Evaluation of variability in high-resolution protein structures by global distance scoring

Abstract

Systematic analysis of the statistical and dynamical properties of proteins is critical to understanding cellular events. Extraction of biologically relevant information from a set of high-resolution structures is important because it can provide mechanistic details behind the functional properties of protein families, enabling rational comparison between families. Most of the current structural comparisons are pairwise-based, which hampers the global analysis of increasing contents in the Protein Data Bank. Additionally, pairing of protein structures introduces uncertainty with respect to reproducibility because it frequently accompanies other settings for superimposition. This study introduces intramolecular distance scoring for the global analysis of proteins, for each of which at least several high-resolution structures are available. As a pilot study, we have tested 300 human proteins and showed that the method is comprehensively used to overview advances in each protein and protein family at the atomic level. This method, together with the interpretation of the model calculations, provide new criteria for understanding specific structural variation in a protein, enabling global comparison of the variability in proteins from different species.