Time for another quick quiz on whether you have what it takes to be a big-time medicinal chemist. Prepare for some not-so-welcome old friends to visit you yet again:
1. Your two main assays refuse to act as if they’re part of the same project. Most of your potent compounds in the first enzyme assay don’t do much against the cells, and the best cellular compounds are no great shakes in the enzyme assay. There’s a narrow zone of overlap, but it doesn’t look big or robust enough to base the whole project on. Do you pursue the cellular activity, on the theory that that’s the effect you’re looking for, or pursue the enzyme activity (on the grounds that it’s the right target, and you just have to get the things into the cells), or consider revamping the assays completely, or what?
2. In the next case, your disconnect doesn’t occur until you get to metabolism and PK. When you run your compound across liver enzymes, they grind it into dust. But you did that after you dosed the animals, you buckaroo, and not only did the compound seem to work OK, but its blood levels weren’t bad, either. So how come it looks as if it should be disappearing? The most destructive of the enzymes, by the way, was the human one. Are you worried about that, or not?
3. The project you’re on has a compound profile as a goal – so much potency, at least so much selectivity, and the like. As time goes on, there’s one selectivity assay in particular that you just can’t seem to shake. The only time you see a decent separation between your activity and the one you don’t want is in a compound series that you don’t like – they’re big and greasy, and although they look very active in the enzyme assay, they never perform as well as they should in the animals. But it’s starting to seem as if you have a choice: good properties or selectivity, but not both at the same time. What to do?
4. OK, let’s back up some. You’re working on a project that hasn’t really made it to the medicinal chemistry stage. The screening folks have run the target, and forwarded you their data. Nothing shows up really potent, but there are some 500-nanomolar things scattered around. And “scattered” is the word, all right. You probably have two dozen near-singletons in that range – nothing seems to show much of a robust effect across a given class of compounds. But this is a target that everyone wants to start a program on - it's hot, it's happening. How do you proceed?
1. Kinasepro on April 9, 2008 8:07 AM writes...
Before I answer, I'd like to know how many Wuxi FTE's I'll have to solve these problems?
Permalink to Comment2. milkshake on April 9, 2008 8:52 AM writes...
1. I tend to discount the biochemical data if the compounds work in cell and the assay is sound. The protein used in biochemical assay is often only a torso of the actual stuff (without the membrane bound domain, etc), sometimes even with changes in the aminoacid sequence (to make the protein more stable or permanently activated), and you also don't see the protein-protein interactions that can affect the shape pof active site indirectly and the assay reporting system is highly artificial construct also.
But typically things that work in cell tend to work in biochemical assay but not the other way around, often for reasons that the compound does not get into the cell or will get pumped out. So if you have highly cell-potent compound that does not work in biochemical assay it shows that you got either some artifact (detaching the cells = apparent inhibition) or you may be hitting something else along the same signaling pathway. So I would go with the cell potency but push biologists to do some more work on explaining the discrepancy.
2.Microsome stability only partly correlates with the clearance. Poor microsomal stability means a liability (weak spots in the molecule) but you dont really know how serious the liability is. For example Sutent has mediocre microsomal stability and yet exceedingly long activity in human, including a serious accumulation problem. (High volume of distribution and a long-lived equipotent metabolite is part of the accumulation problem). And I have also seen very similar Sutent analogues with greatly improved microsomal stability that get almost no exposure because their clearance was amazingly rapid.
Microsomal stability should not be used to pre-screen molecules for PK - if you have series that have average halflife 20-40 min and suddenly you see one compound that has 2 min halflife, maybe that one compound has a new problem - but microsomes are no substitute for PK, the same way Caco-2 and solubility data are not reliable as predictors of oral absorbtion. And you cannot even begin to compare compounds between different series.
Human microsomes are of concern though so I would do a panel of 3 animals (mice, rat, dog) to see if PK data shift the same way as the microsomes.
4. Selectivity is good if you can get it but good drug-like properties and cell potency is far more important. You should develop molecule that works in animals in not for other reasons as a proof of principle and maybe you can come back later with a more selective series if there is time.
As for the high-profile project that has 0.5mM hit, it is not too bad. We had one at 1.5mM recently and got it down to 3nM within a year. The important thing is that the nolecule is not too ugly from drug-like standpoint and not too comlicated to work on. The way to differentiate between several ho-hum hits is to re-synthesize them all, make few analogs of each to see if SAR makes sense and if the compounds have a good selectivity/cel potency, then you can decide which two series out of the starting seven hits your group should work on
Permalink to Comment3. CMC guy on April 9, 2008 10:45 AM writes...
As always weight has to be given to resources and context of target desease (chronic vs acute, route of admin) but vote thus:
Permalink to Comment1) Cellular results > enzyme assay
2) Animal > liver panel (but would remain worried)
3) Depends on stage but initial focus on selectivity then trust can add on to modulate properties without big loss of selectivety- later animal data should be driver
4) review data to see if initial screen included limited or multiple examples in each class that hit- if multiples run and not consistent hits probably avoid- if limited pick out the 2-3 that can make analogs quickly (chemical driver). Agree that 500 nM not bad starting place. If got good modelers perhaps they can develop connection to the scatter...
4. HelicalZz on April 9, 2008 12:41 PM writes...
1. In to animals we go - with 3 from column A and 3 from column B. But wait, first try other cell types and tissue isolates if your model permits.
2. Order the human liver microsome assays.
3. Go for properties. Start really understanding the off target effects to see how concerned you'll need to be. DO this even if you are conviced of good selectivity, because it isn't as good as you think anyway.
4. Easiest one yet. Do some literature background research, establish an indication where the targets to these 500 nM binders are relevant, scratch out an SAR program to improve the binding. Put it all into a 15 slide presentation and start calling the venture guys. : )
Zz
Permalink to Comment5. Petros on April 10, 2008 1:29 AM writes...
Part 1 sounds like an old Wonder drug Factory project.
Permalink to CommentScreening against one enzyme was swittched to focusing on whole cell activity and was eventually found to result in optimization of activity against a different enzyme target. This led to a number of development compounds
6. Kay on April 10, 2008 7:54 AM writes...
Um, I don't see any recognition above that humans and animals have different enzymes, so the fit, function, and outcomes cannot predict.
Since the Wuxi folks tend to eat animal parts that we don't - and hence might better recognize the inter-species differences - perhaps they will be more capital efficient.
Permalink to Comment7. Curious Wavefunction on April 10, 2008 11:26 AM writes...
Kinasepro, get back to blogging now!
Permalink to Comment8. rosko on April 10, 2008 7:15 PM writes...
"As for the high-profile project that has 0.5mM hit, it is not too bad."
Unless Derek made a typo, the hits were around 500 nM, not 500 uM. That's very decent potency, given that I've seen my share of SAR studies in which the MOST potent compound was single- or even double-digit uM (NOT nM!). Occasionally, I have even seen such inhibitors referred to by that most subjective adjective in drug design, "potent".
Permalink to Comment9. milkshake on April 10, 2008 8:10 PM writes...
yeah, I made a typo, should have been uM
As for our current project: we got about 7-8 different hit families from HTS which got whittled down to one, over time - except that later one family split into two subclasses as the SAR work progressed. Another two leads came from an inspired combination of re-synthesized lit compounds and an unrelated project compounds that had off-target activity we liked. Still, 3-4 leads divided amongst 8 medicinal chemists is plenty to work on.
Permalink to Comment10. Don on July 4, 2009 9:39 AM writes...
I am new to this group, and am not a chemist, so please forgive me if my etiquette is a little off. I am a molecular biologist at Hopkins who has become very interested in protein kinase inhibitors such as Sutent (sunitinib, SU11248) and their derivatives. I would love to discuss issues related to these molecules with a chemist who knows about their chemistry. If you are interested, it might be best to do it offline. Please contact me at dzack@jhmi.edu thanks
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