This was a busy year for
meetings, starting in January with a FragNet event in Barcelona, then moving to
San Diego in April for the annual CHI FBDD meeting. Boston saw an embarrassment
of riches, from the first US-based NovAliX meeting, to a symposium on FBDD at
the Fall ACS meeting, followed closely by a number of relevant talks at CHI’s
Discovery on Target. Finally, the tenth anniversary of the renowned FBLD meeting
returned to San Diego. Look for a schedule of 2019 events later this month.
If meetings were abundant, the
same can be said for reviews.
Lead optimization
Writing in J. Med. Chem., Dean Brown and Jonas Boström (AstraZeneca) asked “where
do recent small molecule clinical development candidates come from?” For three
quarters of the 66 molecules published in J.
Med. Chem. in 2016 and 2017 the answer is from known compounds or HTS,
though fragments accounted for four examples. Although average molecular weight
increased during lead optimization, lipophilicity did not, suggesting the
importance of this parameter.
The importance of keeping
lipophilicity in check is also emphasized by Robert Young (GlaxoSmithKline) and
Paul Leeson (Paul Leeson Consulting) in a massive J. Med. Chem. treatise on lead optimization. Buttressed with dozens
of examples, including several from FBLD, they show that the final molecule is
usually among the most efficient (in terms of LE and LLE) in a given series,
even when metrics were not explicitly used by the project team. Perhaps with
pedants like Dr. Saysno in mind, they also emphasize the complexity of drug
discovery, and note that “seeking optimum efficiencies and physicochemical
properties are guiding principles and not rules.”
Lipophilic ligand efficiency
(LLE) is also the focus of a paper in Bioorg.
Med. Chem. by James Scott (AstraZeneca) and Michael Waring (Newcastle
University). This is based largely on personal experiences and provides lots of
helpful tips. Importantly, the researchers note that calculated lipophilicity
values can differ dramatically from measured values, and go so far as to say
that “this variation is sufficient to render LLEs derived from calculated
values meaningless.”
Turning wholly to fragments,
Chris Johnson and collaborators (including yours truly) from Astex, Carmot, Vrije
Universiteit Amsterdam, and Novartis have published an analysis in J. Med. Chem. of fragment-to-lead
success stories from last year. This review, the third in a series, also
summarizes all 85 examples published between 2015 and 2017, confirming and
expanding some of the trends we mentioned last year.
Targets
Two reviews focus on specific
target classes. Bas Lamoree and Rod Hubbard (University of York) cover antibiotics in SLAS Discovery. After
a nice, concise review of fragment-finding methods, the researchers discuss a
number of case studies, many of which will be familiar to regular readers of
this blog, including an early example of whole-cell screening.
David Bailey and collaborators
from IOTA and University of Cambridge discuss cyclic nucleotide
phosphodiesterases (PDEs) in J. Med. Chem.
The researchers provide a good overview of the field, including mining the open
database ChEMBL for fragment-sized inhibitors. As they point out, the first
inhibitors discovered for these cell-signaling enzymes were fragment-sized, so
it is no surprise that FBLD has been fruitful – see here for an example from
earlier this year. Interestingly though, although at least six fragment-sized
PDE inhibitor drugs have been approved, none of these were actually discovered using
FBLD.
PDEs are an example of
“ligandable” targets, for which small molecule modulators are readily
discovered. In Drug Discovery Today,
Sinisa Vukovic and David Huggins (University of Cambridge) discuss
ligandability “in terms of the balance between effort and reward.” They use a
published database of protein-ligand affinities to develop a metric, LIGexp,
for experimental ligandability, and also describe their computational metric,
Solvaware, which is based on identifying clusters of water molecules binding
weakly to a protein. Comparisons with experimental data and with other
predictive metrics, such as FTMap, reveal that while the computational methods
are useful, there is still room for improvement.
We have previously written about
how target-guided synthesis methods such as dynamic combinatorial chemistry
have – despite decades of research – yielded few truly novel, drug-like ligands.
Is this because the targets chosen were simply not ligandable? In J. Med. Chem., Anna Hirsch and
collaborators at the University of Groningen, the Helmholtz Institute for
Pharmaceutical Research, and Saarland University review some (though by no means
all) published examples and examine their computationally determined
ligandability scores. There seems to be no difference between these targets and
a set of traditional drug targets.
Finding fragments
Crystallography continues to be a
key tool for FBLD: as we noted in the review of the 2017 literature, 21 of the
30 examples made use of a crystal structure of either the starting fragment or
an analog, and only 3 projects didn’t use crystallography at all. That said,
FBLD is possible without crystallography, as illustrated through multiple
examples in a Cell Chem. Biol. review
by Wolfgang Jahnke (Novartis), Ben Davis (Vernalis), and me (Carmot).
In the absence of a crystal
structure, NMR is best suited for providing structural information, and this is
the subject of a review in Molecules
by Barak Akabayov and colleagues at Ben-Gurion University of the Negev. The
researchers provide a nice summary of NMR screening methods and success stories
within a broader history of FBLD. They also include an extensive list of
fragment library providers as well as a discussion of virtual screening.
Speaking of virtual screening,
three reviews cover this topic. In Methods
Mol. Biol., Durai Sundar and colleagues at Indian Institute of Technology
Delhi touch on a number of computational approaches for de novo ligand design,
though the lack of structures sometimes makes it challenging to read. A
broader, more visually appealing review is published in AAPS Journal by Yuemin Bian and Xiang-Qun Xie at University of
Pittsburgh. In addition to an overview and case studies, the researchers also
provide a nice table summarizing 15 different computational programs. One of
these, SEED, is a main focus of a review in Eur.
J. Med. Chem. by Jean-Rémy Marchand and Amedeo Caflisch (University of Zürich).
The researchers describe how this docking program can be combined with X-ray
crystallography (SEED2XR) to rapidly identify fragments; we highlighted an
example with a bromodomain. Their ALTA protocol uses SEED to generate larger,
more potent molecules, as we described for the kinase EphB4. The researchers
note that together these protocols have led to about 200 protein-ligand crystal
structures deposited in the PDB over the past five years.
Rounding out methods, Sten Ohlson
and Minh-Dao Duong-Thi (Nanyang Technological University) provide a detailed how-to
guide in Methods for performing weak
affinity chromatography, and how this can be combined with mass spectrometry
(WAC-MS), as we noted last year.
Chemistry
One drawback of some
computational approaches for fragment optimization is that they do not consider
synthetic accessibility. In Mol. Inform.,
Philippe Roche, Xavier Morelli, and collaborators at Aix-Marseille University
and Institut Paoli-Calmettes focus on hit to lead approaches that do, and provide a handy
table summarizing nearly a dozen computational methods. We highlighted one from the authors,
DOTS, earlier this year.
DOTS is an example of using DOS, or
diversity-oriented synthesis. In Front.
Chem., David Spring and colleagues at University of Cambridge review recent
applications of DOS for generating new fragments, some of which we recently
highlighted. Only a couple examples of successfully screening these new fragments
are described, but the authors note that this is likely to increase as virtual library
screening continues to advance.
Perhaps the most productive
fragment of all time is 7-azaindole, the origin of three fragment-derived
clinical compounds. (The moiety appears in both approved FBLD-derived drugs,
vemurafenib and venetoclax.) Takayuki Irie and Masaaki Sawa of Carna
Biosciences devote their attention to this little bicycle in Chem. Pharm. Bull. The researchers count
six clinical kinase inhibitors that contain 7-azaindole (not all from FBLD) as
well as more than 100,000 disclosed compounds containing the fragment. More than
90 kinases have been targeted by molecules containing 7-azaindole, and the
paper provides a list of 70 PDB structures of 37 different kinases bound to
molecules containing the moiety.
Finally, in J. Med. Chem., Brian Raymer and Samit Bhattacharya (Pfizer) survey
the universe of “lead-like” drugs. Among the most highly prescribed small
molecule drugs, 36% have molecular weights below 300 Da. Only 28 of 174 drugs
approved between 2011 and 2017 fall into this category, consistent with the
increasing size of newer drugs. The researchers discuss 16 recently approved
drugs, and find that 13 have very high ligand efficiencies (at least 0.4 kcal mol-1
per heavy atom). As noted above, optimization often entails adding molecular weight
by growing or linking, and the researchers suggest that alternative strategies
such as conformational restriction and truncation also be investigated.
And with that, Practical Fragments wishes you a happy
new year. Thanks for reading some of our 686 posts over the past decade plus,
and please keep the comments coming!