AI-Predicted mTOR Inhibitor Reduces Cancer Cell Proliferation and Extends the Lifespan of C. elegans
OPEN ACCESS
Loading...
Author / Creator
Date
2023-05-01
Publication Type
Journal Article
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
Abstract
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 to be capable of slowing aging. We used machine learning to predict novel small molecules targeting mTOR. We selected one small molecule, TKA001, based on in silico predictions of a high on-target probability, low toxicity, favorable physicochemical properties, and preferable ADMET profile. We modeled TKA001 binding in silico by molecular docking and molecular dynamics. TKA001 potently inhibits both TOR complex 1 and 2 signaling in vitro. Furthermore, TKA001 inhibits human cancer cell proliferation in vitro and extends the lifespan of Caenorhabditis elegans, suggesting that TKA001 is able to slow aging in vivo.
Permanent link
Publication status
published
External links
Editor
Book title
Journal / series
Volume
24 (9)
Pages / Article No.
7850
Publisher
MDPI
Event
Edition / version
Methods
Geographic location
Date collected
Date created
Subject
AI drug discovery; mTOR; rapalog; C. elegans; cancer; longevity
Organisational unit
09598 - Ewald, Collin Y. (ehemalig) / Ewald, Collin Y. (former)
Notes
Funding Info about funding
Related publications and datasets
Is new version of: https://doi.org/10.3929/ethz-b-000648270