Evidence map›Paper›PMID 40104088›Full record

ArticleF1000Research2024

Study anti-viral drugs for their efficiency against multiple SARS CoV-2 drug targets within molecular docking, molecular quantum similarity, and chemical reactivity indices frameworks.

Alejandro Morales-Bayuelo, Jesús Sánchez-Márquez, Ricardo Vivas-Reyes, Savaş Kaya

Abstract read
In one paragraph

Article in F1000Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Alejandro Morales-BayueloUniversidad del Sinú, Grupo GENOMA, Cartagena, Bolivar, 36987, Colombia.ORCID https://orcid.org/0000-0001-9159-5289
Jesús Sánchez-MárquezDepartamento de Química-Física, Universidad de Cadiz, Cádiz, Andalusia, 544578, Spain.
Ricardo Vivas-ReyesGroup of Quantum and Theoretical Chemistry, Faculty of Exacts and Naturals Sciences, University of Cartagena, Bolívar, Colombia.ORCID https://orcid.org/0000-0002-7462-1948
Savaş KayaFaculty of Science Department of Chemistry, Sivas Cumhuriyet University, Sivas, 58140, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study focused on drug discovery for COVID-19, emphasizing the challenges posed by the pandemic and the importance of understanding the virus's biology. The research utilized molecular docking and quantum similarity analyses to explore potential ligands for SARS-CoV-2 RNA-dependent RNA polymerase. Docking Results: Docking outcomes for various ligands, including Oseltamivir, Prochloraz, Valacyclovir, Baricitinib, Molnupiravir, Penciclovir, Famciclovir, Lamivudine, and Nitazoxanide, were presented. Interactions between ligands and specific residues in the RNA-dependent RNA polymerase were analyzed. Reactivity Descriptors: Global parameters, such as electronic chemical potential, chemical hardness, global softness, and global electrophilicity, were computed for the ligands. For the local reactivity descriptors, the Fukui Functions were used. Fukui functions, representing electrophilic and nucleophilic sites, were calculated for selected ligands (Valacyclovir and Penciclovir). Nucleophilic character assignments for specific molecular regions were discussed, providing insights into potential charge-donating interactions. Results and Discussion: Challenges in COVID-19 drug discovery, such as virus mutability, rapid evolution, and resource limitations, were summarized. Progress in vaccine development and the need for ongoing research to address variants and breakthrough cases were emphasized. Overlap Operator Analysis: Higher MQSM between Lamivudine and Molnupiravir (0.5742) indicates structural and electronic similarity. Lowest MQSM between Oseltamivir and Prochloraz (0.2233) implies structural dissimilarity. Coulomb Operator Analysis: Higher MQSM between Lamivudine and Molnupiravir (0.9178) suggests both structural and electronic similarity. Lowest MQSM between Baricitinib and Famciclovir (0.6001) indicates greater structural diversity. Measurements above 0.5 in Table 3 suggest electronic similarity, emphasizing the electronic aspects in molecular analysis.In this sense, it study employed a multi-faceted approach combining molecular docking, quantum similarity analyses, and chemical reactivity assessments to explore potential drug candidates for COVID-19. The findings provide valuable insights into ligand interactions, reactivity patterns, and the challenges associated with drug discovery in the context of the global pandemic.

Indexed as

Antiviral AgentsCOVID-19 Drug TreatmentMolecular Docking SimulationSARS-CoV-2COVID-19Drug DiscoveryHumansLigandsQuantum TheoryRNA-Dependent RNA PolymeraseAntiviral AgentsLigandsRNA-Dependent RNA Polymerasechemical reactivity indicesCOVID-19 treatmentsDensity Functional Theory.molecular dockingmolecular quantum similaritySARS-CoV-2 virus

Identifiers

PMID40104088
PMCPMC11915800

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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.