Evidence mapPaperPMID 41477589Full record

ArticleFrontiers in bioinformatics2025

In silico identification of novel natural compounds as potential KIFC1 inhibitors for the therapeutic intervention of triple-negative breast cancer.

Prashant Kumar Tiwari, Mukesh Kumar, Richa Mishra, Xiaomeng Zhang, Sanjay Kumar

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Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Prashant Kumar TiwariBiological and Bio-computational Lab, Department of Life Science, Sharda School of Bio-Science & Technology, Greater Noida, Uttar Pradesh, India.
Mukesh KumarDepartment of Optometry, School of Medical and allied Sciences, Galgotias University, Greater Noida, India.
Richa MishraDepartment of Computer Engineering, Parul Institute of Engineering and Technology (PIET), Parul University, Vadodara, Gujarat, India.
Xiaomeng ZhangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Sanjay KumarBiological and Bio-computational Lab, Department of Life Science, Sharda School of Bio-Science & Technology, Greater Noida, Uttar Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

TNBC is an aggressive and various subtype of breast cancer, notable by the lack of specific oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), consequential in limited treatment options and poor prognosis. Kinesin Family Member C1 (KIFC1), a mitotic motor protein critical for centrosome clustering and spindle formation, has critical role in TNBC progress. In this situation, natural compounds were explored as probable inhibitors of this protein. we utilized molecular docking, ADMET profiling, density functional theory calculations, molecular dynamics simulations, MM/GBSA binding free energy analysis, and principal component analysis to thoroughly evaluate binding affinity, stability, and drug-likeness property of natural compounds against KIFC1. Of the 36,900 compounds utilized, five natural compounds were carefully chosen for further assessment. All five compounds Fosfocytocin, Molybdopterin Compound Z, 5-amino-2-(3-hydroxy-13-methyltetradecanamido) pentanoic acid, TMC-52A, and Muscimol exhibited significant inhibitory efficacy against KIFC1. These compounds demonstrated persistent interactions with critical residues and had advantageous binding properties in computational evaluations. The results collectively indicate their potential as effective inhibitors for targeting KIFC1 in forthcoming studies. These data collectively identify all five natural compounds as possible inhibitors of KIFC1. Nonetheless, their effectiveness and safety must be confirmed through

Indexed as

KIFC1MD simulationnatural compoundsprincipal component analysisTriple negative breast cancer

Identifiers

PMID41477589
PMCPMC12748000

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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 Socratic graph.