# AI-designed proteins could help target cancer cells

Markdown copy of https://realalpha.app/s/ai-designed-proteins-could-help-target-cancer-cells/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Ray Kurzweil](https://realalpha.app/people/ray-kurzweil/) · Ray Kurzweil is an inventor, AI researcher and futurist.
- Host: [Peter Diamandis](https://realalpha.app/people/peter-diamandis/) · Founder & executive chairman, XPRIZE Foundation · Co-founded Singularity University and founded Zero-G; co-wrote the books Abundance and Bold.
- Show: Moonshots
- Episode: [The Man Who Predicted AGI Decades Ago w/ Ray Kurzweil | EP #125](https://realalpha.app/v/xqS5PDYbTsE/), Oct 24, 2024
- Moment: 40:21 to 42:57 of the episode (3 min), playing on https://realalpha.app/s/ai-designed-proteins-could-help-target-cancer-cells/; the episode from there: https://realalpha.app/v/xqS5PDYbTsE/?t=2421

## Quote

> “we can actually **design new proteins** that bind to a given target protein, and we can actually create something”
> — [Ray Kurzweil](https://realalpha.app/people/ray-kurzweil/) at [42:05](https://realalpha.app/v/xqS5PDYbTsE/?t=2525) · Moonshots

## Takeaways

1. AlphaFold predicted protein structures at a scale prior methods could not.
2. AlphaProteo can design proteins that bind to chosen targets.
3. A proposed protein flags cancerous division and destroys the cell.

## About this segment

Ray Kurzweil describes protein-design systems and a proposed cell-level cancer detector. The example shows how AI-generated proteins could move from prediction toward treatment.

From “The Man Who Predicted AGI Decades Ago w/ Ray Kurzweil | EP #125”, Oct 24, 2024. [Watch the full episode](https://realalpha.app/v/xqS5PDYbTsE/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[40:26](https://realalpha.app/v/xqS5PDYbTsE/?t=2426) Yeah, we just saw two Nobel Prizes, obviously, the prize that Jeffrey Hinton received, and then the prize that Demis and John Gemper received, both at DeepMind, related to AI and directly in AI, you know, in AlphaFold. Yes, it was very much for AI. Yes, it was a great year. And here's the question. It seems to me like I would imagine in the next two to 10 years and then beyond, almost every Nobel Prize in chemistry, math and physics will be enabled by or directly discovered by AI. Do you agree with that?

[41:15](https://realalpha.app/v/xqS5PDYbTsE/?t=2475) yes i mean right now 95 of the nobel prizes in medicine go to people with mds i think they should get rid of that requirement uh because computer scientists they may not have studied anything but they know computer science and they can develop alpha fold for example which should stymie human beings 50 years get alpha fold yeah i remember when i was a medical school the the huge grand challenge was can you predict the folding of a protein yeah it was the unknown super some people could do that but they didn't do it very accurately and we only did a few hundred thousand then one year we did you know 200 million proteins and when one year and then alpha proteo we can actually design new proteins that bind to a given target protein, and we can actually create something, for example, that goes into a cell, determine

[42:19](https://realalpha.app/v/xqS5PDYbTsE/?t=2539) whether or not it can divide cancerously, and if it divides cancerously, it will set a flag, and if that flag is set, it will destroy. that cell. So basically, there would be a cure for cancer. And we can actually do that with alpha proteo. We have to actually design the protein. So there's a few steps left. But that's actually done a very large fraction of curing cancer, for example. Let's switch on that note to the subject