A few days ago, there was this post by Derek Lowe, reviewing a recent paper on magic methyls and their occurrence and impact in medicinal chemistry practice. They're called 'magic' because, although methyls are relatively insignificant in terms of size, polarity or lipophilicity, the addition of one in a compound can sometimes have a dramatic impact in its potency - much more that it would be attributed to any simple desolvation effects.
More generally, the 'magic methyl' phenomenon pops up in discussions about the validity of the molecular similarity principle, descriptors, QSAR - almost everything in the applied Chemoinformatics field - and belongs to the general class of 'activity cliffs'.
Methylation is a chemical transformation, and transformations along with their impact on a property of choice can be easily mined and studied using the so-called Matched Molecular Pairs analysis (MMPA). We already have a comprehensive database of all the matched pairs and transformations in ChEMBL, so it was relatively straightforward to extract all the methylations (H>>CH3) recorded in ChEMBL_17 and analyse their impact in binding affinity. (b.t.w., MMPs are coming to the ChEMBL interface soon, so look out for this feature if you are interested in this area).
So, in more detail, I extracted all the H>>CH3 pairs and joined them with their pActivities (Ki, IC50, EC50) against human proteins as reported in the literature (our data validity flags were quite useful in this case). The trick here is to only consider molecule pairs tested against the same assay, so that their respective activities are directly comparable and one can safely subtract one from the other.
I ended up with 37,771 data points - much more than another recent publication that looked at this. Here's how the histogram of Delta pActivity (log units) looks like:
As you can see, the scale tilts slightly to the left of zero, meaning that methylation has overall neutral to negative effect on binding affinity. This is not the first time people see this. There are indeed, however, several examples (~2.3K out of 37.8K, to be exact) of magic methyls with more than 10-fold increase in activity. More about this later.
Some of you will ask: 'OK, but what about the context? - methylation of a carbon, nitrogen or oxygen is not the same'. You're right, it's not. So I trellised the above plot by a perception of context - i.e. whether the methylation happens next to an aromatic/aliphatic C or N or next to an oxygen:
The same trend, more or less, is observed with the exception of the aromatic carbon context, whereby methylation seems to have more favourable effect that expected by the overall distribution. Perhaps that could be explained by introducing torsional and planarity changes, etc. For a more thorough explanation of this, see here.
Here are some examples of 'magic methyls' in the literature:
The take home message is: Magic methyls, unlike magic carpets, do exist but there are also equally as many, or even more, 'nasty' methyls. However, both of them are just a rather small minority compared to the 'boring' methyls - i.e. methyls with minimal or zero impact on potency.
It's just human nature to remember the few exceptions and outliers and forget the vast evidence to the contrary. However, isolating and understanding such edge cases and black swans is what could make the difference in drug discovery.