NONGLOBULAR DOMAINS IN PROTEIN SEQUENCES - AUTOMATED SEGMENTATION USING COMPLEXITY-MEASURES

Computational methods based on mathematically-defined measures of comp ositional complexity have been developed to distinguish globular and n on-globular regions of protein sequences. Compact globular structures in protein molecules are shown to be determined by amino acid sequence s of high informational complexity. Sequences of known crystal structu re in the Brookhaven Protein Data Bank differ only slightly from rando mly shuffled sequences in the distribution of statistical properties s uch as local compositional complexity. In contrast, in the much larger body of deduced sequences in the SWISS-PROT database, approximately o ne quarter of the residues occur in segments of non-randomly low compl exity and approximately half of the entries contain at least one such segment. Sequences of proteins with known, physicochemically-defined n on-globular regions have been analyzed, including collagens, different classes of coiled-coil proteins, elastins, histones, non-histone prot eins, mucins, proteoglycan core proteins and proteins containing long single solvent-exposed alpha-helices. The SEG algorithm provides an ef fective general method for partitioning the globular and non-globular regions of these sequences fully automatically. This method is also fa cilitating the discovery of new classes of long, non-globular sequence segments, as illustrated by the example of the human CAN gene product involved in tumor induction.