Immunological protein-protein interactions:a critical reflection

Life, and the biochemistry of which it is ultimately comprised, is built from the interactions of proteins, and the study of protein-protein interactions is fast becoming a central feature of molecular bioscience. This is as true of immunobiology as it is of other areas of the wider biological milieu. Protein-protein interactions within an immunological setting comprise both the kind familiar from other areas of biology and instantiations of protein-protein interactions special to the immune arena. Of the generic kind of protein-protein interaction, co-stimulatory receptors, such as CD28, and the interaction of accessory proteins, such as CD4 or CD8, are amongst the most prevalent and apposite of examples. The key examples of special immunological instantiations of protein-protein interactions are the binding of antigens by antibodies and the formation of peptide-MHC-TCR complexes; both prime examples of vital molecular recognition events mediated by protein-protein interactions. In this brief review, and within the context of this burgeoning field, we examine immunological protein-protein interactions, focussing on the problematic nature of defining such interactions. © 2011 by Nova Science Publishers, Inc. All rights reserved.

Accurate estimation of isoelectric point of protein and peptide based on amino acid sequences

Motivation: In any macromolecular polyprotic system - for example protein, DNA or RNA - the isoelectric point - commonly referred to as the pI - can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge - and thus the electrophoretic mobility - of the ampholyte sums to zero. Different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Protein separation by isoelectric point is a critical part of 2-D gel electrophoresis, a key precursor of proteomics, where discrete spots can be digested in-gel, and proteins subsequently identified by analytical mass spectrometry. Peptide fractionation according to their pI is also widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. Therefore accurate theoretical prediction of pI would expedite such analysis. While such pI calculation is widely used, it remains largely untested, motivating our efforts to benchmark pI prediction methods. Results: Using data from the database PIP-DB and one publically available dataset as our reference gold standard, we have undertaken the benchmarking of pI calculation methods. We find that methods vary in their accuracy and are highly sensitive to the choice of basis set. The machine-learning algorithms, especially the SVM-based algorithm, showed a superior performance when studying peptide mixtures. In general, learning-based pI prediction methods (such as Cofactor, SVM and Branca) require a large training dataset and their resulting performance will strongly depend of the quality of that data. In contrast with Iterative methods, machine-learning algorithms have the advantage of being able to add new features to improve the accuracy of prediction. Contact: yperez@ebi.ac.uk Availability and Implementation: The software and data are freely available at https://github.com/ypriverol/pIR. Supplementary information: Supplementary data are available at Bioinformatics online.

PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.

Specific binding of the mammalian high mobility group protein AT-hook 2 to the minor groove of AT -rich DNAs: Thermodynamic and specificity studies

The mammalian high mobility group protein AT-hook 2 (HMGA2) is a small transcriptional factor involved in cell development and oncogenesis. It contains three "AT-hook" DNA binding domains, which specifically recognize the minor groove of AT-rich DNA sequences. It also has an acidic C-terminal motif. Previous studies showed that HMGA2 mediates all its biological effects through interactions with AT-rich DNA sequences in the promoter regions. In this dissertation, I used a variety of biochemical and biophysical methods to examine the physical properties of HMGA2 and to further investigate HMGA2's interactions with AT-rich DNA sequences. The following are three avenues perused in this study: (1) due to the asymmetrical charge distribution of HMGA2, I have developed a rapid procedure to purify HMGA2 in the milligram range. Preparation of large amounts of HMGA2 makes biophysical studies possible; (2) Since HMGA2 binds to different AT-rich sequences in the promoter regions, I used a combination of isothermal titration calorimetry (ITC) and DNA UV melting experiment to characterize interactions of HMGA2 with poly(dA-dT) 2 and poly(dA)poly(dT). My results demonstrated that (i) each HMGA2 molecule binds to 15 AT bp; (ii) HMGA2 binds to both AT DNAs with very high affinity. However, the binding reaction of HMGA2 to poly(dA-dT) 2 is enthalpy-driven and the binding reaction of HMGA2 with poly(dA)poly(dT) is entropy-driven; (iii) the binding reactions are strongly depended on salt concentrations; (3) Previous studies showed that HMGA2 may have sequence specificity. In this study, I used a PCR-based SELEX procedure to examine the DNA binding specificity of HMGA2. Two consensus sequences for HMGA2 have been identified: 5'-ATATTCGCGAWWATT-3' and 5'-ATATTGCGCAWWATT-3', where W represents A or T. These consensus sequences have a unique feature: the first five base pairs are AT-rich, the middle four to five base pairs are GC-rich, and the last five to six base pairs are AT-rich. All three segments are critical for high affinity binding. Replacing either one of the AT-rich sequences to a non-AT-rich sequence causes at least 100-fold decrease in the binding affinity. Intriguingly, if the GC-segment is substituted by an AT-rich segment, the binding affinity of HMGA2 is reduced approximately 5-fold. Identification of the consensus sequences for HMGA2 represents an important step towards finding its binding sites within the genome.

Insight into determinants of substrate binding and transport in a multidrug efflux protein

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that 'aromatic clamps' formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such 'clamps' may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.

Prediction of peptide and protein propensity for amyloid formation

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

Genes involved in germline regulative pathways in metazoa: an integrative approach to investigate a key feature of animal biology

In Metazoa, the germline represents the cell lineage devoted to transmission of genetic heredity across generations. Its functions intuitively evoke the crucial roles that it plays in the development of a new organism and in the evolution of the species. Germline establishment is tightly tied to animal multicellularity itself, in which the complex differentiation of cell lineages is favoured by the confinement of totipotency in specific cell populations. In the present thesis, I addressed the subject of germline characterization in animals through different approaches, in an attempt to cover different sides and scales. First, I investigated the extent and nature of shared differentially transcribed molecular factors in 10 different species germline-related lineages. I observed that newly evolved genes are less likely to be involved in germline-related mechanisms and that the mostly shared transcriptional signal across the species considered was the upregulation of genes associated to proper DNA replication, instead of the expected transcriptional and post-transcriptional regulation, that apparently have a higher level of lineage-specificity. I then focused on the evolutionary history of Tudor domain containing proteins, a gene family that underwent germline-associated expansions in animals. Using data from 24 holozoan phyla, I could confirm the previously proposed evolution of the Tudor domain secondary structure. Also, I associated lineage-specific family reductions and expansions to peculiar genomic dynamics and to the evolution of germline-associated piRNA pathway of retrotransposon silencing. Lastly, I characterized and investigated the expression of the Tudor protein TDRD7 in the clam Ruditapes philippinarum. Through immunolocalization, I could compare its expression profiles in gametogenic specimens to the previously characterized germline marker vasa. Combining results with literature, I proposed that, in this species, TDRD7 is involved in the assembly of germ granules, i.e. cytoplasmic structures associated to germline differentiation in virtually all animals, but whose assemblers can be taxon specific.

Taurine Supplementation Increases K(atp) Channel Protein Content, Improving Ca2+ Handling And Insulin Secretion In Islets From Malnourished Mice Fed On A High-fat Diet.

Pancreatic β-cells are highly sensitive to suboptimal or excess nutrients, as occurs in protein-malnutrition and obesity. Taurine (Tau) improves insulin secretion in response to nutrients and depolarizing agents. Here, we assessed the expression and function of Cav and KATP channels in islets from malnourished mice fed on a high-fat diet (HFD) and supplemented with Tau. Weaned mice received a normal (C) or a low-protein diet (R) for 6 weeks. Half of each group were fed a HFD for 8 weeks without (CH, RH) or with 5% Tau since weaning (CHT, RHT). Isolated islets from R mice showed lower insulin release with glucose and depolarizing stimuli. In CH islets, insulin secretion was increased and this was associated with enhanced KATP inhibition and Cav activity. RH islets secreted less insulin at high K(+) concentration and showed enhanced KATP activity. Tau supplementation normalized K(+)-induced secretion and enhanced glucose-induced Ca(2+) influx in RHT islets. R islets presented lower Ca(2+) influx in response to tolbutamide, and higher protein content and activity of the Kir6.2 subunit of the KATP. Tau increased the protein content of the α1.2 subunit of the Cav channels and the SNARE proteins SNAP-25 and Synt-1 in CHT islets, whereas in RHT, Kir6.2 and Synt-1 proteins were increased. In conclusion, impaired islet function in R islets is related to higher content and activity of the KATP channels. Tau treatment enhanced RHT islet secretory capacity by improving the protein expression and inhibition of the KATP channels and enhancing Synt-1 islet content.

A Putative Otu Domain-containing Protein 1 Deubiquitinating Enzyme Is Differentially Expressed In Thyroid Cancer And Identifies Less-aggressive Tumours.

This study aimed to identify novel biomarkers for thyroid carcinoma diagnosis and prognosis. We have constructed a human single-chain variable fragment (scFv) antibody library that was selected against tumour thyroid cells using the BRASIL method (biopanning and rapid analysis of selective interactive ligands) and phage display technology. One highly reactive clone, scFv-C1, with specific binding to papillary thyroid tumour proteins was confirmed by ELISA, which was further tested against a tissue microarray that comprised of 229 thyroid tissues, including: 110 carcinomas (38 papillary thyroid carcinomas (PTCs), 42 follicular carcinomas, 30 follicular variants of PTC), 18 normal thyroid tissues, 49 nodular goitres (NG) and 52 follicular adenomas. The scFv-C1 was able to distinguish carcinomas from benign lesions (P=0.0001) and reacted preferentially against T1 and T2 tumour stages (P=0.0108). We have further identified an OTU domain-containing protein 1, DUBA-7 deubiquitinating enzyme as the scFv-binding antigen using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. The strategy of screening and identifying a cell-surface-binding antibody against thyroid tissues was highly effective and resulted in a useful biomarker that recognises malignancy among thyroid nodules and may help identify lower-risk cases that can benefit from less-aggressive management.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

The Effect Of Celastrol, A Triterpene With Antitumorigenic Activity, On Conformational And Functional Aspects Of The Human 90kda Heat Shock Protein Hsp90α, A Chaperone Implicated In The Stabilization Of The Tumor Phenotype.

Hsp90 is a molecular chaperone essential for cell viability in eukaryotes that is associated with the maturation of proteins involved in important cell functions and implicated in the stabilization of the tumor phenotype of various cancers, making this chaperone a notably interesting therapeutic target. Celastrol is a plant-derived pentacyclic triterpenoid compound with potent antioxidant, anti-inflammatory and anticancer activities; however, celastrol's action mode is still elusive. In this work, we investigated the effect of celastrol on the conformational and functional aspects of Hsp90α. Interestingly, celastrol appeared to target Hsp90α directly as the compound induced the oligomerization of the chaperone via the C-terminal domain as demonstrated by experiments using a deletion mutant. The nature of the oligomers was investigated by biophysical tools demonstrating that a two-fold excess of celastrol induced the formation of a decameric Hsp90α bound throughout the C-terminal domain. When bound, celastrol destabilized the C-terminal domain. Surprisingly, standard chaperone functional investigations demonstrated that neither the in vitro chaperone activity of protecting against aggregation nor the ability to bind a TPR co-chaperone, which binds to the C-terminus of Hsp90α, were affected by celastrol. Celastrol interferes with specific biological functions of Hsp90α. Our results suggest a model in which celastrol binds directly to the C-terminal domain of Hsp90α causing oligomerization. However, the ability to protect against protein aggregation (supported by our results) and to bind to TPR co-chaperones are not affected by celastrol. Therefore celastrol may act primarily by inducing specific oligomerization that affects some, but not all, of the functions of Hsp90α. To the best of our knowledge, this study is the first work to use multiple probes to investigate the effect that celastrol has on the stability and oligomerization of Hsp90α and on the binding of this chaperone to Tom70. This work provides a novel mechanism by which celastrol binds Hsp90α.

Treadmill Training Increases Sirt-1 And Pgc-1 α Protein Levels And Ampk Phosphorylation In Quadriceps Of Middle-aged Rats In An Intensity-dependent Manner.

The present study investigated the effects of running at 0.8 or 1.2 km/h on inflammatory proteins (i.e., protein levels of TNF- α , IL-1 β , and NF- κ B) and metabolic proteins (i.e., protein levels of SIRT-1 and PGC-1 α , and AMPK phosphorylation) in quadriceps of rats. Male Wistar rats at 3 (young) and 18 months (middle-aged rats) of age were divided into nonexercised (NE) and exercised at 0.8 or 1.2 km/h. The rats were trained on treadmill, 50 min per day, 5 days per week, during 8 weeks. Forty-eight hours after the last training session, muscles were removed, homogenized, and analyzed using biochemical and western blot techniques. Our results showed that: (a) running at 0.8 km/h decreased the inflammatory proteins and increased the metabolic proteins compared with NE rats; (b) these responses were lower for the inflammatory proteins and higher for the metabolic proteins in young rats compared with middle-aged rats; (c) running at 1.2 km/h decreased the inflammatory proteins and increased the metabolic proteins compared with 0.8 km/h; (d) these responses were similar between young and middle-aged rats when trained at 1.2 km. In summary, the age-related increases in inflammatory proteins, and the age-related declines in metabolic proteins can be reversed and largely improved by treadmill training.

Reduced Insulin Clearance And Lower Insulin-degrading Enzyme Expression In The Liver Might Contribute To The Thrifty Phenotype Of Protein-restricted Mice.

Nutrient restriction during the early stages of life usually leads to alterations in glucose homeostasis, mainly insulin secretion and sensitivity, increasing the risk of metabolic disorders in adulthood. Despite growing evidence regarding the importance of insulin clearance during glucose homeostasis in health and disease, no information exists about this process in malnourished animals. Thus, in the present study, we aimed to determine the effect of a nutrient-restricted diet on insulin clearance using a model in which 30-d-old C57BL/6 mice were exposed to a protein-restricted diet for 14 weeks. After this period, we evaluated many metabolic variables and extracted pancreatic islet, liver, gastrocnemius muscle (GCK) and white adipose tissue samples from the control (normal-protein diet) and restricted (low-protein diet, LP) mice. Insulin concentrations were determined using RIA and protein expression and phosphorylation by Western blot analysis. The LP mice exhibited lower body weight, glycaemia, and insulinaemia, increased glucose tolerance and altered insulin dynamics after the glucose challenge. The improved glucose tolerance could partially be explained by an increase in insulin sensitivity through the phosphorylation of the insulin receptor/protein kinase B and AMP-activated protein kinase/acetyl-CoA carboxylase in the liver, whereas the changes in insulin dynamics could be attributed to reduced insulin secretion coupled with reduced insulin clearance and lower insulin-degrading enzyme (IDE) expression in the liver and GCK. In summary, protein-restricted mice not only produce and secrete less insulin, but also remove and degrade less insulin. This phenomenon has the double benefit of sparing insulin while prolonging and potentiating its effects, probably due to the lower expression of IDE in the liver, possibly with long-term consequences.

Ghost Cells In Pilomatrixoma, Craniopharyngioma, And Calcifying Cystic Odontogenic Tumor: Histological, Immunohistochemical, And Ultrastructural Study.

Pilomatrixoma, craniopharyngioma, and calcifying cystic odontogenic tumor are the main entities presenting ghost cells as an important histological feature, in spite their quite different clinical presentation; it seems that they share a common pathway in the formation of these cells. The aim of this study is to examine and compare the characteristics of ghost and other cells that form these lesions. Forty-three cases including 21 pilomatrixomas, 14 craniopharyngiomas, and eight calcifying cystic odontogenic tumors were evaluated by immunohistochemistry for cytokeratins, CD138, β-catenin, D2-40, Glut-1, FAS, CD10 and also by scanning electron microscopy. The CKs, CD138, β-catenin, Glut-1, FAS, and CD10 were more often expressed by transitional cells of craniopharyngioma and calcifying cystic odontogenic tumor, compared with pilomatrixoma. Basaloid cells of pilomatrixoma showed strong positivity for CD138 and CD10. Differences on expression pattern were identified in transitional and basal cells, as ghost cells were negative for most antibodies used, except by low expression for cytokeratins. By scanning electron microscopy, the morphology of ghost cells were similar in their fibrillar cytoplasm, but their pattern varied from sheets in pilomatrixoma to small clusters in craniopharyngioma and calcifying cystic odontogenic tumor. Mechanisms involved in formation of ghost cells are unknown, but probably they follow different pathways as protein expression in the basal/transitional cells was not uniform in the three tumors studied.