Mass Spec Screening in Solution

Mass spectrometry is a technique that most people are familiar with, as a QC tool.  It also has been demonstrated as a screening/validation tool.  Native mass spectrometry (nMS) has been discussed here, Weak Affinity Chromatography (WAC) here, and Hydrogen-deuterium exchange (HDX) here.  All of these methods have advantages and disadvantages.  A "new" method is the ligand-observed MS screening (LO-MS).  [I put new in quotes because I know of at least one company that has been using this method for screening for years via a CRO.]

The concept of LO-MS is straight forward (Figure 1) and very similar to WAC.  A mixture of fragments, in this case 384, are mixed with target (NS5B), incubated, and the ultrafiltrated (50kDa cutoff).  This step eliminates the need for the immobilization step in WAC, ensuring the native conformation.  The fragments were at 25 uM, while the target was at 50 uM. 

Figure 1.  Fragments MW 165 and 130 are binders.  MW162 and 150 are not. 

Retained fragments are then dissociated with 90% methanol and those showing intensity higher than the protein-minus control are considered binders (S/N  greater than 10).  In their library, 5% of the compounds were not amenable to mass spec detection, but they included them to increase the complexity of the mixture.  In the end, they ended up with 20 binders in 20 minutes!  They repeated the screen with smaller mixtures (50 and 84 fragments) where they found 12 binders (a subset of the original 20).  As a follow up, they ran the binders by SPR, validating 10 of the binders (50%).  5 out of these 10 gave useable crystals (observable electron density for the fragment) (50%).  They also show how the data can be used to generate Kds (like WAC).

This method raises some issues with me, but first let me say, it sure seems to work, and fast to boot.  From people I know who have used this to screen, they have been very happy.  Here is what bothers me: self-competition in the tube a discussed here and here, this is a non-equilibrium method (variable protein concentration during the ultrafiltration), and it is an indirect method.  For me, I prefer methods that directly detect ligand-target interactions, like NMR, SPR, and nMS.

Fragment Design Done Right

As many of you probably know, I am not a fan of virtual screening, computational design, in silico much of anything.  I think it tends to be poorly applied, or academic.  Now, don't mark me as a Luddite, I think that computational tools can be quite useful, when appropriately applied.  What is appropriate?  Read on and let Hoffmann-LaRoche-Nutley show you in this beautiful paper.  

This is one of a line of great papers coming out of the closing Nutley site, so that is the one upside.  In this paper, the authors present how they leveraged the expertise of their chemists to design fragments against HCV NS5B, a well known drug target.  The story starts (I hesitate to say "their efforts start...") with a screen of 2700 fragments by SPR.  They identified 163 hits of which 29 were selected (criteria unstated) for co-crystallization.  Only one fragment delivered, 1.   

Fragment 1 had a 78uM KD, 130 uM IC50, but it could not be optimized for affinity, physicochemical or ADME properties at all.  They one important discovery from the co-crystal of 1 was an unexpected, and they believe, first ever interaction of its type: the NH hydrogen interacting with Q446 (Figure 1). 

Figure 1. 

Using this and the published structures internally (2-3) and externally (4-6) the built a model. The following guidelines were proposed for the new fragments: 1. Satisfy carbonyl of Q446 and NH of Y448, optionally displacing or engaging the conserved water molecule, 2. Occupy large hydrophobic pocket, exploring its size, 3. Position aromatic chain to make edge to face interaction with Y448, 4. And at least one hydrophobic interaction with G410 and/or M414.

Figure 2.

In a triumph of democracy and teamwork, the chemist woud discuss his ideas with the compchemist and have them modeled.  The ideas were presented to the team and the best ideas selected for synthesis.  They also chose to avoid acidic functionality.  Since 1 was the only known binder in the region without acidic functionality, they focused on incorporating the unique Q446 interaction.  What they found was that compounds capable of 1,2 and 1,3 interactions were best.  Table 1. shows their SAR. 

Their first two compounds were dead, dead as a this parrot.  Compound 9 satisfied 3 of the 4 criteria they established, yet showed very poor activity and bad ligand efficiency. Using LE was crucial, the authors state, because it allows the to distinguish affinity through bulk, vs. affinity through efficiency.  Finally, adding substituents to the hydantoin to explore the hydrophobic pocket showed significant increases in activity, e.g. 9->12.  Fragment 12 was co-crystallized and confirmed the expected binding mode.  A 2-pyridone fragment (13) gave similar activity to 9.  So, starting with a Pfizer-inspired compound gave 14 which demonstrated an increase in potency, but NOT ligand efficiency.   They next tried 15 and voila! a 100x increase in affinity with four less heavy atoms, the ligand efficiency went way up!  Co-crystallization showed that 15 bound as expected.  Two more heavy atoms added to 15 led to 16 and showed increased potency and ligand efficiency while retaining the desireable phyiscochemical properties of 15.  Compound 16 was further optimized and entered clinical trials with all of the atoms presented in it. 

So, what makes this "Fragment Design Done Right" in my eyes?  In this case, they utilized fragment docking as an aid to chemist's designing ligands.  They used in silico tools, like modeling, to test the potentially validity of the chemist's hypotheses.  In the end, their computation was as good as their experimental follow up, in this case X-ray.  What differentiates humans from the brute beasts (except for all the exceptions out there where tool usage has been shown) is that we use tools.  Using tools correctly, is what differentiates the smart humans from the herd.