This approach is pretty much like the TED approach from a few years back. As far as I remember there wasn’t a ridiculous amount of fold diversity there either. It turns out evolution isn’t averse to a bit of liberal protein plagiarism.
> Natural selection has no analogy with any aspect of human behavior, However, if one wanted to play with a comparision, one would have to say natural selection does not work as an engineer works. It works like a tinkerer - a tinkerer who does not know exactly what he is going to produce but uses whatever he finds around him whether it be pieces of string, fragments or wood, or old cardboards; in short it works like a tinkerer who uses everything at his disposal to produce some kind of workable object.
"This review has focused only on small fragments of fold space with examples given for folds generated from a single secondary structure string consisting of around ten SSEs. Even in this small corner, the number of possible folds, under the current constraints, is of the order of 1000"
I think there was a Twitter/Bluesky thread on the results from adding all the predicted folds from metagenomics too, and not ending up with many new clusters. If this continues to hold true as we keep looking at stuff, I will be relieved that at least natural protein folds and domains has a limited (tractable) solution space. All we need to do now is annotate the variation of these couple of thousands of fold variants. Challenging, but at least a bounded problem.
I understood it as metaphor - just that evolutionarily distant sequences can adopt the same (or very similar) folds because there are only a limited number of stable, accessible folds that are possible.
Yes, that is exactly what I meant! Here’s an experiment to try: Frances Arnold got a nobel prize for work related to directed evolution. However, we know evolution is limited by the tools available to it as you mention. If we add random chaperones and co-factors to bacteria that we know other organisms use, can we push evolution outside of the known fold space? Is the limited fold space an absolute limit or the “accessible” limit?
I see. I meant 'energetically accessible', but you mean more like 'affordably accessible' (in the sense that the molecular toolkit of a cell is what can 'afford' certain structures, due to chaperones available and so on).
Who knows what might be possible if you designed a cell from scratch - perhaps you could rework all the machinery to access other parts of fold space. After all, there are some weird and wonderful machines out there like the 'Vault' (https://en.wikipedia.org/wiki/Vault_(organelle)) that can fit whole proteins inside them. Possibly a different cage-like structure could help fold designed proteins into as-before unseen structures.
It could also mean "evolutionarily accessible". The basin of attraction in sequence space has to be sufficiently large that evolution could stumble across it.
One answer mentions actin and hexokinase. I'm not familiar with the actin fold, but looks like a bab sandwich of some kind.
Another commenter on this page mentioned the 'Rossman fold', another classic, and TIM barrels also occur to me. One caution is that some of these I would consider higher-level patterns - the 'Topology' level of CATH hierarchy.
Naturally, the more high-level (abstract) the fold pattern, the larger the sequence space it covers. It is less interesting to say that a helical bundle (for example) covers a lot of diverse sequences.
This looks very cool. Does the window picker for multi-window apps work with the pinning? So if I have a safari windows I want to have associated with a profile, and the option-tab will ignore all the other windows?
It is a constant pain when I cmd-tab in a space with safari, and it throws me out of the space to another one because the window that gets focus isn’t the “closest” one on the current space.
right now it shows all safari windows not just the ones on your current space, so the "wrong space" problem could still happen.
I'll look into Space aware window filtering.
Even better, don’t ban it, but require companies to do age verification (above a certain age?) before displaying advertising. You get two wins in one: make the child market less attractive for algorithmic feeds, and you also can get a better product (no algorithmic feeds) without ads if you don’t age verify. Win-win situation!
It is a huge worry for me that unless we decouple the publishing “system” from the career pathways (i.e., rewards), we are going to lose access to both the careers (to robot-weilding bullshitters) and even worse, the shared space where scientific communication took place.
Does anyone know of any writing on the network effects of the publishing system? What would happen if the actual value of the journals (of the little they provide!) were to go away?
The death of scientific twitter, and the failure to establish any replacement makes me worry that we won’t be able to coalesce around a replacement system. Obviously preprints play a role, but we really need our scientific communities to engage with them in a more serious way.
The arxiv should itself embed a review and commenting system, possibly even blogging. Publishers are archaic, scientific social media should be arxiv's future.
The risk is that publishers might then start opposing the publication of manuscripts that have been shared as preprints on arXiv, if they start perceiving it as a competitor and not a supplement to their "service". But I concur, arXiv with social media features would be nice.
Can you say what field that is? I hear this sometimes, but my feed there is significantly low signal to noise, and I have had to pollute my “connections” to the point where I accept everything, as I have been trying to advertise job openings using it too (which frankly has been pretty poor too).
My field now is Earth observation/geoinformatics and my recent connections are mostly academics and applied programmers. Also, mostly Europe-based and very few in the US. My feed is mainly about new papers, conferences, tools, webinars etc..
I used to do corporate software dev and my feed (and work) back then wasn't that interesting. I barely used the site.
That is really insightful regarding the ritual improving outcomes through better communication - something I see reflected in many meetings I turn up to now which involve an introduction round between participants, and anecdotally improves participation in the meeting.
It would be amazing if someone had a link to a page with the MSF story, as that is a great reference to have! My google-fu hasn’t helped me in this case.
This is great - now I can get the authentic conference experience of a disengaged speaker reading out the slides in a monotone, without all the hassle of international travel and scheduling.
In all seriousness, there could be more utility in this if it helped explain the figures. I jumped ahead to one of the figures in the example video, and no real attention was given to it. In my experience, this is really where presentations live and die, in the clear presentation of datapoints, adding sufficient detail that you bring people along.
Besides just porn or nudity, maybe we could also add violence into the arsenal of engagement. For example, maybe the viewer could use a virtual sword or shotgun on some key concepts in the presentation to initiate a tangent going on a deep dive on the concept, and then come back to the presentation once done with the rabbit hole.
I was just thinking about this movie on Friday while at a concert. Lorna Shore, awesome show. Anyways, the person in front of me was watching an overweight person (purpose of the niche I suspect which is why I mention it) do their daily chore routine (laundry, cleaning, etc) on tiktok. After the video was finished, my fellow concert attendee quickly went to Amazon and purchased the iron in the video. No links clicked, just serious chore fomo leading to a purchase. All while standing 3 feet from a circle pit/wall of death/etc while Lorna Shore was playing 20 ft from their face.
A VR interactive thesis defense/sword fighting crossover game sounds just weird enough to work. Maybe base it on the fight mechanics of Until You Fall [1], we could call it "Until You Graduate" (I will see myself out for that one) or "Thesis Offense" [2].
If it doesn’t cram text at a tiny point size and introduce a slide with “you can’t see this but” then it’s likely better than the majority of scientific presentations I’ve seen.
I was ruminating about how Atproto would be great for re-thinking the peer review system for scientific journals.
Imagine a world where a preprint is “published” onto the social web, from which you could aggregate reviews/comments. I eventually ended up thinking about exactly what you raise - it would be great to have some degree of access control on this so both comments and published things can be selectively shared (with an option to make everything public later on, maintaining all the links).
It is a real shame that peer review reports were only first published relatively recently. These would have provided valuable training information as to what peer review performs. Unfortunately now, I fully expect the public peer review reports will be poorer in quality, and oftentimes superficial.
On this tool, I fully expect that it will not capture high level conceptual peer review, but could very much serve a role in identifying errors of omission from a manuscript as a checklist to improve quality (as long as this remains an author controlled process).
I will be interested to throw in some of my own published papers to see if it catches all the things I know I would have liked to improve in my papers.
Thanks for the feedback. Totally agree. It’s a real shame we don’t have more historical peer review data. It would be great if research was fully transparent.
There’s also interesting potential in comparing preprints to their final published versions to reverse-engineer the kinds of changes peer review typically drives.
A growing number of journals and publishers, like PLOS, Nature Communications, and BMJ—now publish peer review reports openly, which could be valuable as training data.
That said, while this kind of data might help generate feedback to improve publication odds (by surfacing common reviewer demands early), I am not fully convinced it would lead to the best feedback. In our experience, reviewer comments can be inconsistent or even unreasonable, yet authors often comply anyway to get past the gate.
We're also working on a pre-submission screening tool that checks whether a manuscript meets hard requirements like formatting or scope for specific journals and conferences, hoping this will save a lot of time.
Not my subject area, but at least one other group looked at ABCA1, and judging from this abstract, it has been linked via GWAS already, and furthermore concludes it doesn’t play a role (I haven’t looked at the data though).
I don’t know, but if we were to reframe this as some software to take a hit from a GWAS, look up the small molecule inhibitor/activator for it, and then do some RNA-seq on it, I doubt it would gain any interest.
Wouldn't the fact that another group researched ABCA1 validate that the assistant did find a reasonable topic to research?
Ultimately we want effective treatments but the goal of the assistant isn't to perfectly predict solutions. Rather it's to reduce the overall cost and time to a solution through automation.
Not if (a) it misses a line of research has been refuted 1-2 years ago, (b) the experiments at recommends (RNA-Seq) are a limited resource that requires a whole lab to be setup to efficiently act based upon it, and (c) the result of the work is genetic upregulation of a gene, which could mean just about anything.
Genetic regulation can at best let us know _involvement_ of a gene, but nothing about why. Some examples of why a gene might be involved: it's a compensation mechanism (good!), it modulates the timing of the actual critical processes (discovery worthy but treatment path neutral), it is causative of a disease (treatment potential found) etc...
We don't need pipelines for faster scientific thinking ... especially if the result is experts will have to re-validate each finding. Most experts are anyway truly limited by access to models or access to materials. I certainly don't have a shortage of "good" ideas, and no machine will convince me they're wrong without doing the actual experiments. ;)
This is, I think, what I've been struggling to get across to people: while some domains have problems that you can test entirely in code, there are a lot more where the bottleneck is too resource-conatrained in the physical world to have an experiment-free researcher have any value.
There's practically negative utility for detecting archeological sites in South America, for example: we already know about far more than we could hope to excavate. The ideas aren't the bottleneck.
There's always been an element of this in AI: RL is amazing if you have some way to get ground truth for your problem, and a giant headache if you don't. And so on. But I seem to have trouble convincing people that sometimes the digital is insufficient.
This is a great framing - would you please expound on it a bit. Software is almost exclusively gated by the "thinking" step, except for very large language models, so it would be helpful to understand the gates ("access to models or access to materials") in more detail.
https://www.science.org/doi/10.1126/science.adq4946