Evidence map›Paper›PMID 33893357›Full record

ArticleScientific reports2021

A small interfering RNA (siRNA) database for SARS-CoV-2.

Inácio Gomes Medeiros, André Salim Khayat, Beatriz Stransky, Sidney Santos, Paulo Assumpção, Jorge Estefano Santana de Souza

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

17 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Current drug discovery technologies · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Potential of siRNA in COVID-19 therapy: Emphasis onFrontiers in bioengineering and biotechnology · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Ex vivo and in vivo suppression of SARS-CoV-2 with combinatorial AAV/RNAi expression vectors.Molecular therapy : the journal of the American Society of Gene Therapy · 2022
    Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. 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

6 authors at 2 institutions in 1 country.

Inácio Gomes MedeirosBioinformatics Graduate Program, Metrópole Digital Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, 59078-400, Brazil.ORCID 0000-0002-3407-218X
André Salim KhayatInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, 66075-110, Brazil.ORCID 0000-0002-3451-6369
Beatriz StranskyBioinformatics Multidisciplinary Environment (BioME), Metrópole Digital Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, 59078-400, Brazil.
Sidney SantosInstituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, 66075-110, Brazil.
Paulo AssumpçãoNúcleo de Pesquisas Em Oncologia, Universidade Federal do Pará, Belém, Pará, 66073-110, Brazil.
Jorge Estefano Santana de SouzaBioinformatics Graduate Program, Metrópole Digital Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, 59078-400, Brazil. jorge@imd.ufrn.br.
Universidade Federal do Pará · BRUniversidade Federal do Rio Grande do Norte · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) rapidly transformed into a global pandemic, for which a demand for developing antivirals capable of targeting the SARS-CoV-2 RNA genome and blocking the activity of its genes has emerged. In this work, we presented a database of SARS-CoV-2 targets for small interference RNA (siRNA) based approaches, aiming to speed the design process by providing a broad set of possible targets and siRNA sequences. The siRNAs sequences are characterized and evaluated by more than 170 features, including thermodynamic information, base context, target genes and alignment information of sequences against the human genome, and diverse SARS-CoV-2 strains, to assess possible bindings to off-target sequences. This dataset is available as a set of four tables, available in a spreadsheet and CSV (Comma-Separated Values) formats, each one corresponding to sequences of 18, 19, 20, and 21 nucleotides length, aiming to meet the diversity of technology and expertise among laboratories around the world. A metadata table (Supplementary Table S1), which describes each feature, is also provided in the aforementioned formats. We hope that this database helps to speed up the development of new target antivirals for SARS-CoV-2, contributing to a possible strategy for a faster and effective response to the COVID-19 pandemic.

Indexed as

COVID-19Databases, GeneticHumansRNA InterferenceRNA, Small InterferingRNA, ViralSARS-CoV-2RNA, Small InterferingRNA, Viral

Identifiers

PMID33893357
PMCPMC8065152
OpenAlexW3155663480

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.