In fragment-based lead discovery,
small is good – at least down to a certain point. While most fragments consist
of between 7 and 20 non-hydrogen atoms, some investigators have built libraries
of much smaller fragments with at most 7 or 8 heavy atoms. We’ve written
about MiniFrags and MicroFrags, which are typically screened
crystallographically at high concentrations to find hot spots. In a new
open-access J. Med. Chem. paper, Franz-Josef Meyer-Almes, György Keserű,
and collaborators at the Budapest University of Technology and Economics, the
University of Applied Sciences Darmstadt, and the University of Veterinary Medicine
Vienna have applied the concept to covalent fragments.
The researchers started with a
set of 84 fragments, all heterocycles functionalized with one of six warheads,
which we wrote about here. They systematically methylated nitrogen atoms on some
of these to generate 58 more fragments containing obligate positive charges,
such as compound B6+ below. The intrinsic reactivity of the fragments was assessed
by reacting them with the biologically relevant thiol glutathione (GSH).
Methylating the heterocycles made them more electrophilic
and thus more reactive. For example, only 16 of the 84 non-methylated fragments
had a half-life (t1/2) < 48 hours against GSH, in contrast with
30 of the 58 methylated fragments. In fact, 17 of the methylated fragments had t1/2
< 10 minutes.
Next, all 142 fragments were
screened at 250 µM for 2 hours at 30 ºC in a biochemical assay against histone
deacetylase 8 (HDAC8), an enzyme important for cell cycle progression. Hits
were confirmed in dose-response experiments after 1 hour pre-incubation.
Consistent with the glutathione data, only 12 of the non-methylated compounds
showed IC50 < 50 µM, while 54 of the 58 methylated compounds were
active. One of the fragments, B6+, had a kinact/KI value
of 4006 M-1s-1, not far from that found in approved
covalent drugs.
HDAC8 contains ten cysteine
residues, and sites of modification were determined using both site-directed
mutagenesis as well as tryptic digestion followed by mass spectrometry. In
total, seven residues could be labeled by one or more fragments. The most
reactive cysteine, C153, is close to the binding site of a previously reported
inhibitor (compound 1), and the researchers tried merging reactive fragments
such as B6+ onto this molecule. The best molecule, compound 3, had a kinact/KI
value of 1566 M-1s-1. However, the drop from B6+ alone
suggests that the non-covalent affinity component of compound 1 may have been
lost.
This is an interesting approach,
and as the researchers note, activity assays available for covalent fragments
are higher-throughput than the crystallographic screens required for MiniFrags
and MicroFrags. On the other hand, there are limitations. For one thing, the obligate
positive charge on the methylated fragments could overwhelm other properties,
and could even lead to denaturation of proteins at high concentrations,
rendering screens uninformative. These fragments are also less likely to be cell
permeable.
Finally, as we wrote ten years
ago, characterizing irreversible covalent fragments presents a challenge in deconvoluting
intrinsic reactivity from specific binding. Computational mapping of hot spots
on HDAC8 using FTMap revealed that some correlate
with modified cysteine residues. But other modified cysteine residues are in
surface-exposed flexible loops with no nearby pockets, and hits against these
are likely not advanceable. The fact that some of the fragments modify as many
as five cysteine residues on HDAC8 suggests they may be too reactive.
Still, the systematic characterization
of this library is useful experimentally and for training models. It will be interesting
to see it deployed against additional protein targets.
Hi Dan and happy New Year. It is also possible to define ‘bang for buck’ (extent to which activity beats a trend) for irreversible inhibitors. The use of residuals to normalize of affinity with respect to molecular size that I suggested in NoLE can also be used for other measures of activity (e.g., k.inact/K.i and other risk factors (e.g., logP).
ReplyDeleteThanks Pete and happy New Year to you too. What would the use of residuals look like for kinact/KI in this case?
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