Proteins and their interacting partners: an introduction to protein–ligand binding site prediction methods

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Increased vascular O-GlcNAcylation augments reactivity to constrictor stimuli - Vasoactive Peptide Symposium

O-linked N-acetylglucosaminylation (O-GlcNAcylation) plays a role in many aspects of protein function. Whereas elevated O-GlcNAc levels contribute to diabetes-related end-organ damage, O-GlcNAcylation is also physiologically important. Because proteins that play a role in vascular tone regulation can be O-GlcNAcylated, we hypothesized that O-GlcNAcylation increases vascular reactivity to constrictor stimuli, Aortas front male Sprague-Dawley rats and C57BL/6 mice were incubated for 24 hours with vehicle or PugNAc (O-GlcNAcase inhibitor. 100 mu M). PugNAc incubation significantly increased O-GlcNAc proteins, as determined by Western blot. PugNAc also increased vascular contractions to phenylephrine and serotonin, an effect not observed in the presence of N(omega)-nitro-L-arginine methyl ester or in endothelium-denuded vessels. Acetylcholine-induced relaxation. but not that to sodium nitroprusside, was decreased by PugNAc treatment, an effect accompanied by decreased levels of phosphorylated endothelial nitric oxide synthase (eNOS)(Ser-1177) and Akt(Ser-473). Augmented O-GlcNAcylation increases vascular reactivity to constrictor stimuli, possibly due to its effects oil eNOS expression and activity, reinforcing the concept that O-GlcNAcylation modulates vascular reactivity and may play a role in pathological conditions associated with abnormal vascular function. J Am Soc Hypertens 2008:2(6): 410-417. (C) 2008 American Society of Hypertension. All rights reserved.

Mapping the Intramolecular Vibrational Energy Flow in Proteins Reveals Functionally Important Residues

Unveiling the mechanisms of energy relaxation in biomolecules is key to our understanding of protein stability, allostery, intramolecular signaling, and long-lasting quantum coherence phenomena at ambient temperatures. Yet, the relationship between the pathways of energy transfer and the functional role of the residues involved remains largely unknown. Here, we develop a simulation method of mapping out residues that are highly efficient in relaxing an initially localized excess vibrational energy and perform site-directed mutagenesis functional assays to assess the relevance of these residues to protein function. We use the ligand binding domains of thyroid hormone receptor (TR) subtypes as a test case and find that conserved arginines, which are critical to TR transactivation function, are the most effective heat diffusers across the protein structure. These results suggest a hitherto unsuspected connection between a residue`s ability to mediate intramolecular vibrational energy redistribution and its functional relevance.

Metal ions and carcinogenesis

Metals are essential for the normal functioning of living organisms. Their uses in biological systems are varied, but are frequently associated with sites of critical protein function, such as zinc finger motifs and electron or oxygen carriers. These functions only require essential metals in minute amounts, hence they are termed trace metals. Other metals are, however, less beneficial, owing to their ability to promote a wide variety of eleterious health effects, including cancer. Metals such as arsenic, for example, an produce a variety of diseases ranging from keratosis of the palms and feet to cancers in multiple target organs. The nature and type of metal-induced pathologies appear to be dependent on the concentration, speciation, and length of exposure. Unfortunately, human contact with metals is an inescapable consequence of human life, with exposures occurring from both occupational and environmental sources. A uniform mechanism of action for all harmful metals is unlikely, if not implausible, given the diverse chemical properties of each metal. In this chapter we will review the mechanisms of carcinogenesis of arsenic, cadmium, chromium, and nickel, the four known carcinogenic metals that are best understood. The key areas of speciation, bioavailability, and mechanisms of action are discussed with particular reference to the role of metals in alteration of gene expression and maintenance of genomic integrity.

Improving an inverse model of sheet metal forming by neural network based regression

An inverse model for a sheet meta l forming process aims to determine the initial parameter levels required to form the final formed shape. This is a difficult problem that is usually approached by traditional methods such as finite element analysis. Formulating the problem as a classification problem makes it possible to use well established classification algorithms, such as decision trees. Classification is, however, generally based on a winner-takes-all approach when associating the output value with the corresponding class. On the other hand, when formulating the problem as a regression task, all the output values are combined to produce the corresponding class value. For a multi-class problem, this may result in very different associations compared with classification between the output of the model and the corresponding class. Such formulation makes it possible to use well known regression algorithms, such as neural networks. In this paper, we develop a neural network based inverse model of a sheet forming process, and compare its performance with that of a linear model. Both models are used in two modes, classification mode and a function estimation mode, to investigate the advantage of re-formulating the problem as a function estimation. This results in large improvements in the recognition rate of set-up parameters of a sheet metal forming process for both models, with a neural network model achieving much more accurate parameter recognition than a linear model.

High torsional energy disulfides : relationship between cross-strand disulfides and right-handed staples

Redox-active disulfides are capable of being oxidized and reduced under physiological conditions. The enzymatic role of redox-active disulfides in thiol-disulfide reductases is well-known, but redox-active disulfides are also present in non-enzymatic protein structures where they may act as switches of protein function. Here, we examine disulfides linking adjacent β-strands (cross-strand disulfides), which have been reported to be redox-active. Our previous work has established that these cross-strand disulfides have high torsional energies, a quantity likely to be related to the ease with which the disulfide is reduced. We examine the relationship between conformations of disulfides and their location in protein secondary structures. By identifying the overlap between cross-strand disulfides and various conformations, we wish to address whether the high torsional energy of a cross-strand disulfide is sufficient to confer redox activity or whether other factors, such as the presence of the cross-strand disulfide in a strained β-sheet, are required.

Disulfides as redox switches : from molecular mechanisms to functional significance

The molecular mechanisms underlying thiol-based redox control are poorly defined. Disulfide bonds between Cys residues are commonly thought to confer extra rigidity and stability to their resident protein, forming a type of proteinaceous spot weld. Redox biologists have been redefining the role of disulfides over the last 30–40 years. Disulfides are now known to form in the cytosol under conditions of oxidative stress. Isomerization of extracellular disulfides is also emerging as an important regulator of protein function. The current paradigm is that the disulfide proteome consists of two subproteomes: a structural group and a redox-sensitive group. The redoxsensitive group is less stable and often associated with regions of stress in protein structures. Some characterized redox-active disulfides are the helical CXXC motif, often associated with thioredoxin-fold proteins; and forbidden disulfides, a group of metastable disulfides that disobey elucidated rules of protein stereochemistry. Here we discuss the role of redox-active disulfides as switches in proteins.

Transcriptional profiling of growth perturbations of the human malaria parasite Plasmodium falciparum

Functions have yet to be defined for the majority of genes of Plasmodium falciparum, the agent responsible for the most serious form of human malaria. Here we report changes in P. falciparum gene expression induced by 20 compounds that inhibit growth of the schizont stage of the intraerythrocytic development cycle. In contrast with previous studies, which reported only minimal changes in response to chemically induced perturbations of P. falciparum growth, we find that ~59% of its coding genes display over three-fold changes in expression in response to at least one of the chemicals we tested. We use this compendium for guilt-by-association prediction of protein function using an interaction network constructed from gene co-expression, sequence homology, domain-domain and yeast two-hybrid data. The subcellular localizations of 31 of 42 proteins linked with merozoite invasion is consistent with their role in this process, a key target for malaria control. Our network may facilitate identification of novel antimalarial drugs and vaccines.

X-ray crystallography : applications in the biotechnology research

X-ray crystallography is essentially a form of very high resolution microscopy. It enables us to visualize protein structures at the atomic level and enhances our understanding of protein function. Specifically we can study how proteins interact with other molecules, how they undergo conformational changes, and how they perform catalysis in the case of enzymes. Armed with this information we can design novel drugs that target a particular protein, or rationally engineer an enzyme for a specific industrial process.

Glutaredoxin1 protects neuronal cells from copper-induced toxicity

Glutaredoxin1 (GRX1) is a glutathione (GSH)-dependent thiol oxidoreductase. The GRX1/GSH system is important for the protection of proteins from oxidative damage and in the regulation of protein function. Previously we demonstrated that GRX1/GSH regulates the activity of the essential copper-transporting P1B-Type ATPases (ATP7A, ATP7B) in a copper-responsive manner. It has also been established that GRX1 binds copper with high affinity and regulates the redox chemistry of the metallochaperone ATOX1, which delivers copper to the copper-ATPases. In this study, to further define the role of GRX1 in copper homeostasis, we examined the effects of manipulating GRX1 expression on copper homeostasis and cell survival in mouse embryonic fibroblasts and in human neuroblastoma cells (SH-SY5Y). GRX1 knockout led to cellular copper retention (especially when cultured with elevated copper) and reduced copper tolerance, while in GRX1-overexpressing cells challenged with elevated copper, there was a reduction in both intracellular copper levels and copper-induced reactive oxygen species, coupled with enhanced cell proliferation. These effects are consistent with a role for GRX1 in regulating ATP7A-mediated copper export, and further support a new function for GRX1 in neuronal copper homeostasis and in protection from copper-mediated oxidative injury.

Clustering and visualization of failure modes using an evolving tree

Despite the popularity of Failure Mode and Effect Analysis (FMEA) in a wide range of industries, two well-known shortcomings are the complexity of the FMEA worksheet and its intricacy of use. To the best of our knowledge, the use of computation techniques for solving the aforementioned shortcomings is limited. As such, the idea of clustering and visualization pertaining to the failure modes in FMEA is proposed in this paper. A neural network visualization model with an incremental learning feature, i.e., the evolving tree (ETree), is adopted to allow the failure modes in FMEA to be clustered and visualized as a tree structure. In addition, the ideas of risk interval and risk ordering for different groups of failure modes are proposed to allow the failure modes to be ordered, analyzed, and evaluated in groups. The main advantages of the proposed method lie in its ability to transform failure modes in a complex FMEA worksheet to a tree structure for better visualization, while maintaining the risk evaluation and ordering features. It can be applied to the conventional FMEA methodology without requiring additional information or data. A real world case study in the edible bird nest industry in Sarawak (Borneo Island) is used to evaluate the usefulness of the proposed method. The experiments show that the failure modes in FMEA can be effectively visualized through the tree structure. A discussion with FMEA users engaged in the case study indicates that such visualization is helpful in comprehending and analyzing the respective failure modes, as compared with those in an FMEA table. The resulting tree structure, together with risk interval and risk ordering, provides a quick and easily understandable framework to elucidate important information from complex FMEA forms; therefore facilitating the decision-making tasks by FMEA users. The significance of this study is twofold, viz., the use of a computational visualization approach to tackling two well-known shortcomings of FMEA; and the use of ETree as an effective neural network learning paradigm to facilitate FMEA implementations. These findings aim to spearhead the potential adoption of FMEA as a useful and usable risk evaluation and management tool by the wider community.

What causes violent crime?

This study uses a new data set of crime ratesfor a large sample of countriesfor the period 1970- 1994, based on information from the United Nations World Crime Surveys, to ana/yze the determinants ofnational homicide and robbery rates. A simple model of the incentives to commit crimes is proposed, which explicit/y considers possible causes of the persistence of crime over time (criminal inertia). Several econometric mode/s are estimated, attempting to capture the . determinonts of crime rates across countries and over time. The empirical mode/s are first run for cross-sections and then applie'd to panel data. The former focus on erplanatory variables that do not change markedly over time, while the panel data techniques consider both the eflect of the business cyc1e (i.e., GDP growth rate) on the crime rate and criminal inertia (accountedfor by the inclusion of the /agged crime rate as an explanatory variable). The panel data techniques a/so consider country-specific eflects, the joint endogeneity of some of the erplanatory variables, and lhe existence of some types of measurement e"ors aJjlicting the crime data. The results showthat increases in income inequality raise crime rates, dete"ence eflects are significant, crime tends to be counter-cyclical, and criminal inertia is significant even after controlling for other potential determinants of homicide and robbery rates.

Gene Mutations and Polymorphisms of TP53 and FHIT in Chronic Esophagitis and Esophageal Carcinoma

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Interfacial fracture of dentin adhesively bonded to quartz-fiber reinforced composite

The paper presents the results of an experimental study of interfacial failure in a multilayered structure consisting of a dentin/resin cement/quartz-fiber reinforced composite (FRC). Slices of dentin close to the pulp chamber were sandwiched by two half-circle discs made of a quartz-fiber reinforced composite, bonded with bonding agent (All-bond 2, BISCO, Schaumburg) and resin cement (Duo-link. BISCO, Schaumburg) to make Brazil-nut sandwich specimens for interfacial toughness testing. Interfacial fracture toughness (strain energy release rate, G) was measured as a function of mode mixity by changing loading angles from 0 degrees to 15 degrees. The interfacial fracture surfaces were then examined using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX) to determine the failure modes when loading angles changed. A computational model was also developed to calculate the driving forces, stress intensity factors and mode mixities. Interfacial toughness increased from approximate to 1.5 to 3.2 J/m(2) when the loading angle increases from approximate to 0, 0 to 15 degrees. The hybridized dentin/cement interface appeared to be tougher than the resin cement/quartz-fiber reinforced epoxy. The Brazil-nut sandwich specimen was a suitable method to investigate the mechanical integrity of dentin/cement/FRC interfaces. (C) 2011 Elsevier B.V. All rights reserved.

Apoptose em otorrinolaringologia e cabeça e pescoço

This paper intend to review recent advances in our understanding of programmed cell death, or apoptosis, and discuss implications of these basic science advances in the development of causes and potential treatments of a variety of diseases of the head and neck. Conclusions: apoptosis is now understood to be important in the normal development and survival of all multicellular organism. Deregulation of this normally tighly controlled process underlies a variety of disease states, including neoplasia, autoimmune disease, and disorders of the central nervous system. A better understanding of this process and regulation may help otolaryngologists better understand diseases relevant to this specialty and will lead to improved therapeutic interventions.