Molecular characteristics of fibroblast growth factor–fibroblast growth factor receptor–heparin-like glycosaminoglycan complex

Fibroblast growth factor (FGF) family plays key roles in development, wound healing, and angiogenesis. Understanding of the molecular nature of interactions of FGFs with their receptors (FGFRs) has been seriously limited by the absence of structural information on FGFR or FGF–FGFR complex. In this study, based on an exhaustive analysis of the primary sequences of the FGF family, we determined that the residues that constitute the primary receptor-binding site of FGF-2 are conserved throughout the FGF family, whereas those of the secondary receptor binding site of FGF-2 are not. We propose that the FGF–FGFR interaction mediated by the ‘conserved’ primary site interactions is likely to be similar if not identical for the entire FGF family, whereas the ‘variable’ secondary sites, on both FGF as well as FGFR mediates specificity of a given FGF to a given FGFR isoform. Furthermore, as the pro-inflammatory cytokine interleukin 1 (IL-1) and FGF-2 share the same structural scaffold, we find that the spatial orientation of the primary receptor-binding site of FGF-2 coincides structurally with the IL-1β receptor-binding site when the two molecules are superimposed. The structural similarities between the IL-1 and the FGF system provided a framework to elucidate molecular principles of FGF–FGFR interactions. In the FGF–FGFR model proposed here, the two domains of a single FGFR wrap around a single FGF-2 molecule such that one domain of FGFR binds to the primary receptor-binding site of the FGF molecule, while the second domain of the same FGFR binds to the secondary receptor-binding site of the same FGF molecule. Finally, the proposed model is able to accommodate not only heparin-like glycosaminoglycan (HLGAG) interactions with FGF and FGFR but also FGF dimerization or oligomerization mediated by HLGAG.

Estimating the probability for a protein to have a new fold: A statistical computational model

Structural genomics aims to solve a large number of protein structures that represent the protein space. Currently an exhaustive solution for all structures seems prohibitively expensive, so the challenge is to define a relatively small set of proteins with new, currently unknown folds. This paper presents a method that assigns each protein with a probability of having an unsolved fold. The method makes extensive use of protomap, a sequence-based classification, and scop, a structure-based classification. According to protomap, the protein space encodes the relationship among proteins as a graph whose vertices correspond to 13,354 clusters of proteins. A representative fold for a cluster with at least one solved protein is determined after superposition of all scop (release 1.37) folds onto protomap clusters. Distances within the protomap graph are computed from each representative fold to the neighboring folds. The distribution of these distances is used to create a statistical model for distances among those folds that are already known and those that have yet to be discovered. The distribution of distances for solved/unsolved proteins is significantly different. This difference makes it possible to use Bayes' rule to derive a statistical estimate that any protein has a yet undetermined fold. Proteins that score the highest probability to represent a new fold constitute the target list for structural determination. Our predicted probabilities for unsolved proteins correlate very well with the proportion of new folds among recently solved structures (new scop 1.39 records) that are disjoint from our original training set.

STACK: Sequence Tag Alignment and Consensus Knowledgebase

STACK is a tool for detection and visualisation of expressed transcript variation in the context of developmental and pathological states. The datasystem organises and reconstructs human transcripts from available public data in the context of expression state. The expression state of a transcript can include developmental state, pathological association, site of expression and isoform of expressed transcript. STACK consensus transcripts are reconstructed from clusters that capture and reflect the growing evidence of transcript diversity. The comprehensive capture of transcript variants is achieved by the use of a novel clustering approach that is tolerant of sub-sequence diversity and does not rely on pairwise alignment. This is in contrast with other gene indexing projects. STACK is generated at least four times a year and represents the exhaustive processing of all publicly available human EST data extracted from GenBank. This processed information can be explored through 15 tissue-specific categories, a disease-related category and a whole-body index and is accessible via WWW at http://www.sanbi.ac.za/Dbases.html. STACK represents a broadly applicable resource, as it is the only reconstructed transcript database for which the tools for its generation are also broadly available (http://www.sanbi.ac.za/CODES).

ICB database: the gyrB database for identification and classification of bacteria

The Identification and Classification of Bacteria (ICB) database (http:/www.mbio.co.jp/icb) contains currently available information about the DNA gyrase subunit B (gyrB) gene in bacteria. The database is designed to provide the scientific community with a reference point for using gyrB as an evolutionary and taxonomic marker. Nucleic and amino acid sequence data are currently available for over 850 strains, along with alignments at several different taxonomic levels and an exhaustive review of primer selection and background information.

Does recombination improve selection on codon usage? Lessons from nematode and fly complete genomes

Understanding the factors responsible for variations in mutation patterns and selection efficacy along chromosomes is a prerequisite for deciphering genome sequences. Population genetics models predict a positive correlation between the efficacy of selection at a given locus and the local rate of recombination because of Hill–Robertson effects. Codon usage is considered one of the most striking examples that support this prediction at the molecular level. In a wide range of species including Caenorhabditis elegans and Drosophila melanogaster, codon usage is essentially shaped by selection acting for translational efficiency. Codon usage bias correlates positively with recombination rate in Drosophila, apparently supporting the hypothesis that selection on codon usage is improved by recombination. Here we present an exhaustive analysis of codon usage in C. elegans and D. melanogaster complete genomes. We show that in both genomes there is a positive correlation between recombination rate and the frequency of optimal codons. However, we demonstrate that in both species, this effect is due to a mutational bias toward G and C bases in regions of high recombination rate, possibly as a direct consequence of the recombination process. The correlation between codon usage bias and recombination rate in these species appears to be essentially determined by recombination-dependent mutational patterns, rather than selective effects. This result highlights that it is necessary to take into account the mutagenic effect of recombination to understand the evolutionary role and impact of recombination.

Increased accommodation of nascent RNA in a product site on RNA polymerase II during arrest.

RNA polymerases encounter specific DNA sites at which RNA chain elongation takes place in the absence of enzyme translocation in a process called discontinuous elongation. For RNA polymerase II, at least some of these sequences also provoke transcriptional arrest where renewed RNA polymerization requires elongation factor SII. Recent elongation models suggest the occupancy of a site within RNA polymerase that accommodates nascent RNA during discontinuous elongation. Here we have probed the extent of nascent RNA extruded from RNA polymerase II as it approaches, encounters, and departs an arrest site. Just upstream of an arrest site, 17-19 nucleotides of the RNA 3'-end are protected from exhaustive digestion by exogenous ribonuclease probes. As RNA is elongated to the arrest site, the enzyme does not translocate and the protected RNA becomes correspondingly larger, up to 27 nucleotides in length. After the enzyme passes the arrest site, the protected RNA is again the 18-nucleotide species typical of an elongation-competent complex. These findings identify an extended RNA product groove in arrested RNA polymerase II that is probably identical to that emptied during SII-activated RNA cleavage, a process required for the resumption of elongation. Unlike Escherichia coli RNA polymerase at a terminator, arrested RNA polymerase II does not release its RNA but can reestablish the normal elongation mode downstream of an arrest site. Discontinuous elongation probably represents a structural change that precedes, but may not be sufficient for, arrest by RNA polymerase II.

Hyperplane arrangements, interval orders, and trees.

A hyperplane arrangement is a finite set of hyperplanes in a real affine space. An especially important arrangement is the braid arrangement, which is the set of all hyperplanes xi - xj = 1, 1 enumeration of trees. For instance, the number of labeled interval orders that can be obtained from n intervals I1,..., In of generic lengths is counted. There is also discussed an arrangement due to N. Linial whose number of regions is the number of alternating (or intransitive) trees, as defined by Gelfand, Graev, and Postnikov [Gelfand, I. M., Graev, M. I., and Postnikov, A. (1995), preprint]. Finally, a refinement is given, related to counting labeled trees by number of inversions, of a result of Shi [Shi, J.-Y. (1986), Lecture Notes in Mathematics, no. 1179, Springer-Verlag] that a certain deformation of the braid arrangement has (n + 1)n-1 regions.

Analysis of differential gene expression by display of 3' end restriction fragments of cDNAs.

We have developed an approach to study changes in gene expression by selective PCR amplification and display of 3' end restriction fragments of double-stranded cDNAs. This method produces highly consistent and reproducible patterns, can detect almost all mRNAs in a sample, and can resolve hidden differences such as bands that differ in their sequence but comigrate on a gel. Bands corresponding to known cDNAs move to predictable positions on the gel, making this a powerful approach to correlate gel patterns with cDNA data bases. Applying this method, we have examined differences in gene expression patterns during T-cell activation. Of a total of 700 bands that were evaluated in this study, as many as 3-4% represented mRNAs that are upregulated, while approximately 2% were down-regulated within 4 hr of activation of Jurkat T cells. These and other results suggest that this approach is suitable for the systematic, expeditious, and nearly exhaustive elucidation of subtle changes in the patterns of gene expression in cells with altered physiologic states.