Using Residual Dipolar Couplings from Two Alignment Media to Detect Structural Homology
This work addresses the challenge of structural homology detection for protein researchers, representing an incremental improvement over previous methods by enhancing database search capabilities.
The researchers tackled the problem of identifying protein structures from experimental data by extending Probability Density Profile Analysis to incorporate paired residual dipolar couplings from two alignment media, resulting in a method that successfully identified structures from a database of 600 protein fold family representatives with synthetic data containing +/-1 Hz error.
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.