Extracting interactions between proteins from the literature

During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experimental and computational biomedical data have been generated along with new discoveries, which are accompanied by an exponential increase in the number of biomedical publications describing these discoveries. In the meantime, there has been a great interest with scientific communities in text mining tools to find knowledge such as protein-protein interactions, which is most relevant and useful for specific analysis tasks. This paper provides a outline of the various information extraction methods in biomedical domain, especially for discovery of protein-protein interactions. It surveys methodologies involved in plain texts analyzing and processing, categorizes current work in biomedical information extraction, and provides examples of these methods. Challenges in the field are also presented and possible solutions are discussed.

Gold nanoparticles decorated with oligo(ethylene glycol) thiols:protein resistance and colloidal stability

The interactions between proteins and gold colloids functionalized with protein-resistant oligo(ethylene glycol) (OEG) thiol, HS(CH(2))(11) (OCH(2)CH(2))(6)OMe (EG(6)OMe), in aqueous solution have been studied by small-angle X-ray scattering (SAXS) and UV-vis spectroscopy. The mean size, 2R, and the size distribution of the decorated gold colloids have been characterized by SAXS. The monolayer-protected gold colloids have no correlations due to the low volume fraction in solution and are stable in a wide range of temperatures (5-70 degrees C, pH (1.3-12.4), and ionic strength (0-1.0 M). In contrast, protein (bovine serum albumin) solutions with concentrations in the range of 60-200 mg/mL (4.6-14.5 vol show a pronounced correlation peak in SAXS, which results from the repulsive electrostatic interaction between charged proteins. These protein interactions show significant dependence on ionic strength, as would be expected for an electrostatic interaction (Zhang et al. J. Phys. Chem. B 2007, 111, 251). For a mixture of proteins and gold colloids, the protein-protein interaction changes little upon mixing with OEG-decorated gold colloids. In contrast, the colloid-colloid interaction is found to be strongly dependent on the protein concentration and the size of the colloid itself. Adding protein to a colloidal solution results in an attractive depletion interaction between functionalized gold colloids, and above a critical protein concentration, c*, the colloids form aggregates and flocculate. Adding salt to such mixtures enhances the depletion effect and decreases the critical protein concentration. The aggregation is a reversible process (i.e., diluting the solution leads to dissolution of aggregates). The results also indicate that the charge of the OEG self-assembled monolayer at a curved interface has a rather limited effect on the colloidal stabilization and the repulsive interaction with proteins.

The use of erythrocytic and animal models in the study of protein phosphorylation

Phosphorylation processes are common post-transductional mechanisms, by which it is possible to modulate a number of metabolic pathways. Proteins are highly sensitive to phosphorylation, which governs many protein-protein interactions. The enzymatic activity of some protein tyrosine-kinases is under tyrosine-phosphorylation control, as well as several transmembrane anion-fluxes and cation exchanges. In addition, phosphorylation reactions are involved in intra and extra-cellular 'cross-talk' processes. Early studies adopted laboratory animals to study these little known phosphorylation processes. The main difficulty encountered with these animal techniques was obtaining sufficient kinase or phosphatase activity suitable for studying the enzymatic process. Large amounts of biological material from organs, such as the liver and spleen were necessary to conduct such work with protein kinases. Subsequent studies revealed the ubiquity and complexity of phosphorylation processes and techniques evolved from early rat studies to the adaptation of more rewarding in vitro models. These involved human erythrocytes, which are a convenient source both for the enzymes, we investigated and for their substrates. This preliminary work facilitated the development of more advanced phosphorylative models that are based on cell lines. © 2005 Elsevier B.V. All rights reserved.

Receptor for activated C Kinase 1 protein binds to and activates the human estrogen receptor α

The classical concept of estrogen receptor (ER) activation is that steroid passes the cell membrane, binds to its specific protein receptor in the cell's cytoplasm and the steroid-receptor complex travels to the nucleus where it activates responsive genes. This basic idea has been challenged by results of experiments demonstrating insulin-like growth factor 1 (IGF-1) activation of the ER in the complete absence of estrogen suggesting at least one other mechanism of ER activation not involving steroid. One explanation is that activation of the cell surface IGF-1 receptor leads to synthesis of an intracellular protein(s) able to bind to and stimulate the ER. Based on results using the two-hybrid system, coimmunoprecipitation and transfection-luciferase assays, we herein show that one of these proteins could well be receptor for activated C kinase 1 (RACK-1). Using the human ER type α (ER-α) as bait, a cloned complementary deoxyribonucleic acid (cDNA) library from IGF-1 treated human breast cancer MCF-7 cells was screened for ER-α - protein interactions. Many positive clones were obtained which contained the RACK-1 cDNA sequence. Coimmunoprecipitation of in-vitro translation products of the ER-α and RACK-1 confirmed the interaction between the two proteins. Transfection studies using the estrogen response element spliced to a luciferase reporter gene revealed that constitutive RACK-1 expression was able to powerfully stimulate ER-α activity under estrogen-free conditions. This effect could be enhanced by 17β-estradiol (E2) and blocked by tamoxifen, an E2 antagonist. These results show that RACK-1 is able to activate the ER-α in the absence of E2, although together with the latter, enhanced effects occur. Since RACK-1 gene expression is stimulated by IGF-1, it is distinctly possible that RACK-1 is the mediator of the stimulatory effects of IGF-1 on ER-α. © 2014 JMS.

Reversible oxidation of phosphatase and tensin homolog (PTEN) alters its interactions with signaling and regulatory proteins

Phosphatase and tensin homolog (PTEN) is involved in a number of different cellular processes including metabolism, apoptosis, cell proliferation and survival. It is a redox-sensitive dual-specificity protein phosphatase that acts as a tumor suppressor by negatively regulating the PI3K/Akt pathway. While direct evidence of redox regulation of PTEN downstream signaling has been reported, the effect of PTEN redox status on its protein-protein interactions is poorly understood. PTEN-GST in its reduced and a DTT-reversible H2O2-oxidized form was immobilized on a glutathione-sepharose support and incubated with cell lysate to capture interacting proteins. Captured proteins were analyzed by LC-MSMS and comparatively quantified using label-free methods. 97 Potential protein interactors were identified, including a significant number that are novel. The abundance of fourteen interactors was found to vary significantly with the redox status of PTEN. Altered binding to PTEN was confirmed by affinity pull-down and Western blotting for Prdx1, Trx, and Anxa2, while DDB1 was validated as a novel interactor with unaltered binding. These results suggest that the redox status of PTEN causes a functional variation in the PTEN interactome. The resin capture method developed had distinct advantages in that the redox status of PTEN could be directly controlled and measured.

The C-terminus of Raf-1 acts as a 14-3-3-dependent activation switch

The Raf-1 protein kinase is a major activator of the ERK MAPK pathway, which links signaling by a variety of cell surface receptors to the regulation of cell proliferation, survival, differentiation and migration. Signaling by Raf-1 is regulated by a complex and poorly understood interplay between phosphorylation events and protein-protein interactions. One important mode of Raf-1 regulation involves the phosphorylation-dependent binding of 14-3-3 proteins. Here, we have examined the mechanism whereby the C-terminal 14-3-3 binding site of Raf-1, S621, controls the activation of MEK-ERK signaling. We show that phosphorylation of S621 turns over rapidly and is enriched in the activated pool of endogenous Raf-1. The phosphorylation on this site can be mediated by Raf-1 itself but also by other kinase(s). Mutations that prevent the binding of 14-3-3 proteins to S621 render Raf-1 inactive by specifically disrupting its capacity to bind to ATP, and not by gross conformational alteration as indicated by intact MEK binding. Phosphorylation of S621 correlates with the inhibition of Raf-1 catalytic activity in vitro, but 14-3-3 proteins can completely reverse this inhibition. Our findings suggest that 14-3-3 proteins function as critical cofactors in Raf-1 activation, which induce and maintain the protein in a state that is competent for both ATP binding and MEK phosphorylation.

Structure-function analysis of RAMP1 by Alanine Mutagenesis

Receptor activity modifying protein 1 (RAMP1) is an integral component of several receptors including the calcitonin gene-related peptide (CGRP) receptor. It forms a complex with the calcitonin receptor-like receptor (CLR) and is required for receptor trafficking and ligand binding. The N-terminus of RAMP1 comprises three helices. The current study investigated regions of RAMP1 important for CGRP or CLR interactions by alanine mutagenesis. Modeling suggested the second and third helices were important in protein-protein interactions. Most of the conserved residues in the N-terminus (M48, W56, Y66, P85, N66, H97, F101, D113, P114, P115), together with a further 13 residues spread throughout three helices of RAMP1, were mutated to alanine and coexpressed with CLR in Cos 7 cells. None of the mutations significantly reduced RAMP expression. Of the nine mutants from helix 1, only M48A had any effect, producing a modest reduction in trafficking of CLR to the cell surface. In helix 2 Y66A almost completely abolished CLR trafficking; L69A and T73A reduced the potency of CGRP to produce cAMP. In helix 3, H97A abolished CLR trafficking; P85A, N86A, and F101A had caused modest reductions in CLR trafficking and also reduced the potency of CGRP on cAMP production. F93A caused a modest reduction in CLR trafficking alone and L94A increased cAMP production. The data are consistent with a CLR recognition site particularly involving Y66 and H97, with lesser roles for adjacent residues in helix 3. L69 and T73 may contribute to a CGRP recognition site in helix 2 also involving nearby residues.

Functional proteomics to dissect tyrosine kinase signalling pathways in cancer

Advances in the generation and interpretation of proteomics data have spurred a transition from focusing on protein identification to functional analysis. Here we review recent proteomics results that have elucidated new aspects of the roles and regulation of signal transduction pathways in cancer using the epidermal growth factor receptor (EGFR), ERK and breakpoint cluster region (BCR)-ABL1 networks as examples. The emerging theme is to understand cancer signalling as networks of multiprotein machines which process information in a highly dynamic environment that is shaped by changing protein interactions and post-translational modifications (PTMs). Cancerous genetic mutations derange these protein networks in complex ways that are tractable by proteomics.

Cells, surfaces and adhesion

This thesis concerns cell adhesion to polymer surfaces with an experimental emphasis on hydrogels. The thesis begins with a review of the literature and a synthesis of recent evidence to describe the process of cell adhesion in a given situation. The importance of understanding integrin-adhesion protein interactions and adhesion protein-surface interactions is emphasised. The experimental chapters describe three areas of investigation. Firstly, in vitro cell culture techniques are used to explore a variety of surfaces including polyethylene glycol methacrylate (PEGMA) substituted hydrogels, sequence distribution modified hydrogels and worn contact lenses. Cell adhesion to PEGMA substituted gels is found to decrease with increases in polyethylene oxide chain length and correlations are made between sequence distribution and adhesion. Worn contact lenses are investigated for their cell adhesion properties in the presence of antibodies to specific adhesion proteins, demonstrating the presence of vitronectin and fibronectin on the lenses. The second experimental chapter addresses divalent cation regulation of integrin mediated cell adhesion. Several cell types and various cations are used. Zinc, previously not regarded as an important cation in the process, is found to inhibit 3T3 cell adhesion to vitronectin that is promoted by other divalent cations. The final experimental chapter concerns cell adhesion and growth on macroporous hydrogels. A variety of freeze-thaw formed porous gels are investiated and found generally to promote cell growth rate.Interpenetrating networkbased gels (IPN) are made porous by elution of dextrin particles of varying size and loading density. These materials provide the basis for synthetic cartilage. Cartilage cells (chondrocytes) plated onto the surface of the porous IPN materials maintain a rounded shape and hence phenotypic function when a critical pore size and density is achieved. In this way, a prospective implant, made porous at the perpendicular edges contacting natural cartilage can be both mechanically stabilised and encourage the maintenance of normal matrix production at the tissue interface.

Biomedical events extraction using the hidden vector state model

Objective: Biomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein-protein interactions (PPIs) extraction task which often only involves the extraction of binary relations between two proteins, biomedical events extraction is much harder since it needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In this paper, we propose an information extraction system based on the hidden vector state (HVS) model, called HVS-BioEvent, for biomedical events extraction, and investigate its capability in extracting complex events. Methods and material: HVS has been previously employed for extracting PPIs. In HVS-BioEvent, we propose an automated way to generate abstract annotations for HVS training and further propose novel machine learning approaches for event trigger words identification, and for biomedical events extraction from the HVS parse results. Results: Our proposed system achieves an F-score of 49.57% on the corpus used in the BioNLP'09 shared task, which is only 2.38% lower than the best performing system by UTurku in the BioNLP'09 shared task. Nevertheless, HVS-BioEvent outperforms UTurku's system on complex events extraction with 36.57% vs. 30.52% being achieved for extracting regulation events, and 40.61% vs. 38.99% for negative regulation events. Conclusions: The results suggest that the HVS model with the hierarchical hidden state structure is indeed more suitable for complex event extraction since it could naturally model embedded structural context in sentences.

Peptide binding to the HLA-DRB1 supertype:a proteochemometrics analysis

A proteochemometrics approach was applied to a set of 2666 peptides binding to 12 HLA-DRB1 proteins. Sequences of both peptide and protein were described using three z-descriptors. Cross terms accounting for adjacent positions and for every second position in the peptides were included in the models, as well as cross terms for peptide/protein interactions. Models were derived based on combinations of different blocks of variables. These models had moderate goodness of fit, as expressed by r2, which ranged from 0.685 to 0.732; and good cross-validated predictive ability, as expressed by q2, which varied from 0.678 to 0.719. The external predictive ability was tested using a set of 356 HLA-DRB1 binders, which showed an r2(pred) in the range 0.364-0.530. Peptide and protein positions involved in the interactions were analyzed in terms of hydrophobicity, steric bulk and polarity.

Biomedical relation extraction:from binary to complex

Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.

Fluorescent microplate-based analysis of protein-DNA interactions I:immobilized protein

A simple protein-DNA interaction analysis has been developed using a high-affinity/high-specificity zinc finger protein. In essence, purified protein samples are immobilized directly onto the surface of microplate wells, and fluorescently labeled DNA is added in solution. After incubation and washing, bound DNA is detected in a standard microplate reader. The minimum sensitivity of the assay is approximately 0.2 nM DNA. Since the detection of bound DNA is noninvasive and the protein-DNA interaction is not disrupted during detection, iterative readings may be taken from the same well, after successive alterations in interaction conditions, if required. In this respect, the assay may therefore be considered real time and permits appropriate interaction conditions to be determined quantitatively. The assay format is ideally suited to investigate the interactions of purified unlabeled DNA binding proteins in a high-throughput format.

Fluorescent microplate-based analysis of protein-DNA interactions II:immobilized DNA

A simple protein-DNA interaction analysis has been developed using both a high-affinity/high-specificity zinc finger protein and a low-specificity zinc finger protein with nonspecific DNA binding capability. The latter protein is designed to mimic background binding by proteins generated in randomized or shuffled gene libraries. In essence, DNA is immobilized onto the surface of microplate wells via streptavidin capture, and green fluorescent protein (GFP)-labeled protein is added in solution as part of a crude cell lysate or protein mixture. After incubation and washing, bound protein is detected in a standard microplate reader. The minimum sensitivity of the assay is approximately 0.4 nM protein. The assay format is ideally suited to investigate the interactions of DNA binding proteins from within crude cell extracts and/or mixtures of proteins that may be encountered in protein libraries generated by codon randomization or gene shuffling.

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.