FastROCS is an extremely fast shape comparison application, based on the idea that molecules have similar shape if their volumes overlay well and any volume mismatch is a measure of dissimilarity. It uses a smooth Gaussian function to represent the molecular volume [Grant-1996], so it is possible to routinely minimize to the best global match. FastROCS will perform millions of these global shape matches every second.
Now, in just seconds, FastROCS can perform a virtual screen over an entire multi-conformer representation of a corporate collection to find active compounds with similar shape to a lead compound (a task that could previously take up to a day [Rush-2005]). Recent work suggests that the underlying ligand-based shape similarity approach is competitive with, and often superior to, structure-based approaches in virtual screening [Hawkins-2007] [Venhorst-2008], both in terms of overall performance and consistency [Sheridan-2008]. Alignments to crystallographic conformations have also been useful in pose prediction in the absence of a protein structure [Sutherland-2007].
In addition to virtual screening and lead hopping, FastROCS can be used to performing NxN shape comparisons over an entire multiconformer database. A prototype of clustering with FastROCS can be found in the karma.py example program.