Skip to Content

Chemical News

Give It to the Machines

Here’s another paper for the automated med-chem files. A group at Merck (Boston) reports a combination of very small-scale automated synthesis with a screening assay in situ (no purification). You may be wondering how that works, or how it can possibly work, especially when you hear that the nanoscale reactions are transition-metal catalyzed. After all, we usually spend a good deal of effort trying to make sure that our assay candidates are cleaned up and (most especially) free of metal contamination.

Springer/Nature

The key is the type of protein assay. It’s not a functional readout, which is where the metals can give you all sorts of false positives, but rather just a binding assay, done by mass spec. That’s generally done in an is-anything-there binary mode, but in this paper, they’re actually titrating in the amount of protein to get a rough order of affinities. Still, one strike against that sort of detection has always been “But you’re only measuring binding, not real inhibition, etc.” That’s still true, but now you can always consider going the targeted protein degradation route, in which case all you need is some sort of binder. As mentioned here in another recent post, the same consideration applies to DNA-encoded libraries, which also just give you a binding affinity readout – the Merck authors don’t mention this aspect, but it’s a real consideration these days.

In this case, they did a test with 20 reactions each using amide formation, Suzuki couplings, and Buchwald-Hartwig C-N couplings (which certainly cover a lot of real-world medicinal chemistry, for better or worse).  They used the small-scale reaction setup to screen conditions for the latter two, in a smaller-scale version of this sort of thing. In each case, they also synthesized the products on a 20mg scale and purified them by traditional means, in order to compare them with the nanoscale assay results. (These all produced compounds in known kinase inhibitor space, which I’m afraid is also pretty realistic.) And the correlation was strong: the affinity-mass-spec assay could indeed pick out the potent compounds (as it should) without giving false positives along the way (since you’re looking for the particular mass signature of the product associated with the enzyme.

With this confirmation in hand, the group then took one of the intermediates and coupled it in each individual well of a 384 plate after an automated reaction conditions screen. They got 345 products and rank-ordered them by titrating in CHK1 protein, with a mass spec readout each time, and identified three new potent binders. These reactions are done on about 0.05mg of material each, so you can plow through quite a few of them without plowing through a lot of starting material, and generate a lot of SAR data rather quickly. The reaction screening is a key part of the process – taking robust but generic coupling conditions across that same 384 set only gave 158 products (and thus missed several nanomolar inhibitors). Overall, to optimize the 384 set and assay them took 3114 reactions, consuming about 120mg of the starting material. You are not going to be able to do that by hand. I don’t care how much of a machine you are in the lab, you’re not more of a machine than a machine is.

As the authors note, machine-learning algorithms may eventually make it easier to navigate both reaction condition space and SAR space, but for now, we really have to attack these things empirically, and this (in general) seems like the way to do it. Small scale, highly automated, optimized, high-throughput: you’re not going to be able to sort things so thoroughly any other way. And since we often have to resort to brute force, we should be letting the machines take that on whenever possible, because brute force is exactly what they do the best. That was proven on the high-throughput screening end of the business many years ago, and it’s true on the compound synthesis end of things, too. Bring ’em on.

 

23 comments on “Give It to the Machines”

  1. Anon says:

    No end to an absolute madness at Merck. As an ex-Merck employee it saddens me to see no end to stupidity having seen the failure of Combi chem, HTLD, siRNA etc. and my list is long! In our zeal to discover medicinal drug we lost our sight and perhaps vision as well. The drive by delivery mentality works only for fast food restaurant.

    1. AChemist says:

      I would have to agree. Wouldn’t surprise me at all if this just results in another one to add to the long list of the above-mentioned failures. Trying to convert the drug discovery process into an automation is doomed to produce close to nothing. The real way to go is precisely the opposite, but try peddling that to capitalist CEO’s.

      1. Derek Lowe says:

        But to me, this is just a sped-up version of what medicinal chemists do by hand. . .

      2. CB1 says:

        IRT affinity ranking; this could accelerate the early SAR of drug discovery where lots of SAR is done to eliminate what does and doesn’t work in broad strokes since it’s just a binding assay. Maybe that would save a couple months work for a team of chemists. I wonder if they will try to use this throughout a project to expand SAR in the hopes for serendipity to occur with minimal thinking.

        Nano-scale reaction screening is always welcome in my view (Fig 2b.). Anything to help sift through catalyst, base, and solvent is welcome especially on tougher aryl bromides which can be maddening doing this manually to just get a yes/no from an affinity assay.

      3. SD Chemist says:

        My old Director of Med Chem(may he rest in peace) has a poster of a fish with a giant front tooth. “Adapt or Die” it said. We still need great medicinal chemists but these new tools are not going away.

    2. Passerby says:

      Madness?!! THIS. IS. MERCK. (Nod to “300”)

  2. Anon says:

    @ Derek Lowe….Aha, I hear you say, sleight of hand?

  3. Marcin says:

    Derek, I think your enthusiasm is not shared by your readers because of the respective position on the corporate food chain

    1. Derek Lowe says:

      Could be. But at the same time, if your position involves cranking out analogs in a way that can be done by a machine, you need to think seriously about your career prospects. They aren’t rosy.

      1. Marcin says:

        That is why I switched to medicine

      2. Fauxtoredox says:

        …which is why I find it confusing that synthetic chemists from the “top groups” in catalysis (hired by Merck, BMS etc) are just glorified screening robots that can make well-composed slides in helvetica. The number of substrates in Science/Nature/JACS method papers eclipses 50 (or even 100!) with alarming regularity now, and rejections for “lack of scope” are common. We’re training people to be obsolete. Additionally, the demand for all yields/ees to be over 90 wastes at least as much time manually optimizing and playing with the baseline of the trace…

  4. John Wayne says:

    This is pretty neat. Screening reaction mixtures with affinity and MS is a clever way to get at some meaningful data. This is a pretty niche tool; very handy for quickly focusing you in on the important parts of chemical space if binding activity is something you need to optimize.

    I think the real story here is similar to a report from a week or two ago … how is this in Nature? It seems like there is reputation (or at least impact factor) to be made understanding how nonchemists view what is a big deal in chemistry, and taking advantage of the delta. If the technique allowed you to optimize PK this would be huge; this seems more like a headlining paper in J. Med. Chem.

    1. Anon1 says:

      We in the biz know this is only useful for hit-to-lead (and only in some cases), not lead optimization and beyond. This is the disconnect I think, academics don’t realize the limited application.

  5. ChairmanMao says:

    Why is Merck reporting this if its so Great? You would think they would keep such chemistry confidential so that the competition doesn’t learn form this. Companies are in the business of making money, not acting like insecure academics that have to show everyone how smart and great they are- even when they aren’t.

    I’d fire them all and hire those who don’t need their egos stroked while earning the highest pay in the industry.

    1. Unbridled Enthusiasm? says:

      I must say, the open-mindedness of commentators has been cringe-worthy as of late. What happened to the forward-looking, optimistic, and enthusiastic scientist that takes risks and chances to drive innovative medicine forward? Comparing a 1st-gen paper or technology to “failed” approaches in pharma of the past (e.g CombiChem) is simply idiotic. The industry suffers from a <1% success rate from lab to market… why would ANY idea be criticized? If anything, shareholder-driven companies that still support and/or promote this type of thinking and basic research should be commended on every level – today's data drive tomorrow's discoveries. This is RESEARCH.

      1. fajensen says:

        I think maybe “the recovery” is beginning to reach into the higher levels of the middle classes?

        Forward-looking and Enthusiasm are some of those luxuries that gets squeezed out really fast when people are feeling that even the lower tiers in the Maslow Pyramid becomes their stake in the competitiveness game!

        I certainly experienced this effect when I was working in IT during the ‘naughties. People worrying about bills are not creative people.

    2. BellJar says:

      …well Merck has been trying to improve their public image for a few years now by asking, if not begging, their employees to publish…ANYTHING! Plus a first author publication is required for anyone wishing to be promoted…

    3. AVS-600 says:

      Yeah, it’s really annoying how all those scientists they hire seem interested in contributing to science.

  6. Fullo says:

    Machine learning algorithms have not shown why titanium needs pladium to catalyze hydroelectrolysis. Its silly to involve statistical principles to explain something we have not hammered out in basic theory.

  7. Me says:

    Interesting paper – and discussion.

    How I see this fitting in is as follows:-

    HTS to get 1-shot hits >>> This technology ^^^ to separate the singletons vs those with vague SAR >>> Full Lead Op = ADDED VALUE!

    This is a decent shout for something that will aid you.

    If you are not *only a synthetic chemist* that is….

  8. Schmerck says:

    This is typical the tail wags the dog research ongoing at Merck. Yes, it is somewhat interesting scientifically, but practically who wants to spend years developing the assay before starting a project if you don’t have to.

    1. Scott says:

      Correct me if I’m wrong (not a chemist), but isn’t the point of this to quickly sort through a large number of possibilities for something, before you start doing the heavy lifting of making enough for toxicity or whatever studies?

  9. BernardFlappleGast says:

    Surely this brute force approach shown in the paper will just permeate the problem of having compound libraries which are full of flat and achiral molecules? Obviously this is a really cool proof of concept and shows how hit-to-lead can be replaced by a machine churning out molecules. But, until the variety of reactions which the machine can actually do is increased I can’t see this having a direct impact in the near future.

Leave a Reply

Your email address will not be published. Required fields are marked *

Time limit is exhausted. Please reload CAPTCHA.