They found a bunch of potential molecules that bind to 5HT2A, that's cool.
But the really important conclusion of the paper, which I truly hope bears out, is that AF2 models are useful for finding binders to GPCRs.
GPCRs are one of the largest (if not largest) drug targets and work (including my own) showed that modelling protein dynamics using expensive simulations was likely to be necessary to make accurate predictions of GPCR binding molecules. If this paper is correct, AF2 is actually able to recapitulate much of the detail that we previously believed required expensive dynamics simulations, which is about the best possible news because it suggests that we can omit these costly calculations.
It's almost certain now that AF2 will win the Nobel Prize, as this represents some of the most exciting breakthroughs in the past few decades.
Even if it has to go through extensive vetting on the theory side, the ability of these models to improve the starting points for the harder process is very strong.
For example, in daylight modeling - and this is 2-3 years ago mind you - it has been found that "AI" is perfect for getting 99% closer to the actual luminance in something like 01% the computation. So that even if you feed those "precalculated" models into the traditional raytracers, the improvement to the first guess is well, well worth it.
I don't really think there's an analogy between radiosity simulations and drug discovery. Drug discovery will probably remain fairly ad-hoc and stochastic for some time.
That's fair. I was merely talking about being able to make better "first guesses." Nowhere near the predictability of a much simpler phenomenon such as radiance mapping, of course.
And as the article says,
>"There were a lot of models that we didn’t even try because we thought they were so bad,...”
To me the analogy is that generic AI techniques with minimal problem domain specific adaptations is providing huge boosts in efficiency on a wide variety of applications. It’s like the steam engine causing mechanical work to become vastly more efficient. AI in many ways is doing the same thing to intellectual work.
The long-anticipated "mental gym" industry! Where people pay to exercise their atrophied mental muscles the same way they exercise their barely-needed physical muscles now.
With all the associated bullshit and snake oil and romanticizing of the "good old natty days" too, of course.
Big $$$ industry, at least until our brave future does away with voluntary reproduction altogether, being the reason people bother to exercise in the first place.
As an expert, do you think this might lead to easier discovery of much more selective GPCR ligands?
Agree finding new 5HT2A ligands is cool, what would be truly interesting is having a suite of totally selective ligands for the entire 5-HT receptor family.
I feel like a lot psychopharmacological research into a lot of mental disorder is severely hampered by
1) the complex interactions of the various serotonin receptors(and also with other receptors like D2)
2) the lack of truly selective ligands, necessitating a hodge podge of less selective agonists combined with selective antagonists to isolate the effects of specific receptor interactions(making it hard to do this sort of thing in humans). Or using knockout mice, which is also kind of dubious because you've now made a fundamentally different brain and are trying to compare it to a normal one. And that's sort of hit and miss.
> But the really important conclusion of the paper, which I truly hope bears out, is that AF2 models are useful for finding binders to GPCRs.
What seems more likely to you: that the (obviously worse [1]) structures produced by alphafold are somehow magically capturing protein dynamics, or…the virtual screening method (DOCK) used by the paper is relatively insensitive to the quality of the underlying model? They say right there in the article that neither screen was obviously enriched versus the other (the hit rate was around 50% for both branches, which was essentially the same as for the very different retrospective screening method in the same paper [2]).
I’m putting my money on the parsimonious answer. Running structures through a large enough virtual screen will almost always find something that binds, even if the starting model isn't great.
[1] at least in the case of the x-ray structure. Using a cryoEM structure is sort of interesting, since they’re blurry anyway.
I don't have a good answer. I don't think AF2 captures protein dynamics in a direct way. And I think docking programs have inadequate loss functions and sampling to really find accurate answers. I suppose AF2 could be modified to produce structures that are well mapped to docking programs.
I think you're right, that running lots of structures through virtual screens will find lots of binders. In the middle days of protein design (well before AF2), people went from not being able to design anything, to being able to easily design "rocks"- proteins that were exceptionally stable, but didn't do anything interesting. Their loss function that they maximized for was stability. But that comes at a cost: high stability seems to prevent lability (which is useful for enzymes). And I think that if you just pass enough stuff through a good-enough program, you'll find lots of binders, but those binders won't actually be useful binders. We already know from decades of work that we can find lots of nanomolar and picomolar binders that don't do anything worthwhile (or have side effects).
My conclusion is: we may very well be on the tip of solving another bottleneck in the drug discovery pipeline, or, we might just be bumbling around in a big space and found a nice local minimum. I don't think AF2 or similar systems on their own are going to completely solve the problem, and until DeepMind or somebody else creates something that can truly address the hard problems in human biology, the most we can hope for is finding more effective new drugs more cheaply and somehow couple that with improvements in genetic personalization.
That is unrelated work by a different team. The merits of AF2 have been demonstrated already and accepted by the community (which has reproduced those results both theoretically and experimentally) although the community is still arguing about just how good AF2 (and its descendants) are.
I agree the chemistry paper does not look g ood but it's hard to say yet. Like I've said elsewhere DM and Google Researchers are under huge pressure to make their results look as good as possible. Already people have serious concerns about another Google paper using ML for IC layout.
I would extrapolate from existing GPCR-targeting drugs, but the list is so long I can't really give a survey. As a protein family, GPCRs do a lot of different things but basically it boils down to signal transduction: there's something outside a cell and the cell wants to know that so it can respond. GPCRs mediate the binding of the thing outside to the surface of the cell, and transduct the information into the cell, delivering a signal to the nucleus, where the transcriptional machinery is manipulated to make new proteins (or stop making proteins). I left out some steps. This allows the cell to be responsive to the outside in a secure way, without the outside molecule coming into the cell.
The 3d structure of GPCRs is intimately associated with the cell membrane, with one end sticking out into the extracellular environment, and another sticking out into the interior of the cell. Simply getting that sort of protein, which is not soluble in water, was a massive challenge and the first structures didn't arrive until the early 2000s, when people learned how to crystallize GPCRs using detergents and other solvents that simulated cell membranes.
So many diseases are caused by misregulation of signal trandsduction... let's take some examples. Vasopressin is a drug that also happens to be a natural body product. In some diseases, people don't make enough vasopressin to regular the kidneys properly, leading to a form of diabetes, and simply giving people more of it helps reduce the symptoms. I guess in this case (not certain), people have mutations in the GPCR that receives the vasopressin signal that attenuates the signal "too much" and by just dosing the patient with a lot more, more signal gets sent inside the cell.
I think at least 10 nobel prizes in medicine have been awarded for research related to GPCRs, which has uncovered a wide range of medically relevant knowledge of physiology. The NERSC supercomputer "Cori" was named for Gertie Cori, who helped discover some of the core mechanisms in human metabolism during the golden age of metabolic biochemistry.
I think the simplest way to think about it is being able to target specific GPCRs is like being in front of a switchboard with buttons and knobs controlling every critical detail of how human bodies manage and maintain themselves.
A better question would be what don't they enable. Something like 30+% of FDA approved drugs operate along that pathway. Besides for the boring stuff like being able to trigger cancer cells to kill themselves, we could have a molecule you inject into your eye that opens up your vision to be able to see infrared and ultraviolet light(and beyond).
I mean, if I had all the power in the world and I didn't want anyone coming to take it, I'd probably give everyone free drugs to keep them happy/content.
Power over people does not come from making them happy, historically it comes from doing something close to the opposite, which is to convince them that they are missing "X" from their lifes, that there are greener pastures for those who purchase it ("x" being some soda, some new phone, et al) or the promise that they will get it if they do something they want (e.g. in religious context "x" can be heaven and they only get it by following some behaviors/commands)
But that was when our labor was needed to generate wealth and power for those people. The churches wanted of to work to provide tithes and offerings, the markets want us to work to buy and produce goods.
What happens when that labor isn't as valuable? It seems like someone in power would either want to pacify us or eliminate us.
> PiHKAL: A Chemical Love Story is a book by Dr. Alexander Shulgin and Ann Shulgin, published in 1991. The subject of the work is psychoactive phenethylamine chemical derivatives, notably those that act as psychedelics and/or empathogen-entactogens. The main title, PiHKAL, is an acronym that stands for "Phenethylamines I Have Known and Loved."
> The book is arranged into two parts, the first part being a fictionalized autobiography of the couple and the second part describing 179 different psychedelic compounds (most of which Shulgin discovered himself), including detailed synthesis instructions, bioassays, dosages, and other commentary.
As a mostly "retired" psychonaut, I think this can easily be avoided by just legalising drugs.
Very few people are going to want to try RCs if conventional alternatives don't present more legal risk. Most people using them are avoiding legal risk or trying to beat drug tests etc.
There is a tiny minority of "true psychonauts" who are in it for the experimentation, but we tend to be acutely aware of the risk and take much better precautions than someone who is chasing a high they're addicted to.
And adults knowingly taking risks(on their own behalf) and suffering consequences is just the human condition.
I think they meant that some compounds are unsafe for consumption, and we don't necessarily know which without research.
My recollection is inexact, but there was a story about a person who synthesized a novel theoretical psychedelic, tested it on himself, rapidly developed Parkinson's-like symptoms which deteriorated until his death. I don't know that Shulgin was ever or always the first to try novel syntheses, but I do think allowing known-safes is better that challenging people to put themselves at risk through self-experimentation.
>The neurotoxicity of MPTP was hinted at in 1976 after Barry Kidston, a 23-year-old chemistry graduate student in Maryland, US, synthesized MPPP with MPTP as a major impurity and self-injected the result. Within three days he began exhibiting symptoms of Parkinson's disease. The National Institute of Mental Health found traces of MPTP and other pethidine analogs in his lab. They tested the substances on rats, but due to rodents' tolerance for this type of neurotoxin, nothing was observed. Kidston's Parkinsonism was treated with levodopa but he died 18 months later from a cocaine overdose. Upon autopsy, Lewy bodies and destruction of dopaminergic neurons in the substantia nigra were discovered.
1. The toxin was an impurity in his synthesis of MPPP, which is a synthetic opioid.
2. He was diagnosed with parkinsonism and treated, but died from a cocaine OD(one wonders whether the cocaine was an attempt at self-medication, or a deliberate suicide attempt).
According to the article this case of MPTP-induced parkinsonism has happened again in the 80s, again with tainted batches of MPPP.
I'd say this young chemist was more similar to Shulgin than most psychonauts, but he was also skipping steps and clearly had issues with addiction.
This would likely be avoided by Shulgin because he'd probably get the chemistry right in the first place.
Shulgin also had a lot of pharmacology understanding that allowed him to make educated guesses about what kind of structures might be very dangerous.
But he definitely was the first to both synthesise and ingest a lot of these more obscure psychedelic compounds. But he was extremely careful, which is why he lived well into his 80s.
The stories of people getting limbs amputated because the RC they were shipped by accident was an insanely strong vasoconstrictor while still tripping 24h after dosing is the stuff of nightmares.
and also, the stories in Phikal and Tikal of more disciplined people following titration protocols etc. and discovering hidden kingdoms of the mind, is the stuff of dreams.
Me and my friends found this drug conceptually hilarious back in the day and used to crack a lot of jokes about it.
Its apparently almost as strong as LSD, takes hours to start working and the effect lasts several days. Worse in every respect. Why would anyone ever choose it?
Mislabeled and tainted RCs became enough of a risk when fentanyl and fentanyl analogs started gaining popularity that the guys I knew who were ordering from overseas just stopped messing with RCs. It's disappointing that it ended up like that. 2009-12 I had access to pure and dirt cheap 2C-E, methylone, 4-ACO-DMT, the JWHs, ketamine, methoxetamine, LSD (I don't think there were any analogs available yet?). It was a crazy time.
Yuuuuuuup this right here. That's right when I was in university and was definitely the peak. Maybe a bit before when mephedrone was big. I feel like I aged out of it at just the right time. Now I don't even recognize the names of what's going around.
I hung out with people who got various powder packages in the mail at that time. It was interesting, but already I knew it wasn't my scene. Still I learned a lot of names and watched the use on occasion. Looking at it now I'm glad it was then and I didn't have to worry about the various opioids getting mixed in. I don't think I thought enough about the consequences even though I worried about my friends dealing with various manners of contamination.
This was when I was in college/just out of college too. Most of the guys I knew who became dealers were students and concert promoters and most of the customers were hippy and rave kids. This group was into Bitcoin early on because of silk road. But a lot of this stuff predates Bitcoin and was sold on the clearnet as plant food and bath salts. That's where the term bath salts came from. It wasn't necessarily one cathinone, it was just like this isn't for human consumption, it's just bath salts. The stuff would be shipped here either hidden in other objects or just mislabeled as common chemicals. I only know of one guy who got a package confiscated, but he was using a fake ID to rent mailboxes so wasn't a big deal. Oh yeah, fake IDs were big back then too. I'm in my mid/late 30s now and I wonder what kind of devious shit the kids are getting up to these days. Anyway, the paranoia from being involved in all of this was part of what lead me to leave the country to clear my head. The funny thing with that is I almost got involved in the same shit in Australia because I met this meth dealer who had heard about methylone but didn't have a source. I was talking to someone back home about setting up some deals that we'd route through the US but I figured that was a bad idea and I didn't want to go to prison in another country. Anyway, things chilled out and I'm just a dude working a blue collar job and I eat THC gummies every now and then. Speaking of THC gummies, wow, marijuana has been legal in the US since 2018. I was in that industry for a couple years but my business was too small to survive. Thanks for reading rambling thoughts as I drink my morning coffee.
After seeing all the fakery from how AI models handle programming (being "very good" at tasks where it turns out it was just trained on the problem in the first place), I do wonder if AlphaFold is likewise a red herring.
How many of the AlphaFold protein folding predictions have been actually verified by a lab? And are any of those actually new proteins or just tiny variations on things in the training set?
Alphafold was largely trained on the structures in the Protein Data Bank, which includes lots of important protein targets. Just by virtue of evolutionary biology, many proteins are variants of one another, so if you're doing something like running AF on all of the proteins in the human body (only 24k or so), you're including lots of targets that were part of the training set, lots of targets that are closely related, and lots of targets we don't have structures for. Many (most?) proteins are also dynamic, so can't really be represented well by a single structure (rotating a sidechain inside a pocket when using a structure for virtual screening will frequently yield completely different 'hit' molecules, for instance). AF2 is a better guesser than previous tools for a reasonable structure, but that's like 1 step in a 47 step process to 'finding a new drug.' Even here, "AlphaFold" didn't find the drugs candidates, it generated the structure(s) that they ran common virtual screening tools on (which introduces all kinds of other assumptions and approximations depending on the tool).
The linked article is not about AlphaFold itself, but about researchers verifying AlphaFold's predictions. So the article directly addresses your question. Unfortunately HN only shows the first half of the headline.
> Shoichet agrees that AlphaFold predictions are not universally useful. “There were a lot of models that we didn’t even try because we thought they were so bad,” he says. But he estimates that in about one-third of cases, an AlphaFold structure could jump-start a project. “Compared to actually going out and getting a new structure, you could advance the project by a couple of years and that’s huge,” he says.
I don't agree with your assessment of AI and programming at all. In fact, I think you're being insidious when framing your skepticism against this using words such as "likewise", making it sound like it has been unanimously agreed upon. It's like me saying "after seeing that the earth is flat, why wouldn't other planets be flat?".
AI is definitely capable of solving novel programming problems and I'm constantly surprised how well Copilot understands the esoteric context of my code.
> AI is definitely capable of solving novel programming problems
I don't believe that. I think you are being fooled by the enormity of the training set, followed by the non-novelty of things you personally haven't seen before.
I'm not saying AI tools aren't useful though. I'm just saying they are what they are: a fuzzy search in an enormous problem space. This is impressive and cool, but not the same as being able to solve truly novel problems.
Some have speculated psychedelics like psilocybin played a pivotal role in Homo Sapiens consciousness development. If true, the poetic symmetry of AI inventing psychedelics and smart drugs to fuel the next jump in human development is fascinating. Is there a genre of scifi for this yet?
What you're referring to is called, no joke, the Stoned Ape Theory. It is not really taken seriously at the moment, as it completely lacks in evidence.
However listening to it's originator Terence McKenna explain the stoned ape theory while intoxicated on the correct substances is a very fun experience.
An animal in the wild will try to eat everything and learn through trial and error what is good to eat and what isn’t. Selection might even lead to behavioral changes that naturally predispose one to one substance over another. I don’t see why humans would be any different.
Trial and error? I think most animals have an instinct of what they should eat when. I think humans have that too, but kind of forgot about it, or at least we are out of touch with these things and mostly judge intellectually.
For many animals that instinct is to chew something and either swallow or spit it out. See a tiger shark. They basically probe the entire environment through constant trial and error. Bite it all should a small portion bleed, they have concluded.
I have always been fascinated in the fact that psychedelics, and, indeed, any plant-based molecule that can mimic a neurotransmitter, exists.
Us and plants aren't creating the same molecule because we share a common ancestor. There are far too many other plants that don't create cannabinoids or opiates or whatever, and far too many other animals that don't create them, for this to be at all likely. It had to have evolved multiple times.
It's not any kind of symbiotic relationship. Our ancestors didn't cause opiates to evolve by selectively eating and spreading their seeds.
So it's a coincidental convergent evolution. But these are really complex molecules doing quite different things. Both cannabinoids and opiates evolved in plants to defend them from viruses and fungi. I don't know what other neurotransmitter-mimics are for, but they're not being used for plant nerves.
I'm sure people know the answers to this, and I could read a book about it.
I don't think they do. AFAIK most of your assertions above are unknowns.
My theory, at least re: psilocybin and the like, is that a parasitic fungus developed neurotransmitter agonists as a way of manipulating its host. The complete cocktail that was needed to make the target species behave in a way that completed the fungus' lifecycle may be lost to time, but certain components of it still exist in the gene pool.
And if you're going to have millions of spores (rather than the two or three offspring that, say, humans have) you can afford to set them up with a wider array of gene expression profiles. So you've got these fungi just trying stuff to see what works--now armed with neurotransmitter agonists as part of that "stuff".
Later on you've got other organisms eating those mushrooms and behaving strangely. If you're a fungal spore, and you're in an animal's digestive tract, "strangely" is probably how you want it to be behaving. You're going to end up in a different place or with different nutrients or in some other situation which is abnormal for your host--you end up with greater habitat diversity.
How specifically that host-behavior-strangeness would lead to a lifecycle that would reinforce the inclusion of psychedelics to the point where P. Cubensis is reliably psychedelic, rather than just the occasional mutant, I have no idea, but when you've got billions of years to play with, it's not hard to accept that some pretty weird animal-fungus interactions came up here and there.
Many psychoactive molecules are also structurally very similar to other hormones, and molecules produced for other aspects of biological function. Take a look at NN-DMT and Melatonin:
Just a slight mutation, or even biological synthesis under non-ideal conditions could easily result in synthesizing one or the other via the same pathway.
It's equally likely that alkaloids like psilocybin are insect or bird repellents or mere metabolic byproducts, and that the fact they sort of slot into the 5-HT2A receptor in the brains of some species, wreaking havoc on various processing systems there, is a mere coincidence.
Indeed, it's a reasonable argument that fungi evolved these molecules specifically to affect animal's brains. After all, we can see specific behaviors that help spores spread, like the zombie ants.
I think marijuana or poppies have less plausible explanations for how they would have evolved specifically to mess with animal's minds.
THC and opiates in poppies basically are animal neurotransmitters, so I disagree. Their original function was probably to discourage animals from eating the plant. Animals seems to have a reflex by which any drastic changes to brain function induce vomiting of and aversion to any food the animal just ate.
I don't really buy this theory. Taking mushrooms is more likely to make me want to curl up in bed rather than run around. And would it really last long enough to get an animal outside of it's normal range? Not in my opinion.
For me, psilocybin catalyzed such pivotal decisions as moving out of my parents' house, getting married, and changing careers. It seems plausible that it would be relevant to the founder effect (https://www.genome.gov/genetics-glossary/Founder-Effect) in other animals.
Sometimes we need a little shove to start doing new things that end up being advantageous. There's no reason to believe that we're unique in that way. If that shove is advantageous enough to be worth returning for a second shove, well now you've got the seed of a cross-kingdom relationship.
Well in that particular case, moving out meant I could dedicate a whole closet to cultivating them. But I don't think that cultivation is a necessary step, merely returning for more is enough to start the kind of relationship where adaptations which allow for one party to help the other are selected for.
There is a lot of complexity in a million years of mixing spores and mycelial karyotypes. I haven't done the math but it seems like it could easily rival a human brain.
Humans always assume intelligence requires a brain. I think sugar cane are quite intelligent on the other hand. They have came up with a means to coopt another species for breeding: us humans, who have in turn created this cult of the sugar cane where it is now the most cultivated crop on the planet for probably the forseeable future. What an amazingly efficient way to proliferate your lineage. You don’t need to evolve these costly and highly derived structures like brains or articulated thumbs yourself, let the dumb human break their back harvesting you and spreading your lineage around the world.
Totally. Between bread and alcohol, yeast has basically managed to domesticate humans. Maybe our experiences differ so much that we can't strike up a conversion, but that's no reason to discount intelligence.
> Us and plants aren't creating the same molecule because we share a common ancestor.
That is, in fact, exactly the reason.
You are of course correct that synthesis of many biological molecules has evolved countless times over the eons, but chirality of certain critical molecules, amino acids, ribosomes, all evolved exceedingly early. Once the cellular machinery is synthesizing these things, synthesis of similar molecules, one, two, three mutations away become likely across swaths of related organisms, however distant.
In short, we're all playing with the same lego bricks, and there are only so many different models possible to build with the set.
Yes, sure, we're all playing with amino acids in order to create proteins that can then synthesize complex things. This doesn't mean that it's easy to create the pathways that create these complex things.
The synthesis of opium, for instance, requires two specialized cell types, complex organelles, and hundreds of different proteins, all told requiring thousands of different genes [1]. This is all for the purpose of creating one single highly-complex molecule. This isn't something you get at easily by "playing with the same Lego blocks."
The question is, if it's not a coincidence that both poppies and a small subset of animals both go through all this work to create two versions of this extremely-specific molecule, then what's the reason?
Sure, in the end the reason will be "it's advantageous for both species," but it's still pretty mind-blowing, and I think we're still missing a bunch of steps.
Perhaps plants and animals are not so far removed from each other as you think. At the cellular level they are far more similar to each other than to any bacterium. And as to why they manufacture similar molecules, i would suspect reason #1 to be that they derive similar utility. Plants and animals both perform chemical signalling between cells. Both use ion channels. Similarities go on and on. And when we're talking about molecules with only a few dozen constituent atoms, there really is a very finite set of possible combinations which are not toxic and structurally suited to perform some task in the biochemical mechanistic computational environment of the cell.
Also, this is not a refutation of your point, just interesting, but complete opioid synthesis has been engineered into yeast by at least two different teams at his point: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4924617/
I would state this as "chemical space is so large it's surprising that an evolutionarily distance biosynthetic pathway would, through evolution, actually find and optimize molecules that were remarkably effective modulators of an extremely distantly related organism." (I'm not ascribing intent or desire to evolution here, when I say "find and optimize").
But like many things in biology, if you view it through a billion-year evolutionary lens, it's not completely surprising. I doubt anybody could come up with a general rule or law that explained this well, and anything I did would just speculative arm-waving, of which this site has enough.
If a substance is abundant in the environment, you don’t need to spend your energy and reduce fitness in other areas to produce it on your own. Many species as a result might need things like certain amino acids found in their food that they don’t produce on their own, instead taking advantage of what is there. That logic shouldn’t really stop at nutrients or amino acids. There is no doubt an advantage to seeking out environmental compounds that act as neurotransmitters, saving you from having to spend energy generating those compounds internally.
Right, but the point is that certain plants and mammals do produce these independently. Humans don't require smoking weed to get enough cannabinoids into their system to get their brain to actually work. Likewise poppies aren't stealing humans' opiates to defend against fungi.
Both sets of species are each doing a whole bunch of work to create these very specific, very complex molecules, and using them for different purposes.
It's not a well supported theory, but fascinating. Possibly an epigenetic influence? Much more likely a cultural effect, if any, that nudged early humans down the path of spiritual pursuit as a sort of cultural glue. The more spiritually inclined you were, the more likely you were to thrive in the societal hierarchy.
Use of psychedelics could have helped accelerate an individual's "spiritual" development and therefore afforded them additional offspring. So the correlation, if any, might be a favoring of genes that paired well with the effects of psychedelics. Pure speculation on my part.
As for AI, it seems highly likely a new class of designer drugs will emerge, tailored to a specific individual to enhance societal adaptation. We've already seen this in play over the past 40+ years in the pharmaceutical industry. AI will only accelerate it IMO.
Imagine your cognitive abilities today if no one ever spoke a language to you through your childhood. Cultural influence is able to significantly improve this. Thats not a genetic factor but an environmental one that is predominantly responsible for this phenotype of a developed and modern adult.
Todays babies rapidly grow their brain while learning new languages. Kids who wind up feral for whatever reason have severe cognitive issues from a lack of learning language at a critical age.
It makes you wonder how this brittle system got its start. Considering everyone today needs this language kick start induced by cultural practice, maybe the initial kick was also some cultural practice that also introduced new ideas where there wouldn’t be otherwise. Maybe that practice at one time was a shamanic like experience considering the proliferation of these practices in the most basal religions we have around the world. Its really hard to say what came first, the language or cultural practices such as ritualized drug taking, considering what archaeological evidence we have seems to suggest these things were happening at the same time.
Yes, it's nonsense. The neocortex doesn't work from the lack of lead, and psychedelics appear to start it up in some way. People didn't used to need to be drugged up on shrooms to be conscious.
AlphaFold’s potential in revolutionizing drug discovery, especially in the realm of psychedelics for antidepressants, marks a significant paradigm shift.
The protein class they bind to has historically been hard to determine structures experimentally and had high flexibility. The preprint that is the basis of the article showed that using traditional virtual screening against Alphafold structures had similar success rates as screening against experimental structures. Additionally, the Alphafold structures may represent alternative conformations of the proteins not seen in the experiment-derived structures.
AI's matching hit rates in drug discovery is a game-changer. It's like AlphaFold just gave us the GPS coordinates for the biochemical treasure we've been blindly digging for. LSD's serotonin link and the quest for similar, safer compounds?
Exactly. If they discovered any new drug that has even a tiny potential for recreational use, it's going to be banned quickly. Hell, we can't even have certain plants that grow entirely in nature. No way they're going to allow new synthetics. Unless our current social Puritan outlook starts to change, it's not gonna happen. And we're headed toward puritanism right now, rather than away from it, so I wouldn't be counting on it during our life times
It can cause permanent damage to vision or sanity. Sure, it's not addictive, and you practically can't overdose -- but it makes you temporarily insane and blind, and both of these can persist without there being a cure. And just, a general point: [CITATION NEEDED]. Unlike you, I'll provide my own citation: https://www.frontiersin.org/articles/10.3389/fpsyt.2017.0024...
> And there are a lot of similarly safe compounds with "smoother" psychological effects.
If you mean the party drug 2C-B, it has some similar risks.
Yes, there are some, quite rare, side effects. The visual disturbances of HPPD are quite subtle (ibid.), and definitely not making you blind as you claim. The psychedelic experience can be extremely distressing, especially at high dosages and in difficult settings, and this may cause longer term mental health problems.
Almost all drugs (illegal or legal) have potential side effects. Most psychotropic medicine have quite nasty side effects and/or cause dependence. SSRIs can make you insane or to lose your libido. Benzodiazepines are very addictive and their discontinuation may cause fatal delirium. Eating a box of Tylenol can easily destroy your liver permanently.
Comparably, LSD is pretty darn safe. At least when taken in well controlled doses and in safe settings. Hard to see LSD's side effects being a showstopper for its medicinal use.
Yes, 2C-B and the many many similar compounds tend to have similar side effects.
As someone who suffers greatly from an autoimmune condition, I could not agree more. It makes me wish I had developed a background that would allow me to work on this problem. Once my kids are raised, if it hasn't been done already at that point, I'll be giving it a try
Here is maybe a helpful analogy for the challenges behind protein folding.
The 5HT2A receptor is comprised of 471 amino acids. Proteins fold based on interaction between each of those amino acids, plus the external environment (plus post-translational modification).
So imagine a length of string with 471 magnets attached to it with different magnetic field strength (ranging from weak to strong). Now imagine it floating in space - how would the string fold upon itself? Now imagine different segments of the string have different stiffness - some are super flexible, others are rigid.
Difficult to predict how it might fold? Oh yeah!
Now imagine the string not in space, but in a solution of water with a number of other magnets floating in it (the cytoplasm within the cell and external environment outside the cell). Oh, and also imbedded in a wall with magnets in it as well (the cell membrane).
Now how does it fold?
Ok, now we think we have a good approximation of the structure just based off of various pieces of data. But wait! Other proteins are also embedded in the cell wall - all with their own structures and selection of weak and strong magnets, stiff and flexible segments interact with the receptor! Oh, and not all receptors have the same external environment - that can differ based on another laundry list of factors. Yeah, that's another layer of complexity.
Then add on top that the external environment (inside the cell on one side, outside the cell on the other) has a ton of water, but also dissolved ions like Na+, K+, Cl-, plus a bunch of other proteins with their own "magnets" and "stiff and flexible segments". These outside molecules will bind and disassociate from the receptor on a constant basis, ever so tweaking the shape.
Oh crap.
Of course AI has a good starting point - we can get x-ray crystal structures of the receptor and identify the position of atoms. But wait! That's in a crystal, not a human body! So that structure is likely incorrect in several ways. We also have other analytical techniques that can give clues to the structure in a solution that more closely mimics what's inside the body, so we can at least tell when the x-ray structure is just wrong (at least in some places).
That should give people an idea just how complex protein folding is. AI is good at taking all known "rules" about protein folding (and molecule interactions with the protein) to improve the predictions. But we're still far off from truly understanding all the factors in play.
But the really important conclusion of the paper, which I truly hope bears out, is that AF2 models are useful for finding binders to GPCRs.
GPCRs are one of the largest (if not largest) drug targets and work (including my own) showed that modelling protein dynamics using expensive simulations was likely to be necessary to make accurate predictions of GPCR binding molecules. If this paper is correct, AF2 is actually able to recapitulate much of the detail that we previously believed required expensive dynamics simulations, which is about the best possible news because it suggests that we can omit these costly calculations.
It's almost certain now that AF2 will win the Nobel Prize, as this represents some of the most exciting breakthroughs in the past few decades.