Programmable protein responses could give researchers finer control over when cellular processes begin and end. Krishna and Lester compare the possibilities with early computing, while treating that comparison as a way to imagine future uses rather than a prediction of a finished technology. The immediate contribution is a method for evolving dynamic behavior that can support further experiments.
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49:58you know have proteins that only turn on based on an external stimuli that we define. >> Mh. >> And so, right, you know, if you're putting something in the body, you don't want it to be always be on. >> You want it to be on only when you want it to be on. >> And now we kind of have the early makings of a mechanism that we can repeat that is discrete, controllable. Y >> and has also the ability to terminate at the end which is like different you know the we we talked about a story for example where it's you have the halflife of a drug in the body and drugs can have a really long halflife which then goes really and but
50:39>> you can't really >> you can't just decide today we want to turn it off. You kind of just need to let it >> the system dissipate naturally. >> In this case for this particular use case we can say like nope we're done. >> Yeah. Yeah. And and I just I the the possibility of all the stuff that we can do with this is endless, right? So So it's really it's really like like when I say that like like you know right now I don't have exact ideas about how this is going to be used. But that's kind of the beauty of it. It's so it's such a new paradigm to take this oscillator tie it to the cell cycle and make it such that the protein toggles on and off. Right now it's a whole new avenue of directed
51:20evolution that we can now use to create a myriad of different proteins. A space that we didn't even have access to before. >> Right. >> It would it would have would a a an analogy that makes sense be like it's like when we first figured out how to use binary in computing systems. >> Yeah. Like even before the transistor, right, the the vacuum tube was big was huge. >> Right. >> Yeah. >> Right. And we didn't know that we were going to get Uber or or Facebook when we were starting to just be like, "Oh, we can like have an on andoff game." >> Yeah. Uh that that's >> Yeah. Imagine all the logic that we can now put in a cell in a cell. >> In a cell, we we can have the same level
52:00of sort of software style engineering that we have in computers. Again, I know there's a lot of other details in >> Yeah. Yeah. Yeah. This will be more machine language, >> right? But as a as a rough kind of reference point for people to try to understand who might not be who might not grasp the concept as organically uh we are building our own ability to create programs at a biological level. >> Yes. Exactly. >> Like the equivalent of software program. >> It's the it's it's the beginning of that. >> It's the very very early early early early stages. >> Yeah. It's exciting. >> This is very very good. And this was this came out of um I want to make sure
52:41>> that's right echol something something >> echoly technique federal de la there we go >> university deirut beirut not beirut b a y r e u t h >> not the uh anyway uh >> we got to be careful of that so no but but this is and again you know um >> it's so it's very this was very dense. >> Yeah. >> Um but I I think it's again the the level of depth of previous knowledge and work. >> Mhm. That created the base by which
53:21these researchers are now building on top of to try to move away from this previous directed evolutionary approach and trying to find a way to be able to create these control mechanisms within it and the three different breakthroughs. >> It was just it was just proof of concept. They were just doing proof of concept. Imagine what other people are going to come up with. Right. >> Right. Right. And that's another interesting point is like not all people are sometimes like well not all not all science is has a consumer product at the end of it. >> It's just more science >> right >> but imagine the amount of more science we can do with this new tool >> which will ultimately end up in real world yeah >> uh impacts this is very different than
54:02>> uh folks who well I was going to I was going to talk about dark matter which we'll never figure out and we'll never know in our lifetime. So that's one area where we don't have the ability to have real world impacts. Um, fascinating, fascinating story. Uh, we've had a lot of protein stories. I mean, we we talked about the the Yale uh, uh, Lego block story last year. >> Yeah. I mean, at the end of the day, when you get to the molecular level, everything is proteins, right? Right. >> And we have to we have to be we want to
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