The other day, during an after-symposium discussion on detecting BS AI/ML papers, one of my colleagues suggested doing a text search for “random split” as a good test.
A lot of what you write is to the point and very valid. However, I think you are missing part of the story. Let’s start with
“Unlike drug development, where you’re trying to precisely hit some key molecular mechanism, assessing toxicity almost feels…brutish in nature”
I assume you don’t really believe this. Toxicity is often exactly about precisely hitting some key molecular mechanism. A mechanism that you may have no idea your chemistry is going to hit before hand. A mechanism moreover that you cannot use a straight forward ML to find because your chemistry is not in any training set that an ML model could access. It is very easy to underestimate the... (read more)
Yes, I agree, I think it is pretty unlikely. But not completely impossible. As I said it should be pretty easy to find them if they are in the lysate via, HP liquid chromatography. Brain penetrant cyclic peptides should on the whole be significantly less polar than acyclic polypeptides of similar mass.
An excellent analysis and I’m almost sure your mistrust in the pharmaceutical efficacy of Cerebrolysin is well founded. However, having some experience working in the field of brain-penetrant drugs, I can comment that your restrictions on molecular weight and properties are too conservative. Small molecules of >550 dalton are capable of crossing the blood brain barrier if very well tailored. Also small cyclic peptides can hide their polar backbones within buried intramolecular hydrogen bond networks and become membrane permeable. The bicyclic peptide SFTI-1, a 14mer peptide, has been shown brain penetrant in rat in what looks to me a reasonable study. So, playing devil’s advocate, there is a hypothesis that the lysis... (read more)
There is an additional important point that needs to be made. Alphafold3 is using predominantly “positive” data. By this I mean the training data encapsulates considerable knowledge of favourable atom-atom or group-group interactions and relative propensities can be deduced. But “negative” data, in other words repulsive electrostatic or Van der Waals interactions, are only encoded by absence because these are naturally not often found in stable biochemical systems. There are no relative propensities available for these interactions. So AF3 can be expected to not perform as well when applied to real-world drug design problems where such interactions have to be taken into account and balanced against each other and against favourable interactions.... (read more)
I have similar concerns regarding the ligand sets used to test Alphafold3. I’ve had a cursory look at them and it seemed to me there were a lot phosphate containing molecules, a fair few sugars, and also some biochemical co-factors. I haven’t done a detailed analysis, so some caveats. But if true, there are two points here. Firstly there will be a lot of excellent crystallographic training material available on these essentially biochemical entities, so AlphaFold3 is more likely to get these particular ones right. Secondly, these are not drug-like molecules and docking programs are generally parameterized to dock drug-like molecules correctly, so are likely to have a lower success rate on... (read more)
So after tearing my hair out trying to generate increasingly complex statistical analyses of scientific data in Excel, my world changed completely when I started using KNIME to process and transform data tables. It is perfect for a non-programmer such as myself, allowing the creation of complex yet easily broken-down workflows, that use spreadsheet input and output. Specialist domain tools are easily accessible (e.g chemical structure handling and access to the RDKit toolkit for my own speciality) and there is a thriving community generating free-to-use functionality. Best of all it is free to the single desk-top user.
Useful post. I can expand on one point and make a minor correction. Single Particle Cryo-EM is indeed a new(ish) powerful method of protein structure elucidation starting to make an impact in drug design. It is especially useful when a protein cannot easily be crystallised to allow more straightforward X-Ray structure determination. This is usually the case with transmembrane proteins for example. However it is actually best if the protein molecules are completely unaligned in any preferred direction as the simplest application of the refinement software assumes a perfectly random 3D orientation of the many thousands of protein copies imaged on the grid. In practice this is not so easy to achieve and corrections for unwanted preferred orientation need to be made.
I’m not going to say I don’t share deep disquiet about where AI is taking us, setting aside existential risk. One thing that gives me hope, however, is seeing what has happened in chess. The doom mongers might have predicted, with the advent of StockFish and AlphaZero, that human interest in chess would greatly diminish, because, after all, what is the point when the machines are so much better than the world champion ( world champion ELO ~2800, StockFish ELO ~4000) . But this hasn’t happened, chess is thriving and the games of the best human players are widely streamed and analysed and their brilliancies greatly admired. The machines have actually been... (read more)
Bridge, like most card games, is a game of incomplete information. It is a game of many facets, most of which will have to remain unstated here. However the calculation of probabilities, and the constant revision of probabilities during play, is a key feature. Much the same can be said of poker and of certain other card games. But bridge is the game I know and I am still learning from, 45 years after I first got infected with the bridge bug
We have Alpha Go and Alpha Zero but the wizards at DeepMind have not yet seen fit to release an Alpha Bridge. Poker is played to high expert standard by specialist... (read 4067 more words →)
I agree with the OP that the search for a broad spectrum anti-cancer drug is still a worthwhile endeavour. But I think it would be wrong to hold back on research into the more specific cancer remedies because the current most effective therapies are very often combination therapies of a type-specific anti-cancer drug co-administered or post-administered alongside a classical broad-spectrum anticancer agent such as cis-platin, or an anti-hormone agent for hormone dependant cancers. It is unlikely that new broad-spectrum treatments be so effective that this situation will change.
Having said that, there is huge research into targets ubiquitous for many cancers but formerly considered undruggable, such as P53 and Myc. We are getting... (read more)