6 ms·

What are the immediate real-world applications of this? Just asking, because I have very little knowledge in this area.

candiodari 6y ago
Given the DNA code for one of the "machines" that run cells, we can generate an atomic model of that machine. This means we can "compile" (one part of) the DNA code. It was already possible, but so slow that entire datacenters would spend months calculating this for a single protein and even then we can't use them on the really complex ones at all, necessitating things like neutron spectroscopy which are totally insane, and only work on like 1% of proteins. This is useful because for example chemical simulation tools don't run on DNA code, but on atomic models. And also to produce "images" of the molecules (images between quotes because most proteins are too small to interact with reasonable photons, and no interaction with photons means you can't see them in any way) DNA has other parts that are really important but we don't understand at all yet, where this doesn't help at all. This applies to sections of DNA sent to ribosomes, to produce actual molecules. Besides that, there are pieces of DNA that "index" the DNA, pointers (from one gene to another), triggers (that for instance start production of an enzyme based on some external influence, like detection of a marker molecule) and export markers (that tell you what to do once the protein is produced, for example, mark a protein to be removed from the cell, incorporated into the cell membrane, or for instance used inside the cell nucleus, and there's also one that essentially says "at this point stop producing a protein and instead couple the rest of the DNA code to the end of the protein you just made").
- Rochus 6y ago
  This is about proteins, not DNA.
  - shawnz 6y ago
    Proteins which are coded by DNA.
    - Rochus 6y ago
      So what? The DNA only codes for the RNA and amino acid sequence. Structure determination is yet another topic. When we determine the protein structure we already know the sequence. Neither DeepMind has to look at the DNA to train their DNN.
      - shawnz 6y ago
        They are two topics which are both relevant to the discussion. Structure determination is what allows you to see the purpose/effect of the sequence that the DNA encoded.
        Rochus 6y ago
        Have you read the article? It's about protein structure determination. The DNA only determines the RNA and amino acid sequence. But who cares. I will get a bit less work and citations because http://cara.nmr.ch/doku.php http://cara.nmr.ch/doku.php will be less used in future.
  - candiodari 6y ago
    The full chain is DNA -> mRNA -> Ribosome -> tRNA combinations -> amino acid chain -> protein. It's true that in nature there are many steps between DNA and proteins (this list doesn't even include the steps that mediate the translation, ie. start it, stop it, slow it down, ...), but the structure of a protein is fully determined by the DNA code. Protein folding is about you start from the DNA code that is fed into the ribosome ignoring all the meta information, and come up with an atomic model (VERY long list like "H atom at 3.27,2.17,12.18, C atom at 2.87, 2.19, 12.33, ..."). Now there's a million niceties we've discovered to make this problem simpler and nicer looking, but that's what it boils down to.
    - Rochus 6y ago
      Thank you very much; almost forgot I did a Phd on the subject ;-) But anyway your answer does not contradict my statement. What you say belongs to the basics of molecular biology, but does not justify that DNA should be considered when determining the structure of proteins. In practice, the amino acid sequence is always already present.
      - Rochus 6y ago
        For the sceptics: if you read the referenced article, you will see that it is about protein structure determination by means of deep neural networks. It's not about gene expression, which is a different topic. What benefit does it have to respond to the question "What are the immediate real-world applications of this" (see above) by reciting some molecular biology dogmas from text books mixed with misconceptions, instead of responding to the real question?
        shawnz 6y ago
        Nobody is suggesting that this research has anything to do with gene expression or anything like that. Their point was simply that we now have better tools to actually see the meaning/effect of a given DNA sequence. Also, there is no need to passive-agressively highlight your credentials. I already researched them before replying.
Rochus 6y ago
> What are the immediate real-world applications of this? A protein is actually a linear sequence of amino acids, but in a cell this sequence has a three-dimensional arrangement like a clew of thread. The arrangement is not random, but dependent on the specific composition of the sequence (i.e. selection and order of amino acids) and some other factors. To understand the function of a protein, we need to know this three-dimensional arrangement (i.e. structure). Up to now the structure determination process was mostly manual, complex, time-consuming (several months up to more than a year) and error prone. If structure determination by DNN is reliable, this is a big win for life science. There are still a lot of problems open: e.g. the structure is not constant over time but there are "moving parts" in the structure which are important for its function.
randcraw 6y ago
For-profit corporations that value protein engineering will beat a path to DeepMind's door ASAP, like pharmas. Protein conformation prediction is essential when engineering new small-molecule drug compounds that must 'dock' with the specific proteins that regulate disease. Knowing how to create a protein with the precise shape to become biologically active has soaked up a lot of R&D funding toward pie-in-the-sky techniques that promise to advance that agenda (like quantum or DNA computing). If this method works as DeepMind says, it will immediately be adopted by every pharma to assess and tweak the shape of candidate proteins.
- dekhn 6y ago
  you give pharma too much credit. I had built a previous system to do something similar to this that produced excellent results and tried to give it away for free to Genentech, which ignored me. They said it didn't work for their purchasing department.
  - TheRealPomax 6y ago
    I don't believe you, but I look forward to you showing proof of this with some links (and if you tried giving it for free, I assume you just open sourced the whole deal, so I look forward to a repo link or the like).
    - dekhn 6y ago
      I developed the Exacycle system at Google and used it to publish my work (I wrote that blog entry): https://ai.googleblog.com/2013/12/groundbreaking-simulations-by-google.html https://ai.googleblog.com/2013/12/groundbreaking-simulations... we offered the service for free to Genentech since I used to work there and knew they could probably use it to get some good publications. We didn't open source the distributed computing framework, but the underlying technology (Folding@Home) is based on gromacs, which is open source. It's the scale at which it ran, and the processing pipeline for filtering the results that had the real value.
  - deeviant 6y ago

Given the DNA code for one of the "machines" that run cells, we can generate an atomic model of that machine. This means we can "compile" (one part of) the DNA code. It was already possible, but so slow that entire datacenters would spend months calculating this for a single protein and even then we can't use them on the really complex ones at all, necessitating things like neutron spectroscopy which are totally insane, and only work on like 1% of proteins. This is useful because for example chemical simulation tools don't run on DNA code, but on atomic models. And also to produce "images" of the molecules (images between quotes because most proteins are too small to interact with reasonable photons, and no interaction with photons means you can't see them in any way) DNA has other parts that are really important but we don't understand at all yet, where this doesn't help at all. This applies to sections of DNA sent to ribosomes, to produce actual molecules. Besides that, there are pieces of DNA that "index" the DNA, pointers (from one gene to another), triggers (that for instance start production of an enzyme based on some external influence, like detection of a marker molecule) and export markers (that tell you what to do once the protein is produced, for example, mark a protein to be removed from the cell, incorporated into the cell membrane, or for instance used inside the cell nucleus, and there's also one that essentially says "at this point stop producing a protein and instead couple the rest of the DNA code to the end of the protein you just made").

Rochus 6y ago
This is about proteins, not DNA.
- shawnz 6y ago
  Proteins which are coded by DNA.
  - Rochus 6y ago
    So what? The DNA only codes for the RNA and amino acid sequence. Structure determination is yet another topic. When we determine the protein structure we already know the sequence. Neither DeepMind has to look at the DNA to train their DNN.
    - shawnz 6y ago
      They are two topics which are both relevant to the discussion. Structure determination is what allows you to see the purpose/effect of the sequence that the DNA encoded.
      - Rochus 6y ago
        Have you read the article? It's about protein structure determination. The DNA only determines the RNA and amino acid sequence. But who cares. I will get a bit less work and citations because http://cara.nmr.ch/doku.php http://cara.nmr.ch/doku.php will be less used in future.
- candiodari 6y ago
  The full chain is DNA -> mRNA -> Ribosome -> tRNA combinations -> amino acid chain -> protein. It's true that in nature there are many steps between DNA and proteins (this list doesn't even include the steps that mediate the translation, ie. start it, stop it, slow it down, ...), but the structure of a protein is fully determined by the DNA code. Protein folding is about you start from the DNA code that is fed into the ribosome ignoring all the meta information, and come up with an atomic model (VERY long list like "H atom at 3.27,2.17,12.18, C atom at 2.87, 2.19, 12.33, ..."). Now there's a million niceties we've discovered to make this problem simpler and nicer looking, but that's what it boils down to.
  - Rochus 6y ago
    Thank you very much; almost forgot I did a Phd on the subject ;-) But anyway your answer does not contradict my statement. What you say belongs to the basics of molecular biology, but does not justify that DNA should be considered when determining the structure of proteins. In practice, the amino acid sequence is always already present.
    - Rochus 6y ago
      For the sceptics: if you read the referenced article, you will see that it is about protein structure determination by means of deep neural networks. It's not about gene expression, which is a different topic. What benefit does it have to respond to the question "What are the immediate real-world applications of this" (see above) by reciting some molecular biology dogmas from text books mixed with misconceptions, instead of responding to the real question?
      - shawnz 6y ago
        Nobody is suggesting that this research has anything to do with gene expression or anything like that. Their point was simply that we now have better tools to actually see the meaning/effect of a given DNA sequence. Also, there is no need to passive-agressively highlight your credentials. I already researched them before replying.

Rochus 6y ago

> What are the immediate real-world applications of this? A protein is actually a linear sequence of amino acids, but in a cell this sequence has a three-dimensional arrangement like a clew of thread. The arrangement is not random, but dependent on the specific composition of the sequence (i.e. selection and order of amino acids) and some other factors. To understand the function of a protein, we need to know this three-dimensional arrangement (i.e. structure). Up to now the structure determination process was mostly manual, complex, time-consuming (several months up to more than a year) and error prone. If structure determination by DNN is reliable, this is a big win for life science. There are still a lot of problems open: e.g. the structure is not constant over time but there are "moving parts" in the structure which are important for its function.

randcraw 6y ago

For-profit corporations that value protein engineering will beat a path to DeepMind's door ASAP, like pharmas. Protein conformation prediction is essential when engineering new small-molecule drug compounds that must 'dock' with the specific proteins that regulate disease. Knowing how to create a protein with the precise shape to become biologically active has soaked up a lot of R&D funding toward pie-in-the-sky techniques that promise to advance that agenda (like quantum or DNA computing). If this method works as DeepMind says, it will immediately be adopted by every pharma to assess and tweak the shape of candidate proteins.

dekhn 6y ago
you give pharma too much credit. I had built a previous system to do something similar to this that produced excellent results and tried to give it away for free to Genentech, which ignored me. They said it didn't work for their purchasing department.
- TheRealPomax 6y ago
  I don't believe you, but I look forward to you showing proof of this with some links (and if you tried giving it for free, I assume you just open sourced the whole deal, so I look forward to a repo link or the like).
  - dekhn 6y ago
    I developed the Exacycle system at Google and used it to publish my work (I wrote that blog entry): https://ai.googleblog.com/2013/12/groundbreaking-simulations-by-google.html https://ai.googleblog.com/2013/12/groundbreaking-simulations... we offered the service for free to Genentech since I used to work there and knew they could probably use it to get some good publications. We didn't open source the distributed computing framework, but the underlying technology (Folding@Home) is based on gromacs, which is open source. It's the scale at which it ran, and the processing pipeline for filtering the results that had the real value.
- deeviant 6y ago