scholarly journals Computationally repurposed drugs and natural products against RNA dependent RNA polymerase as potential COVID-19 therapies

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Sakshi Piplani ◽  
Puneet Kumar Singh ◽  
David A. Winkler ◽  
Nikolai Petrovsky
Keyword(s):  
Natural Products ◽  
Rna Polymerase ◽  
Kinase Inhibitor ◽  
Binding Energies ◽  
Dynamics Simulation ◽  
Rna Dependent Rna Polymerase ◽  
Starting Point ◽  
Potential Activity ◽  
Repurposed Drugs ◽  
Multiple Drugs

AbstractRepurposing of existing drugs and drug candidates is an ideal approach to identify new potential therapies for SARS-CoV-2 that can be tested without delay in human trials of infected patients. Here we applied a virtual screening approach using Autodock Vina and molecular dynamics simulation in tandem to calculate binding energies for repurposed drugs against the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). We thereby identified 80 promising compounds with potential activity against SARS-Cov2, consisting of a mixture of antiviral drugs, natural products and drugs with diverse modes of action. A substantial proportion of the top 80 compounds identified in this study had been shown by others to have SARS-CoV-2 antiviral effects in vitro or in vivo, thereby validating our approach. Amongst our top hits not previously reported to have SARS-CoV-2 activity, were eribulin, a macrocyclic ketone analogue of the marine compound halichondrin B and an anticancer drug, the AXL receptor tyrosine kinase inhibitor bemcentinib. Our top hits from our RdRp drug screen may not only have utility in treating COVID-19 but may provide a useful starting point for therapeutics against other coronaviruses. Hence, our modelling approach successfully identified multiple drugs with potential activity against SARS-CoV-2 RdRp.

scholarly journals Suramin, Penciclovir and Anidulafungin bind nsp12, which governs the RNA-dependent-RNA polymerase activity of SARS-CoV-2, with higher interaction energy than Remdesivir, indicating potential in the treatment of Covid-19

2020 ◽  
Author(s):  
Sanjay Kumar Dey ◽  
Manisha Saini ◽  
Chetna Dhembla ◽  
Shruti Bhatt ◽  
A. Sai Rajesh ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
Molecular Mechanisms ◽  
Therapeutic Potential ◽  
Drug Repositioning ◽  
Polymerase Activity ◽  
Binding Energies ◽  
Dynamics Simulation ◽  
Dimensional Structure ◽  
Rna Dependent Rna Polymerase ◽  
Rna Polymerase Activity

Structured abstract:Introduction: COVID-19, for which no vaccine or confirmed therapeutic agents are available, has claimed over 7,30,000 lives globally. A feasible and quicker method to resolve this problem may be ‘drug repositioning’.Areas covered: We investigated selected FDA and WHO-EML approved drugs based on their previously promising potential as antivirals, antibacterials or antifungals. These drugs were docked onto the three-dimensional structure of nsp12 protein, which reigns the RNA-dependent RNA polymerase activity of SARS-CoV-2 and is one of the major therapeutic targets for corona viruses. Inhibitor-protein complexes were also subjected to molecular dynamics simulation. The binding energies and the mode of interaction of the active site of the protein with the drugs were evaluated.Results: Suramin, Penciclovir and Anidulafungin were found to bind to nsp12 with similar binding energies as that of Remdesivir, which is currently being used in the treatment of COVID-19. In addition, recent experimental evidences indicate that these drugs exhibit antiviral efficacy against SARS-CoV-2. Thus, they might have a prospective therapeutic potential against the key viral enzyme.Expert opinion: Repurposed drugs will provide viable options for the treatment of COVID-19 and insight into the molecular mechanisms by which these potential drug candidates exhibit anti-SARSCoV-2 activity.

scholarly journals RNA-Dependent RNA Polymerase as a Target for COVID-19 Drug Discovery

2020 ◽  
Vol 25 (10) ◽  
pp. 1141-1151 ◽  
Author(s):  
Wei Zhu ◽  
Catherine Z. Chen ◽  
Kirill Gorshkov ◽  
Miao Xu ◽  
Donald C. Lo ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Host Cells ◽  
Host Proteins ◽  
Rna Dependent Rna Polymerase ◽  
Global Health Issue ◽  
Repurposed Drugs ◽  
Viral Enzyme ◽  
Target Effects

COVID-19 respiratory disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has rapidly become a global health issue since it emerged in December 2019. While great global efforts are underway to develop vaccines and to discover or repurpose therapeutic agents for this disease, as of this writing only the nucleoside drug remdesivir has been approved under Emergency Use Authorization to treat COVID-19. The RNA-dependent RNA polymerase (RdRP), a viral enzyme for viral RNA replication in host cells, is one of the most intriguing and promising drug targets for SARS-CoV-2 drug development. Because RdRP is a viral enzyme with no host cell homologs, selective SARS-CoV-2 RdRP inhibitors can be developed that have improved potency and fewer off-target effects against human host proteins and thus are safer and more effective therapeutics for treating COVID-19. This review focuses on biochemical enzyme and cell-based assays for RdRPs that could be used in high-throughput screening to discover new and repurposed drugs against SARS-CoV-2.

scholarly journals Deep learning-based computational drug discovery to inhibit the RNA Dependent RNA Polymerase: application to SARS-CoV and COVID-19

2020 ◽  
Author(s):  
Sayalee Patankar
Keyword(s):  
Deep Learning ◽  
Rna Polymerase ◽  
Short Term Memory ◽  
Comparison Group ◽  
Binding Energies ◽  
Therapeutic Options ◽  
Rna Dependent Rna Polymerase ◽  
Drug Candidates ◽  
Zinc Database ◽  
Binding Data

There is an urgency to find drugs and vaccines for the 2019 coronavirus disease (COVID-19). Therapeutic options include repurposing existing drugs or finding new ones. One approach is to target the RNA-dependent RNA polymerase (RdRp) and block viral RNA synthesis. Currently clinical trials to repurpose remdesivir, a RdRp targeting pro-drug for Ebola, to COVID-19 is under way. More such potential drugs need to be identified to efficiently find best therapeutic options. To address this need, a Long Short Term Memory (LSTM) model from literature was trained to read the SMILES fingerprint of a molecule and predict the IC50 of the molecule when binding to an RdRp. This model was trained using IC50 binding data from the PDB database. 310,000 drug-like compounds from the ZINC database were then screened using the trained LSTM model. Additionally, the 310,000 molecules with their predicted IC50s were used to train a generative Semi-Supervised Variational AutoEncoder (SSVAE) model from literature. Although not trained by actual experimental data (sufficient data are not available), the SSVAE model was used to generate 10 new molecules by sampling from the latent space to demonstrate its utility. These 10 molecules and the 1025 molecules with the lowest predicted IC50s from the LSTM model were docked onto the SARS coronavirus (a virus similar to COVID-19) RdRp using AutoDock Vina. Top four most stable inhibitors from the screened ZINC database compounds had binding energies of less than -33.89 kJ/mol. These binding energies were less than the binding energies of the comparison group consisting of prior drugs remdesivir, favipiravir, and galidesivir. Among the ten new molecules generated by the SSVAE model, the most stable new molecule had binding energy lower than the comparison group of prior drugs. The low binding energies of these molecules indicate they could potentially be good drug candidates for the SARS CoV and COVID-19. These results also show the utility of deep learning-based models in screening existing compound and generating new molecules to find drugs for COVID-19.

scholarly journals Probing remdesivir nucleotide analogue insertion to SARS-CoV-2 RNA dependent RNA polymerase in viral replication

2021 ◽  
Author(s):  
Moises Ernesto Romero ◽  
Chunhong Long ◽  
Daniel La Rocco ◽  
Anusha Mysore Keerthi ◽  
Dajun Xu ◽  
...  
Keyword(s):  
Free Energy ◽  
Rna Polymerase ◽  
Active Site ◽  
Energy Barrier ◽  
Umbrella Sampling ◽  
Dynamics Simulation ◽  
Free Energy Barrier ◽  
Base Stacking ◽  
Rna Dependent Rna Polymerase ◽  
Nucleotide Analogue

Remdesivir (RDV) prodrug can be metabolized into a triphosphate form nucleotide analogue (RDV-TP) to bind and insert into the active site of viral RNA dependent RNA polymerase (RdRp) to further interfere with the viral genome replication. In this work, we computationally studied how RDV-TP binds and inserts to the SARS-CoV-2 RdRp active site, in comparison with natural nucleotide substrate adenosine triphosphate (ATP). To do that, we first constructed atomic structural models of an initial binding complex (active site open) and a substrate insertion complex (active site closed), based on high-resolution cryo-EM structures determined recently for SARS-CoV-2 RdRp or non-structural protein (nsp) 12, in complex with accessory protein factors nsp7 and nsp8. By conducting all-atom molecular dynamics simulation with umbrella sampling strategies on the nucleotide insertion between the open and closed state RdRp complexes, our studies show that RDV-TP can bind comparatively stabilized to the viral RdRp active site, as it primarily forms base stacking with the template Uracil nucleotide (at +1), which is under freely fluctuations and supports a low free energy barrier of the RDV-TP insertion (~ 1.5 kcal/mol). In comparison, the corresponding natural substrate ATP binds to the RdRp active site in Watson-Crick base pairing with the template nt, and inserts into the active site with a medium low free energy barrier (~ 2.6 kcal/mol), when the fluctuations of the template nt are well quenched. The simulations also show that the initial base stacking of RDV-TP with the template can be particularly stabilized by motif B-N691, S682, and motif F-K500 with the sugar, base, and the template backbone, respectively. Although the RDV-TP insertion can be hindered by motif-F R555/R553 interaction with the triphosphate, the ATP insertion seems to be facilitated by such interactions. The inserted RDV-TP and ATP can be further distinguished by specific sugar interaction with motif B-T687 and motif-A D623, respectively.

scholarly journals Fragment-Based Virtual Screening to Discover Potential Plasmodium PI4KIIIβ Ligands

2021 ◽  
Author(s):  
Akachukwu Ibezim ◽  
Mbanefo S. Madukaife ◽  
Sochi C Osigwe ◽  
Nadja Engel ◽  
Ramanathan Karuppasamy ◽  
...  
Keyword(s):  
Antimalarial Activity ◽  
Plasmodium Species ◽  
Homology Model ◽  
Binding Energies ◽  
Dynamics Simulation ◽  
Active Site Residues ◽  
Starting Point ◽  
Binding Cavity

Plasmodium species that cause malaria, a disease responsible for about half a million deaths per annum despite concerted efforts to combat it. The causative agent depends on type III beta phosphatidylinositol 4-kinase (PPI4K) during the development of merozoite. PPI4K is the only clinically validated Plasmodium kinase so far and its inhibitors are effective both in vitro and in vivo. In this work, a small library of ~22 000 fragments was virtually screened using PPI4K homology model to discover potential ligands of the enzyme. 16 virtual hits were selected based on ≤ -9.0 kcal/mol binding energy cut off and were subjected to similarity and substructure searching after they had passed PAINS screening. The derivatives obtained showed improved binding energies, which ranged from -10.00 to -13.80 kcal/mol. Moreover, the topmost ranking compound 31, with interesting drug-like quality was stable within the protein’s binding cavity during the 10 ns molecular dynamics simulation period. In addition, analysis of its binding pose revealed some unique binding interactions with PPI4K active site residues as the basis for the observed improved binding affinity. Overall, compound 31 appears to be a viable starting point for the development of PPI4K inhibitors with antimalarial activity.

Virtual Screening of the Indonesian Medicinal Plant and Zinc Databases for Potential Inhibitors of the RNA-Dependent RNA Polymerase (RdRp) of 2019 Novel Coronavirus

2020 ◽  
Vol 20 (6) ◽  
pp. 1430
Author(s):  
Muhammad Arba ◽  
Andry Nur-Hidayat ◽  
Ida Usman ◽  
Arry Yanuar ◽  
Setyanto Tri Wahyudi ◽  
...  
Keyword(s):  
Binding Energy ◽  
Rna Polymerase ◽  
Antiviral Drug ◽  
Dynamics Simulation ◽  
Human Beings ◽  
Rna Dependent Rna Polymerase ◽  
Energy Prediction ◽  
Binding Energy Prediction ◽  
Solvation Energies ◽  
Novel Coronavirus

The novel coronavirus disease 19 (Covid-19) which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a pandemic across the world, which necessitate the need for the antiviral drug discovery. One of the potential protein targets for coronavirus treatment is RNA-dependent RNA polymerase. It is the key enzyme in the viral replication machinery, and it does not exist in human beings, therefore its targeting has been considered as a strategic approach. Here we describe the identification of potential hits from Indonesian Herbal and ZINC databases. The pharmacophore modeling was employed followed by molecular docking and dynamics simulation for 40 ns. 151 and 14480 hit molecules were retrieved from Indonesian herbal and ZINC databases, respectively. Three hits that were selected based on the structural analysis were stable during 40 ns, while binding energy prediction further implied that ZINC1529045114, ZINC169730811, and 9-Ribosyl-trans-zeatin had tighter binding affinities compared to Remdesivir. The ZINC169730811 had the strongest affinity toward RdRp compared to the other two hits including Remdesivir and its binding was corroborated by electrostatic, van der Waals, and nonpolar contribution for solvation energies. The present study offers three hits showing tighter binding to RdRp based on MM-PBSA binding energy prediction for further experimental verification.

scholarly journals Structural analogues of existing anti-viral drugs inhibit SARS-CoV-2 RNA dependent RNA polymerase: A computational hierarchical investigation

2020 ◽  
Author(s):  
Md. Kamrul Hasan ◽  
Mohammad Kamruzzaman ◽  
Omar Hamza Bin Manjur ◽  
Araf Mahmud ◽  
Nazmul Hussain ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
Inhibitory Effects ◽  
Rna Dependent Rna Polymerase ◽  
Drug Candidates ◽  
Structural Analogues ◽  
Repurposed Drugs ◽  
Potential Inhibitors ◽  
Structural Homologues ◽  
Prime Target ◽  
Potential Therapeutics

Abstract It’s been more than 8 months since COVID-19 became a pandemic and scientists all over the world are struggling to find suitable solutions to combat it. Multiple repurposed drugs have already been in several trials or recently completed. However, none of them shows any promising effect in combating COVID-19. Therefore, developing an effective drug is an unmet global need. RdRP (RNA dependent RNA polymerase) plays a pivotal role in viral replication therefore, it is considered as a prime target of drugs that may treat COVID-19. In this study, we have screened a library of compounds, containing approved RdRP inhibitor drugs in use to treat other viruses (Favipiravir, Sofosbuvir, Ribavirin, Lopinavir, Tenofovir, Ritonavir, Galidesivir and Remdesivir) and their structural homologues, in order to identify potential inhibitors of SARS-Cov-2 RdRP. Extensive screening, molecular docking and molecular dynamics show that five structural analogues have notable inhibitory effects against RdRP of SARS-Cov-2. Importantly, comparative protein-antagonists interaction revealed that these compounds fit well in the pocket of RdRP. ADMET analysis of these compounds suggests their potency as drug candidates. Our identified compounds may serve as potential therapeutics for COVID-19.

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