ReviewAnnals of medicine and surgery (2012)2022
Modern drug discovery applications for the identification of novel candidates for COVID-19 infections.
Review in Annals of medicine and surgery (2012), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Atractylenolide I ameliorates post-infectious irritable bowel syndrome by inhibiting the polymerase I and transcript release factor and c-Jun N-terminal kinase/inducible nitric oxide synthase pathway.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2025Article
- Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis.Pharmaceuticals (Basel, Switzerland) · 2023Review
- A comprehensive perspective of traditional Arabic or Islamic medicinal plants as an adjuvant therapy against COVID-19.Saudi journal of biological sciences · 2023Review
- Computational Bioprospecting Guggulsterone against ADP Ribose Phosphatase of SARS-CoV-2.Molecules (Basel, Switzerland) · 2022Article
- Immunoinformatics design of B and T-cell epitope-based SARS-CoV-2 peptide vaccination.Frontiers in immunology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In early December 2019, a large pneumonia epidemic occurred in Wuhan, China. The World Health Organization is concerned about the outbreak of another coronavirus with the powerful, rapid, and contagious transmission. Anyone with minor symptoms like fever and cough or travel history to contaminated places might be suspected of having COVID-19. COVID-19 therapy focuses on treating the disease's symptoms. So far, no such therapeutic molecule has been shown effective in treating this condition. So the treatment is mostly supportive and plasma. Globally, numerous studies and researchers have recently started fighting this virus. Vaccines and chemical compounds are also being investigated against infection. COVID-19 was successfully diagnosed using RNA detection and very sensitive RT-PCR (reverse transcription-polymerase chain reaction). The evolution of particular vaccinations is required to reduce illness severity and spread. Numerous computational analyses and molecular docking have predicted various target compounds that might stop this condition. This paper examines the main characteristics of coronavirus and the computational analyses necessary to avoid infection.
Indexed as
Identifiers
What OpenQuestion holds
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.