Structural building blocks

The paper proposes a modified version of the mountain clustering method (MCM) to find a library of structural building blocks for the construction of three-dimensional (3-D) structures of proteins. The algorithm decides on building blocks based on a measure of local density of structural patterns. The algorithm was tested on a well-known data set and found it to successfully reconstruct a set of 71 test proteins (up to first 60 residues as done by others) with lower global-fit root mean square (RMS) errors compared to an existing method that inspired our algorithm. The constructed library of building blocks is also evaluated using some other benchmark data set for comparison. The algorithm achieved good local-fit RMS errors, indicating that these building blocks can model the nearby fragments quite accurately. In this context, two alternative ways are proposed to compare the quality of such quantization and reconstruction results, which can be used in other applications too.