Evidence map›Paper›PMID 40093584›Full record

ArticleIn silico pharmacology2025

Molecular docking, pharmacological profiling, and MD simulations of glycolytic inhibitors targeting novel SARS CoV-2 main protease and spike protein.

Nikhil Kumar, Chandraprakash Gond, Jai Deo Singh, Anupama Datta

Abstract read
In one paragraph

Article in In silico pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Nikhil KumarInstitute of Nuclear Medicine and Allied Sciences, DRDO, Brig S. K. Mazumdar Marg, Delhi, 110054 India.
Chandraprakash GondInstitute of Nuclear Medicine and Allied Sciences, DRDO, Brig S. K. Mazumdar Marg, Delhi, 110054 India.
Jai Deo SinghDepartment of Chemistry, Indian Institute of Technology, Delhi, 110016 India.
Anupama DattaInstitute of Nuclear Medicine and Allied Sciences, DRDO, Brig S. K. Mazumdar Marg, Delhi, 110054 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Abstract: Coronavirus infection (COVID-19), designated a global health emergency by the World Health Organization in 2020, continues to spur the search for effective therapeutics. The causative agent, SARS-CoV-2, depends on viral proteins and host metabolic reprogramming for replication. This study explores the potential of glycolytic inhibitors as dual-action agents against SARS-CoV-2, explicitly targeting the main protease and the spike protein due to their critical roles in viral replication and cellular entry. These inhibitors disrupt the activity of viral proteins and host cell glycolysis, thereby preventing viral propagation. Through a combination of virtual screening, molecular docking, and molecular dynamics simulations, fluoro-deoxy-glucose folate (FDGF) and N-(2-fluoro-3-(6-O-glucosylpropyl-azomycin)) were identified as potent candidates. The docking results showed strong binding affinities, with scores of -8.6 and -7.1 kcal/mol for main protease and -9.9 and - 7.5 kcal/mol for spike receptor-binding domain bound to ACE2. Further molecular dynamic simulations confirmed the stability of the FDGF complexes, with RMSD fluctuations consistently remained within 1.6-2.9 Å over a 100 ns trajectory. Additionally, MM-GBSA binding free energy calculations revealed favorable binding energies, underscoring the stability and potential efficacy of these compounds. Overall, the findings suggest that FDGF and N-(2-fluoro-3-(6-O-glucosylpropyl-azomycin)) show promise as SARS-CoV-2 therapeutics, warranting further in vitro and in vivo validation to confirm their antiviral potential. Graphical abstract: Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-025-00336-2.

Indexed as

COVID-19GlycolysisInhibitorsMolecular dockingSARS-CoV-2 MproSwiss ADMEViral replication

Identifiers

PMID40093584
PMCPMC11908997

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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 OpenQuestion graph.