  The method of Probability Density Profile Analysis has been introduced
previously as a tool to find the best match between a set of experimentally
generated Residual Dipolar Couplings and a set of known protein structures.
While it proved effective on small databases in identifying protein fold
families, and for picking the best result from computational protein folding
tool ROBETTA, for larger data sets, more data is required. Here, the method of
2-D Probability Density Profile Analysis is presented which incorporates paired
RDC data from 2 alignment media for N-H vectors. The method was tested using
synthetic RDC data generated with +/-1 Hz error. The results show that the
addition of information from a second alignment medium makes 2-D PDPA a much
more effective tool that is able to identify a structure from a database of 600
protein fold family representatives.
