Evidence map›Paper›PMID 37780803›Full record

Article3 Biotech2023

Computational design and validation of effective siRNAs to silence oncogenic KRAS.

Prasanna Srinivasan Ramalingam, Sivakumar Arumugam

Open access · greenAbstract read
In one paragraph

Article in 3 Biotech, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 11 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

2 authors at 1 institution in 1 country.

Prasanna Srinivasan RamalingamProtein Engineering Lab, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India.ORCID 0000-0002-8281-2779
Sivakumar ArumugamProtein Engineering Lab, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India.ORCID 0000-0001-8834-8834
Vellore Institute of Technology University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oncogenic KRAS mutations drive cancer progression in lung, colon, breast, and pancreatic ductal adenocarcinomas. Apart from the current strategies, such as KRAS upstream inhibitors, downstream effector inhibitors, interaction inhibitors, cell cycle inhibitors, and direct KRAS inhibitors, against KRAS-mutated cancers, the therapeutic small interfering RNAs (siRNAs) represent a promising alternative strategy that directly binds with the target mRNA and inhibits protein translation via mRNA degradation. Here, in the present study, we utilized various in silico approaches to design potential siRNA candidates against KRAS mRNA. We have predicted nearly 17 siRNAs against the KRAS mRNA, and further through various criteria, such as U, R, and A rules, GC%, secondary structure formation, mRNA-siRNA duplex stability, Tm (Cp), Tm (Conc), and inhibition efficiency, they have been filtered into 4 potential siRNAs namely siRNA8, siRNA11, siRNA12, and siRNA17. Further, the molecular docking analysis revealed that the siRNA8, siRNA11, siRNA12, and siRNA17 showed higher negative binding energies, such as - 379.13 kcal/mol, - 360.19 kcal/mol, - 288.47 kcal/mol, and - 329.76 kcal/mol, toward the human Argonaute2 protein (hAgo2) respectively. In addition, the normal mode analysis of the hAgo2-siRNAs complexes indicates the structural changes and deformation of the hAgo2 protein upon the binding of siRNA molecules in the dynamic environment which suggests that these siRNAs could be effective. Finally, we conclude that these 4 siRNAs have therapeutic potential against KRAS mRNA and also have to be studied in vitro and in vivo to evaluate their specificity toward mutant KRAS (not degrading wild-type KRAS) Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03767-w.

Indexed as

CancerGene silencingKRASRNA interferencesiRNA

Identifiers

PMID37780803
PMCPMC10541393
OpenAlexW4387187204

What Socratic 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 Socratic graph.