Characterizing conserved structural contacts by pair-wise relative contacts and relative packing groups.
To adequately deal with the inherent complexity of interactions between protein side-chains, we develop and describe here a novel method for characterizing protein packing within a fold family. Instead of approaching side-chain interactions absolutely from one residue to another, we instead consider the relative interactions of contacting residue pairs. The basic element, the pair-wise relative contact, is constructed from a sequence alignment and contact analysis of a set of structures and consists of a cluster of similarly oriented, interacting, side-chain pairs. To demonstrate this construct's usefulness in analyzing protein structure, we used the pair-wise relative contacts to analyze two sets of protein structures as defined by SCOP: the diverse globin-like superfamily (126 structures) and the more uniform heme binding globin family (a 94 structure subset of the globin-like superfamily). The superfamily structure set produced 1266 unique pair-wise relative contacts, whereas the family structure subset gave 1001 unique pair-wise relative contacts. For both sets, we show that these constructs can be used to accurately and automatically differentiate between fold classes. Furthermore, these pair-wise relative contacts correlate well with sequence identity and thus provide a direct relationship between changes in sequence and changes in structure. To capture the complexity of protein packing, these pair-wise relative contacts can be superimposed around a single residue to create a multi-body construct called a relative packing group. Construction of convex hulls around the individual packing groups provides a measure of the variation in packing around a residue and defines an approximate volume of space occupied by the groups interacting with a residue. We find that these relative packing groups are useful in understanding the structural quality of sequence or structure alignments. Moreover, they provide context to calculate a value for structural randomness, which is important in properly assessing the quality of a structural alignment. The results of this study provide the framework for future analysis for correlating sequence changes to specific structure changes.
Holmes
J Bradley
JB
Laboratory of Molecular Genetics NICHD-NIH, Bethesda, MD 20952, USA.
Tsai
Jerry
J
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D005914:Globins / Q000737:chemistry* / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010802:Phylogeny; D017510:Protein Folding; D017434:Protein Structure, Tertiary; D016415:Sequence Alignment
D005914:Globins