MOTIVATION: The underlying assumption of many sequence-based comparative studies in proteomics is that different aspects of protein structure and therefore functionality may be linked to particular sequence motifs. This holds true if sequence similarity is sufficiently high, but in general the relationship between protein sequence and structure appears complex and is not well understood. RESULTS: Statistical analysis of multiple and pairwise structural alignments of protein structures within SCOP folds is performed. The results indicate that multiple conservation of residue identity is not common and that relationship between sequence and structure may be explained by a model based on the assumption that protein structure is tolerant to residue substitutions preserving hydropathic profile of the sequence. This model also explains the origin and specific value of the sequence similarity threshold, noticed in many previous studies, below which structural resemblance is not statistically expected.

Abstract Graph theory offers a convenient and highly attractive approach to various tasks of pattern recognition. Provided there is a graph representation of the object in question (e.g. a chemical structure or protein fold), the recognition procedure is reduced to the problem of common subgraph isomorphism (CSI). Complexity of this problem shows combinatorial dependence on the size of input graphs, which in many practical cases makes the approach computationally intractable. Among the optimal algorithms for CSI, the leading place in practice belongs to algorithms based on maximal clique detection in the association graph. Backtracking algorithms for CSI, first developed two decades ago, are rarely used. We propose an improved backtracking algorithm for CSI, which differs from its predecessors by better search strategy and is therefore more efficient. We found that the new algorithm outperforms the traditional maximal clique approach by orders of magnitude in computational time. Copyright © 2004 John Wiley & Sons, Ltd.