Evidence map›Paper›PMID 42040413›Full record

ArticleACS omega2026

Molecular Dynamics Simulation-Assisted siRNA Design for Dual-Ubiquitinated SKP2 Silencing via Ago2 Anchoring in Breast Cancer.

Manshi Kumari Gupta, Chinnappan Sudandiradoss

Abstract read
In one paragraph

Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Manshi Kumari GuptaDepartment of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu 632014, India.
Chinnappan SudandiradossDepartment of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu 632014, India.ORCID https://orcid.org/0000-0001-5144-8612

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

S-phase kinase-associated protein 2 (SKP2) functions as a dual-ubiquitin modulator in breast cancer progression by orchestrating two distinct ubiquitination process. Through Ub-K48-linked degradation, SKP2 facilitates proteasomal turnover of tumor suppressors while Ub-K63-linked modification amplifies oncogenic signaling cascades. Together, these mechanisms drive uncontrolled cell proliferation, enhance metastatic potential, and contribute to therapeutic resistance. To therapeutically intercept SKP2, this study employed a consolidated structural informatics framework to rationally design small interfering RNAs (siRNAs) with high target specificity. Commencing with a curated library of 127 siRNA sequences, a multiparametric filtration cascade of thermodynamic profiling, secondary structure interrogation, and genome-wide off-target exclusion refined the pool of eight high-confidence siRNA candidates. These were further subjected to binding against human Argonaute 2 (hAgo2), a catalytic epicenter of the RNA-induced silencing complex (RISC). Interestingly, siRNA 10 and siRNA 11 emerged as lead candidates, exhibiting robust binding affinities, precise spatial accommodation within the Ago2 binding cleft, and predicted silencing efficiencies of 96.5%. To further assess their dynamic stability and conformational behavior, all-atom molecular dynamics simulations were performed to both bound and unbound siRNA with the Ago2 complex using the CHARMM-GUI interface and CHARMM36m force field, optimized for RNA-protein interactions. We report our designed siRNA 10 (5'AUCACUUAAGUCUAGAUGGAC'3) and siRNA 11 (5'UAUCACUUAAGUCUAGAUGGA'3) for precise silencing of SKP2, offering a targeted therapeutic avenue to disrupt dual-ubiquitin-driven oncogenic progression in breast cancer.

Identifiers

PMID42040413
PMCPMC13103777

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LicenceCC BY-NC-ND
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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.