A surface of minimum area metric for the structural comparison of proteins

A new method for comparing protein structures, based on a minimal surface metric, is developed. A virtual polypeptide backbone is created by joining consecutive C alpha atoms in a protein structure. The minimal surface between the virtual backbones of two proteins (the Area Functional) is determined numerically using an iterative triangulation strategy. The first protein is then rotated and translated in space until the smallest minimal surface is obtained. Such a technique yields the optimal structural superposition between two protein segments. It requires no initial sequence alignment, is relatively insensitive to insertions and deletions, and obviates the need to select a gap penalty. The optimal minimal area can then be converted to the Area-C alpha distance, measured in angstroms, to determine the structural similarity. This technique has been applied to a large class of proteins and is able to detect not only small-scale differences between closely related proteins but also large-scale topological similarities between evolutionary unrelated proteins that lack any obvious sequence homology. To measure the similarity between structurally dissimilar proteins, an additional measure (the Fit Comparison) is developed. This is a scale-invariant measure of a structural similarity that is useful for determining topological similarities between dissimilar proteins with unrelated sequences.