COMPUTER ANALYSIS OF LOW-COMPLEXITY AMINO ACID SEQUENCES

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The goal of this project is to define, classify and analyze, using computational analysis, all segments of protein sequences of improbably low compositional complexity. These include residue clusters of predominantly one or a few amino acid types, which commonly contain homopolymeric tracts or mosaics of these, aperiodic patterns and sections of low-period repeats. The abundance of these segments in sequence databases has been determined and their properties are being related to evidence of biological functions and protein structure, dynamics and assembly. A. Different formal definitions of local compositional complexity were used to make unbiased identification of low-complexity segments, at different levels of stringency. Algorithms were refined to (a) select segments for further study and (b) filter out non-informative segments prior to database searches. New methods for automated classification and neighboring of low-complexity sequences have been developed. B. Abundance and biological properties: Approximately 25% of the residues in protein databases are in compositionally biased segments (including some known long non-globular regions) and approximately 55% of proteins contain one or more such segments. Interspersed low- complexity sequences are particularly abundant in many eukaryotic proteins crucial in morphogenesis and embryonic development, RNA processing, transcriptional regulation, signal transduction and aspects of cellular and extracellular structural integrity. C. Structures, dynamics and interactions: The limited structuralinformation available for low-complexity regions of proteins indicates that they are generally non-globular and polymorphic or mobile. The project has highlighted the high abundance and biological importance of low-complexity protein segments and emphasized the relative lack of knowledge of their molecular structure and dynamics. Low complexity segments evidently have non- compact structures and dynamics which are necessary for biological function. The new computer methods are valuable in eliminating many artefacts in sequence database searches and alignment analysis.