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I used to work in medicinal chemistry and agree 100%.

It's not to say ML has no value, but predicting molecular behavior, even in the simplest system is really dam hard.

Wheb you only under 10% of the factors influencing behavior, ML doesn't get you far.

That means they need 90% more data, right? Like, how other molecules behave in context, not stand alone. Some of them have similar properties.

That's true, but we don't even know what to look for to find that remaining 90% of data!

I remember working with some computational scientists:"just put a methyl group on this nitrogen and we should increase binding by 100x!".

So we make the molecule, give it to the biologists and find out binding is actually 1000x worse!

I'd put even odds on some sort of ML replacement for Lipinski's rule of five. But there are also whole classes of exceptions, like strategically methylated cyclic peptides.

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