Evidence map›Paper›PMID 33137330›Full record

ArticleEuropean journal of pharmacology2021

Functional and druggability analysis of the SARS-CoV-2 proteome.

Claudio N Cavasotto, Maximiliano Sánchez Lamas, Julián Maggini

Open access · greenAbstract read
In one paragraph

Article in European journal of pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
0.9field-weighted citation impact, top 14% 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

24 citing papers in PubMed, 39 citations in OpenAlex.

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  19. Structure- and Ligand-BasedArabian journal of chemistry · 2021
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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

3 authors at 1 institution in 2 countries.

Claudio N CavasottoComputational Drug Design and Biomedical Informatics Laboratory, Translational Medicine Research Institute (IIMT), CONICET-Universidad Austral, Pilar, Buenos Aires, Argentina; Facultad de Ciencias Biomédicas, Facultad de Ingeniería, Universidad Austral, Pilar, Buenos Aires, Argentina; Austral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina. Electronic address: CCavasotto@austral.edu.ar.
Maximiliano Sánchez LamasAustral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina; Meton AI, Inc., Wilmington, DE, 19801, USA.
Julián MagginiAustral Institute for Applied Artificial Intelligence, Universidad Austral, Pilar, Buenos Aires, Argentina; Technology Transfer Office, Universidad Austral, Pilar, Buenos Aires, Argentina.
Austral University · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The infectious coronavirus disease (COVID-19) pandemic, caused by the coronavirus SARS-CoV-2, appeared in December 2019 in Wuhan, China, and has spread worldwide. As of today, more than 46 million people have been infected and over 1.2 million fatalities. With the purpose of contributing to the development of effective therapeutics, we performed an in silico determination of binding hot-spots and an assessment of their druggability within the complete SARS-CoV-2 proteome. All structural, non-structural, and accessory proteins have been studied, and whenever experimental structural data of SARS-CoV-2 proteins were not available, homology models were built based on solved SARS-CoV structures. Several potential allosteric or protein-protein interaction druggable sites on different viral targets were identified, knowledge that could be used to expand current drug discovery endeavors beyond the currently explored cysteine proteases and the polymerase complex. It is our hope that this study will support the efforts of the scientific community both in understanding the molecular determinants of this disease and in widening the repertoire of viral targets in the quest for repurposed or novel drugs against COVID-19.

Indexed as

Models, MolecularProteomeAntiviral AgentsBinding SitesCOVID-19 Drug TreatmentDrug DiscoveryHumansSARS-CoV-2Viral ProteinsAntiviral AgentsProteomeViral ProteinsBinding hot-spotsCoronavirusCOVID-19Drug discoveryDruggabilitySARS-CoV-2

Identifiers

PMID33137330
PMCPMC7604074
OpenAlexW3095231304

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.