[ricksunny]

I’m sorry but why don’t tbey just release the ability for a user to enter a known real-world sequence’s accession number from Genbank / GISAID, and generate the protein structure from that? Why do they have to abstract the user from the process by only exposing a completed database of the protein structures the Alphafold researchers decided would be worth producing?

[tazjin]

You can use the open-source code, and we also have a Colab notebook for that: https://bit.ly/alphafoldcolab

More info: https://deepmind.com/blog/article/putting-the-power-of-alpha...

[ricksunny]

Thanks for that - I can see why my comment was downvoted now, as the the posted article's FAQ lists these links for those who would like to study their favorite sequenced-but-unmodeled protein. I'm glad Alphafold is as open source as it is, and I recognize that it didn't have to be so.

I think I was primed for a knee-jerk reaction because when Alphafold's results were announced back in Dec. 2020, with expressions of what a boon it would be for researchers around the globe, I anticipated there would be a timeline announced for exposing a tool or for the open-sourcing. (The Github repo has only just been released about 6 days ago ...)

With all the work on SARS-CoV-2's 'interactome', as well as human proteins & enzymes involved in pharmacology of antiviral drugs under development / repurposing , it's easy to imagine that drug developers would have liked to exercise Alphafold as soon as it was announced. (I myself have wanted a structure for human enzyme OATP1A2 that wasn't available on the PDB for such a drug pharmacology study - quite glad it is available at hand now.. .:) ).

Anyway I'm sure good arguments will be made about the need to really 'get it right' before releasing, or internal deliberations on how much to open up vs charging for it.

But 7 months lead time during a pandemic is a long time...

In all cases thanks again for this innovation's availability now. :)

[ricksunny]

A little addendum (for posterity as this is now an old article post)

• RosettaFold came out in academic paper form as well as open-source github repo slightly prior to AlphaFold. Was AlphaFold's decision to open up motivated by RosettaFold's publishing / opening-up activity? So I feel that the extent of AF's altruism in this (while high) deserves some scrutiny, as perhaps it falls short of the extent that several of us commenting interpreted a couple days ago.

• While RosettaFold allows online execution to the best of their spec, they currently have a backlog queue of ~3000 jobs going back to mid-July. This is telling about the processing power required for folding. AlphaFold has access to a lot of processing power (even if it could ultimately & reasonably end up being on a charge-per-job basis).

[sveme]

I'd guess the ad-hoc simulation of the structure is computationally quite expensive and takes a while, though that's just a guess and I haven't read the original paper yet.

[ricksunny]

In fact a cost of $1-$4 for the preferred implementation:

https://news.ycombinator.com/item?id=27894060

The colab provides a slightly-less-accurate version that operates in the cloud. For the real mccoy it seems one must set up one’s own environment and leverage the git repo.

[sherjilozair]

DeepMind has already released the open source code and model parameters. The database makes it easier to access the predictions.