ReviewFrontiers in cellular and infection microbiology2022
Review in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Article
- An Integrated Computational Approach to Identify Potent HIV-1 Protease Inhibitors from Marine Sources.Combinatorial chemistry & high throughput screening · 2025Article
- Exploration of potential inhibitors against chikungunya envelope: an in-silico clue.In silico pharmacology · 2025Article
- Article
- Interference of small compounds and MgScientific reports · 2024Article
- In silico Molecular Docking Approach to Identify Potential Antihypertensive Compounds fromAdvances and applications in bioinformatics and chemistry : AABC · 2024Article
- Phytochemical constituents analysis inCommunicative & integrative biology · 2024Article
- Cheminformatics Strategies Unlock Marburg Virus VP35 Inhibitors from Natural Compound Library.Viruses · 2023Article
- In Silico Discovery of Small-Molecule Inhibitors Targeting SARS-CoV-2 Main Protease.Molecules (Basel, Switzerland) · 2023Article
- Integrating Computational Methods in Network Pharmacology andACS omega · 2023Article
- A potential host and virus targeting tool against COVID-19: Chemical characterization, antiviral, cytoprotective, antioxidant, respiratory smooth muscle relaxant effects of Paulownia tomentosa Steud.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2023Article
- Modified coptisine derivatives as an inhibitor against pathogenicFrontiers in pharmacology · 2023Article
- Target specific inhibition of West Nile virus envelope glycoprotein and methyltransferase using phytocompounds: anFrontiers in microbiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a substantial number of deaths around the world, making it a serious and pressing public health hazard. Phytochemicals could thus provide a rich source of potent and safer anti-SARS-CoV-2 drugs. The absence of approved treatments or vaccinations continues to be an issue, forcing the creation of new medicines. Computer-aided drug design has helped to speed up the drug research and development process by decreasing costs and time. Natural compounds like terpenoids, alkaloids, polyphenols, and flavonoid derivatives have a perfect impact against viral replication and facilitate future studies in novel drug discovery. This would be more effective if collaboration took place between governments, researchers, clinicians, and traditional medicine practitioners' safe and effective therapeutic research. Through a computational approach, this study aims to contribute to the development of effective treatment methods by examining the mechanisms relating to the binding and subsequent inhibition of SARS-CoV-2 ribonucleic acid (RNA)-dependent RNA polymerase (RdRp). The
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Registered trials
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.