Poll results: how small are your fragments?

The results of our most recent poll are in - here are the smallest fragments readers would allow in their library:

 

It looks like the smallest fragment most people would include in their library has a median of 7 or 8 non-hydrogen atoms, just slightly smaller than azaindole. More than 85% of respondents set a minimum size of 5 to 10 heavy atoms, so if we take the Pfizer rule of thumb that each heavy atom averages 13.3 Da, we’re talking 67 to 133 Da for the smallest fragments.

These sound like reasonable limits; slightly smaller molecules start becoming too volatile to handle reliably. Also, as Teddy pointed out, you’ll probably need either very sensitive methods to detect the smallest fragments, or very impressive ligand efficiencies.

Our poll last year asked about the largest fragments, so together these polls set a range of 5 to 20 heavy atoms for typical fragment libraries.

Thanks to the 75 of you who voted in this most recent poll.

Poll results: how big are your fragments?

The poll results are in, and it looks like most of the 46 respondents look askance at fragments that are larger than about 20 heavy atoms:

Since each non-hydrogen atom adds about 13 Da to a molecule, this means fragment sizes are limited to about 260 Da, well below the Rule of 3. And some folks are even more stringent – 30% of respondents set an upper limit of 16 non-hydrogen atoms, or about 210 Da.

By way of comparison, I looked at the size of fragments in a fairly large (albeit somewhat dated) review. Of the 42 fragments reported, 79% consist of 20 or fewer heavy atoms, so clearly this is a fruitful area.

Of course, as the graph above shows, larger fragments have been discovered and advanced, but perhaps it is generally better to avoid the more obese fragments.

Poll: how many atoms are too many?

The recent rant about average molecular weight (AMW) leads to the question of how large a molecule can be and still be called a fragment. The Rule of 3 sets an upper limit of 300 Da, but perhaps we should think instead in terms of number of heavy atoms. If we take Andrew Hopkin’s calculation that the mean heavy atom adds 13.286 Da to a molecule, this would set an upper limit of 22-23 heavy atoms, but is that already super-sized?

Now is your chance to weigh in – please vote (on the right of the page) on the largest fragments you would put into your library, and feel free to comment too.

Why NOT AMW

I have been thinking a lot lately about library design, especially after the roundtable at breakfast in SD. I found a rant from an old friend/colleague, from the very early days of FBDD for me (2002 or 2003).   With his permission, but no citation for obvious reasons, I am reprinting it here.  I find this particularly interesting as AMW is still being used as recently as last year in papers describing fragment library design. 

The Average Molecular Weight [Ed:AMW] is currently an accepted orthodoxy within the Medicinal Chemistry community, a role reinforced by the recent popularity of things like the Rule of Five. To be sure, molecules with large molecular weights are not typically observed to be successful drugs.

In all the rest of this note, I’d like to focus on the common scenario of selecting molecules for purchase or testing. I’ve often seen people apply AMW cutoffs or scalings to these processes. I’d like to show why this may be sub-optimal.

First, I contend that the number of heavy atoms may be a much better proxy for “size” than AMW. Certainly, if you want to discriminate against heavier elements like Phosphorus, Sulphur, Chlorine, Bromine and Iodine, then by all means, use AMW. But with an AMW contribution of 126, a molecule with a single Iodine atom would be considered heaver/less desirable than the same molecule with a C6H9N2O substituent! Again, if you have good reasons for wanting to suppress these elements, AMW is a (very) good way of doing that.

The case of the third row and beyond elements is fairly straightforward, but what happens within the organic group Carbon, Nitrogen and Oxygen. Does AMW vs natoms mean anything in there?

Imagine we are selecting molecules for an assay and imposed an AMW cutoff of 180 – admittedly very low. We would then ignore Aspirin, with an AMW of 180.66, and instead we would test the “lighter” .

But it gets worse. Imagine if the Lilly chemists looking for antidepressants had imposed an AMW cutoff of 308. That would have excluded Prozac, with an AMW of 309,

and instead they would have tested the “more desirable lighter molecule”with an AMW of just 306.

Again, an AMW cutoff or bias could see us miss Zyprexa, AMW 312.4 and instead use the “lighter” molecule AMW 308.

Or the even more lighter still Oxygen variant! Now, of course, no medicinal chemist faced with the choice between these molecules would choose the second one, that’s obvious. Logp estimates would probably eliminate molecules that are all or mostly carbon atoms.

But what the examples above show is that in any automated system that is basing decisions on AMW, there will be a systematic, albeit small, bias towards Carbon atoms and against Nitrogen and Oxygen atoms. Why? A single CH2 group contributes 14 to AMW, whereas an NH contributes 15, and a two connected Oxygen atom 16. As terminal groups, CH3 is 15, NH2 is 16 and OH is 17. A Pyridine Nitrogen contributes 14, but an aromatic Carbon contributes 13, t-butyl groups preferred over CF3. Carbon wins the low AMW contest every time.

Now, how significant is this. Probably very small in most practical applications. I’d say that if you are setting up some kind of automated process, and you have equivalent access to AMW and the number of heavy atoms, use the number of heavy atoms in order to eliminate any small, pro-Carbon bias.

Conclusion

We see that automated procedures using AMW instead of natoms, will not only systematically suppress elements like P, S, Cl, Br and Iodine, but may also work to drive out N and O atoms as well!