevent mortality. Repurposed drugs and vaccines are the immediate solutions for this medical emergency until discover a new drug to treat this disease. As of now, no specific drug is available to cure this disease completely. Several drug targets were identified in SARS-CoV-2, in which RdRp protein is one of the potential targets to inhibit this virus infection. In-Silico studies plays a vital role to understand the binding nature of the drugs at the atomic level against the disease targets. The present study explores the binding mechanism of reported 53 nucleoside and non-nucleoside RdRp inhibitors and Ivermectin which are in clinical trials. These molecules were screened by molecular docking simulation; in which, the molecules are showing high binding affinity and forming interactions with the key amino acids of active site of RdRp protein are chosen for molecular dynamics simulation (MD) and binding free energy analysis. The results of molecular docking and MD simulation studies reveal that IDX184 is a stable molecule and forms strong interactions with the key amino acids and shows high binding affinity towards RdRp. Hence, IDX184 may also be considered as a potential inhibitor of RdRp after clinical study.Communicated by Ramaswamy H. Sarma.

Molecular docking, molecular dynamics simulation and MM-GBSA studies of the activity of glycyrrhizin relevant substructures on SARS-CoV-2 RNA-dependent-RNA polymerase

SARS-CoV-2 is the causative agent of Coronavirus Disease (COVID-19), which is a life-threatening disease. The World Health Organization has classified COVID-19 as a severe worldwide public health pandemic due to its high death rate, quick transmission, and lack of medicines. To counteract the recurrence of the severe acute respiratory syndrome, active antiviral medications are urgently required. Glycyrrhizin was documented with activity on different viral proteins, including SARS-CoV-2; in this study, the activity of glycyrrhizin and its substructures (604 molecules) were screened on SARS-CoV-2 RNA-dependent-RNA polymerase using molecular docking, molecular dynamic (MD) simulation, and MM/GBSA. Sixteen molecules exhibited docking energy higher than -7 kcal/mol; four compounds (10772603, 101088272, 154730753 and glycyrrhizin) showed the highest binding energy, and good stability during MD simulation. The glycyrrhizin compound exhibited favorable docking energy (-7.9 kcal/mol), and it was the most stable complex during MD simulation. The predicted binding free energy of the glycyrrhizin complex was -57 ± 8 kcal/mol. These findings suggest that this molecule, after more validation, could become a good candidate for developing and manufacturing an anti-SARS-CoV-2 medication.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation, 3D-pharmacophore and scaffold hopping analysis in the design of multi-target drugs to inhibit potential targets of COVID-19

SARS-CoV-2 has posed serious threat to the health and has inflicted huge costs in the world. Discovering potent compounds is a critical step to inhibit coronavirus. 3CL^pro and RdRp are the most conserved targets associated with COVID-19. In this study, three-dimensional pharmacophore modeling, scaffold hopping, molecular docking, structure-based virtual screening, QSAR-based ADMET predictions and molecular dynamics analysis were used to identify inhibitors for these targets. Binding free energies estimated by molecular docking for each ligand in different binding sites of RdRp were used to predict the active site. Previously reported active 3CL^pro and RdRp inhibitors were used to build a pharmacophore model to develop different scaffolds. Structure-based simulations and pharmacophore modeling based on Hip Hop algorithm converged in a state that suggest hydrogen bond acceptor and donor features have a critical role in the two binding sites. Further validations indicated that the best pharmacophore model has fairly good correlation values compared with approved inhibitors. Structure-based simulation results approved that GLu166 and Gln189 in 3CL^pro and Lys551 and Glu811 in RdRp, are critical residues for dual activities. Ten compounds were extracted from pharmacophore-based virtual screening in six databases. The results, gained by repurposing approach, suggest the effectiveness of these ten compounds with different scaffolds as possible inhibitors of the two targets. Some quinoline-based hybrid derivatives also were designed. QSAR descriptors plot predicted that the scaffolds have had accepted pharmacokinetic profiles. Multiple molecular dynamics simulations in 100 ns and MM/PBSA studies of some reference inhibitors and the novel compounds in complex with both targets demonstrated stable complexes and confirmed the interaction modes. Based on different computational methods, COVID-19 multi-target inhibitors are proposed. Communicated by Ramaswamy H. Sarma.

Repurposing of potential antiviral drugs against RNA-dependent RNA polymerase of SARS-CoV-2 by computational approach

The high incidences of COVID-19 cases are believed to be associated with high transmissibility rates, which emphasizes the need for the discovery of evidence-based antiviral therapies for curing the disease. The rationale of repurposing existing classes of antiviral small molecule therapeutics against SARS-CoV-2 infection has been expected to accelerate the tedious and expensive drug development process. While Remdesivir has been recently approved to be the first treatment option for specific groups of COVID-19 patients, combinatory therapy with potential antiviral drugs may be necessary to enhance the efficacy in different populations. Hence, a comprehensive list of investigational antimicrobial drug compounds such as Favipiravir, Fidaxomicin, Galidesivir, GC376, Ribavirin, Rifabutin, and Umifenovir were computationally evaluated in this study. We performed in silico docking and molecular dynamics simulation on the selected small molecules against RNA-dependent RNA polymerase, which is one of the key target proteins of SARS-CoV-2, using AutoDock and GROMACS. Interestingly, our results revealed that the macrocyclic antibiotic, Fidaxomicin, possesses the highest binding affinity with the lowest energy value of -8.97 kcal/mol binding to the same active sites of RdRp. GC376, Rifabutin, Umifenovir and Remdesivir were identified as the next best compounds. Therefore, the above-mentioned compounds could be considered good leads for further preclinical and clinical experimentations as potentially efficient antiviral inhibitors for combination therapies against SARS-CoV-2.

In silico evaluation of potential inhibitory activity of remdesivir, favipiravir, ribavirin and galidesivir active forms on SARS-CoV-2 RNA polymerase

Since the outbreak emerged in November 2019, no effective drug has yet been found against SARS-CoV-2. Repositioning studies of existing drug molecules or candidates are gaining in overcoming COVID-19. Antiviral drugs such as remdesivir, favipiravir, ribavirin, and galidesivir act by inhibiting the vital RNA polymerase of SARS-CoV-2. The importance of in silico studies in repurposing drug research is gradually increasing during the COVID-19 process. The present study found that especially ribavirin triphosphate and galidesivir triphosphate active metabolites had a higher affinity for SARS-CoV-2 RNA polymerase than ATP by molecular docking. With the Molecular Dynamics simulation, we have observed that these compounds increase the complex's stability and validate the molecular docking results. We also explained that the interaction of RNA polymerase inhibitors with Mg++, which is in the structure of NSP12, is essential and necessary to interact with the RNA strand. In vitro and clinical studies on these two molecules need to be increased.

Investigating the binding affinity, interaction, and structure-activity-relationship of 76 prescription antiviral drugs targeting RdRp and Mpro of SARS-CoV-2

SARS-CoV-2 virus outbreak poses a major threat to humans worldwide due to its highly contagious nature. In this study, molecular docking, molecular dynamics, and structure-activity relationship are employed to assess the binding affinity and interaction of 76 prescription drugs against RNA dependent RNA polymerase (RdRp) and Main Protease (Mpro) of SARS-CoV-2. The RNA-dependent RNA polymerase is a vital enzyme of coronavirus replication/transcription complex whereas the main protease acts on the proteolysis of replicase polyproteins. Among 76 prescription antiviral drugs, four drugs (Raltegravir, Simeprevir, Cobicistat, and Daclatasvir) that are previously used for human immunodeficiency virus (HIV), hepatitis C virus (HCV), Ebola, and Marburg virus show higher binding energy and strong interaction with active sites of the receptor proteins. To explore the dynamic nature of the interaction, 100 ns molecular dynamics (MD) simulation is performed on the selected protein-drug complexes and apo-protein. Binding free energy of the selected drugs is performed by MM/PBSA. Besides docking and dynamics, partial least square (PLS) regression method is applied for the quantitative structure activity relationship to generate and predict the binding energy for drugs. PLS regression satisfactorily predicts the binding energy of the effective antiviral drugs compared to binding energy achieved from molecular docking with a precision of 85%. This study highly recommends researchers to screen these potential drugs in vitro and in vivo against SARS-CoV-2 for further validation of utility.

Computational drug repurposing study of antiviral drugs against main protease, RNA polymerase, and spike proteins of SARS-CoV-2 using molecular docking method

OBJECTIVES

The new Coronavirus (SARS-CoV-2) created a pandemic in the world in late 2019 and early 2020. Unfortunately, despite the increasing prevalence of the disease, there is no effective drug for the treatment. A computational drug repurposing study would be an appropriate and rapid way to provide an effective drug in the treatment of the coronavirus disease of 2019 (COVID-19) pandemic. In this study, the inhibitory potential of more than 50 antiviral drugs on three important proteins of SARS-CoV-2, was investigated using the molecular docking method.

METHODS

By literature review, three important proteins, including main protease, RNA-dependent RNA polymerase (RdRp), and spike, were selected as the drug targets. The three-dimensional (3D) structure of protease, spike, and RdRp proteins was obtained from the Protein Data Bank. Proteins were energy minimized. More than 50 antiviral drugs were considered as candidates for protein inhibition, and their 3D structure was obtained from Drug Bank. Molecular docking settings were defined using Autodock 4.2 software and the algorithm was executed.

RESULTS

Based on the estimated binding energy of docking and hydrogen bond analysis and the position of drug binding, five drugs including, indinavir, lopinavir, saquinavir, nelfinavir, and remdesivir, had the highest inhibitory potential for all three proteins.

CONCLUSIONS

According to the results, among the mentioned drugs, saquinavir and lopinavir showed the highest inhibitory potential for all three proteins compared to the other drugs. This study suggests that saquinavir and lopinavir could be included in the laboratory phase studies as a two-drug treatment for SARS-CoV-2 inhibition.

CASTELO: clustered atom subtypes aided lead optimization-a combined machine learning and molecular modeling method

Background

Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots.

Results

The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization.

Conclusion

With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04214-4.

Modeling the Binding Mechanism of Remdesivir, Favilavir, and Ribavirin to SARS-CoV-2 RNA-Dependent RNA Polymerase

Recent efforts to repurpose drugs to combat COVID-19 have identified Remdesivir as a candidate. It acts on the RNA-dependent, RNA polymerase (RdRp) of the SARS-CoV-2 virus, a protein complex responsible for mediating replication of the virus's genome. However, its exact action mechanism, and that of other nucleotide analogue inhibitors, is not known. In this study, we examine at the molecular level the interaction of this drug and that of similar nucleotide analogue inhibitors, ribavirin and favilavir, by relying on atomistic molecular simulations and advanced sampling. By analyzing the binding free energies of these different drugs, it is found that all of them bind strongly at the active site. Surprisingly, however, ribavirin and favilavir do not bind the nucleotide on the complementary strand as effectively and seem to act by a different mechanism than remdesivir. Remdesivir exhibits similar binding interactions to the natural base adenine. Moreover, by analyzing remdesivir at downstream positions of the RNA, we also find that, consistent with a "delayed" termination mechanism, additional nucleotides can be incorporated after remdesivir is added, and its highly polar 1'-cyano group induces a set of conformational changes that can affect the normal RdRp complex function. By analyzing the fluctuations of residues that are altered by remdesivir binding, and comparing them to those induced by lethal point mutations, we find a possible secondary mechanism in which remdesivir destabilizes the protein complex and its interactions with the RNA strands.

Bisindolylmaleimide IX: A novel anti-SARS-CoV2 agent targeting viral main protease 3CLpro demonstrated by virtual screening pipeline and in-vitro validation assays

SARS-CoV-2, the virus that causes COVID-19 consists of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs/compounds. We targeted seven proteins with enzymatic activities known to be essential at different stages of the viral cycle including PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2'-O-MT. For virtual screening, energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard (Schrodinger LLC 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs and investigational molecules (n = 5903). The screening was performed against viral targets using three sequential docking modes (i.e., HTVS, SP, and XP). Virtual screening identified ∼290 potential inhibitors based on the criteria of energy, docking parameters, ligand, and binding site strain and score. Drugs specific to each target protein were further analyzed for binding free energy perturbation by molecular mechanics (prime MM-GBSA) and pruning the hits to the top 32 candidates. The top lead from each target pool was further subjected to molecular dynamics simulation using the Desmond module. The resulting top eight hits were tested for their SARS-CoV-2 anti-viral activity in-vitro. Among these, a known inhibitor of protein kinase C isoforms, Bisindolylmaleimide IX (BIM IX), was found to be a potent inhibitor of SARS-CoV-2. Further, target validation through enzymatic assays confirmed 3CLpro to be the target. This is the first study that has showcased BIM IX as a COVID-19 inhibitor thereby validating our pipeline.

SARS-CoV-2: Repurposed Drugs and Novel Therapeutic Approaches-Insights into Chemical Structure-Biological Activity and Toxicological Screening

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic represents the primary public health concern nowadays, and great efforts are made worldwide for efficient management of this crisis. Considerable scientific progress was recorded regarding SARS-CoV-2 infection in terms of genomic structure, diagnostic tools, viral transmission, mechanism of viral infection, symptomatology, clinical impact, and complications, but these data evolve constantly. Up to date, neither an effective vaccine nor SARS-CoV-2 specific antiviral agents have been approved, but significant advances were enlisted in this direction by investigating repurposed approved drugs (ongoing clinical trials) or developing innovative antiviral drugs (preclinical and clinical studies). This review presents a thorough analysis of repurposed drug admitted for compassionate use from a chemical structure-biological activity perspective highlighting the ADME (absorption, distribution, metabolism, and excretion) properties and the toxicophore groups linked to potential adverse effects. A detailed pharmacological description of the novel potential anti-COVID-19 therapeutics was also included. In addition, a comprehensible overview of SARS-CoV-2 infection in terms of general description and structure, mechanism of viral infection, and clinical impact was portrayed.

Available Evidence and Ongoing Clinical Trials of Remdesivir: Could It Be a Promising Therapeutic Option for COVID-19?

The novel coronavirus strain, severe acute respiratory syndrome coronavirus-2, the causative agent of COVID-19 emerged in Wuhan, China, in December 2019 and is skyrocketing throughout the globe and become a global public health emergency. Despite promising preventive measures being taken, there is no vaccine or drug therapy officially approved to prevent or treat the infection. Everybody is waiting the findings of ongoing clinical trials in various chemical and biological products. This review is specifically aimed to summarize the available evidence and ongoing clinical trials of remdesivir as a potential therapeutic option for COVID-19. Remdesivir is an investigational drug having broad spectrum antiviral activity with its target RNA dependent RNA polymerase. It has not yet been officially approved for Ebola and Coronaviruses. Several studies showed that remdesivir had promising in vitro and in vivo antiviral activities against SARS-CoV-1 and MERS-CoV strains. On the top of this, it exhibited a promising in vitro activity against SARS-CoV-2 strains though there are no published studies that substantiate its activity in vivo until the time of this review. There are few phase 3 randomized double-blind placebo controlled trials on the way to investigate the safety and efficacy of remdesivir. Of which, one completed double blind, placebo controlled trial showed that remdesivir showed faster time to clinical improvement in severe COVID-19 patients compared to placebo though not found statistically significant. In addition, two phase 3 randomized open label clinical trials coordinated by Gilead Sciences are being conducted. In addition, WHO Solidarity trial and INSERM DisCoVeRy trials (randomized open labels) were launched recently.