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A New Metabolism Predictor

Drug metabolism is a perennial topic for us small-molecule people. Watching your lovingly optimized molecules go through the shredding-machine of the liver is an instructive experience, not least when you consider how hard it would be for you to do some of the chemistry that it does. (For reference and getting up to speed on the details, the comments section here has had reader recommendations for the Drug Metabolism and Pharmacokinetics Quick Guide).
Here’s a review of a new sites-of-metabolism predictor, FAME, a decision-tree type program that’s been trained on data from 20,000 known compounds. It handles both Phase I and Phase II metabolism (a “Pharma 101” entry on that topic is here, for those who’d like to know more), and it looks like it’s well worth considering if you’re in need for something like this.
Here’s my question for the med-chem and PK types: have you made use of predictive metabolism software? Did it save you time, or did you either go down the wrong alleys or not see anything you wouldn’t have predicted yourself? I’m interested in real-world experiences, since I haven’t had too many myself in this area.

10 comments on “A New Metabolism Predictor”

  1. Anonymous PK Scientist says:

    I’ve not used the metabolism prediction programs as much as some of my colleagues that focus specifically on MetID, but when I did use them they never seemed to provide anything useful. I remember evaluating a particular program a couple years back (I won’t name the guilty party)…we were feeding it compounds from our library for which metabolites had already been characterized and it either came up with predictions that were blatantly obvious or crazy ones that we never actually saw in vivo. After that, I quit paying attention to metabolite prediction software.

  2. Anonymous BMS Researcher says:

    Wonder if this will be much of an improvement on three chemists looking at an SAR matrix of structures and talking rapidly while waving their hands around…

  3. Rock says:

    I have never found them to be very useful. As you suggested, they usually predict the obvious primary and sometimes secondary metabolites. However, I do enjoy reading about the exhaustive met ID work on clinical candidates published frequently in DMD (especially when they include human clinical metabolite data). It is often amazing how some compounds can get chewed down to a stub, sometimes requiring 6 or 7 sequential steps. It usually requires radiolabeled drug to identify them all.

  4. anon says:

    If it is all so obvious why do people still make compounds with inappropriate PK?

  5. Anonymous says:

    @4: Because everything is obvious in hindsight.

  6. Tim says:

    @4, because some sites of metabolism are obvious and some are simply unpredictable.

  7. annon fore says:

    My former group had tried them and dismissed their value very quickly. I find them to be a one dimensional analysis & predictor while the real PK, metabolism, disposition, and elimination is based on a multidimensional world of biology, biochemistry, and physiology.

  8. FAcehiker says:

    The software Meteor,Metasite have been around for a while. They do a pretty good job of using a knowledge base to predict the possible metabolism sites. And there is no reason they won’t get better if Samantha and her OS friends start paying attention. The algorithms help the MetID scientist channel his structure proof and help the MedChem scientist model attempts to stabilize a molecule. But they cannot predict metabolic stability, enzyme kinetics is too elastic. Stop one CYP with a fluorine and you turn another one on.

  9. LiqC says:

    At some point I will have to put a compound with N-alkylaniline into a mouse. Could someone give a hint of what alkyl group to choose to avoid extensive metabolism?
    Would benzyl thioether also be a liability?
    I should say I’m not making a drug out of it, this is for tracer purposes. But it would be important for the aniline to persist for at least a few hours.

  10. tommy says:

    For house-wife predictions these programs are good enough at an early stage. But do not expect miracles to predict relative ratios of different metabolite a, b, c in species x or y. We are still dealing with rather unspecific enzymes.

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