ArticleJournal of personalized medicine2022
Discovering Tuberosin and Villosol as Potent and Selective Inhibitors of AKT1 for Therapeutic Targeting of Oral Squamous Cell Carcinoma.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 17 citations in OpenAlex.
- Article
- Unveiling Promising PARP12 Inhibitors through Virtual Screening for Cancer Therapy.Current pharmaceutical design · 2025Article
- CMSP suppresses oral squamous cell carcinoma progression by targeting the JAK2/STAT3/c-Myc axis.Frontiers in oncology · 2025Article
- Association ofInternational journal of molecular sciences · 2024Article
- Identification of potential bioactive phytochemicals for the inhibition of platelet-derived growth factor receptor β: a structure-based approach for cancer therapy.Frontiers in molecular biosciences · 2024Article
- Deoxyelephantopin induces cell death in oral cancer cells via the downregulation of AKT1-mTOR-mediated mechanisms.Journal of oral and maxillofacial pathology : JOMFPArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 7 institutions in 4 countries.
Funding
Abstract
Oral squamous cell carcinoma (OSCC) is a major cause of death in developing countries because of high tobacco consumption. RAC-alpha serine-threonine kinase (AKT1) is considered as an attractive drug target because its prolonged activation and overexpression are associated with cancer progression and metastasis. In addition, several AKT1 inhibitors are being developed to control OSCC and other associated forms of cancers. We performed a screening of the IMPPAT (Indian Medicinal Plants, Phytochemistry and Therapeutics) database to discover promising AKT1 inhibitors which pass through various important filters such as ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties, physicochemical properties, PAINS (pan-assay interference compounds) filters, PASS (prediction of activity spectra for substances) analysis, and specific interactions with AKT1. Molecules bearing admirable binding affinity and specificity towards AKT1 were selected for further analysis. Initially, we identified 30 natural compounds bearing appreciable affinity and specific interaction with AKT1. Finally, tuberosin and villosol were selected as potent and selective AKT1 inhibitors. To obtain deeper insights into binding mechanism and selectivity, we performed an all-atom molecular dynamics (MD) simulation and principal component analysis (PCA). We observed that both tuberosin and villosol strongly bind to AKT1, and their complexes were stable throughout the simulation trajectories. Our in-depth structure analysis suggested that tuberosin and villosol could be further exploited in the therapeutic targeting of OSCC and other cancers after further clinical validations.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.