ReviewChemical Society reviews2021
A critical overview of computational approaches employed for COVID-19 drug discovery.
Review in Chemical Society reviews, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 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
77 citing papers in PubMed.
- Screening of putative inhibitors for cytotoxin VacA from Helicobacter pylori.Scientific reports · 2026Article
- A Fivefold Maximum Drug-Likeness Strategy for Prioritizing Antibacterial Candidates AgainstPharmaceuticals (Basel, Switzerland) · 2026Article
- Investigating Marine Natural Products as Potential Antivirals of Mpox Virus Replication by Targeting Thymidylate Kinase.ACS omega · 2026Article
- Identification of Antibacterial Hits Associated with Penicillin-Binding Protein 2 inDrug design, development and therapy · 2026Article
- Integrative machine learning-guidedRSC advances · 2025Article
- Drug repositioning as a promising approach for the eradication of emerging and re-emerging viral agents.Molecular diversity · 2025Review
- Strategies for robust, accurate, and generalizable benchmarking of drug discovery platforms.Bioinformatics (Oxford, England) · 2025Article
- VCTatDot and VCTatMLP: novel deep learning models with triadic attention embeddings for synergistic drug combination prediction.Scientific reports · 2025Article
- Strategies for robust, accurate, and generalizable benchmarking of drug discovery platforms.bioRxiv : the preprint server for biology · 2025Article
- Discriminating High from Low Energy Conformers of Druglike Molecules: An Assessment of Machine Learning Potentials and Quantum Chemical Methods.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025Article
- Spectra-descriptor-based machine learning for predicting protein-ligand interactions.Chemical science · 2025Article
- The Six Ds of Exponentials and drug discovery: A path toward reversing Eroom's law.Drug discovery today · 2025Review
- Molecular Crowding by Computational Approaches.Sub-cellular biochemistry · 2025Review
- Identification and Ranking of Binding Sites from Structural Ensembles: Application to SARS-CoV-2.Viruses · 2024Article
- In Silico Identification of Potential Inhibitors of SARS-CoV-2 Main Protease (MPathogens (Basel, Switzerland) · 2024Article
- Machine learning in preclinical drug discovery.Nature chemical biology · 2024Review
- Investigation of substituent effects on the electronic structure and antiviral activity of favipiravir derivatives for Covid-19 treatment using DFT and molecular docking.Scientific reports · 2024Article
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- An Overview of SARS-CoV-2 Potential Targets, Inhibitors, and Computational Insights to Enrich the Promising Treatment Strategies.Current microbiology · 2024Review
17 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the most severe disruptions to societies and economies since the Great Depression. Massive experimental and computational research effort to understand and characterize the disease and rapidly develop diagnostics, vaccines, and drugs has emerged in response to this devastating pandemic and more than 130 000 COVID-19-related research papers have been published in peer-reviewed journals or deposited in preprint servers. Much of the research effort has focused on the discovery of novel drug candidates or repurposing of existing drugs against COVID-19, and many such projects have been either exclusively computational or computer-aided experimental studies. Herein, we provide an expert overview of the key computational methods and their applications for the discovery of COVID-19 small-molecule therapeutics that have been reported in the research literature. We further outline that, after the first year the COVID-19 pandemic, it appears that drug repurposing has not produced rapid and global solutions. However, several known drugs have been used in the clinic to cure COVID-19 patients, and a few repurposed drugs continue to be considered in clinical trials, along with several novel clinical candidates. We posit that truly impactful computational tools must deliver actionable, experimentally testable hypotheses enabling the discovery of novel drugs and drug combinations, and that open science and rapid sharing of research results are critical to accelerate the development of novel, much needed therapeutics for COVID-19.
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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.