Article3 Biotech2021
In silico identification of potential inhibitor for TP53-induced glycolysis and apoptosis regulator in head and neck squamous cell carcinoma.
Article in 3 Biotech, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 7 citations in OpenAlex.
- Metabolic Regulation of Immune Responses: Molecular Mechanisms, Diseases, and Therapeutic Targets.MedComm · 2026Review
- Phosphofructokinase-1 redefined: a metabolic hub orchestrating cancer hallmarks through multi-dimensional control networks.Journal of translational medicine · 2025Review
- Article
- Anticancer Potential of Sulfonamide Moieties via In-Vitro and In-Silico Approaches: Comparative Investigations for Future Drug Development.International journal of molecular sciences · 2023Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Head and neck squamous cell carcinoma (HNSCC) is the six most common cancer globally and most common cancer in men in India. The metabolic regulation is highly altered and is considered as a hall mark of HNSCC. TP53-induced glycolysis and apoptosis regulator (TIGAR) plays very important role in the development and progression of HNSCC. The aim of our study is to identify a novel FDA approved anticancer inhibitor against mutated TP53-induced glycolysis and apoptosis regulator (TIGAR) through drug repurposing approach. A library of 105 FDA approved anticancer compounds were screened using molecular docking approach against TIGAR (PDB: 3DCY) both Wild-Type (WT) and mutated (Mut). Specific mutations in TIGAR were identified using cBioPortal, a cancer genomics database and mutated structure was modelled using SWISS-MODEL. Out of 510 sequenced cases/patients samples, 17(3%) patients showed alteration in TIGAR [TIGAR
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Registered trials
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