Evidence map›Paper›PMID 34697818›Full record

ReviewMedicinal research reviews2022

Haste makes waste: A critical review of docking-based virtual screening in drug repurposing for SARS-CoV-2 main protease (M-pro) inhibition.

Guillem Macip, Pol Garcia-Segura, Júlia Mestres-Truyol, Bryan Saldivar-Espinoza, María José Ojeda-Montes, Aleix Gimeno, Adrià Cereto-Massagué, Santiago Garcia-Vallvé, Gerard Pujadas

Open access · bronzeAbstract readReview
In one paragraph

Review in Medicinal research reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
9.8field-weighted citation impact, top 2% of its field
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

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.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 1 synthesis or guideline pooled it, 93 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Bridging between Structure-Based and Data-Driven Affinity Prediction.Journal of chemical information and modeling · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. KRASAVA-An Expert System for Virtual Screening of KRAS G12D Inhibitors.International journal of molecular sciences · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
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

9 authors at 4 institutions in 2 countries.

Guillem MacipDepartament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.ORCID 0000-0003-4016-5558
Pol Garcia-SeguraDepartament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.ORCID 0000-0002-0169-824X
Júlia Mestres-TruyolDepartament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.ORCID 0000-0002-8552-5281
Bryan Saldivar-EspinozaDepartament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.ORCID 0000-0002-9667-2818
María José Ojeda-MontesMolecular Modeling Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.ORCID 0000-0002-9290-1935
Aleix GimenoJoint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.ORCID 0000-0002-7654-6689
Adrià Cereto-MassaguéEURECAT Centre Tecnològic de Catalunya, Centre for Omic Sciences (COS), Joint Unit Universitat Rovira i Virgili-EURECAT, Unique Scientific and Technical Infrastructures (ICTS), Reus, Spain.ORCID 0000-0002-9319-6377
Santiago Garcia-VallvéDepartament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.ORCID 0000-0002-0348-7497
Gerard PujadasDepartament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Research group in Cheminformatics & Nutrition, Tarragona, Tarragona, Spain.ORCID 0000-0003-2598-8089
Universitat Rovira i Virgili · ESCentre for Omic Sciences · ESInstitute for Research in Biomedicine · ESSIB Swiss Institute of Bioinformatics · CH

Funding

European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement 713679Universitat Rovira i Virgili 2019PFR-URV-B2-69
6 · The paper itself

Abstract

This review makes a critical evaluation of 61 peer-reviewed manuscripts that use a docking step in a virtual screening (VS) protocol to predict SARS-CoV-2 M-pro (M-pro) inhibitors in approved or investigational drugs. Various manuscripts predict different compounds, even when they use a similar initial dataset and methodology, and most of them do not validate their methodology or results. In addition, a set of known 150 SARS-CoV-2 M-pro inhibitors extracted from the literature and a second set of 81 M-pro inhibitors and 113 inactive compounds obtained from the COVID Moonshot project were used to evaluate the reliability of using docking scores as feasible predictors of the potency of a SARS-CoV-2 M-pro inhibitor. Using two SARS-CoV-2 M-pro structures and five protein-ligand docking programs, we proved that the correlation between the pIC

Indexed as

COVID-19Drug RepositioningAntiviral AgentsCoronavirus 3C ProteasesHumansMolecular Docking SimulationMolecular Dynamics SimulationReproducibility of ResultsSARS-CoV-23C-like proteinase, SARS-CoV-2Antiviral AgentsCoronavirus 3C Proteasesdrug repurposingmolecular dockingM-pro inhibitorsSARS-CoV-2 3C proteasevirtual screening

Identifiers

PMID34697818
PMCPMC8662214
OpenAlexW3209925230

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.