16 April 2014

What we do in life, echoes in eternity (or the life of the patent)

Next week is the Drug Discovery Chemistry conference where Dan and I will be co-teaching our award-winning FBDD short course (or at least our mom's think it is great). We look forward to seeing any/all of you next week.  Blogging may be light next week, but we promise to give an update of the going-ons at the conference soon after.  

Kinases are fun, and those of us who have worked in them have probably all worked on the same ones.  I always loved the MAP family.  Why would I have a favorite kinase family?  Because of the cascading MAP kinases, like the one in this paper, Mitogen-activated protein kinase kinase kinase kinase 4 (that's a lot of kinase!).  But, unlike a lot of other kinases, there is no good tool compound.  So, using SPR, they decided to generate one. This paper is not particular interesting in terms of what they did, but rather it raises interesting questions. While the approach they describe is not novel, it is nice to see the data supporting them. 

They screened their 2500 fragment library against immobilized protein at 100 uM (single point).  225 hits were found with Kd ranging from 10 to 2000 uM (LE =0.24 to 0.59) for a 9% hit rate.This paper is about progressing this oxazole fragment 1

Based upon its structure and the wealth of kinase structure knowledge extant, they surmised it would be ATP-competitive and a hinge binder.  Based upon a binding model, the attempted to prosecute this fragment by "close-in" analogs and looking for groups that would extend farther into the hydrophobic pocket, but with MW less than 350 Da and clogP less than 3.5.  Exploring bi-aryl space resulted in 8:  
This compound had an activity of 143 nM and it was at this point that they decided to switch to the biochemical assay as their primary assay.  In the end, using X-ray focusing on LLE, they ended up deliveringa low molecular weight compound with favorable in vivo PK.  It also demonstrated a pathway functional response. 

This raises an excellent point, something I get asked frequently.  When do you switch from a biophysical assay to a biochemical one?  This maybe arguing semantics, but I think as more and more companies enter this arena these are exactly the things we need to discuss.  I think the switch happens when you feel comfortable, there is no hard and fast rule.  There is a difference in the SPR Kd and biochemical IC50 by more than 10x.  It is very important to note that they relied heavily on LE (-RTlnKd/HA) and LLE (pKd-cLogP), or pIC50 for biochemical assays.  But, it also raises the issue of correlation between SPR Kd and IC50.  I raise these socratically, and as maybe as a topics for discussion next week (or in July and September).   


Dan Erlanson said...

I'd say you switch from a biophysical to a biochemical assay when 1) you can measure a response in the biochemical assay, and 2) you can assure yourself that the response you are seeing is real.

Biophysical assays are often more sensitive than biochemical assays, so it may take some initial optimization to get a signal in the latter (see for example here).

And of course, biochemical assays are particularly prone to false positives, particularly at high concentrations (see for example here and here) so it really depends on how robust your assay is.

Anonymous said...

This might be a stupid question, but would it be more appropriate to compare KD and IC50 after converting IC50 to Ki through the Cheng-Prussoff equation?

Unknown said...

Yes, even though Cheng-Prussoff is a simplification that itself is condition - dependent and subject to assumptions, the IC50 values should systematically deviate from Kd values in a manner related to the competitive substrate concentration (which Cheng-Prussoff attempts to correct for). There are other considerations, including the enzyme/protein concentration relative to the inhibitor concentration (for tight - binding inhibitors) that systematically affect IC50 values. Furthermore, Kd values are only as good as the applicability of the binding model used to fit the data, especially when using kinetic data where equilibrium was not fully established.