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Intro
Simple idea, which is to use a version of hierarchical clustering where instead of using a metric of distance computed once, instead use a maximum-common substructure algorithm to find the # of atoms in the common substructure.
In a sense, I'm trying to match a Medicinal Chemists intuition of what the scaffolds are for a set of heterogeneous hits you might get from a screen. I've found that doing this with fingerprint distances, etc doesn't really work in the way I'd like.
I think this similar to how MedChemica's MCPairs algorithm works, so I might end up just recommending that instead, but I think this will be a good exercise and potentially useful to a few different projects I'm working on.
To-Do
while
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