An idiot's guide to lead optimisation for proteins

Oh heck, this is awesome to see on the front page! I wrote the underlying Cradle-1 paper that is being discussed!

I used to work for Cradle and writing this paper was the last thing I did before leaving – on good terms – to found my own startup. :D And we'll 100% be using Cradle for our lead optimization.

(On the off-chance: I'm at PEGS Boston this week chatting all things AI+antibodies, in particular for rare diseases. If this topic is of interest to any other protein+tech geeks here then send me an email, let's grab coffee.)

After spending an entire career doing 'by hand' (and a helluva lot of molecular orbital calculations) on the problem this post is about, i've got to tersely weigh in with: there's (still) not enough available data given the size of protein 'phase space' to hope for a proper covering with one's trained up linear algebra model. Or typed another way: you've got to include at some stage some physical modeling parameters, like molecular orbitals [1], otherwise the 'response curve' will only optimize if one gets quite lucky, (which is actually unlucky as then you'll delude yourself into thinking it's a generally applicable, which it isn't). For instance, swap in a carboxylic acid moiety where there was previously an aldehyde, a protein side-chain flips over, and you're in a completely different corner of the energetic 'galaxy'.

[1] e.g. https://proteindf.github.io/