Comparative Study on the Use of Coherent Radar-Derived Electric Fields vs. Statistical Electric Fields for the Initialization of a High-Latitude Ionospheric Model

The structure and time development of the magnetosphere-ionosphere system have significant impacts on the Air Force and its mission. Specifically, an accurate knowledge of ionospheric plasma densities is important for the operation of many Air Force systems. This research analyzes plasma density structure development through comparing two distinct electric field models. The two models compared here are a commonly used statistical model created by Heppner and Maynard 1987, and a more recently developed model using real-time coherent radar measurements from the SuperDARN radar network. Ionospheric simulations were run using Utah State University s Time-Dependent Ionospheric Model (TDIM) with the two electric field models as drivers, and density results from the simulations were compared with both a conceptual model and in-situ DMSP satellite measurements. While there are limitations to the comparison technique, results indicate that, in general, using the SuperDARN-derived electric fields to drive the TDIM has advantages over using the statistical fields. The higher spatial and temporal resolution of the input electric fields generally seem to produce more realistic morphological density structures, with smoothing due to statistical averaging and geomagnetic index-binning reduced. This research provides an essential first step in using high resolution, real-time SuperDARN-derived electric fields to drive a physical model of the ionosphere in order to create realistic ionospheric density results

Kangaroo – A pattern-matching program for biological sequences

BACKGROUND: Biologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells. RESULTS: Kangaroo is a web-based regular expression pattern-matching program that can search for patterns in DNA, protein, or coding region sequences in ten different organisms. The program is implemented to facilitate a wide range of queries with no restriction on the length or complexity of the query expression. The program is accessible on the web at http://bioinfo.mshri.on.ca/kangaroo/ and the source code is freely distributed at http://sourceforge.net/projects/slritools/. CONCLUSION: A low-level simple pattern-matching application can prove to be a useful tool in many research settings. For example, Kangaroo was used to identify potential genetic targets in a human colorectal cancer variant that is characterized by a high frequency of mutations in coding regions containing mononucleotide repeats

NBLAST: a cluster variant of BLAST for NxN comparisons

BACKGROUND: The BLAST algorithm compares biological sequences to one another in order to determine shared motifs and common ancestry. However, the comparison of all non-redundant (NR) sequences against all other NR sequences is a computationally intensive task. We developed NBLAST as a cluster computer implementation of the BLAST family of sequence comparison programs for the purpose of generating pre-computed BLAST alignments and neighbour lists of NR sequences. RESULTS: NBLAST performs the heuristic BLAST algorithm and generates an exhaustive database of alignments, but it only computes [Image: see text] alignments (i.e. the upper triangle) of a possible N(2) alignments, where N is the set of all sequences to be compared. A task-partitioning algorithm allows for cluster computing across all cluster nodes and the NBLAST master process produces a BLAST sequence alignment database and a list of sequence neighbours for each sequence record. The resulting sequence alignment and neighbour databases are used to serve the SeqHound query system through a C/C++ and PERL Application Programming Interface (API). CONCLUSIONS: NBLAST offers a local alternative to the NCBI's remote Entrez system for pre-computed BLAST alignments and neighbour queries. On our 216-processor 450 MHz PIII cluster, NBLAST requires ~24 hrs to compute neighbours for 850000 proteins currently in the non-redundant protein database

An automated method for finding molecular complexes in large protein interaction networks

BACKGROUND: Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. RESULTS: This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. CONCLUSION: Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from

Species-specific protein sequence and fold optimizations

BACKGROUND: An organism's ability to adapt to its particular environmental niche is of fundamental importance to its survival and proliferation. In the largest study of its kind, we sought to identify and exploit the amino-acid signatures that make species-specific protein adaptation possible across 100 complete genomes. RESULTS: Environmental niche was determined to be a significant factor in variability from correspondence analysis using the amino acid composition of over 360,000 predicted open reading frames (ORFs) from 17 archae, 76 bacteria and 7 eukaryote complete genomes. Additionally, we found clusters of phylogenetically unrelated archae and bacteria that share similar environments by amino acid composition clustering. Composition analyses of conservative, domain-based homology modeling suggested an enrichment of small hydrophobic residues Ala, Gly, Val and charged residues Asp, Glu, His and Arg across all genomes. However, larger aromatic residues Phe, Trp and Tyr are reduced in folds, and these results were not affected by low complexity biases. We derived two simple log-odds scoring functions from ORFs (C(G)) and folds (C(F)) for each of the complete genomes. C(F )achieved an average cross-validation success rate of 85 ± 8% whereas the C(G )detected 73 ± 9% species-specific sequences when competing against all other non-redundant C(G). Continuously updated results are available at . CONCLUSION: Our analysis of amino acid compositions from the complete genomes provides stronger evidence for species-specific and environmental residue preferences in genomic sequences as well as in folds. Scoring functions derived from this work will be useful in future protein engineering experiments and possibly in identifying horizontal transfer events

Near-membrane ensemble elongation in the proline-rich LRP6 intracellular domain may explain the mysterious initiation of the Wnt signaling pathway

<p>Abstract</p> <p>Background</p> <p>LRP6 is a membrane protein crucial in the initiation of canonical Wnt/β-catenin signalling. Its function is dependent on its proline-serine rich intracellular domain. LRP6 has five PPP(S/T)P motifs that are phosphorylated during activation, starting with the site closest to the membrane. Like all long proline rich regions, there is no stable 3D structure for this isolated, contiguous region.</p> <p>Results</p> <p>In our study, we use a computational simulation tool to sample the conformational space of the LRP6 intracellular domain, under the spatial constraints imposed by (a) the membrane and (b) the close approach of the neighboring intracellular molecular complex, which is assembled on Frizzled when Wnt binds to both LRP6 and Frizzled on the opposite side of the membrane. We observe that an elongated form dominates in the LRP6 intracellular domain structure ensemble. This elongation could relieve conformational auto-inhibition of the PPP(S/T)PX(S/T) motif binding sites and allow GSK3 and CK1 to approach their phosphorylation sites, thereby activating LRP6 and the downstream pathway.</p> <p>Conclusions</p> <p>We propose a model in which the conformation of the LRP6 intracellular domain is elongated before activation. This is based on the intrusion of the Frizzled complex into the ensemble space of the proline rich region of LRP6, which alters the shape of its available ensemble space. To test whether this observed ensemble conformational change is sequence dependent, we did a control simulation with a hypothetical sequence with 50% proline and 50% serine in alternating residues. We confirm that this ensemble neighbourhood-based conformational change is independent of sequence and conclude that it is likely found in all proline rich sequences. These observations help us understand the nature of proline rich regions which are both unstructured and which seem to evolve at a higher rate of mutation, while maintaining sequence composition.</p

Comparison of terbium (III) luminescence enhancement in mutants of EF hand calcium binding proteins.

The luminescent isomorphous Ca2+ analogue, Tb3+, can be bound in the 12-amino acid metal binding sites of proteins of the EF hand family, and its luminescence can be enhanced by energy transfer from a nearby aromatic amino acid. Tb3+ can be used as a sensitive luminescent probe of the structure and function of these proteins. The effect of changing the molecular environment around Tb3+ on its luminescence was studied using native Cod III parvalbumin and site-directed mutants of both oncomodulin and calmodulin. Titrations of these proteins showed stoichiometries of fill corresponding to the number of Ca2+ binding loops present. Tryptophan in binding loop position 7 best enhanced Tb3+ luminescence in the oncomodulin mutant Y57W, as well as VU-9 (F99W) and VU-32 (T26W) calmodulin. Excitation spectra of Y57F, F102W, Y65W oncomodulin, and Cod III parvalbumin revealed that the principal Tb3+ luminescence donor residues were phenylalanine or tyrosine located in position 7 of a loop, despite the presence of other nearby donors, including tryptophan. Spectra also revealed conformational differences between the Ca2+- and Tb(3+)-bound forms. An alternate binding loop, based on Tb3+ binding to model peptides, was inserted into the CD loop of oncomodulin by cassette mutagenesis. The order of fill of Tb3+ in this protein reversed, with the mutated loop binding Tb3+ first. This indicates a much higher affinity for the consensus-based mutant loop. The mutant loop inserted into oncomodulin had 32 times more Tb3+ luminescence than the identical synthetic peptide, despite having the same donor tryptophan and metal binding ligands. In this paper, a ranking of sensitivity of luminescence of bound Tb3+ is made among this subset of calcium binding proteins. This ranking is interpreted in light of the structural differences affecting Tb3+ luminescence enhancement intensity. The mechanism of energy transfer from an aromatic amino acid to Tb3+ is consistent with a short-range process involving the donor triplet state as described by Dexter (Dexter, D. L. (1953) J. Chem. Phys. 21, 836). This cautions against the use of the Forster equation in approximating distances in these systems

Domain-based small molecule binding site annotation

BACKGROUND: Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. DESCRIPTION: Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at . The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. CONCLUSION: By focusing on protein domain-small molecule interactions, SMID is able to cluster similar interactions and detect subtle binding patterns that would not otherwise be obvious. Using SMID-BLAST, small molecule targets can be predicted for any protein sequence, with the only limitation being that the small molecule must exist in the PDB. Validation results and specific examples within illustrate that SMID-BLAST has a high degree of accuracy in terms of predicting both the small molecule ligand and binding site residue positions for a query protein

Terbium luminescence in synthetic peptide loops from calcium-binding proteins with different energy donors.

Fourteen 14-mer peptides corresponding to a consensus sequence of metal-binding loops from proteins of the calmodulin family were synthesized. The effect of varying both the position in the binding loop, and the type of aromatic side chains as energy donors for enhancement of terbium luminescence, was studied. It was concluded that tryptophan in loop position 7 gave optimal luminescence enhancement, and that the additional inclusion of a tyrosine in the loop at positions 2 or 4 could further boost emission from the bound terbium. In all further cases energy transfer from aromatic residues at positions other than 7 was markedly less efficient. These results suggest that the peptides assume a configuration which allows a hexadentate ligand structure around the bound terbium ion. This is consistent with a Dexter-type electron exchange model of energy transfer