Not all aromatics stink the same

A couple years ago we highlighted research suggesting that the more aromatic rings in a molecule, the less “developable” it is likely to be. In the February issue of Drug Discovery Today, the same researchers have now published an update in which they dig into the data in more depth and find that not all aromatic rings are created equal.

As before, the researchers turned to the GlaxoSmithKline internal database of tens of thousands of compounds to correlate chemical features with a variety of measured properties that have an impact on drug development, including solubility, logD, human serum albumin binding, inhibition of several cytochrome P450 isozymes, and hERG inhibition. What they found is summarized in the figure:

In short, while an increase in the number of all-carbon aromatic rings (carboaromatics) had a serious negative effect on nearly all parameters, an increase in the number of heteroaromatic rings was much less problematic. All-carbon aliphatic rings were relatively benign (albeit also relatively rare), while heteroaliphatic rings actually improved most of the properties with the exception of hERG inhibition (and this was only a problem with charged molecules).

One point that was unaddressed in the previous paper was whether an increasing number of aromatic rings is problematic in and of itself, or if this is merely a proxy for larger molecules. In this paper, the authors probed this question directly by examining the properties of molecules with similar molecular weights and lipophilicities but different numbers of aromatic rings. Significantly, the deleterious effects of aromatics appear relatively independent of both size and lipophilicity.

The authors also analyzed ring counts in 1200 oral drugs and found that, while the number of carboaromatic and aliphatic rings has remained relatively constant over time, the number of heteroaromatic rings has roughly doubled from the 1960s to today.

These results provide more support for making sure that fragment libraries contain a good assortment of aliphatics - particularly heteroaliphatics. Aromatics are still very useful of course: as the researchers note, there are thousands of commercially available aromatics, many robust chemistries exist for modifying them, and aromatics provide rigid scaffolds. Thus, fragment libraries should still include a fair share of these moieties, but it is probably worth cutting the number of carboaromatics in favor of more heteroaromatics.

Updated: Fragment-based events in 2011

The first few fragment events of 2011 are almost upon us, but so far it's looking like the second half of the year is completely empty. If you know of anything let us know and we'll get the word out.

February 21-22: SMi’s 10th Annual Advances & Progress in Drug Design Conference will be held in London, and has a number of fragment-based talks. There is also a separate half-day post-conference workshop on the topic on February 23.

February 23-25: CHI’s Molecular Medicine Tri-Conference will again be held in my beautiful city of San Francisco, with a program on medicinal chemistry that includes a fragment section. Notes on last year’s meeting can be found here.

March 7-8: Fragments 2011, the Third RSC-BMCS Fragment-based Drug Discovery meeting, will be held in Stevenage, UK. This is a biennial event; the last was in Alderley Park in 2009 (you can read about it here and here).

April 12-13: CHI’s Sixth Annual Fragment-Based Drug Discovery will be held in San Diego. I will be helping teach one of two pre-conference short courses on the topic on April 11. You can read impressions of last year’s meeting here.

June 8-10: CHI's Eleventh Annual Structure-Based Drug Discovery will be held in Cambridge, MA, with a full session on FBDD on June 9.

Finally, if anyone attends one of these and wants to write a summary please let us know and we'll post it.

Looks can be deceiving: Getting misled by crystal structures – part 3

It’s been a while since we’ve touched on some of the hazards of interpreting crystal structures (see here, here, and here). In a recent issue of J. Comput. Aided Mol. Des., Alpeshkumar Malde and Alan Mark of the University of Queensland, Australia describe some mishaps taken from the literature, and how molecular modeling could have avoided them.

The authors start by noting that although protein structure determination using crystallography has been highly optimized, small molecule ligands are a different matter. Part of the problem is that small molecules may show more disorder than protein side chains, thus making it more challenging to fit the model into the observed electron density. Moreover, the parameters for refining protein structures do not always transfer to small molecules: electrostatic interactions are frequently ignored, as are alternative conformations.

As an example, the authors revisit the structure of noradrenochrome bound to an enzyme that synthesizes adrenaline. A racemic mixture of the ligand was used during crystallization, and when the crystal was solved at modest resolution it was possible to fit the ligand within the electron density in eight different orientations – four for each enantiomer. Despite this ambiguity, only a single structure was deposited in the protein data bank (pdb). Malde and Mark ran molecular dynamics (MD) simulations and free energy calculations and found that this structure is likely incorrect: it is higher energy than other structures and binds in a different orientation than the natural ligand, whose structure had previously been solved. In fact, the conformation suggested by MD is the opposite enantiomer from that deposited in the pdb and rotated 180 degrees.

In another example, the authors examine a high-resolution structure of a pyrazole-containing compound bound to the kinase CDK2. Pyrazoles can adopt two different tautomers in which the hydrogen is on either of two adjacent nitrogens, and in this particular case the original paper suggested that both tautomers were present in equal amounts, and both were deposited in the pdb. However, computations suggested that one tautomer is 7 kJ/mol higher energy than the other, and Malde and Mark suggest that in fact probably just a single tautomer is present in the structure.

Finally, the authors describe cases where a primary amide or primary sulfonamide group is in the wrong orientation. In most cases it is difficult to distinguish between a nitrogen and oxygen atom on the basis of electron density alone, and given that there are about 1000 ligands containing a -CONH2 group and about 200 containing a -SO2NH2 there are probably many mistakes.

The authors acknowledge that the examples they present are relatively simple, and one could argue that some of them would have been caught if they were critical structures in a lead optimization program. Nonetheless, the fact that they weren’t suggests that one must always be on guard, particularly in virtual screening where dozens or hundreds of structures are used in an automated fashion to develop or validate docking algorithms. Malde and Mark also note that, in the case of fragment screening with very small low-affinity ligands, one needs be especially cautious.

There is something extremely attractive about a crystal structure: it looks so real that it is easy to lose sight of the fact that it is just a model. Checking one’s assumptions with a bit of computation can prevent costly mistakes.

Paying the fee for ligand efficiency

Practical Fragments has highlighted a couple cases in which larger molecules have been deconstructed into fragments and then analyzed for binding (see for example here and here). In the most recent issue of J. Med. Chem., Peter Brandt, Matthis Geitmann, and U. Helena Danielson of Beactica have applied this strategy to inhibitors of HIV reverse transcriptase (HIV-1 RT). They also delve into the theory and energetics.

The researchers dissect three non-nucleoside reverse transcriptase inhibitors (NNRTIs) into a total of 21 commercially available “fragments”. Each of these was then tested for binding using SPR (see also this paper for a detailed account of how they perform these screens, and this one for discovery of new fragments against this target). If the binding energies of the fragments were evenly distributed across the entire parent NNTRIs, most of the fragments would be predicted to be sub-millimolar. In fact, most of them were much worse: only 9 showed any evidence at for binding, and only 3 were fragment-sized (the other six had molecular weights above 300 Da).

This sort of result – that fragments of larger molecules bind less effectively than predicted – has now been seen several times, and the researchers asked why. One issue is that when a molecule binds to a protein it loses translational and rotational entropy, and this imposes an energetic cost. This “fee” is, unfortunately, hard to estimate, and complicated by the fact that there may be further energetic costs if the protein itself is flexible (as in the case of HIV-1 RT). The authors provide a nice review of the literature, where values range from 2.5 to a whopping 16 kcal/mol (see here for more discussion on this). When they (admittedly arbitrarily) subtracted 7.0 kcal/mol, the agreement between expected and observed binding of their fragments improved.

However, as the researchers acknowledge, this model still assumes that the binding energy is equally distributed over the entire parent molecule – in other words, it ignores the existence of hot spots. The fact that hot spots exist probably accounts for the decrease in maximum observed ligand efficiency with an increase in the number of heavy atoms:

Once [the hot spot] is occupied, larger molecules need also to interact with other parts of the ligand binding pocket. Hence, a decrease in ligand efficiency will be observed for larger molecules.

True, and to complicate things even more, different proteins will have hot spots of different sizes and “temperature” – or perhaps none at all. This variation calls into question the utility of using notions such as fit quality or %LE, which attempt to normalize ligand efficiency for the size of the ligand. The problem is that different proteins are likely to have different maximal affinity ligands; kinases tend to have high-affinity binding sites where high ligand efficiency can be achieved, while for protein-protein interactions the ligand binding site is likely to be larger and the ligand efficiencies lower. Thus, one-size fits all metrics could prove too stringent – or not stringent enough.

Fragments in Nature

The most recent issue of Nature has a brief but trenchant summary of fragment-based screening (FBS) by Abbott’s Phil Hajduk, of SAR by NMR fame. This is the first half of a drug discovery forum comparing FBS with diversity-oriented synthesis, or DOS, covered by Warren Galloway and David Spring of the University of Cambridge.

Hajduk summarizes the advantages of FBS:

Fragment libraries are more diverse, synthetic resources are used more efficiently and the leads identified from FBS are more likely to yield drug candidates that have optimal physico-chemical properties.

He also points out that fragment-based approaches have led to a number of drugs in the clinic.

In the spirit of “vigorous debate,” Hajduk also takes aim at DOS. In comparison with fragment-based approaches, which start with small libraries of small fragments, DOS generally makes use of larger libraries of structurally diverse molecules which are usually drug-sized and are often inspired by natural products. However, Hajduk alleges that:

Most compounds in DOS libraries would be excluded from many corporate screening collections because of their poor physico-chemical properties.

I don’t know about “most”, but I will say that many DOS compounds look suspiciously like PAINS. Still, DOS does have at least one strength: FBS is generally limited to well-characterized systems with purified proteins, whereas DOS libraries can be used in complex phenotypic assays where the target may not be known. Whether these will ultimately yield new drugs remains to be seen.

What do you think?