ReviewRSC advances2021
Computational methods directed towards drug repurposing for COVID-19: advantages and limitations.
Review in RSC advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled 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.
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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- On the momentum toward vaccine self-sufficiency in the BRICS: an integrative review of the role of pharmaceutical entrepreneurship and innovation.Frontiers in public health · 2023Pooled it
- Automated Processes and Artificial Intelligence in Generating Candidates for Oncology Drug Repurposing: Three-Year Scoping Review of Data.Pharmacy (Basel, Switzerland) · 2026Review
- Redefining Breast Cancer Care by Harnessing Computational Drug Repositioning.Medicina (Kaunas, Lithuania) · 2025Review
- In silico screening and experimental validation identify riboflavin as an RNA-targeted antiviral against SARS-CoV-2.Scientific reports · 2025Article
- Drug repositioning pipeline integrating community analysis in drug-drug similarity networks and automated ATC community labeling to foster molecular docking analysis.Frontiers in bioinformatics · 2025Article
- Drug target of natural products and COVID-19: how far has science progressed?Annals of medicine and surgery (2012) · 2023Article
- Interaction of Camptothecin Anticancer Drugs with Ribosomal Proteins L15 and L11: A Molecular Docking Study.Molecules (Basel, Switzerland) · 2023Article
- Article
- Virtual Screening ofMolecules (Basel, Switzerland) · 2022Article
- Hybrid Approach to Identifying Druglikeness Leading Compounds against COVID-19 3CL Protease.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Drug Repurposing for COVID-19: A Review and a Novel Strategy to Identify New Targets and Potential Drug Candidates.Molecules (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent for COVID-19, it continues to transmit and newer variants of concern have been consistently emerging world-wide. Computational strategies involving drug repurposing offer a viable opportunity to choose a medication from a rundown of affirmed drugs against distinct diseases including COVID-19. While pandemics impede the healthcare systems, drug repurposing or repositioning represents a hopeful approach in which existing drugs can be remodeled and employed to treat newer diseases. In this review, we summarize the diverse computational approaches attempted for developing drugs through drug repurposing or repositioning against COVID-19 and discuss their advantages and limitations. To this end, we have outlined studies that utilized computational techniques such as molecular docking, molecular dynamic simulation, disease-disease association, drug-drug interaction, integrated biological network, artificial intelligence, machine learning and network medicine to accelerate creation of smart and safe drugs against COVID-19.
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.