Evidence map›Paper›PMID 33186044›Full record

ReviewJournal of medicinal chemistry2022

Targeting SARS-CoV-2 Proteases and Polymerase for COVID-19 Treatment: State of the Art and Future Opportunities.

Rolando Cannalire, Carmen Cerchia, Andrea R Beccari, Francesco Saverio Di Leva, Vincenzo Summa

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of medicinal chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
122citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 4% 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

122 citing papers in PubMed, 1 synthesis or guideline pooled it, 245 citations in OpenAlex.

  1. Pooled it
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  15. Identifying Inhibitor-SARS-CoV2-3CLMolecules (Basel, Switzerland) · 2025
    Article
  16. Review
  17. Approaching Pharmacological Space: Events and Components.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  18. Article
  19. Review
  20. Article

62 more citing papers are in PubMed but not listed here.

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

5 authors at 2 institutions in 1 country.

Rolando CannalireDepartment of Pharmacy, University of Naples "Federico II", via D. Montesano 49, 80131 Napoli, Italy.
Carmen CerchiaDepartment of Pharmacy, University of Naples "Federico II", via D. Montesano 49, 80131 Napoli, Italy.
Andrea R BeccariDompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy.
Francesco Saverio Di LevaDepartment of Pharmacy, University of Naples "Federico II", via D. Montesano 49, 80131 Napoli, Italy.
Vincenzo SummaDepartment of Pharmacy, University of Naples "Federico II", via D. Montesano 49, 80131 Napoli, Italy.ORCID 0000-0002-6288-2681
University of Naples Federico II · ITDompé (Italy) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The newly emerged coronavirus, called SARS-CoV-2, is the causing pathogen of pandemic COVID-19. The identification of drugs to treat COVID-19 and other coronavirus diseases is an urgent global need, thus different strategies targeting either virus or host cell are still under investigation. Direct-acting agents, targeting protease and polymerase functionalities, represent a milestone in antiviral therapy. The 3C-like (or Main) protease (3CL

Indexed as

COVID-19 Drug TreatmentAntiviral AgentsCoronavirus 3C ProteasesCOVID-19HumansMolecular StructureProtease InhibitorsRNA-Dependent RNA PolymeraseSARS-CoV-23C-like proteinase, SARS-CoV-2Antiviral AgentsCoronavirus 3C ProteasesProtease InhibitorsRNA-Dependent RNA Polymerase

Identifiers

PMID33186044
PMCPMC7688049
OpenAlexW3100998741

What OpenQuestion holds

Textmetadata
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.