SCIENTIFIC RESEARCH

New AI-predicted mTOR inhibitor shows promise in cancer treatment and ageing

16.05.2023

The mechanistic target of rapamycin (mTOR) kinase is one of the top drug targets for promoting health and lifespan extension. Besides rapamycin, only a few other mTOR inhibitors have been developed and shown their ability to slow ageing.

In this study, machine learning was used to predict novel small molecules targeting mTOR. One small molecule, TKA001, was selected based on in silico predictions of a high on-target probability, low toxicity, favorable physicochemical properties, and preferable ADMET profile.

The study confirmed TKA001 binding in silico by molecular docking. TKA001 potently inhibits both TOR complex 1 and 2 downstream signaling in vitro.

Furthermore, TKA001 inhibits human cancer cell proliferation in vitro and extended the lifespan of Caenorhabditis elegans, suggesting that TKA001 can slow ageing in vivo.

The study concluded that TKA001 is a promising candidate for the development of a new mTOR inhibitor that could be used to treat cancer and slow ageing.

AI-predicted mTOR inhibitor may slow ageing and treat cancer

Here are our key takeaways from the article,  AI-Predicted mTOR Inhibitor Reduces Cancer Cell Proliferation and Extends the Lifespan of C. elegans.

mTOR is a kinase that plays a role in cell growth and proliferation

mTOR stands for mechanistic target of rapamycin. It is a kinase, which is an enzyme that phosphorylates (adds a phosphate group to) other proteins. mTOR regulates a variety of cellular processes, including cell growth, proliferation, metabolism, and autophagy.

 

mTOR inhibitors can slow ageing and treat cancer

mTOR inhibitors are a class of drugs that block the activity of mTOR. mTOR inhibitors have been shown to slow ageing in animal models and to treat cancer in humans.

TKA001 is a novel mTOR inhibitor that was predicted by machine learning

TKA001 is a small molecule that was predicted by machine learning to be an mTOR inhibitor.

Machine learning is a type of artificial intelligence that can be used to analyse large amounts of data to identify patterns. In this case, the authors used machine learning to analyse the structures of known mTOR inhibitors to identify new potential mTOR inhibitors.

TKA001 inhibits mTOR signalling in vitro and in vivo

TKA001 was shown to inhibit mTOR signalling in vitro, which means that it blocked the activity of mTOR in cells grown in the laboratory.

TKA001 was also shown to inhibit mTOR signalling in vivo, which means that it blocked the activity of mTOR in animals.

Anti-cancer potential: TKA001 inhibits cancer cell proliferation in vitro

TKA001 was shown to inhibit the proliferation of cancer cells grown in the laboratory.

This means that TKA001 can stop cancer cells from growing and dividing.

Lifespan extension: TKA001 extends the lifespan of C. elegans

TKA001 was shown to extend the lifespan of C. elegans, a small nematode worm that is often used as a model organism for ageing research. This means that TKA001 can slow the ageing process in animals.

TKA001 is a promising candidate for the development of a new mTOR inhibitor that could be used to treat cancer and slow ageing

TKA001 is a promising new mTOR inhibitor that has shown potential for the treatment of cancer and the slowing of ageing.

However, more research is needed to confirm these findings and to determine the safety and efficacy of TKA001 in humans.

Reference: Vidovic T, Dakhovnik A, Hrabovskyi O, MacArthur MR, Ewald CY. AI-Predicted mTOR Inhibitor Reduces Cancer Cell Proliferation and Extends the Lifespan of C. elegans. International Journal of Molecular Sciences. 2023; 24(9):7850. https://doi.org/10.3390/ijms24097850

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