From fold to function predictions: an apoptosis regulator protein BID

With the rapidly increasing pace of genome sequencing projects and the resulting flood of predicted amino acid sequences of uncharacterized proteins, protein sequence analysis, and in particular, protein structure prediction is quickly gaining in importance. Prediction algorithms can be used for preliminary annotation of newly sequenced proteins and, at least in some cases, provide insights into their function and specific mode of action. Such annotations for several microbial genomes were performed by several groups and placed in public domain for evaluation. An example presented in this work comes from a related project of structural and functional predictions for proteins involved in the process of controlled cell death (apoptosis). The BID protein belongs to an important class of regulators of apoptosis identified by short sequence motifs. Here, several fold prediction methods are used to build a series of three-dimensional models. Structure analysis of the models with reference to the biological data available allows selection of the most appropriate model. It is found that the most likely structural model of BID is built on the structure of Bcl-X(L). The model is discussed in terms of experimental data on specific proteolytic cleavage of BID and its effect on BID interactions with other proteins and membranes.     

Old proteins and the Achilles heel of mass spectrometry. The role of proteomics in the etiology of human cataract

Proteomics may have enabled the root cause of a major human-blinding condition, age-related cataract, to be established. Cataract appears to result from the spontaneous decomposition of long-lived macromolecules in the human lens, and recent proteomic analysis has enabled both the particular crystallins, and the specific sites of amino acid modification within each polypeptide, to be identified. Analysis of proteins from cataract lenses has demonstrated that there are key sites on some structural proteins that show a consistently greater degree of deterioration than age-matched normal lenses. Proteomic analysis, using MS, revealed that the most abundant posttranslational modification of aged lens proteins is racemization. This is somewhat ironic, since structural isomers can be viewed as the “Achilles heel” of MS and there are typically few, if any, differences in the MS/MS spectra of tryptic peptides containing one d -amino acid. It is proposed that once a certain level of spontaneous PTM at key sites occurs, that protein–protein interactions are disrupted, and binding of complexes to cell membranes takes place that impairs cell-to-cell communication. These findings may apply more widely to age-related human diseases, in particular where the deterioration of long-lived proteins is a crucial component in the etiology.     

Regression model for predicting pathogenic properties of SOD1 mutants based on the analysis of conformational stability and conservation of hydrogen bonds

Intracellular aggregation of proteins is thought to be involved in the aetiology of various neurodegenerative diseases. In particular, mutations in the SOD1 gene are linked to the familial form of amyotrophic lateral sclerosis (ALS). Recently, we developed a regression model for estimating the survival time of ALS patients carrying mutations in SOD1. This model was built based on an analysis of the stability of hydrogen bonds formed in SOD1 mutant proteins during a molecular dynamics (MD) simulation. In the present paper, the regression model was improved by taking into account a new hydrogen-bond property that reflects the conservation measure of a hydrogen bond in the space of protein conformational states. Conformational conservation of hydrogen bonds, being obtained with elastic network (EN) models, allowed us to find eight hydrogen bonds that might affect the pathogenic SOD1 mutants’ properties in addition to the bonds that were found via MD in our previous work. The correlation coefficient between survival time of patients with ALS-linked mutations in SOD1 predicted within the improved model and that observed in the literature was 0.91. SOD1 amino acid residues forming these pathogenic hydrogen bonds are found in zinc-binding and electrostatic loops as well as at zinc-binding sites and are in contact with SOD1 aggregates, which implies that these regions are sensitive to perturbations from pathogenic mutations.     

Continuum electrostatic approach for evaluating positions and interactions of proteins in a bilayer membrane

Orientations of proteins in the membranes are crucial to their function and stability. Unfortunately the exact positions of these proteins in the lipid bilayer are mostly undetermined. Here, the spatial orientation of membrane proteins within the lipid membrane was evaluated using a Poisson–Boltzmann solvent continuum approach to calculate the electrostatic free energy of the protein solvation at various orientations in an implicit bilayer. The solvation energy was obtained by computing the difference in electrostatic energies of the protein in water and in lipid/water environments, treating each as an implicit solvent model. The optimal position of transmembrane proteins (TMP) in a lipid bilayer is identified by the minimum in the “downhill” pathway of the solvation energy landscape. The energy landscape pattern was considerably conserved in various TMP classes. Evaluation of the position of 1060 membrane proteins from the orientations of proteins in membranes (OPM) database revealed that most of the polytopic and β-barrel proteins were in good agreement with those of the OPM database. The study provides a useful scheme for estimating the membrane solvation energy made by lipid-exposed amino acids in membrane proteins. In addition, our results tested with the bacterial potassium channel model demonstrated the potential usefulness of the approach in assessing the quality of membrane protein models. The present approach should be applicable for constructing transmembrane proteins–lipid configuration suitable for membrane protein simulations and will have utility for the structural modeling of membrane proteins.     

Analysis of membrane microdomain-associated proteins in the insular cortex of post-mortem human brain

Membrane microdomains (MM) are membrane rafts within the cell membrane enriched in cholesterol and glycosphingolipids that have been implicated in the trafficking and sorting of membrane proteins, secretory and endocytotic pathways, and signal transduction. To date, MM have not been characterised in the human brain. We reason that by identifying MM in the normal human cortex, we may better understand the molecular mechanisms of human brain dysfunction. To characterize the protein composition of MM in the human brain, we have carried out a comprehensive proteomic analysis of detergent resistant membranes (DRMs) associated proteins derived from human postmortem insular cortex using 1-DE separation prior to LC coupled to MS/MS or GeLC-MS/MS. Eighty five proteins were identified including 57 unique to human brain cortex DRMs (by comparison with DRM proteins reported in other cell types). High levels of signal transduction, cell adhesion, cell transport and cell trafficking proteins were identified including synaptic proteins such as synapsin II and synaptic vesicle membrane protein, mitochondrial proteins such as ATPase subunits and metabolic enzymes such as malate dehydrogenase. This data will facilitate our understanding of protein expression changes within membranes in candidate brain regions in human brain diseases such as schizophrenia, bipolar disorder and other psychiatric and neurodegenerative disorders.     

Modulation of cancer cell line differentiation: A neglected proteomic analysis with potential implications in pathophysiology, diagnosis, prognosis, and therapy of cancer

The recent development of compounds that induce cell differentiation in various types of cancer cells has enabled the molecular mechanisms governing this kind of induced cancer regression to be investigated. Moreover, this approach to investigating the pathophysiology of neoplasia represents a promising experimental model for proteomic analysis of cancer cells. Modulating neoplastic cell differentiation grade may reveal cytodifferentiation-related protein expression changes, and doing so in vitro has the advantage of less biological variation. Hence, this analysis brings attention to molecular targets of the so-called differentiating factors (i.e., retinoids, hybrid polar compounds, tyrosine kinase inhibitors, etc.) as well as proteins that are frequently associated with differentiation/dedifferentiation processes. The in vitro study of these proteins and of their pathogenetic roles in cancer may ultimately result in the discovery of cancer biomarkers with diagnostic, prognostic, and therapeutic applications.     

Protein radial distribution function (P-RDF) and Bayesian-Regularized Genetic Neural Networks for modeling protein conformational stability: chymotrypsin inhibitor 2 mutants

Development of novel computational approaches for modeling protein properties is a main goal in applied Proteomics. In this work, we reported the extension of the radial distribution function (RDF) scores formalism to proteins for encoding 3D structural information with modeling purposes. Protein-RDF (P-RDF) scores measure spherical distributions on protein 3D structure of 48 amino acids/residues properties selected from the AAindex data base. P-RDF scores were tested for building predictive models of the change of thermal unfolding Gibbs free energy change (DeltaDeltaG) of chymotrypsin inhibitor 2 upon mutations. In this sense, an ensemble of Bayesian-Regularized Genetic Neural Networks (BRGNNs) yielded an optimum nonlinear model for the conformational stability. The ensemble predictor described about 84% and 70% variance of the data in training and test sets, respectively.     

Atomistic simulation of hydrophobin HFBII conformation in aqueous and fluorous media and at the water/vacuum interface

Hydrophobins are proteins of interest for numerous applications thanks to their unique conformational and surface properties and their ability to self-assemble at interfaces. Here we report fully atomistic molecular mechanics and molecular dynamics results together with circular dichroism experimental data, aimed to study the conformational properties of the hydrophobin HFBII in a fluorinated solvent in comparison with a water solution and/or at an aqueous/vacuum interface. Both the atomistic simulations and the circular dichroism data show the remarkable structural stability of HFBII at all scales in all these environments, with no significant structural change, although a small cavity is formed in the fluorinated solvent. The combination of theoretical calculations and circular dichroism data can describe in detail the protein conformation and flexibility in different solvents and/or at an interface, and constitutes a first step towards the study of their self-assembly.     

A new analytical solution for the load-deflection of squaremembranes

Accurate models are essential for the determination of the elastic properties of thin films from load-deflection experiments. Although finite element method (FEM) models have the potential to be very accurate, analytical models are desirable because of their simplicity. In this paper we present a new analytical solution for the load-deflection of membranes. Our solution yields the same relationship between the load and the deflection as the known analytical solution. However, the values of two constants are up to 35% higher and correspond well with the results from FEM analysis. In addition, the new solution yields analytical forms of the bending lines, which agree well with experimental measurements carried out with silicon nitride membranes     

Understanding the "Horizontal Dimension' of Molecular Evolution to Annotate, Classify, and Discover Proteins with Functional Domains

Protein evolution proceeds by two distinct processes: 1) individual mutation and selection for adaptive mutations and 2) rearrangement of entire domains within proteins into novel combinations, producing new protein families that combine functional properties in ways that previously did not exist. Domain rearrangement poses a challenge to sequence alignment-based search methods, such as BLAST, in predicting homology since the methodology implicitly assumes that related proteins primarily differ from each ot...     

基于PXE技术的计算机实验室软件系统架设

PXE作为一种网络启动技术,目前得到了广泛的应用。本文介绍了PXE技术的工作原理,结合Symantec Ghost 10.0企业版功能,阐明利用PXE技术实现计算机实验室软件系统架设及维护更新的具体过程。     

Halogenated ligands and their interactions with amino acids: implications for structure-activity and structure-toxicity relationships

The properties of chemicals are rooted in their molecular structure. It follows that structural analysis of specific interactions between ligands and biomolecules at the molecular level is invaluable for defining structure-activity relationships (SARs) and structure-toxicity relationships (STRs). This study has elucidated the structural and molecular basis of interactions of biomolecules with alkyl and aryl halides that are extensively used as components in many commercial pesticides, disinfectants, and drugs. We analyzed the protein structures deposited in Protein Data Bank (PDB) for structural information associated with interactions between halogenated ligands and proteins. This analysis revealed distinct patterns with respect to the nature and structural characteristics of halogen interactions with specific types of atoms and groups in proteins. Fluorine had the highest propensity of interactions for glycine, while chlorine for leucine, bromine for arginine, and iodine for lysine. Chlorine, bromine and iodine had the lowest propensity of interactions for cysteine, while fluorine had a lowest propensity for proline. These trends for highest propensity shifted towards the hydrophobic residues for all the halogens when only interactions with the side chain were considered. Halogens had equal propensities of interaction for the halogen bonding partners (nitrogen and oxygen atoms), albeit with different geometries. The optimal angle for interactions with halogens was approximately 120 degrees for oxygen atoms, and approximately 96 degrees for nitrogen atoms. The distance distributions of halogens with various amino acids were mostly bimodal, and the angle distributions were unimodal. Insights gained from this study have implications for the rational design of safer drugs and commercially important chemicals.     

Fabrication process of open surfaces by robotic fibre placement

Composite materials are being used extensively in many industrial sectors. They offer excellent material properties compared to other structural materials available. However, the traditional fabrication process using manual hand lay-up is time consuming and labour intensive. Therefore, robotic fibre placement has been introduced to overcome these drawbacks. This approach may greatly reduce cycle time and manufacturing costs. This paper describes the overall strategy for the establishment of a flexible robotic fibre placement technique. The fabrication process planning of this new technique is presented. Three different types of fibre placement for open surfaces are discussed. These include simulation-based fibre path generation, fibre steering, and sensory-based contour following methodologies. The system architecture for the process control is also presented.     

Finite element analysis of laminated shells of revolution

A finite element formulation for the analysis of axisymmetric fibre reinforced laminated shells subjected to axisymmetric load is presented. The formulation includes arbitrary number of bonded layers each of which may have different thicknesses, orientation of elastic axes, and elastic properties. Superparamatric curved elements[17] having four degrees of freedom per node including the normal rotation, are used. Stress-strain relation for an arbitrary layer is obtained from the consideration of three dimensional aspect of the problem. The element stiffness matrix has been obtained by using Gauss quadrature numerical integration, even though the elasticity matrix is different for different layers. The formulation is checked for a cylindrical tube subjected to internal pressure and axial tension, and the results are found to compare very well with the elastic solution [9].     

FAST (Flexible Analysis by Software Tool) and CHAMP (CHemico-physical AMinoacidic Parameter data bank): a new tool to investigate protein structure

A flexible package designed to study protein structure is described. The package is devoted to the analysis of protein sequences by drawing structural profiles of specific structure-related amino acid parameters. An Aminoacidic Parameters Data Bank (CHAMP) containing 32 different series of physico-chemical parameters of amino acids is available. Sequences can be loaded from any ASCII format data bank or from keyboard. The program possesses a routine which enables easy updating of the protein data bank and CHAMP Data Bank. FAST reads statistical correlations between two plots in order to identify structural similarities. Plots can be printed, saved or used for correlation, comparison or graph overlap by using common spreadsheets (e.g. Lotus 123). Plots can be smoothed by a running mean or a running median. The program also has a special feature--a global flexibility analysis of proteins. The package runs on IBM or compatibles and requires DOS 3.0 or later.     

Analysing the localisation sites of proteins through neural networks ensembles

Scientists involved in the area of proteomics are currently seeking integrated, customised and validated research solutions to better expedite their work in proteomics analyses and drug discoveries. Some drugs and most of their cell targets are proteins, because proteins dictate biological phenotype. In this context, the automated analysis of protein localisation is more complex than the automated analysis of DNA sequences; nevertheless the benefits to be derived are of same or greater importance. In order to accomplish this target, the right choice of the kind of the methods for these applications, especially when the data set is drastically imbalanced, is very important and crucial. In this paper we investigate the performance of some commonly used classifiers, such as the K nearest neighbours and feed-forward neural networks with and without cross-validation, in a class of imbalanced problems from the bioinformatics domain. Furthermore, we construct ensemble-based schemes using the notion of diversity, and we empirically test their performance on the same problems. The experimental results favour the generation of neural network ensembles as these are able to produce good generalisation ability and significant improvement compared to other single classifier methods.     

基于TPCM的服务器可信PXE启动方法

PXE 启动机制通过网络下载操作系统文件并启动操作系统,广泛应用于服务器网络启动。通过可信计算技术保障PXE启动过程的安全可信,防止PXE启动文件被恶意篡改,确保服务器的安全可信运行。网络安全等级保护标准要求基于可信根对服务器设备的系统引导程序、系统程序等进行可信验证。根据等级保护标准要求,提出一种基于TPCM的服务器可信PXE启动方法,保障服务器的BIOS固件、PXE启动文件、Linux系统文件的安全可信。在服务器进行PXE启动时,由TPCM度量BIOS固件,由BIOS启动环境度量PXE启动文件,由PXE启动环境度量Linux系统文件。以TPCM为信任根逐级度量、逐级信任,建立信任链,建立可信的服务器运行环境。所提方法在国产自主可控申威服务器上进行了实验,实验结果表明所提方法是可行的。