The ideal shape of compounds used
for biological screens is a subject of vigorous debate, with some arguing that shapely
molecules may be superior in various ways to the “flatter” aromatic compounds
that tend to dominate libraries. This view was expressed more than a decade ago
in the paper, “Escape from Flatland: Increasing Saturation as an Approach to
Improving Clinical Success.” However, those conclusions have been challenged.
Since many of us are trying to discover drugs, it is worth asking what actual
drugs look like. This is the subject of a new ACS Med. Chem. Lett. paper
by Seth Cohen and colleagues at University of California, San Diego.
Assessing shapeliness is itself
contentious. Here the researchers chose the intuitive metric, principal moment of
inertia (PMI), which uses a simple triangle plot to assess whether a molecule
is more rod-like, disk-like, or sphere-like. The degree of shapeliness (3D
Score) can be calculated by summing the x- and y-coordinates to give values
between 1 (rod- or disk-like) and 2 (sphere-like).
The researchers first extracted
more than 8500 drugs and nutraceuticals from DrugBank, all of which had associated
three-dimensional structures and MW >100. PMI calculations revealed that
nearly 80% were linear or planar, with 3D Scores < 1.2. Another 17.5% had 3D
Scores up to 1.4, while only 0.5% were greater than 1.6. Interestingly, this distribution
is similar to that of the ZINC database of small molecules. You might expect a
correlation between size and shapeliness, with larger molecules being more
three-dimensional, but this was not the case. Perhaps related, a separate analysis found no
correlation between shapeliness of fragments and resulting leads.
The 3D structures of compounds in
DrugBank are calculated for energy-minimized conformations, which are not
necessarily the biologically relevant conformations. So the researchers next went to the protein
data bank (PDB) and its crystal structures of 502 unique DrugBank molecules bound
to various proteins. Some molecules were represented multiple times (1036 structures
of sapropterin!), and for these the PMIs were averaged. The results of this
analysis were similar, with 83.5% of molecules having a 3D Score < 1.2 and
just three molecules with a 3D Score > 1.6. As with the DrugBank data, there
was no correlation between 3D Score and molecular weight.
Further analyses of compounds
with multiple crystallographic structures was interesting. For diclofenac, with
51 PDB entries, 3D Scores ranged from 1.03 to 1.52, with the minimized score
being 1.22. However, some of these structures are likely low affinity with questionable
biological relevance. In contrast, for five approved HIV drugs, the PMIs remained
very similar for molecules bound in the active sites.
Getting out of flatland is surprisingly
difficult: the researchers examined the PMIs for several fragments from
libraries designed to have shapely members and found that none had 3D Scores
> 1.4. They suggest clever ways of increasing three dimensionality, such as building
organometallic molecules. While this is likely to increase novelty and
patentability, it also introduces unknown biological risks. One analysis that
would be interesting is whether natural-product-derived drugs are significantly
shapelier than their purely synthetic counterparts.
The researchers conclude:
The true need for topological
diversity in feedstocks and final drug molecules remains unclear given the overwhelming
number of linear and planar drugs. The question remains as to whether more 3D
compounds represent attractive and untapped therapeutic space, or if more
linear/planar molecules are indeed the best topologies for bioactive molecules.
This is indeed an interesting
question, and I hope that chemists – particularly those in academia – continue to
make and test ever more exotic molecules. But since the first word of this blog
is “Practical,” I would not discount the more planar molecules that make up
most of our pharmacopoeia.