Membrane interaction and structure of the transmembrane domain of influenza hemagglutinin and its fusion peptide complex

Background  

To study the organization and interaction with the fusion domain (or fusion peptide, FP) of the transmembrane domain (TMD) of influenza virus envelope glycoprotein for its role in membrane fusion which is also essential in the cellular trafficking of biomolecules and sperm-egg fusion.     

Extension of the COG and arCOG databases by amino acid and nucleotide sequences

Background  

The current versions of the COG and arCOG databases, both excellent frameworks for studies in comparative and functional genomics, do not contain the nucleotide sequences corresponding to their protein or protein domain entries.     

Gene and protein nomenclature in public databases

Background  

Frequently, several alternative names are in use for biological objects such as genes and proteins. Applications like manual literature search, automated text-mining, named entity identification, gene/protein annotation, and linking of knowledge from different information sources require the knowledge of all used names referring to a given gene or protein. Various organism-specific or general public databases aim at organizing knowledge about genes and proteins. These databases can be used for deriving gene and protein name dictionaries. So far, little is known about the differences between databases in terms of size, ambiguities and overlap.     

Hydrophobic profiles of the tail anchors in SLMAP dictate subcellular targeting

Background  

Tail anchored (TA) membrane proteins target subcellular structures via a C-terminal transmembrane domain and serve prominent roles in membrane fusion and vesicle transport. Sarcolemmal Membrane Associated Protein (SLMAP) possesses two alternatively spliced tail anchors (TA1 or TA2) but their specificity of subcellular targeting remains unknown.     

Reuse of structural domain–domain interactions in protein networks

Background  

Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases.     

GeneKeyDB: A lightweight,gene-centric,relational database to support data mining environments

Background  

The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a web interface to the resource. We have recognized the growing need for a database which can be used successfully as a backend to computational analysis tools and pipelines. Such database should be sufficiently versatile to allow easy system integration.     

A case study in pathway knowledgebase verification

Background  

Biological databases and pathway knowledgebases are proliferating rapidly. We are developing software tools for computer-aided hypothesis design and evaluation, and we would like our tools to take advantage of the information stored in these repositories. But before we can reliably use a pathway knowledgebase as a data source, we need to proofread it to ensure that it can fully support computer-aided information integration and inference.     

A method for rapid similarity analysis of RNA secondary structures

Background  

Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures.     

Fast index based algorithms and software for matching position specific scoring matrices

Background  

In biological sequence analysis, position specific scoring matrices (PSSMs) are widely used to represent sequence motifs in nucleotide as well as amino acid sequences. Searching with PSSMs in complete genomes or large sequence databases is a common, but computationally expensive task.     

A computational approach identifies two regions of Hepatitis C Virus E1 protein as interacting domains involved in viral fusion process

Background  

The E1 protein of Hepatitis C Virus (HCV) can be dissected into two distinct hydrophobic regions: a central domain containing an hypothetical fusion peptide (FP), and a C-terminal domain (CT) comprising two segments, a pre-anchor and a trans-membrane (TM) region. In the currently accepted model of the viral fusion process, the FP and the TM regions are considered to be closely juxtaposed in the post-fusion structure and their physical interaction cannot be excluded. In the present study, we took advantage of the natural sequence variability present among HCV strains to test, by purely sequence-based computational tools, the hypothesis that in this virus the fusion process involves the physical interaction of the FP and CT regions of E1.     

Structure of a conserved hypothetical protein SA1388 from S. aureus reveals a capped hexameric toroid with two PII domain lids and a dinuclear metal center

Background  

The protein encoded by the SA1388 gene from Staphylococcus aureus was chosen for structure determination to elucidate its domain organization and confirm our earlier remote homology based prediction that it housed a nitrogen regulatory PII protein-like domain. SA1388 was predicted to contain a central PII-like domain and two flanking regions, which together belong to the NIF3-like protein family. Proteins like SA1388 remain a poorly studied group and their structural characterization could guide future investigations aimed at understanding their function.     

SeqX: a tool to detect,analyze and visualize residue co-locations in protein and nucleic acid structures

Background  

The interacting residues of protein and nucleic acid sequences are close to each other – they are co-located. Structure databases (like Protein Data Bank, PDB and Nucleic Acid Data Bank, NDB) contain all in0066ormation about these co-locations; however it is not an easy task to penetrate this complex information. We developed a JAVA tool, called SeqX for this purpose.     

Identification and validation of reference genes for quantitative RT-PCR normalization in wheat

Background  

Usually the reference genes used in gene expression analysis have been chosen for their known or suspected housekeeping roles, however the variation observed in most of them hinders their effective use. The assessed lack of validated reference genes emphasizes the importance of a systematic study for their identification. For selecting candidate reference genes we have developed a simple in silico method based on the data publicly available in the wheat databases Unigene and TIGR.     

Evolution based on domain combinations: the case of glutaredoxins

Background  

Protein domains represent the basic units in the evolution of proteins. Domain duplication and shuffling by recombination and fusion, followed by divergence are the most common mechanisms in this process. Such domain fusion and recombination events are predicted to occur only once for a given multidomain architecture. However, other scenarios may be relevant in the evolution of specific proteins, such as convergent evolution of multidomain architectures. With this in mind, we study glutaredoxin (GRX) domains, because these domains of approximately one hundred amino acids are widespread in archaea, bacteria and eukaryotes and participate in fusion proteins. GRXs are responsible for the reduction of protein disulfides or glutathione-protein mixed disulfides and are involved in cellular redox regulation, although their specific roles and targets are often unclear.     

Feature selection using Haar wavelet power spectrum

Background  

Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum.     

miRAS: a data processing system for miRNA expression profiling study

Background  

The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.     

Functionally specified protein signatures distinctive for each of the different blue copper proteins

Background  

Proteins having similar functions from different sources can be identified by the occurrence in their sequences, a conserved cluster of amino acids referred to as pattern, motif, signature or fingerprint. The wide usage of protein sequence analysis in par with the growth of databases signifies the importance of using patterns or signatures to retrieve out related sequences. Blue copper proteins are found in the electron transport chain of prokaryotes and eukaryotes. The signatures already existing in the databases like the type 1 copper blue, multiple copper oxidase, cyt b/b6, photosystem 1 psaA&B, psaG&K, and reiske iron sulphur protein are not specified signatures for blue copper proteins as the name itself suggests. Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. This work describes the signatures designed based on the copper metal binding motifs in blue copper proteins. The common feature in all blue copper proteins is a trigonal planar arrangement of two nitrogen ligands [each from histidine] and one sulphur containing thiolate ligand [from cysteine], with strong interactions between the copper center and these ligands.     

Virus variation resources at the National Center for Biotechnology Information: dengue virus

Background  

There is an increasing number of complete and incomplete virus genome sequences available in public databases. This large body of sequence data harbors information about epidemiology, phylogeny, and virulence. Several specialized databases, such as the NCBI Influenza Virus Resource or the Los Alamos HIV database, offer sophisticated query interfaces along with integrated exploratory data analysis tools for individual virus species to facilitate extracting this information. Thus far, there has not been a comprehensive database for dengue virus, a significant public health threat.