[A method to compare molecule shapes according to Ballester and Richards, http://www.journals.royalsoc.ac.uk/index/W1J4636Q65R74258.pdf]
This should be quite straightforward to implement within Open Babel - basically, only distances between certain atoms in a molecule have to be measured and the standard statistical moments calculated. I already have a python script based on the Open Babel toolkit to calculate USR and could give support (if needed at all).
ABSTRACT:
Molecular databases are routinely screened for compounds that most closely resemble a
molecule of known biological activity to provide novel drug leads. It is widely believed
that three-dimensional molecular shape is the most discriminating pattern for biological
activity as it is directly related to the steep repulsive part of the interaction potential
between the drug-like molecule and its macromolecular target. However, efficient
comparison of molecular shape is currently a challenge. Here, we show that a new
approach based on moments of distance distributions is able to recognize molecular
shape at least three orders of magnitude faster than current methodologies. Such an
ultrafast method permits the identification of similarly shaped compounds within the
largest molecular databases. In addition, the problematic requirement of aligning
molecules for comparison is circumvented, as the proposed distributions are independent
of molecular orientation. Our methodology could be also adapted to tackle similar hard
problems in other fields, such as designing content-based Internet search engines for
three-dimensional geometrical objects or performing fast similarity comparisons between
proteins. From a broader perspective, we anticipate that ultrafast pattern recognition
will soon become not only useful, but also essential to address the data explosion
currently experienced in most scientific disciplines.
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Ballester et al. have filed a patent (http://cisrg.shef.ac.uk/shef2007/talks/ballester.pdf) so come back to us in 10 years or so. :-/