Evidence map›Paper›PMID 40256168›Full record

ArticleComputational and structural biotechnology journal2025

In Silico and In Vitro development of novel small interfering RNAs (siRNAs) to inhibit SARS-CoV-2.

Noha Samir Taibe, Sara H Mahmoud, Maimona A Kord, Mohamed Ahmed Badawy, Mahmoud Shehata, Mahmoud Elhefnawi

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Noha Samir TaibeBiotechnology Department, Faculty of Science, Cairo University, Giza, Egypt.
Sara H MahmoudCenter of Scientific Excellence for Influenza Viruses (CSEIV), National Research Centre, Cairo 12622, Egypt.
Maimona A KordBotany Department, Faculty of Science, Cairo University, Giza, Egypt.
Mohamed Ahmed BadawyChemistry Department, Faculty of Science, Cairo University, Giza, Egypt.
Mahmoud ShehataCenter of Scientific Excellence for Influenza Viruses (CSEIV), National Research Centre, Cairo 12622, Egypt.
Mahmoud ElhefnawiBiomedical Informatics and Cheminformatics Group, Informatics and Systems Department, National Research Centre, Cairo, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 is causing severe to moderate respiratory tract infections, posing global health, social life, and economic threats. Our design strategy for siRNAs differs from existing studies through a step-by-step filtration process utilizing integrative bioinformatics protocols and web tools. Stage one: Multiple Sequence Alignment was employed to identify the most conserved areas. Stage two involves using various online tools, among the most reputable tools for building siRNA. The first filtration step of siRNA uses the Huesken dataset, estimating a 90 % experimental inhibition. The second filtration stage involves choosing the most suitable and targeted siRNA by utilizing thermodynamics and Target Accessibility of siRNAs. The final filtration step is off-target filtration using BLAST with specific parameters. Four of the 258 siRNAs were chosen for their potency and specificity, targeting conserved regions (NSP8, NSP12, and NSP14) with minimal human transcripts off-targets. We conducted in-vitro experiments, including cytotoxicity, TCID50, and RT-PCR assays. When tested on the SARS-CoV-2 strain hCoV-19/Egypt/NRC-03/2020 at 100 nM, none showed cellular toxicity. The TCID50 assay confirmed viral replication reduction at 12 h.p.i; the efficacy of the four siRNAs and their P value were highly significant. siRNA2 maintaining efficacy at 24, 36, and 48 h.p.i, while siRNA4 had a significant P value (≤0.0001) at 48 h.p.i. At 24 h.p.i, siRNA2 and siRNA4 showed statistical significance in viral knockdown of the virus's S gene and ORF1b gene by 95 %, 89 %, and 96 %, 97 %, respectively. Our computational method and experimental assessment of specific siRNAs have led us to conclude that siRNA2 and siRNA4 could be promising new therapies for SARS-CoV-2 that need further development.

Indexed as

Non-structure proteins (NSP)Open reading frame(ORF)SARS-CoV-2SilencingSiRNATherapy

Identifiers

PMID40256168
PMCPMC12008453

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LicenceCC BY
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Registered trials

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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.