29 October 2013

Biophysics with White Wine (pt 2)

Tarte flambe or flammekuchen.  Doesn't matter what you call it, DELICIOUS!  Another fantastic find from the Novalix Biophysics in Drug Discovery Conference.  Yesterday I wrote up the Biophysical Characterization section, today's yummy-ness: Mechanistic Analysis. 

Ann Boriack-Sjodin -Epizyme:  She emphasized that X-ray is the key to Epizyme's work, but they also use STD, ITC, SPR, Fortebio, thermal shift, and enzymology.  This was a theme, especially for the non-fragment specific talks: we use any and all biophysical techniques.  This talk focused on the methyl-transferase DOT1L. They struck out with a diversity library and in silico screening.  They did find, with SBDD, a selective inhibitor.  They key to this compound was its VERY long residence time: 24 hours.  The concept of koff driven inhibitors was brought up in several other talks.

Glyn Williams -Astex: First off, let me say the best thing Glyn said during his talk was that the Ro3 was meant as a guideline.  His talk spoke about the variety of methods in use at Astex: MS, NMR, Thermal shift, ITC, and X-ray.  MS is used for protein validation and QC, thermal shift was used for affinity ranking, but they have moved away from it (his comment, "when it doesn't work, you don't know"), ITC is a good way to discriminate good compounds from bad, and NMR is used in competition mode.  In terms of their library, they have had 2600 fragments EVER and their current fragment library iteration has 1500 members.  Their core library has a avg MW of 176 (~13 HA) and clogP of 0.9 and the X-ray subset of 350 fragments 146 Da (~10 HA) clogP of 0.5.  40% of their fragments are NOT commercially available.  These are small fragments and he noted that on average each fragment has hit two targets.  Greater than 50% of their hits have never generated a X-ray structure, but have hit in the biophysics assays.  He presented how they do 3D-arity.  The draw a "best plane" through the molecule and then calculate the average deviation of each atom from that plane.  I found this approach unwieldy and I still think PMI is a better way to go.
They take several approaches to fragment screening: with their core fragment library they WATER-LOGSY and thermal shift which then goes into X-ray follow up ( with MS, ITC, and 2D-NMR).  If the X-ray works, they have a X-ray validated hit and it moves forward.  They also sometimes go straight into a X-ray screen (with a 350 fragment subset).  One of the advantages of the NMR-based screening is that NMR can detect hits < Kd, while X-ray can only detect hits > Kd. 
In terms of properties, he showed a fascinating graph (that I bet lots of people have) that shows that improvements in enthalpy occur during H2L and improvements in entropy during LO.  LogP occurs in H2L and stays the same in LO. 

Marku Hamalainen -HealthCare:  This was an interesting talk, especially when contrasted with Goran Dahl's.  He showed a very interesting graph (I am not showing slides without specific permission; I have asked for this one) that shows binding site occupancy as a function of on/off rates.  It is fascinating as it buckets your compounds in various regimes: "Ancient Medchem knowledge", "Without on you are off", "High affinity does not help if clearance is rapid", and "With slow off, you might still be on when the drug is gone". 

Goran Dahl - AZ: This talk was definitely in the "Yeah, of course" category.  Not to diminish his talk, which was excellent, but it makes sense in a only after someone points it out to you kind of way.  Kudos to him for saying it first (chronologically at least): koff does NOT correlate with PK.  Prolongation kicks in when koff< elimination rate.  Pure and simple, yet how many people had actually thought about it that.  Plasma t1/2/ residence time > 1, duration is driven by PK, < 1 and it is driven by binding kinetics. 

Geoff Holdgate -AZ: This was an excellent talk giving a high-level overview and then diving into some very interesting topics.  He spoke on combining thermodynamics and kinetics to drive chemistry.  Key Questions: "How do you improve medchem decisions with kinetic data?" One Kd can arise from many different kinetic profiles this would allow you to pick and chose one that could be beneficial, but how do you know what that would be?
 "Is biophysics simply useful for retrospection?"  There are no examples of the use of biophysical data to drive medchem prospectively. 
"Should you drive affinity/LO by Delta H only?"  From Glyn's talk, it seems like LO is driven by entropy, NOT enthalpy. 
His take home lesson, which I wholeheartedly agree with: the Drug Discovery paradigm of focusing on affinity needs to change. 

6 comments:

Dan Erlanson said...

Sounds like a great conference, though I disagree with the statement that "there are no examples of the use of biophysical data to drive medchem prospectively." After all, what's SBDD without the S?

Dr. Teddy Z said...

Dan,
poor choice of phrases, I think biophysics in that context means thermodynamic/kinetic data.

Pete said...

Something to remember when thinking about binding kinetics is that, for a given Kd, a slow off rate means a slow on rate. In a pharmacokinetic context, one needs to consider both and not focus exclusively on the former.

I would challenge the assertion that LO is driven by entropy. Optimisation of leads is multiparametric in nature and individual different projects will face different issues. Exploring ways of introducing polarity without compromising affinity is a common LO strategy. However, you can do this using logP to quantify polarity. LLE can be used in this context although I believe there are better ways (see http://dx.doi.org/10.1007/s10822-013-9655-5 ). Ionisation is something that really needs to be considered when modulating polarity in a design framework and the biophysical folk (and anybody pushing lipophilicity-based efficiency metrics) do need to show that they are at least thinking about this if they want medicinal chemists to take them seriously.

Dr. Teddy Z said...

Pete, He had a graph showing Enthalpy and entropy as a function of where the compound was in development. So, you can argue with the data not me. :-)

Glyn Williams said...

Hi Pete,

I agree with both of your comments. The talk by Markku Hamalainen was a bit of a wake-up call for me personally since there are a growing number of cases where rates differ from the expectations of diffusion-controlled potency by more than 5-orders of magnitude. There was an anecdotal story of a sleeping-pill trial that led the first volunteer to sleep for a week...
On the second point, I had not intended to imply in my talk that our LO is being driven by entropy gains. Simply that, on average, that seems to be a consequence of our methods. Of course it depends on the average thermodynamic propeties of your compounds at the start of LO and probably says more about our use of structure, LE and LLE up to that point. If you look at individual compounds, not the average, our clinical candidates are not the most entropically favourable members of their series.

Morten Grøftehauge said...

Too many abbreviations.
"LogP occurs in H2L and stays the same in LO."

I assume hit-to-lead and ligand/lead optimisation. LogP is the logarithm of the partition coefficient. The sentence does still not make sense to me.