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Chemistry Nobel: Computational protein design and protein structure prediction

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Re: Chemistry Nobel: Computational protein design and protein structure prediction

#251

Post by IncreasePosts »

stonemetal12 wrote: post #169
DevX101 wrote: post #155

Earlier quoted context omitted.

If you gave the $300,000 Bezos got from his father to 10,000 random Americans in 1994, none of them would have created a company the equivalent of Amazon's scale.

How many of those 10k would have the same background? We can pretend Bezos' dad raised him in a "normal" middle class background then randomly dropped 300K on him, or we can acknowledge he is the business equivalent of an Olympic athlete.

Miguel worked at Exxon for 32 years as an engineer and a manager. It's not like he was the CEO or anything close to that. There would literally be hundreds of thousands of people in a similar position to him across the world.

Also worth noting that Jeff Bezos was(and I think still is) the youngest person who ever became a senior VP at DE Shaw. That is a position earned by merit alone.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#252

Post by JangoSteve »

eig wrote: post #117

I think I disagree with most of the comments here stating it’s premature to give the Nobel to AlphaFold. I’m in biotech academia and it has changed things already. Yes the protein folding problem isn’t “solved” but no problem in biology ever is. Comparing to previous bio/chem Nobel winners like Crispr, touch receptors, quantum dots, click chemistry, I do think AlphaFold already has reached sufficient level of impact.

Interestingly, the award was specifically for the impact of AlphaFold2 that won CASP 14 in 2020 using their EvoFormer architecture evolved from the Transformer, and not for AlphaFold that won CASP 13 in 2018 with a collection of ML models each separately trained, and which despite winning, performed at a much lower level than AlphaFold2 would perform two years later.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#253

Post by svara »

jhbadger wrote: post #152
trott wrote: post #82

Earlier quoted context omitted.

> There are few approaches that will accelerate the field of drug development and chemistry as a whole in a way that the works of these three people will. As the author of one such approach, I'm skeptical. AlphaFold 2 just predicts protein structures. The thing about proteins is that they are often related to each other. If you are trying to predict the structure of a naturally occurring protein, chances are that the…

Protein structures are similar to each other because of evolution (protein families exist because of shared ancestry of protein coding genes). It's not a weird coincidence that helps ML; it's inherent in the problem. Same with drug design -- very, very, few drugs are "novel" as opposed to being analogues of something naturally in the body.

They're referring to the structure of the protein when a drug is bound, that's what's novel. Novel as in, you can't think of it as "just" interpolation between known structures of evolutionarily related proteins.

That said I'm not sure that's entirely fair, since Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured.

You're quite wrong about small molecule drug structures. Historically that has been the case but these days many lead structures are made by combinatorial chemistry and are not derived from natural products.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#254

Post by adastra22 »

roughly wrote: post #240
eig wrote: post #117

I think I disagree with most of the comments here stating it’s premature to give the Nobel to AlphaFold. I’m in biotech academia and it has changed things already. Yes the protein folding problem isn’t “solved” but no problem in biology ever is. Comparing to previous bio/chem Nobel winners like Crispr, touch receptors, quantum dots, click chemistry, I do think AlphaFold already has reached sufficient level of impact.

It also proved that deep learning models are a valid approach to bioinformatics - for all its flaws and shortcomings, AlphaFold solves arbitrary protein structure in minutes on commodity hardware, whereas previous approaches were, well, this: https://en.wikipedia.org/wiki/Folding@home A gap between biological research and biological engineering is that, for bioengineering, the size of the potential solution space and…

AlphaFold doesn’t work for engineering though. Getting a shitty answer ends up being worse than useless.

It seems to really accelerate productivity of researchers investigating bio molecules or molecules very similar to existing bio molecules. But not de novo stuff.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#255

Post by adastra22 »

mk_stjames wrote: post #218
ThePhysicist wrote: post #67

Demis Hasabis has a really interesting and unusual CV for a nobel laureate [1], he started his career in AI game programming (he worked e.g. on Popoulous II, Syndicate, Theme Park for Bullfrog, and later for Lionhead Studios on Black & White) before doing a PhD in neuroscience, becoming an entrepreneur and starting DeepMind. I would say this is a refreshing and highly uncommon pick for a nobel prize, really cool to s…

I'm always interested in hearing about these people who go and get a PhD in an unrelated field to their original studies, often years after leaving university and working in an industry. Here it says Hasabis did an undergraduate degree in a computer science program, and them spent a decade working on computer games at studios, and then somehow just rocked up to a university and asked to do a PhD in neuroscience. I fe…

Why do you think that? It’s not my experience. At the grad school level they’ll take anyone who can do the work and is interested. Outside experience, even in unrelated fields, is often a plus. Grad students just out of undergrad have no idea how the world works.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#256

Post by adastra22 »

stonemetal12 wrote: post #169
DevX101 wrote: post #155

Earlier quoted context omitted.

If you gave the $300,000 Bezos got from his father to 10,000 random Americans in 1994, none of them would have created a company the equivalent of Amazon's scale.

How many of those 10k would have the same background? We can pretend Bezos' dad raised him in a "normal" middle class background then randomly dropped 300K on him, or we can acknowledge he is the business equivalent of an Olympic athlete.

I think you are agreeing with the poster you are responding to, right? Bezos is the equivalent of an Olympic athlete: a combination of innate talent as well as opportunity.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#257

Post by jhbadger »

svara wrote: post #253
jhbadger wrote: post #152

Earlier quoted context omitted.

Protein structures are similar to each other because of evolution (protein families exist because of shared ancestry of protein coding genes). It's not a weird coincidence that helps ML; it's inherent in the problem. Same with drug design -- very, very, few drugs are "novel" as opposed to being analogues of something naturally in the body.

They're referring to the structure of the protein when a drug is bound, that's what's novel. Novel as in, you can't think of it as "just" interpolation between known structures of evolutionarily related proteins. That said I'm not sure that's entirely fair, since Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured. You're quite wrong ab…

But even drugs made by combinatorial chemistry still generally end up being analogues of natural products even if they aren't derived from them. As Leslie Orgel said "Evolution is cleverer than you are"; chemists are unlikely to discover a mechanism of action that millions of years of evolution hasn't already found.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#258

Post by adastra22 »

svara wrote: post #253
jhbadger wrote: post #152

Earlier quoted context omitted.

Protein structures are similar to each other because of evolution (protein families exist because of shared ancestry of protein coding genes). It's not a weird coincidence that helps ML; it's inherent in the problem. Same with drug design -- very, very, few drugs are "novel" as opposed to being analogues of something naturally in the body.

They're referring to the structure of the protein when a drug is bound, that's what's novel. Novel as in, you can't think of it as "just" interpolation between known structures of evolutionarily related proteins. That said I'm not sure that's entirely fair, since Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured. You're quite wrong ab…

> Alphafold does, as far as I know, work for predicting structures that are far away from structures that have previously been measured.

It did very poorly at this last time I checked. Maybe AlphaFold3 is better?

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#259

Post by fastball »

onursurme wrote: post #87
fastball wrote: post #54

Earlier quoted context omitted.

Not all of the work. For example, it doesn't account for the fact that Demis Hassabis, as head of DeepMind, undoubtedly recruited many of the co-authors to participate in this effort, which is worth something when it comes to the final output.

To recruit isn't scientific work.

I didn't realize the Nobel specified that the only work which mattered was that of the "scientific" variety.

Re: Chemistry Nobel: Computational protein design and protein structure prediction

#260

Post by [deleted] »

mk_stjames wrote: post #218
ThePhysicist wrote: post #67

Demis Hasabis has a really interesting and unusual CV for a nobel laureate [1], he started his career in AI game programming (he worked e.g. on Popoulous II, Syndicate, Theme Park for Bullfrog, and later for Lionhead Studios on Black & White) before doing a PhD in neuroscience, becoming an entrepreneur and starting DeepMind. I would say this is a refreshing and highly uncommon pick for a nobel prize, really cool to s…

I'm always interested in hearing about these people who go and get a PhD in an unrelated field to their original studies, often years after leaving university and working in an industry. Here it says Hasabis did an undergraduate degree in a computer science program, and them spent a decade working on computer games at studios, and then somehow just rocked up to a university and asked to do a PhD in neuroscience. I fe…

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