ArticleGenes2025
Integrative Genomic and in Silico Analysis Reveals Mitochondrially Encoded Cytochrome C Oxidase III (MT-CO3) Overexpression and Potential Neem-Derived Inhibitors in Breast Cancer.
Article in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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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.
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Who cites it
7 citing papers in PubMed.
- A critical appraisal of structure-based virtual screening, binding free energy methods, and AI-driven molecular design across the evolving computational landscape of drug discovery.Journal of computer-aided molecular design · 2026Review
- PlasmidRiskNet: An explainable machine-learning framework for antimicrobial resistance plasmid risk stratification.New microbes and new infections · 2026Article
- Artificial intelligence-driven cross-endpoint stacked ensemble learning for separate but meta-feature coupled prediction of six human pharmacokinetic endpoints with RDKit molecular representation and applicability domain control on real TDC benchmark data.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Integration of Clinical Pharmacokinetic Database With Compartmental Modeling and Regulatory Data Analysis.Current therapeutic research, clinical and experimental · 2026Article
- Selective modulation of orexinergic receptors by neem-derived phytochemicals: Computational analysis of structure-activity relationships.Toxicology reports · 2025Article
- Integrated Virtual Screening for Anti-Caries Compounds from Neem: Dual-Target Inhibition of Biofilm Formation and Bacterial DNA Replication.Biomedicines · 2025Article
- Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe increasing global incidence of breast cancer calls for the identification of new therapeutic targets and the assessment of possible neem-derived inhibitors by means of computational modeling and integrated genomic research.
methodsOriginally looking at 59,424 genes throughout 42 samples, we investigated gene expression data from The Cancer Genome Atlas-Breast Cancer (TCGA-BRCA) dataset. We chose 286 genes for thorough investigation following strict screening for consistent expression. R's limma package was used in differential expression analysis. The leading candidate's protein modeling was done with Swiss-ADME and Discovery Studio. Molecular docking studies, including 132 neem compounds, were conducted utilizing AutoDock Vina.
resultsAmong the 286 examined, mitochondrially encoded cytochrome C oxidase III (MT-CO3) turned out to be the most greatly overexpressed gene, showing consistent elevation across all breast cancer samples. Protein modeling revealed a substantial hydrophobic pocket (volume: 627.3 Å
conclusionConnecting traditional medicine with current genomics and computational biology, this work proposes a methodology for structure-guided drug design and development using neem-derived chemicals and finds MT-CO3 as a potential therapeutic target for breast cancer.
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Registered trials
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.