Diversity and Similarity Scoring: Does One Size Ever Fit All?

We spend a lot of time talking about compound similarities in this business. All those schemes for virtual screening, to find new activities for old compounds, to predict side effects and general toxicity, and many others besides rely on some sort of measurement of how similar various compounds (and collections of compounds) are to each other.
But how do you determine similarities? Some might answer “By comparing Tanimoto coefficients, of course”, but that’s an example of a little knowledge being a dangerous thing. Tanimoto distance calculations are a meat grinder, which will grind whatever you shove into the hopper. How, then, are you characterizing the compounds themselves? That’s where things get tricky. There are all sorts of “fingerprint” descriptors for molecules, and different ones will give you different measures of similarity (or of chemical diversity, depending on which end of the tube you’re looking through).
And the problem is, all of them have a tendency to look funny. Many medicinal chemists have experienced this, looking over a list of compounds ranked by similarities. You come across one with a high score, but it doesn’t look that similar to you, because the algorithm liked what look to you like unimportant details. The next list has two compounds that are supposed to be quite different, but they’re a methyl ester versus a t-butyl ester, or something of the sort, and just how different is that when the rest of the molecule is the same? And these are just two-dimensional comparisons. If you want to talk similarity in conformational space, and our drug targets generally want to talk that way, then you’re in for an even bigger universe of choices and tradeoffs. (Here’s a good recent overview from J. Med. Chem.)
The Matsy algorithm is supposed to generate results that look a little less alien, but I haven’t used it myself. I’d be interested in hearing what people have found to be the most useful in their own hands for such measurements. Is this always a case-by-case thing, or are there methods that have enough of a Swiss-army-knife character to them to stick with? Any favorites out there?