The goal of this project is to define and analyze, using computational methods, segments of protein and nucleotide sequences showing compositional bias(low-complexity regions or domains) and to understand their structural, functional and evolutionary significance, and their pathology. In protein sequences, these regions comprise a large proportion of the genome encoded amino acids (approximately 25%in most eukaryotes, and most of the translated protein sequences contain at least one such region). They may contain homopolymeric tracts or mosaics of a few amino acids, or repeated patterns, frequently subtle, including those typical of many non-globular domains. New mathematical definitions and algorithms are continuing to be developed to make unbiased identification of low-complexity segments, and to discover and analyze properties of these regions relevant to their structures, interactions and biological functions. 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. Structural data indicate that low complexity segments of proteins are generally non-globular or conformationally mobile. However, knowledge of the molecular structures and dynamics of these domains is still very limited because they are generally relatively intractable to investigation by crystallography and NMR, and they account for less than 1% of the residues in current structural databases. Hence, mathematically rigorous sequence analysis provides a primary methodology for gaining insights into their biology, and for raising questions to be investigated expermentally. These methods are also valuable, for both nucleotide and amino acid sequences, in detecting and eliminating some artifacts in sequence database searches and alignment analysis. - Computer algorithms, protein sequences, protein complexes, domains, complexity, patterns, repeats, non-globular structure, conformational mobility

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Intramural Research (Z01)
Project #
1Z01LM000025-08
Application #
6290481
Study Section
Special Emphasis Panel (CBB)
Project Start
Project End
Budget Start
Budget End
Support Year
8
Fiscal Year
1999
Total Cost
Indirect Cost
Name
National Library of Medicine
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Altschul, Stephen F; Wootton, John C; Gertz, E Michael et al. (2005) Protein database searches using compositionally adjusted substitution matrices. FEBS J 272:5101-9
Wan, Honghui; Li, Lugang; Federhen, Scott et al. (2003) Discovering simple regions in biological sequences associated with scoring schemes. J Comput Biol 10:171-85
Yu, Yi-Kuo; Wootton, John C; Altschul, Stephen F (2003) The compositional adjustment of amino acid substitution matrices. Proc Natl Acad Sci U S A 100:15688-93
Sonnhammer, E L; Wootton, J C (2001) Integrated graphical analysis of protein sequence features predicted from sequence composition. Proteins 45:262-73
Wan, H; Wootton, J C (2000) A global compositional complexity measure for biological sequences: AT-rich and GC-rich genomes encode less complex proteins. Comput Chem 24:71-94