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AI built to find anti-aging chemical compounds

Date:
July 22, 2021
Source:
University of Surrey
Summary:
Scientists have built an artificial intelligence (AI) model that identifies chemical compounds that promote healthy aging - paving the way towards pharmaceutical innovations that extend a person's lifespan.
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The University of Surrey has built an artificial intelligence (AI) model that identifies chemical compounds that promote healthy ageing -- paving the way towards pharmaceutical innovations that extend a person's lifespan.

In a paper published by Nature Communication's Scientific Reports, a team of chemists from Surrey built a machine learning model based on the information from the DrugAge database to predict whether a compound can extend the life of Caenorhabditis elegans -- a translucent worm that shares a similar metabolism to humans. The worm's shorter lifespan gave the researchers the opportunity to see the impact of the chemical compounds.

The AI singled out three compounds that have an 80 per cent chance of increasing the lifespan of elegans:

  • flavonoids (anti-oxidant pigments found in plants that promote cardiovascular health),
  • fatty acids (such as omega 3), and
  • Organooxygens (compounds that contain carbon to oxygen bonds, such as alcohol).

Sofia Kapsiani, co-author of the study and final year undergraduate student at the University of Surrey, said:

"Ageing is increasingly being recognised as a set of diseases in modern medicine, and we can apply the tools of the digital world, such as AI, to help slow down or protect against ageing and age-related diseases. Our study demonstrates the revolutionary ability of AI to aid the identification of compounds with anti-ageing properties."

Dr Brendan Howlin, lead author of the study and Senior Lecturer in Computational Chemistry at the University of Surrey, said:

"This research shows the power and potential of AI, which is a speciality of the University of Surrey, to drive significant benefits in human health."


Story Source:

Materials provided by University of Surrey. Note: Content may be edited for style and length.


Journal Reference:

  1. Sofia Kapsiani, Brendan J. Howlin. Random forest classification for predicting lifespan-extending chemical compounds. Scientific Reports, 2021; 11 (1) DOI: 10.1038/s41598-021-93070-6

Cite This Page:

University of Surrey. "AI built to find anti-aging chemical compounds." ScienceDaily. ScienceDaily, 22 July 2021. <www.sciencedaily.com/releases/2021/07/210722163003.htm>.
University of Surrey. (2021, July 22). AI built to find anti-aging chemical compounds. ScienceDaily. Retrieved February 21, 2024 from www.sciencedaily.com/releases/2021/07/210722163003.htm
University of Surrey. "AI built to find anti-aging chemical compounds." ScienceDaily. www.sciencedaily.com/releases/2021/07/210722163003.htm (accessed February 21, 2024).

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