Principal coordinate analysis on a protein model

Abstract

A well-studied 46-bead protein model is the vehicle for examining principal coordinate analysis as a tool for interpreting topographies of complex potential surfaces. This study compares the effectiveness of several definitions of the comparison variable for revealing information about topographies. The extent of the information is ascertained by comparing the results of the various forms of principal coordinate analysis with results obtained from construction of interconnected monotonic sequences of linked stationary points (IMSLiSP) on the same surface. The conclusion is that the most powerful formulation of principal coordinate analyses for understanding protein folding and, in general, topographies of complex potentials, uses the changes in the set of interparticle distances as the definition of the comparison vector. However, even with this choice, the more efficient principal coordinate analysis is not able to reveal the extent of information contained in a more cumbersome IMSLiSP analysis.