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This isn't a "do you have references" situation. You're wasting folks time. Nearly all drugs target proteins, with a few that target DNA or RNA.



You can just ignore my comments and walk away? To me you just another "internet expert" which I am not sure why should I blindly trust.


Your sources are talking about the ratio of small molecule vs. large molecule drugs. Even if you're developing small molecule drugs you are likely targeting some aspect of protein signaling/gene expression.

People are being dismissive of your comments because to say that proteins are niche in the context of pharma is like saying advertising is niche in the context of Meta and Google.


> People are being dismissive of your comments because to say that proteins are niche in the context of pharma is like saying advertising is niche in the context of Meta and Google.

its all about how you define word "niche", for google, main revenue stream is supported by several pillars: search tech, infra tech, ads tech, ecosystem+network effect, human management. You remove one pillar, and everything is destroyed, so one can say ads is one of the niches in their food chain. I suspect with proteins it is about the same.

> in the context of pharma

there is no context of pharma. Post is about more broad bio-medical publications.


I'd say it's less like pillars and more like (emergence) layers, with proteins being a pretty important layer .

I'm now not entirely sure what your experience is with bio sciences. You're definitely coming at it from an odd angle though!


I didn't claim expertise, that's why I say "it looks like", "I suspect",


Well, maybe find some time and dive in a bit and see what can be found?

You never know, maybe you'll end up contributing to our understanding of life, maybe (indirectly) even save a few lives!


I am working on the service which potentially can answer questions like in this comment: https://news.ycombinator.com/item?id=38109294

life science is one of potential applications if there is an interest and money.


So the pathway to synthesize every protein is +/- the same: That's gene transcription[1] and translation[2]. If that's broken, you're in big trouble!

But if you mean in general if you're capable of looking at metabolic pathways where each protein catalyses a step in the pathway, that's definitely interesting. If a certain person has a flawed gene coding for protein X, that could indeed cause a problem.

To find valid answers, you might need to eg. track nodes and states in a graph, to figure all the consequences of a break. Not all types of storage systems/engines are equally good at that.

[1] https://en.wikipedia.org/wiki/Transcription_(biology)

[2] https://en.wikipedia.org/wiki/Translation_(biology)

edit: s/protein pathway/metabolic pathway/


> Not all types of storage systems/engines are equally good at that.

Yes, I built system which traverses paths in graphs with 1B nodes and 10B links in 1h on affordable server. But that's only one part of the puzzle.


Neat!


> Word of advice to all those who are chomping at the bit to disrupt pharma with AI.

Literally the first line in the comment that started this thread.


Sure, now let's read the post?


I read the post before I made any criticism of your comments. We're talking on a thread within the larger context of comments on the post. But more importantly, if you read the post, you will see there is a theme of industrial biochemistry (IE, pharma and biotech) running through it, because pharma/biotech is the primary consumer of these products, and the vast majority of the revenue stream.


> there is a theme of industrial biochemistry

that's one of the themes (and you are already working hard to stretch drugs pharma to "biochemistry"), if you can't see other themes in his examples and screenshots, I think this discussion is not interesting to me.




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