Evidence map›Paper›PMID 35380919›Full record

ReviewmAbs

David versus goliath: ACE2-Fc receptor traps as potential SARS-CoV-2 inhibitors.

Mohamed A Alfaleh, Ayat Zawawi, Sawsan S Al-Amri, Anwar M Hashem

Open access · goldAbstract readReview
In one paragraph

Review in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Mohamed A AlfalehDepartment of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah Saudi Arabia.ORCID 0000-0003-3716-0019
Ayat ZawawiVaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah Saudi Arabia.
Sawsan S Al-AmriVaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah Saudi Arabia.
Anwar M HashemVaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah Saudi Arabia.
King Abdulaziz University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anti-SARS-CoV-2 monoclonal antibodies and vaccines have shown improvement in lowering viral burden and hospitalization. However, emerging SARS-CoV-2 variants contain neutralizing antibody-escape mutations. Therefore, several reports have suggested the administration of recombinant angiotensin-converting enzyme 2 (rACE2) as a soluble receptor trap to block SARS-CoV-2 infection and limit viral escape potential. Several strategies have been implemented to enhance the efficacy of rACE2 as a therapeutic agent. Fc fusions have been used to improve pharmacokinetics and boost the affinity and avidity of ACE2 decoys for the virus spike protein. Furthermore, the intrinsic catalytic activity of ACE2 can be eliminated by introducing point mutations on the catalytic site of ACE2 to obtain an exclusive antiviral activity. This review summarizes different evolution platforms that have been used to enhance ACE2-Fc (i.e., immunoadhesins) as potential therapeutics for the current pandemic or future outbreaks of SARS-associated betacoronaviruses.

Indexed as

COVID-19 Drug TreatmentSARS-CoV-2Angiotensin-Converting Enzyme 2HumansProtein BindingReceptors, FcSpike Glycoprotein, CoronavirusAngiotensin-Converting Enzyme 2Receptors, FcSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2ACE2affinity maturationCOVID-19immunoadhesinsreceptor trapsSARS coronavirus 2

Identifiers

PMID35380919
PMCPMC8986284
OpenAlexW4225793663

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.