Venki Ramakrishnan
speaker
313 appearances
2 recordings
2 series
first heard Sep 2024
last heard 25 Apr
Venki Ramakrishnan’s voice in public audio — every appearance, attributed to the second.
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Yeah, that's true. And I think the science of visualization in molecular biology has advanced tremendously. I mean, first it was X-ray crystallography. And now more recently, there's cryo-electron microscopy. And also now predictive algorithms for protein domains and proteins using AI, which is also having a big impact in structural biology.
Yeah, the ribosome, as I said, it's large in molecular terms, but of course, it's only a couple of hundred nanometers across. So you can't really see it with an ordinary microscope, but you can see them under an electron microscope. And the big progress in the visualization field
is that electron microscopy is advanced as a result of better detectors, better algorithms, faster detectors so that they can freeze the movement of particles while they're collecting the image. And that means that you can get high resolution atomic level images without using crystallography. So you don't even need crystals, which is what you needed for x-rays. And that was a big bottleneck.
And the other thing about electron microscopy is you need tiny amounts of sample, and they don't even have to be pure. You can sort the particles computationally. So that has been a big game changer. And it struck me, there was a paper in BioRxiv just a few months ago where they had looked at ribosomes inside a cell. So they hadn't even broken open the cell to purify it.
They just looked at thousands of ribosomes inside cells classified them into groups, and got a whole bunch of structures, each of which represents a snapshot of a ribosome. So what took us years of work, I mean, these guys did, you know, within weeks.
But that's just how science is, right?
We did the painful way of... producing crystals which would take eight weeks to grow and were tiny. Then you'd have to take them to a synchrotron, these powerful x-ray sources, and hit them with x-rays and then analyze the data. And then eventually, if everything went well, you would get an image. And the first images were quite fuzzy. They were what we call low resolution images.
You couldn't see atomic detail, but you could see broader features, like you could see a double helix for the RNA. RNA, of course, also forms double helices like DNA. And when we saw that first double helix in the image of the ribosome, that was a very exciting moment because we knew that it was real because it had the features that you would expect. So it was a very exciting time.
You know, I think... You know, smaller pieces of RNA had been already crystallized and their structures determined. So we knew that that's what RNA double helices should look like. I mean, the thing about the ribosome is not the structure of the individual pieces, but rather how they were put together in this large complex and how they interacted, how the different pieces interacted.
That's still basically the story. Of course, there are some genes which are never made into proteins. They stay as RNAs. And there are other parts of DNA and RNA that are involved in control, you know, start here or do this in response to this stimulus. So there are lots of control signals, but the part that codes for the protein
That's the heart of what we call messenger RNA or mRNA, which again, nobody had heard of a few years ago, but then COVID came along and everybody started shooting mRNA into their muscle. And of course, what that mRNA had was the gene for the spike protein of coronavirus. So when it went into our cells, our ribosomes latched onto it.
and made spike protein and displayed it to our immune system to react. So it's a perfect example of how all this molecular biology knowledge that we had accumulated over decades suddenly became useful. during a pandemic. People think that the vaccine took 11 months to develop, but actually it took decades.
And it just so happened that we were at a time, at a point in time where we could very quickly implement these platforms.
It's jumpy in the sense it's stochastic, but it's fairly deterministic. To give you an example, the error rate in making a protein is typically one in a thousand to one in 10,000. And that's quite a low error rate. It's much lower than the best peptide synthesizers that humans can make in the lab, have a much higher error rate and are much slower.
I mean, a bacterial ribosome adds about 20 residues a second. So if you made a movie of a bacterial ribosome, it would just be a blur. In fact, I have a movie that I sometimes show, and I show it slowly with all the players coming in and out. And then I say, okay, now I'm going to speed it up to real time. And it's just a blur. So it's an amazing machine.
And yes, it's stochastic in the sense binding is stochastic. But there is a deterministic... direction to it. And that's because energy is used at each step. And that's what thermodynamically drives it forward in the forward direction.
Yeah, so the fact that ribosomes can crystallize suggests that ribosomes are largely identical But there's now a debate in the field.
There are a group of scientists who believe that ribosomes can be specialized, that in some cells you may get subsets of ribosomes which translate particular mRNAs or translate under certain, you know, translate meaning translate the genetic information into protein. So that they work under certain circumstances. And this field of specialized ribosomes is still somewhat controversial.
But it does have some strong advocates. And I think... I would say the jury's still out, but there is some evidence for specialized ribosomes.
Very similar. They're not exactly the same because there'll be small genetic differences. So just like, you know, for example, a mouse may be well over 95% or so identical to in some ways to humans. But of course, that same degree will apply to ribosomes and ribosomal proteins. But I will tell you one thing, the core of the ribosome, the part where the amino acids are joined,
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