Evidence map›Paper›PMID 37950101›Full record

ArticleJournal of molecular modeling2023

Targeting the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) with synthetic/designer unnatural nucleoside analogs: an in silico study.

Subhendu Sekhar Bag, Sayantan Sinha, Soumya Dutta, Hirak Jyoti Baishya, Suravi Paul

Abstract read
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In one paragraph

Article in Journal of molecular modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Subhendu Sekhar BagChemical Biology/Genomics Laboratory, Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039. ssbag75@iitg.ac.in.
Sayantan SinhaCentre for the Environment, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039.
Soumya DuttaChemical Biology/Genomics Laboratory, Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039.
Hirak Jyoti BaishyaChemical Biology/Genomics Laboratory, Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039.
Suravi PaulChemical Biology/Genomics Laboratory, Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039.
Indian Institute of Technology Guwahati · IN

Funding

Department of Biotechnology, Ministry of Science and Technology, India BT/PR16620/NER/95/223/2015Department of Science and Technology (DST) SR/SI/OC-69/2008
6 · The paper itself

Abstract

contextSince the outbreak of COVID-19 in December 2019, it developed into a pandemic affecting all the countries and millions of people around the globe. Until now, there is no medicine available to contain the spread of the virus. As an aid to drug discovery, the molecular docking and molecular dynamic tools were applied extensively. In silico studies made it possible for rapid screening of potential molecules as possible inhibitors/drugs against the targeted proteins. As a continuation of our drug discovery research, we have carried out molecular docking studies of our 12 reported unnatural nucleosides and 14 designer Avigan analogs with SARS-CoV-2, RNA-dependent RNA polymerase (RdRp), which we want to report herein. The same calculation was also carried out, taking 11 known/under trail/commercial nucleoside drug molecules for a comparison of the binding interactions in the catalytic site of RdRp. The docking results and binding efficiencies of our reported nucleosides and designer nucleosidic were compared with the binding energy of commercially available drugs such as remdesevir and favipiravir. Furthermore, we evaluated the protein-drug binding efficiency and stability of the best docked molecules by molecular dynamic studies (MD). From our study, we have found that few of our proposed drugs show promising binding efficiency at the catalytic pocket of SARS-CoV-2 RdRp and can be a promising RdRp inhibitor drug candidate. Hence, this study will be of importance to make progress toward developing successful nucleoside-based drugs and conduct the antiviral test in the wet lab to understand their efficacy against COVID-19.

methodAll the docking studies were carried out with AutoDock 4.2, AutoDock Vina and Molegro Virtual Docker. Following the docking studies, the MD simulations were carried out following the standard protocol with the GROMACS ver. 2019.6. by applying the CHARMM36 all-atom biomolecular force field. The drug-protein interaction was studied using the Biovia Discovery Studio suite, Ligplot software, and Protein-Ligand Interaction Profiler (PLIP).

Indexed as

COVID-19NucleosidesAmidesAntiviral AgentsMolecular Docking SimulationMolecular Dynamics SimulationPyrazinesRNA-Dependent RNA PolymeraseRNA, ViralSARS-CoV-2AmidesAntiviral AgentsfavipiravirNucleosidesPyrazinesRNA-Dependent RNA PolymeraseRNA, ViralADMETCOVID-19Designer nucleosidesMolecular dockingMolecular dynamicsSARS-CoV-2 RdRpUnnatural nucleoside

Identifiers

PMID37950101
OpenAlexW4388583716

What Socratic holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.