First off, a note that posting will be a bit irregular this week, but I wanted to let people know that I'm definitely still around! So here's something to talk about:

There's a good new paper in JAMA Internal Medicine looking at a large recent data set in Covid-19 vaccinations in an older population. It's from the Veterans Administration, looking at about one million veterans who got a flu vaccine in 2024, and over three hundred thousand of them also got a coronavirus vaccine. Following up on these cohorts, the authors find that there was a 38% reduction in coronovirus-related major cardiovascular events in that latter vaccinated category, which is very nice to see. Even more interesting is that there was a 24% decrease in all-causes cardiovascular events (that is, including patients who were never diagnosed with a coronavirus infection during this period. That's quite impressive - comparable to the benefits of statins in at-risk patients (and it should be noted at the same time that the effects of statin therapy in otherwise healthy older patients do not seem to be particularly meaningful, although debate continues on that question).

As this excellent overview at Stat details, the most likely explanation for these numbers is a significant undercount of how many of these patients were actually infected with the coronavirus. But that's worth thinking about, too, because that leads one to the idea that many of them may have not felt all that sick (and never bothered getting tested for the virus as a result) but still had enough of an infection to raise their risk of cardiovascular trouble. And that makes a case for really getting those vaccination numbers up higher - the estimate from the paper's authors is the possible avoidance of 3,500 major cardiovascular events per million patients vaccinated in this population.

As the Stat article correctly says, this might surprise some people who associated the coronavirus vaccines (particularly the mRNA ones) with the side effect of myocarditis (particularly in young men). And that's a real finding - the vaccine did produce this in a small number of patients. But (and I've said this before), you know what gives people mycarditis at a significantly greater rate and in greater severity when it does occur, and not just in young men? Yeah: getting infected with the coronavirus. So it's still a very good tradeoff, and in this older population it's almost certainly an even better deal.

This will not sit well with the people who believe that the mRNA coronavirus shots have ravaged the world's population and are the cause of a whole list of diseases (cardiovascular death being a prominent one, for sure). You don't have to go far to find these folks - heck, some of them will be showing up in the comments to this post once they become aware of it, although I (as has been the policy here since the worst days of the pandemic) will not even let the most scurrilous of these even publish to the comments section in the first place. The signal/noise of the world is not improved by several paragraphs of poorly punctuated ranting about secret depopulation experiments, 5G nanobots, irreversible changes that make vaccine recipients subhuman and thus put the few, the brave, who haven't been vaccinated in the position of the Last Pure Humans on Planet Earth, and on and on. Nope, there's plenty of that crap out there already and I see no need to give it a platform here.

But the irony is rather thick: coronavirus vaccines not only keep people out of the hospital with severe viral infections - a fact that has been irrefutably proven in many large studies - but also help to keep elderly patients from dying of major cardiac events. Add that to the mounting evidence that the shingles vaccine helps to prevent dementia in these same age groups, and the recommendation has to be that older patients should be getting vaccinated far more often than they do. I'm not quite 65 yet, but I have taken all of these shots and will continue to get the updated coronavirus ones as they become available. Because I really think that it would be irresponsible to do otherwise.

There are a couple of very interesting AI-assisted-chemistry paper out this week, and I have been trying to find the time to take them on. Let’s do this one first. It’s a report on “Co-Scientist”, a system to help propose hypotheses, potential mechanisms, et al. for biomedical discovery.

The authors first applied this in what I think is a good test bed for it: drug repurposing. Let’s put aside the not-all-that-high success rates seen in these efforts, because nothing in this field has a high success rate when you get right down to it. I saw that it’s a good area because existing drugs at least have a lot of fairly reliable data around them, and that’s what a system like this needs most of all.

The first test was looking for new single-agent and combination therapies in oncology. The program suite is well-named, actually, because it turns out that human input and judgement is required all along the way (you may be relieved to hear). The beginning step was prediction of the effects of 2300 approved drugs profiled across 34 cancer types, with the predictions then human-evaluated by one or more oncologists. The most actionable predictions were deemed by this review to be the ones for acute myeloid leukemia (AML). The human team selected four different AML cell lines and one control line to evaluate compounds in, but as the paper correctly notes, this is more of a reality check than any kind of big step into clinical developability.

The selection of compounds to assay (like the selection of the particular cancer type and the selection of cell lines to evaluate it) was made with “meticulous expert oversight”, i.e. human oncologists. Thirty drug candidate proposals were reviewed by this committee for their potential AML relevance, and five were selected: binimetinib (an MEK/MAP2K inhibitor), pacritinib (which inhibits JAK2 among other kinases), cerivastatin (an HMG-CoA reductase inhibitor statin drug whose withdrawal from the market ultimately led to the closure of the entire research site I used to work at!), pravastatin (another drug in that same class), and dimethyl fumarate. The first three showed activity in relevant cell assays, with binimetinib being the clear winner in potency.

But hold on: I would have to add at this point that targeting the MEK pathway in AML (as with binimetinib) is not exactly a new idea, with a number of lines of research having been investigated. As for the other two that showed cell activity, pacritinib has already been into the clinic in some AML subtypes, and the unusually strong ability of cerivastatin to induce apoptosis in AML cell lines was noted in the literature 25 years ago (which work could also have predicted pravastatin’s lack of activity here. I do not see citations of any of those references in the manuscript in its current form.

The team then used the Co-Scientist system without oversight to propose single-agent drug repurposing ideas for AML, but as before, they did have an expert human panel review its proposals. The paper doesn’t say how many candidates went into that step, but three came out the other end of the review: nanvuranlat (a LAT1 inhibitor), KIRA6, and leflunomide. When these went into the cell assays, only KIRA6 showed activity. It’s an IRE1-alpha inhibitor, and as the paper does note, that mechanism has actually been proposed before as an AML therapy (although not with this particular compound). I’m not sure if I would call that “repurposing” or not, but that’ll vary on your own definition.

Of course, oncology is all about drug combinations, cancer cells being what they are. The paper goes on to look for possible synergistic combinations, and I would have to say up front that synergy in these situations is a lot less common than you’d hope for. The results were complicated, not that that came as a surprise, I’m sure. In one cell line (MOLM-13) a number of the combinations did show at least additive activity, but in another (KG-1a), there was a wide range of results, with some combinations apparently cancelling each other out. As the authors put it, “Further mechanistic studies will be required to define the molecular determinants of response to combination therapy across AML subtypes, and to identify predictive biomarkers that could enable rational regimen selection”, and they sure are right about that.

The other aspects of the paper are rather less well-documented in this manuscript, but that’s because they are covered in other publications. There’s a paragraph or so about using Co-Scientist with human hepatic organoids and cell imaging to come up with new repurposing ideas for liver fibrosis. The one that they specifically mention is vorinostat (there’s more on that here in a separate paper), but as before, a look through the literature shows that this compound as well has activity against fibroblasts and in other models of fibrosis in general. Indeed, the entire class of HDAC inhibitors (of which vorinostat is the prototype) has been investigated in fibrotic disease models and in liver fibrosis in particular, up to animal models. I think it’s good that the system picked up on this, but this is not exactly a de novo result. I should note that none of the papers just mentioned appear to be referenced in the current manuscript, nor do I find references to them in the separate manuscript on this work linked above.

There’s also a mention of Co-Scientist recapitulating a very recent result on an antibiotic resistance mechanism, the exchange of capsid-forming phage-inducible chromosomal islands (cf-PICIs) to spread resistance genes. The system appears to have proposed the same mechanism that the research team had arrived at, which is that these interact with specific phage “tails” to move into new hosts. You can find more on that in this paper and in this one. And that does seem quite useful, using the system as a focused “results digester”. It would be interesting to see what its proposals would have been along the way as the experimental data developed - I suppose this could be recapitulated, with some effort - and if the experiments themselves would have been redesigned and perhaps converged on the answer more quickly. Or not! It would be quite useful to know.

My overall take is that this looks like a promising system, especially for uses like that last one, where you have a large corpus of experimental data and would like to see what the software makes of it. I’d like to see some other examples of just that sort of test being run (where you know the answer and want to see if Co-Scientist arrives at it and at what stage). The open-literature drug repurposing work is to me more of a mixed bag. I think it’s good that the system identified the mechanisms that it did, but I don’t think that the paper does enough to point out that none of these ideas are without precedent - in some cases, a lot of precedent. I wonder how much of the human-review steps mentioned involved people noticing such papers and prioritizing those compounds and mechanisms (naturally enough!) But as you might imagine, the publicity around this work seems to be pointing in the other direction entirely, which I don’t think is doing anyone much of a service. We definitely need all the help with the literature that we can get, but hype we have enough of already.

I’m working on a big post or two, but I did want to get something up today. Have a look at this rather disturbing news from the mouse model world, published here at Science. The authors went to the trouble of genotyping 611 mice tissue samples representing 341 strains at the MMRRC (Mutant Mouse Resource and Research Centers), and as the paper notes, rather dryly and through pursed lips, “Users’ expectations for congenic strains based on nomenclature are not consistently met”.

Yeah, you could say that: nearly half the mice were not really what they were labeled as, with failures at several levels. Worries about this have been building for years as sequencing technology became more and more capable, but I think that this is by far the largest-scale and most detailed look at the problem. To be sure, many of the inconsistencies are believed to be relative minor, but not all of them, for sure. Some of the problem is in the naming conventions used, which are probably promising more than they can deliver:

In addition to the inconsistencies between reported names and genotypes reviewed above, mouse nomenclature as defined by the ICSGNM (10) is not designed to reflect the complexities and nuances in the genetic makeup of many strains. However, names matter, and most users of mouse models have definite expectations for congenic strains based on our frequent conversations with MMRRC and MiniMUGA customers, and with scientists at professional conferences. For example, users expect that congenic names denote strains with the only contribution of the donor strain occurring in the chromosome carrying the relevant mutation. They also expect that such strains are inbred and thus have extremely high levels of genome replicability. These expectations are not consistently met in the MMRRC sample set referenced above, as naming rules allow for a wide range of variation of congenicity and inbreeding levels . . .

A great many might be best described as “incipiently congenic” at best, and the proposal is to capture this in thesummary description of each strain rather than trying to work it into the names themselves. The authors detail an “MMRRC Strain GQC Report” format that tries to get across the key messages using the same layout and the same terms across all the samples - type of strain, the allele and locus of interest, the primary and secondary genetic background, and whether or not the genome is truly replicable (and why not, if that’s the case). It’s designed as well to be able to flag the all-too-common situation of some genetic contributions from yet a third strain of mice along the way., and it also has warnings for constructs that include things that could mess up a variety of experiments, such as having cre recombinase in there or genes for various fluorescent proteins.

It looks like well over a hundred strains have had such reports generated, and teams are working their way through the rest. One hopes that this standard will catch on with other such mutant animal repositories, because there’s no reason whatsoever to think that they have been immune from the problems that got us to this situation. If we’re going to do animal research - and we still have to - we should absolutely be getting the most value out of it and wasting the least number of animals (and the least time and money, needless to say). This is both a scientific and an ethical charge, and I’m glad to see it being addressed.

The arXiv preprint server has become essential to several scientific fields, and has inspired similar services like BioRxiv and ChemRxiv. But the generative AI age has been hard on these sites, and you can see it by their steady imposition of new rules.

Last November, arXiv announced that it was clamping down on the submission of review articles, particularly in computer science. These were becoming alarmingly easy to put together (often as not padded out with references that didn’t even quite exist), and the moderators were getting overwhelmed. No new reviews would be accepted in computer science, they ruled, unless they had already been through a peer-review process at a journal (or for a conference), which sort of turned the entire idea of the arXiv on its head in that manuscript category. But you can understand why.

Then in late January came the announcement that first-time submitters would need an endorsement from another author who had published there before. The stated reason was a rise in outright fraudulent submissions. That article says that the moderator's rejection rates had tripled over 2025 and were apparently still rising, and something obviously had to be done.

Now the chair of the site’s computer science editorial committee (Thomas Diettrich) has turned the flames up. “If the submission contains incontrovertible evidence that the authors did not check the results of LLM generation, it means we can’t trust anything in the paper. The penalty is a 1-year ban from arXiv followed by the requirement that subsequent arXiv submissions must first be accepted at a reputable peer-reviewed venue”. He went on to give examples of such evidence, including the above-mentioned hallucinated references (to papers that just don’t exist) or the presence of meta-comments from the LLM software ("Here is your summary" and so on).

Those fake references are indeed becoming a plague, as illustrated by this manuscript at arXiv itself. Those authors set a lower bound of over 146,000 hallucinated citations appearing in 2025, and it's been rising sharply. This obviously threatens the integrity of the scientific literature itself, and that really didn’t need to take any more torpedos, thanks. If we don’t do something about this we run the risk of an eventual painful de-slopping process, and it would be a *lot* better for everyone if we blocked that crap from getting into the literature in the first place. It’ll be a race. . .

I definitely need to cover this recent work from Merck, because (1) it’s very interesting scientifically and (2) it has over 130 authors on the paper (!) It details the industrial synthesis of enlicitide, which is a beast of a macrocyclic peptide (see below!) Just looking at the structure tells you that this must be a ferociously active molecule with huge commercial potential, because there is just no way that anyone is going to make this on scale - or find a way to make this on scale! - otherwise.

This drug hits the PCSK9 pathway, which has been quite a story over the years. This target was famously discovered by finding a few people with mutations in the underlying gene who had bizarrely low LDL concentrations and who seemed to have correspondingly robust cardiac health. The first drugs on the market to take action on this idea were antibodies to block the receptor, and those were approved by the FDA some years ago as injectables.

They do indeed lower LDL, but (as that last blog post link notes) the results in humans have to be characterized as “good but not revolutionary”. I don’t know of any studies that show a definite advantage compared to statin (HMG-CoA reductase inhibitor) therapy, for example, although there are statin side effects in some patients that have to be taken into account. (On the other side of the question, statins seem to have some beneficial pleiotropic effects that we don’t quite understand, and whether these are shared by PCSK9 inhibition, I don’t know). And there are other people for whom statin therapy just comes up short, to be sure.

Several companies have tried over the years to come up with a small-molecule (well, smallish-molecule) approach that could lead to an orally dosed therapy as opposed to an injectable, and Merck has apparently made it over the finish line with this one. Here are the results of a trial in over 1900 patients (compared to over 900 in the placebo group) treated with the drug over a year, 20mg once a day. Over that time, the placebo group’s LDL went up about 3%, while the treatment group’s went down about 57%, which is what we call “pretty darn significant”, statistically speaking, with no differences in adverse events.

So now that you have a new cardiovascular drug, how do you make it for the hoped-for large patient population when it looks like, well, that thing to the right? That’s quite the multicyclic peptide, and while a lot of the key bond formations are good ol’ amide couplings, you have several that are not. The team divided up the molecules into “Western”, “Eastern”, and “Northern” pieces (based on the three macrocycles in the final structure) and demonstrated that they could make all of these in crystalline form (thus obviating the need for chromatographic purification). The Northern one was the toughest by far, with three unnatural amino acids and a choice of amine nucleophiles.

The answer to putting all this together was harnessing amino acid ligase enzymes, which lets you couple unprotected amino acid partners when everything is working right. The Merck team looked over a list of AAL enzymes and found one from Bifidobacterium adolescentis that was accomodating enough to deal with their intermediate. All of the candidates turned out to be able to handle peptide chains as the nucleophilic partner while only accepting single amino acids as the electrophile. That’s too bad in a way, because you could imagine assembling larger fragments this way, but if you get the enzymatic process running smoothly enough you can just turn things through it several times in a row. And without having to do protection/deprotection steps!

What looks like the nastiest traffic jam in the synthesis was the final stage of making that fragment, because you’re presented simultaneously with three amines and two carboxyls that need to be brought together in the proper pairings. The Merck group turned to esterase enzymes rather than proteases/amidases, not least because those can’t be tempted to run the amide formation in reverse because they don’t have the nucleophilic horsepower in their active sites. A previously-unreported enzyme from a Roseibacillus species showed promise, although I would certainly like to hear how many others got screened along the way, and even that one needed some engineering to increase its selectivity. They ended up being able to make the Northern piece with four enzymes and three separate building blocks in a single pot, which really is a tour de force.

To elaborate on to the final macrocycle the team called on thioesterase enzymes, which are generally what come into play in biosynthesis pathways for natural products of this type. Another (no doubt wide-ranging) screen identified a likely one from Brevibacillus laterosporus, but this also needed artisinal modification in its sequence to get the yields and selectivity up. I am skipping over a lot of work when I write sentences like that one!

The Northern and Eastern fragments also needed a reductive amination to bring them together, and a ketoreductase enzyme from a Kyrpidia species coupled with an imine reductase (from Pseudogymnoascus species) was used to make the requisite aldehyde, both after still more screening and protein engineering. This reaction mixture needed recycling of NADP/NADPH to run the synthesis enzymes, and still more enzymes were brought in for that cycle. In the end, the team achieved a one-pot five-enzyme process that did the overall transformation in 69% isolated yield.

Coupling this to the Western fragment was done through good ol’ chemical means (diphenylphosphinic chloride) while protected a stray primary amine that needed to be ready for the final macrocyclization. There are many such syntheses that have come to grief at such final steps; these macro-ring closures do not always want to happen easily. Another engineered thioesterase (this time from a Streptomyces species) was found to do the job and without the traditional need for high dilution. You often have to do that dilution to encourage your molecule to bite its own tail and make the large ring as opposed to reacting with another one nearby (which makes useless dimers or oligomers), so this enzymatic route is a huge help. The transformation comes though in 84% yield and >99% purity after liquid-liquid extraction and salt formation!

The overall yield, starting from 5-fluoro-N-aminohexyl tryptophan (you can see it hiding in there) is 39% and this has been run on multikilo scale with no chromatography. This is tremendously impressive, truly state-of-the-art process chemistry. I think we’re going to be seeing the reverberations of this work in macrocycle synthesis (and especially macrocyclic peptides) for a long time to come. Now to see if the drug itself performs up to its commercial and medical potential!

Coco is on the left.  I get her and Lizzie mixed up!  Two little black Pekes sitting together. 
No matter where their mom and dad are, they are watching.  And mom is being watched the most.  
Like here.  Coco is with her brother, Elwood, and he's joined them.  Their mom just walked out of the room.  Don't worry guys.  She's coming right back.