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.