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Sequence Determinants (sequence + determinant)
Selected AbstractsListeriolysin O: a key protein of Listeria monocytogenes with multiple functionsFEMS MICROBIOLOGY REVIEWS, Issue 4 2006Samer Kayal Abstract Cholesterol-dependent cytolysins (CDCs) are produced by a large number of pathogenic Gram-positive bacteria. Most of these single-chain proteins are secreted in the extracellular medium. Among the species producing CDCs, only two species belonging to the genus Listeria (Listeria monocytogenes and Listeria ivanovii) are able to multiply intracellularly and release their toxins in the phagosomal compartment of the infected host cell. This review provides an updated overview on the importance of listeriolysin O (LLO) in the pathogenicity of L. monocytogenes, focusing mainly on two aspects: (1) the structure,function relationship of LLO and (2) its role in intra- and extracellular signalling. We first examine the specific sequence determinants, or protein domains, that make this cytolysin so well adapted to the intracellular lifestyle of L. monocytogenes. The roles that LLO has in cellular signalling events in the context of relations to pathogenesis are also discussed. [source] Time-averaged predictions of folded and misfolded peptides using a reduced physicochemical modelJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 7 2008Oliver J. Clarke Abstract Energy-based methods for calculating time-averaged peptide structures are important for rational peptide design, for defining local structure propensities in large protein chains, and for exploring the sequence determinants of amyloid formation. High-end methods are currently too slow to be practicable, and will remain so for the foreseeable future. The challenge is to create a method that runs quickly on limited computer resources and emulates reality sufficiently well. We have developed a simplified off-lattice protein model, incorporating semi-empirical physicochemical potentials, and combined it with an efficient Monte Carlo method for calculating time-averaged peptide structures. Reasonably accurate predictions are found for a set of small ,-helical and ,-hairpin peptides, and we demonstrate a potential application in measuring local structure propensities in protein chains. Time-averaged structures have also been calculated for a set of small peptides known to form ,-amyloid fibrils. The simulations were of three interacting peptides, and in each case the time-averaged structure describes a three-stranded ,-sheet. The performance of our method in measuring the propensities of small peptides to self-associate into possible prefibrillar species compares favorably with more detailed and CPU-intensive approaches. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008 [source] The sequence determinants of cadherin moleculesPROTEIN SCIENCE, Issue 9 2001Alexander E. Kister Abstract The sequence and structural analysis of cadherins allow us to find sequence determinants,a few positions in sequences whose residues are characteristic and specific for the structures of a given family. Comparison of the five extracellular domains of classic cadherins showed that they share the same sequence determinants despite only a nonsignificant sequence similarity between the N-terminal domain and other extracellular domains. This allowed us to predict secondary structures and propose three-dimensional structures for these domains that have not been structurally analyzed previously. A new method of assigning a sequence to its proper protein family is suggested: analysis of sequence determinants. The main advantage of this method is that it is not necessary to know all or almost all residues in a sequence as required for other traditional classification tools such as BLAST, FASTA, and HMM. Using the key positions only, that is, residues that serve as the sequence determinants, we found that all members of the classic cadherin family were unequivocally selected from among 80,000 examined proteins. In addition, we proposed a model for the secondary structure of the cytoplasmic domain of cadherins based on the principal relations between sequences and secondary structure multialignments. The patterns of the secondary structure of this domain can serve as the distinguishing characteristics of cadherins. [source] Interaction of the plant glycine-rich RNA-binding protein MA16 with a novel nucleolar DEAD box RNA helicase protein from Zea maysTHE PLANT JOURNAL, Issue 6 2004Elisenda Gendra Summary The maize RNA-binding MA16 protein is a developmentally and environmentally regulated nucleolar protein that interacts with RNAs through complex association with several proteins. By using yeast two-hybrid screening, we identified a DEAD box RNA helicase protein from Zea mays that interacted with MA16, which we named Z. maysDEAD box RNA helicase 1 (ZmDRH1). The sequence of ZmDRH1 includes the eight RNA helicase motifs and two glycine-rich regions with arginine,glycine-rich (RGG) boxes at the amino (N)- and carboxy (C)-termini of the protein. Both MA16 and ZmDRH1 were located in the nucleus and nucleolus, and analysis of the sequence determinants for their cellular localization revealed that the region containing the RGG motifs in both proteins was necessary for nuclear/nucleolar localization The two domains of MA16, the RNA recognition motif (RRM) and the RGG, were tested for molecular interaction with ZmDRH1. MA16 specifically interacted with ZmDRH1 through the RRM domain. A number of plant proteins and vertebrate p68/p72 RNA helicases showed evolutionary proximity to ZmDRH1. In addition, like p68, ZmDRH1 was able to interact with fibrillarin. Our data suggest that MA16, fibrillarin, and ZmDRH1 may be part of a ribonucleoprotein complex involved in ribosomal RNA (rRNA) metabolism. [source] | |||||||||||||