Comparative Analysis of Protein Structure Alignments

Background  

Several methods are currently available for the comparison of protein structures. These methods have been analysed regarding the performance in the identification of structurally/evolutionary related proteins, but so far there has been less focus on the objective comparison between the alignments produced by different methods.     

FITBAR: a web tool for the robust prediction of prokaryotic regulons

Background  

The binding of regulatory proteins to their specific DNA targets determines the accurate expression of the neighboring genes. The in silico prediction of new binding sites in completely sequenced genomes is a key aspect in the deeper understanding of gene regulatory networks. Several algorithms have been described to discriminate against false-positives in the prediction of new binding targets; however none of them has been implemented so far to assist the detection of binding sites at the genomic scale.     

Cell-based assay for the detection of chemically induced cellular stress by immortalized untransformed transgenic hepatocytes

Background  

Primary hepatocytes, one of the most widely used cell types for toxicological studies, have a very limited life span and must be freshly derived from mice or even humans. Attempts to use stable cell lines maintaining the enzymatic pattern of liver cells have been so far unsatisfactory. Stress proteins (heat shock proteins, HSPs) have been proposed as general markers of cellular injury and their use for environmental monitoring has been suggested. The aim of this work is to develop a bi-transgenic hepatocyte cell line in order to evaluate the ability of various organic and inorganic chemicals to induce the expression of the HSP70 driven reporter gene.     

A comparative study of S/MAR prediction tools

Background  

S/MARs are regions of the DNA that are attached to the nuclear matrix. These regions are known to affect substantially the expression of genes. The computer prediction of S/MARs is a highly significant task which could contribute to our understanding of chromatin organisation in eukaryotic cells, the number and distribution of boundary elements, and the understanding of gene regulation in eukaryotic cells. However, while a number of S/MAR predictors have been proposed, their accuracy has so far not come under scrutiny.     

The 'ins' and 'outs' of intermediate filament organization

A major function shared by several types of cytoplasmic intermediate filaments (IFs) is to stabilize cellular architecture against the mechanical forces it is subjected to. As for other fibrous cytoskeletal arrays, a crucial determinant of this function is the spatial organization of IFs in the cytoplasm. However, very few crossbridging proteins are specific for IFs - most IF-associated proteins known to exert a structural role act to tether IFs to other major cytoskeletal elements, such as F-actin, microtubules or adhesion complexes. In addition, IFs are endowed with the ability to participate in their own organization. This intriguing property is probably connected to the unusual degree of sequence diversity and sequence-specific regulation that characterize IF genes and their proteins. This dependence upon a combination of extrinsic and intrinsic determinants contributes to distinguish IFs from other fibrous cytoskeletal polymers and is key to their function.     

Interest of major serum protein removal for Surface-Enhanced Laser Desorption/Ionization – Time Of Flight (SELDI-TOF) proteomic blood profiling

Background  

Surface-Enhanced Laser Desorption/Ionization – Time Of Flight (SELDI-TOF) has been proposed as new approach for blood biomarker discovery. However, results obtained so far have been often disappointing as this technique still has difficulties to detect low-abundant plasma and serum proteins.     

"Hot cores" in proteins: Comparative analysis of the apolar contact area in structures from hyper/thermophilic and mesophilic organisms

Background  

A wide variety of stabilizing factors have been invoked so far to elucidate the structural basis of protein thermostability. These include, amongst the others, a higher number of ion-pairs interactions and hydrogen bonds, together with a better packing of hydrophobic residues. It has been frequently observed that packing of hydrophobic side chains is improved in hyperthermophilic proteins, when compared to their mesophilic counterparts. In this work, protein crystal structures from hyper/thermophilic organisms and their mesophilic homologs have been compared, in order to quantify the difference of apolar contact area and to assess the role played by the hydrophobic contacts in the stabilization of the protein core, at high temperatures.     

ProFAT: a web-based tool for the functional annotation of protein sequences

Background  

The functional annotation of proteins relies on published information concerning their close and remote homologues in sequence databases. Evidence for remote sequence similarity can be further strengthened by a similar biological background of the query sequence and identified database sequences. However, few tools exist so far, that provide a means to include functional information in sequence database searches.     

A topological algorithm for identification of structural domains of proteins

Background  

Identification of the structural domains of proteins is important for our understanding of the organizational principles and mechanisms of protein folding, and for insights into protein function and evolution. Algorithmic methods of dissecting protein of known structure into domains developed so far are based on an examination of multiple geometrical, physical and topological features. Successful as many of these approaches are, they employ a lot of heuristics, and it is not clear whether they illuminate any deep underlying principles of protein domain organization. Other well-performing domain dissection methods rely on comparative sequence analysis. These methods are applicable to sequences with known and unknown structure alike, and their success highlights a fundamental principle of protein modularity, but this does not directly improve our understanding of protein spatial structure.     

Spontaneous focal activation of invariant natural killer T (iNKT) cells in mouse liver and kidney

Background  

Invariant natural killer T (iNKT) cells differ from other T cells by their hyperactive effector T-cell status, in addition to the expression of NK lineage receptors and semi-invariant T-cell receptors. It is generally agreed that the immune phenotype of iNKT cells is maintained by repeated activation in peripheral tissues although no explicit evidence for such iNKT cell activity in vivo has so far been reported.     

A multi-scale approach to understand the mechanobiology of intermediate filaments

The animal cell cytoskeleton consists of three interconnected filament systems: actin microfilaments, microtubules and the lesser known intermediate filaments (IFs). All mature IF proteins share a common tripartite domain structure and the ability to assemble into 8–12 nm wide filaments. At the time of their discovery in the 1980s, IFs were only considered as passive elements of the cytoskeleton mainly involved in maintaining the mechanical integrity of tissues. Since then, our knowledge of IFs structure, assembly plan and functions has improved dramatically. Especially, single IFs show a unique combination of extensibility, flexibility and toughness that is a direct consequence of their unique assembly plan. In this review we will first discuss the mechanical design of IFs by combining the experimental data with recent multi-scale modeling results. Then we will discuss how mechanical forces may interact with IFs in vivo both directly and through the activation of other proteins such as kinases.     

In search of functional association from time-series microarray data based on the change trend and level of gene expression

Background  

The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored.     

The XMAP215-family protein DdCP224 is required for cortical interactions of microtubules

Background  

Interactions of peripheral microtubule tips with the cell cortex are of crucial importance for nuclear migration, spindle orientation, centrosome positioning and directional cell movement. Microtubule plus end binding proteins are thought to mediate interactions of microtubule tips with cortical actin and membrane proteins in a dynein-dependent manner. XMAP215-family proteins are main regulators of microtubule plus end dynamics but so far they have not been implicated in the interactions of microtubule tips with the cell cortex.     

Evaluation of methods for predicting the topology of β-barrel outer membrane proteins and a consensus prediction method

Background  

Prediction of the transmembrane strands and topology of β-barrel outer membrane proteins is of interest in current bioinformatics research. Several methods have been applied so far for this task, utilizing different algorithmic techniques and a number of freely available predictors exist. The methods can be grossly divided to those based on Hidden Markov Models (HMMs), on Neural Networks (NNs) and on Support Vector Machines (SVMs). In this work, we compare the different available methods for topology prediction of β-barrel outer membrane proteins. We evaluate their performance on a non-redundant dataset of 20 β-barrel outer membrane proteins of gram-negative bacteria, with structures known at atomic resolution. Also, we describe, for the first time, an effective way to combine the individual predictors, at will, to a single consensus prediction method.     

Identification of NAD interacting residues in proteins

Background  

Small molecular cofactors or ligands play a crucial role in the proper functioning of cells. Accurate annotation of their target proteins and binding sites is required for the complete understanding of reaction mechanisms. Nicotinamide adenine dinucleotide (NAD⁺ or NAD) is one of the most commonly used organic cofactors in living cells, which plays a critical role in cellular metabolism, storage and regulatory processes. In the past, several NAD binding proteins (NADBP) have been reported in the literature, which are responsible for a wide-range of activities in the cell. Attempts have been made to derive a rule for the binding of NAD⁺ to its target proteins. However, so far an efficient model could not be derived due to the time consuming process of structure determination, and limitations of similarity based approaches. Thus a sequence and non-similarity based method is needed to characterize the NAD binding sites to help in the annotation. In this study attempts have been made to predict NAD binding proteins and their interacting residues (NIRs) from amino acid sequence using bioinformatics tools.     

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

Background  

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs.