AlphaFold 2 is here: what’s behind the structure prediction miracle
91–98 of 98 posts
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#92So... could anyone with experience in the area give an estimate of how much the likelihood of an unstoppable, untraceable "DIY" bioweapon appearing in the next decade has increased thanks to this?
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#93To me the most interesting part of the article is the cometary on where basic research is going to happen in the future. The fear is that if it only happens in large companies, then the unbiased pool of experts society relies on will be smaller and less informed. Along with the issue of nobody being around for the slog of defining a field, setting up databases, competitions and standards. These are what allow well fu…
> DeepMind claimed that they used “128 TPUv3 cores or roughly equivalent to ~100-200 GPUs”. Although this amount of compute seems beyond the wildest dreams of most academic researchers... So, we're talking like what? Maybe $100K to $300K of hardware? Wet biology labs often have multiple pieces of $100K+ equipment at their disposal. Why shouldn't computational labs too?
All the experimentation and fine tuning probably meant thousands of trials which may have been significantly bigger scale before they got the model optimised ...
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#94Earlier quoted context omitted.
If we can accurately predict protein structures (particularly multiple structures, or structures reflecting what the conformation is in cells), then we can do a couple things: - better predict drug binding to proteins (massive benefits if accurate) - better understand the functional outcomes of missense mutations on proteins - study protein-protein interactions - and in general, just gain a better understanding of bi…
More ominously, this makes it easier for the gain-of-function researchers to more accurately engineer their viruses to bind to human receptors.
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#95Earlier quoted context omitted.
The goal all along has been to design proteins with a specific structure. This can be applied to just about any area of biology. You could design novel antigens to combat disease, and then easily mass-produce them. Or just inject the RNA to have the body produce them. But the applications are boundless, from genetically modifying crops, to anti-aging, and more. It is also one of the key pathways to molecular nanotech…
Is it the structure that's important? Or is the structure just a way to combine certain amino acids in a stable manner and its the combination of acids that we care about? Or is structure just a way of saying a specific permutation of amino acids?
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#96> Like most bioinformatics programs, AlphaFold 2 comes equipped with a “preprocessing pipeline”, which is the discipline’s lingo for “a Bash script that calls some other codes”. Having Bioinformatics people requiring to stray a long way from their core competency to learn a scripting language from the 80's to write glue code seems... suboptimal. How many hours of expert time has been wasted figuring out how to split…
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#97So... could anyone with experience in the area give an estimate of how much the likelihood of an unstoppable, untraceable "DIY" bioweapon appearing in the next decade has increased thanks to this?
https://www.theguardian.com/science/2014/jun/11/crazy-danger...
Re: AlphaFold 2 is here: what’s behind the structure prediction miracle
#98Earlier quoted context omitted.
Again, it's entirely possible I missed some very subtle point in AF2's system, but my understanding is that each target AF2 predicted had an underlying structural template covering the majority of the domain and the mapping was established through the MSA. IE, any MSAs would always include alignments to known protein structures. Are you saying their MSAs don't include alignments to known protein structures? (the reas…
Yes: they predict structures using MSAs, without alignments to known protein structures in a majority of the cases.
I'm going to be a bit skeptical but if that's the case, then it really is a significant improvement. Glad to see that with just the idea, the academic community was able to reach near parity in a short time, demonstrating there was nothing unique to DM except their huge amount of compute, storage, and talent, and this would have happened in the next CASP anyway.