The protein interaction map of bacteriophage lambda

PubMed Central

2011-01-01

Background Bacteriophage lambda is a model phage for most other dsDNA phages and has been studied for over 60 years. Although it is probably the best-characterized phage there are still about 20 poorly understood open reading frames in its 48-kb genome. For a complete understanding we need to know all interactions among its proteins. We have manually curated the lambda literature and compiled a total of 33 interactions that have been found among lambda proteins. We set out to find out how many protein-protein interactions remain to be found in this phage. Results In order to map lambda's interactions, we have cloned 68 out of 73 lambda open reading frames (the "ORFeome") into Gateway vectors and systematically tested all proteins for interactions using exhaustive array-based yeast two-hybrid screens. These screens identified 97 interactions. We found 16 out of 30 previously published interactions (53%). We have also found at least 18 new plausible interactions among functionally related proteins. All previously found and new interactions are combined into structural and network models of phage lambda. Conclusions Phage lambda serves as a benchmark for future studies of protein interactions among phage, viruses in general, or large protein assemblies. We conclude that we could not find all the known interactions because they require chaperones, post-translational modifications, or multiple proteins for their interactions. The lambda protein network connects 12 proteins of unknown function with well characterized proteins, which should shed light on the functional associations of these uncharacterized proteins. PMID:21943085

The "sweet" side of the protein corona: effects of glycosylation on nanoparticle-cell interactions.

PubMed

Wan, Sha; Kelly, Philip M; Mahon, Eugene; Stöckmann, Henning; Rudd, Pauline M; Caruso, Frank; Dawson, Kenneth A; Yan, Yan; Monopoli, Marco P

2015-02-24

The significance of a protein corona on nanoparticles in modulating particle properties and their biological interactions has been widely acknowledged. The protein corona is derived from proteins in biological fluids, many of which are glycosylated. To date, the glycans on the proteins have been largely overlooked in studies of nanoparticle-cell interactions. In this study, we demonstrate that glycosylation of the protein corona plays an important role in maintaining the colloidal stability of nanoparticles and influences nanoparticle-cell interactions. The removal of glycans from the protein corona enhances cell membrane adhesion and cell uptake of nanoparticles in comparison with the fully glycosylated form, resulting in the generation of a pro-inflammatory milieu by macrophages. This study highlights that the post-translational modification of proteins can significantly impact nanoparticle-cell interactions by modulating the protein corona properties.

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

The interactions of peripheral membrane proteins with biological membranes

DOE PAGES

Johs, Alexander; Whited, A. M.

2015-07-29

The interactions of peripheral proteins with membrane surfaces are critical to many biological processes, including signaling, recognition, membrane trafficking, cell division and cell structure. On a molecular level, peripheral membrane proteins can modulate lipid composition, membrane dynamics and protein-protein interactions. Biochemical and biophysical studies have shown that these interactions are in fact highly complex, dominated by several different types of interactions, and have an interdependent effect on both the protein and membrane. Here we examine three major mechanisms underlying the interactions between peripheral membrane proteins and membranes: electrostatic interactions, hydrophobic interactions, and fatty acid modification of proteins. While experimental approachesmore » continue to provide critical insights into specific interaction mechanisms, emerging bioinformatics resources and tools contribute to a systems-level picture of protein-lipid interactions. Through these recent advances, we begin to understand the pivotal role of protein-lipid interactions underlying complex biological functions at membrane interfaces.« less

Using Förster-Resonance Energy Transfer to Measure Protein Interactions Between Bcl-2 Family Proteins on Mitochondrial Membranes.

PubMed

Pogmore, Justin P; Pemberton, James M; Chi, Xiaoke; Andrews, David W

2016-01-01

The Bcl-2 family of proteins regulates the process of mitochondrial outer membrane permeabilization, causing the release of cytochrome c and committing a cell to apoptosis. The majority of the functional interactions between these proteins occur at, on, or within the mitochondrial outer membrane, complicating structural studies of the proteins and complexes. As a result most in vitro studies of these protein-protein interactions use truncated proteins and/or detergents which can cause artificial interactions. Herein, we describe a detergent-free, fluorescence-based, in vitro technique to study binding between full-length recombinant Bcl-2 family proteins, particularly cleaved BID (cBID) and BCL-XL, on the membranes of purified mitochondria.

Oligomerisation status and evolutionary conservation of interfaces of protein structural domain superfamilies.

PubMed

Sukhwal, Anshul; Sowdhamini, Ramanathan

2013-07-01

Protein-protein interactions are important in carrying out many biological processes and functions. These interactions may be either permanent or of temporary nature. Several studies have employed tools like solvent accessibility and graph theory to identify these interactions, but still more studies need to be performed to quantify and validate them. Although we now have many databases available with predicted and experimental results on protein-protein interactions, we still do not have many databases which focus on providing structural details of the interacting complexes, their oligomerisation state and homologues. In this work, protein-protein interactions have been thoroughly investigated within the structural regime and quantified for their strength using calculated pseudoenergies. The PPCheck server, an in-house webserver, has been used for calculating the pseudoenergies like van der Waals, hydrogen bonds and electrostatic energy based on distances between atoms of amino acids from two interacting proteins. PPCheck can be visited at . Based on statistical data, as obtained by studying established protein-protein interacting complexes from earlier studies, we came to a conclusion that an average protein-protein interface consisted of about 51 to 150 amino acid residues and the generalized energy per residue ranged from -2 kJ mol(-1) to -6 kJ mol(-1). We found that some of the proteins have an exceptionally higher number of amino acids at the interface and it was purely because of their elaborate interface or extended topology i.e. some of their secondary structure regions or loops were either inter-mixing or running parallel to one another or they were taking part in domain swapping. Residue networks were prepared for all the amino acids of the interacting proteins involved in different types of interactions (like van der Waals, hydrogen-bonding, electrostatic or intramolecular interactions) and were analysed between the query domain-interacting partner pair and its remote homologue-interacting partner pair. We found that, in exceptional cases, homologous proteins belonging to the same superfamily, but with remote sequence similarity, can share similar interfaces.

Identification of host proteins, Spata3 and Dkk2, interacting with Toxoplasma gondii micronemal protein MIC3.

PubMed

Wang, Yifan; Fang, Rui; Yuan, Yuan; Pan, Ming; Hu, Min; Zhou, Yanqin; Shen, Bang; Zhao, Junlong

2016-07-01

As an obligate intracellular protozoan, Toxoplasma gondii is a successful pathogen infecting a variety of animals, including humans. As an adhesin involving in host invasion, the micronemal protein MIC3 plays important roles in host cell attachment, as well as modulation of host EGFR signaling cascade. However, the specific host proteins that interact with MIC3 are unknown and the identification of such proteins will increase our understanding of how MIC3 exerts its functions. This study was designed to identify host proteins interacting with MIC3 by yeast two-hybrid screens. Using MIC3 as bait, a library expressing mouse proteins was screened, uncovering eight mouse proteins that showed positive interactions with MIC3. Two of which, spermatogenesis-associated protein 3 (Spata3) and dickkopf-related protein 2 (Dkk2), were further confirmed to interact with MIC3 by additional protein-protein interaction tests. The results also revealed that the tandem repeat EGF domains of MIC3 were critical in mediating the interactions with the identified host proteins. This is the first study to show that MIC3 interacts with host proteins that are involved in reproduction, growth, and development. The results will provide a clearer understanding of the functions of adhesion-associated micronemal proteins in T. gondii.

Interaction of Proteins Identified in Human Thyroid Cells

PubMed Central

Pietsch, Jessica; Riwaldt, Stefan; Bauer, Johann; Sickmann, Albert; Weber, Gerhard; Grosse, Jirka; Infanger, Manfred; Eilles, Christoph; Grimm, Daniela

2013-01-01

Influence of gravity forces on the regulation of protein expression by healthy and malignant thyroid cells was studied with the aim to identify protein interactions. Western blot analyses of a limited number of proteins suggested a time-dependent regulation of protein expression by simulated microgravity. After applying free flow isoelectric focusing and mass spectrometry to search for differently expressed proteins by thyroid cells exposed to simulated microgravity for three days, a considerable number of candidates for gravi-sensitive proteins were detected. In order to show how proteins sensitive to microgravity could directly influence other proteins, we investigated all polypeptide chains identified with Mascot scores above 100, looking for groups of interacting proteins. Hence, UniProtKB entry numbers of all detected proteins were entered into the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and processed. The program indicated that we had detected various groups of interacting proteins in each of the three cell lines studied. The major groups of interacting proteins play a role in pathways of carbohydrate and protein metabolism, regulation of cell growth and cell membrane structuring. Analyzing these groups, networks of interaction could be established which show how a punctual influence of simulated microgravity may propagate via various members of interaction chains. PMID:23303277

Diversity in Genetic In Vivo Methods for Protein-Protein Interaction Studies: from the Yeast Two-Hybrid System to the Mammalian Split-Luciferase System

PubMed Central

Stynen, Bram; Tournu, Hélène; Tavernier, Jan

2012-01-01

Summary: The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays. PMID:22688816

Studies of Dynamic Protein-Protein Interactions in Bacteria Using Renilla Luciferase Complementation Are Undermined by Nonspecific Enzyme Inhibition

PubMed Central

Hatzios, Stavroula K.; Ringgaard, Simon; Davis, Brigid M.; Waldor, Matthew K.

2012-01-01

The luciferase protein fragment complementation assay is a powerful tool for studying protein-protein interactions. Two inactive fragments of luciferase are genetically fused to interacting proteins, and when these two proteins interact, the luciferase fragments can reversibly associate and reconstitute enzyme activity. Though this technology has been used extensively in live eukaryotic cells, split luciferase complementation has not yet been applied to studies of dynamic protein-protein interactions in live bacteria. As proof of concept and to develop a new tool for studies of bacterial chemotaxis, fragments of Renilla luciferase (Rluc) were fused to the chemotaxis-associated response regulator CheY3 and its phosphatase CheZ in the enteric pathogen Vibrio cholerae. Luciferase activity was dependent on the presence of both CheY3 and CheZ fusion proteins, demonstrating the specificity of the assay. Furthermore, enzyme activity was markedly reduced in V. cholerae chemotaxis mutants, suggesting that this approach can measure defects in chemotactic signaling. However, attempts to measure changes in dynamic CheY3-CheZ interactions in response to various chemoeffectors were undermined by nonspecific inhibition of the full-length luciferase. These observations reveal an unexpected limitation of split Rluc complementation that may have implications for existing data and highlight the need for great caution when evaluating small molecule effects on dynamic protein-protein interactions using the split luciferase technology. PMID:22905225

Studies of dynamic protein-protein interactions in bacteria using Renilla luciferase complementation are undermined by nonspecific enzyme inhibition.

PubMed

Hatzios, Stavroula K; Ringgaard, Simon; Davis, Brigid M; Waldor, Matthew K

2012-01-01

The luciferase protein fragment complementation assay is a powerful tool for studying protein-protein interactions. Two inactive fragments of luciferase are genetically fused to interacting proteins, and when these two proteins interact, the luciferase fragments can reversibly associate and reconstitute enzyme activity. Though this technology has been used extensively in live eukaryotic cells, split luciferase complementation has not yet been applied to studies of dynamic protein-protein interactions in live bacteria. As proof of concept and to develop a new tool for studies of bacterial chemotaxis, fragments of Renilla luciferase (Rluc) were fused to the chemotaxis-associated response regulator CheY3 and its phosphatase CheZ in the enteric pathogen Vibrio cholerae. Luciferase activity was dependent on the presence of both CheY3 and CheZ fusion proteins, demonstrating the specificity of the assay. Furthermore, enzyme activity was markedly reduced in V. cholerae chemotaxis mutants, suggesting that this approach can measure defects in chemotactic signaling. However, attempts to measure changes in dynamic CheY3-CheZ interactions in response to various chemoeffectors were undermined by nonspecific inhibition of the full-length luciferase. These observations reveal an unexpected limitation of split Rluc complementation that may have implications for existing data and highlight the need for great caution when evaluating small molecule effects on dynamic protein-protein interactions using the split luciferase technology.

A protein interaction network analysis for yeast integral membrane protein.

PubMed

Shi, Ming-Guang; Huang, De-Shuang; Li, Xue-Ling

2008-01-01

Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

Visualization of protein interactions in living Drosophila embryos by the bimolecular fluorescence complementation assay.

PubMed

Hudry, Bruno; Viala, Séverine; Graba, Yacine; Merabet, Samir

2011-01-28

Protein interactions control the regulatory networks underlying developmental processes. The understanding of developmental complexity will, therefore, require the characterization of protein interactions within their proper environment. The bimolecular fluorescence complementation (BiFC) technology offers this possibility as it enables the direct visualization of protein interactions in living cells. However, its potential has rarely been applied in embryos of animal model organisms and was only performed under transient protein expression levels. Using a Hox protein partnership as a test case, we investigated the suitability of BiFC for the study of protein interactions in the living Drosophila embryo. Importantly, all BiFC parameters were established with constructs that were stably expressed under the control of endogenous promoters. Under these physiological conditions, we showed that BiFC is specific and sensitive enough to analyse dynamic protein interactions. We next used BiFC in a candidate interaction screen, which led to the identification of several Hox protein partners. Our results establish the general suitability of BiFC for revealing and studying protein interactions in their physiological context during the rapid course of Drosophila embryonic development.

Analysis of protein interactions within the cytokinin-signaling pathway of Arabidopsis thaliana.

PubMed

Dortay, Hakan; Mehnert, Nijuscha; Bürkle, Lukas; Schmülling, Thomas; Heyl, Alexander

2006-10-01

The signal of the plant hormone cytokinin is perceived by membrane-located sensor histidine kinases and transduced by other members of the plant two-component system. In Arabidopsis thaliana, 28 two-component system proteins (phosphotransmitters and response regulators) act downstream of three receptors, transmitting the signal from the membrane to the nucleus and modulating the cellular response. Although the principal signaling mechanism has been elucidated, redundancy in the system has made it difficult to understand which of the many components interact to control the downstream biological processes. Here, we present a large-scale interaction study comprising most members of the Arabidopsis cytokinin signaling pathway. Using the yeast two-hybrid system, we detected 42 new interactions, of which more than 90% were confirmed by in vitro coaffinity purification. There are distinct patterns of interaction between protein families, but only a few interactions between proteins of the same family. An interaction map of this signaling pathway shows the Arabidopsis histidine phosphotransfer proteins as hubs, which interact with members from all other protein families, mostly in a redundant fashion. Domain-mapping experiments revealed the interaction domains of the proteins of this pathway. Analyses of Arabidopsis histidine phosphotransfer protein 5 mutant proteins showed that the presence of the canonical phospho-accepting histidine residue is not required for the interactions. Interaction of A-type response regulators with Arabidopsis histidine phosphotransfer proteins but not with B-type response regulators suggests that their known activity in feedback regulation may be realized by interfering at the level of Arabidopsis histidine phosphotransfer protein-mediated signaling. This study contributes to our understanding of the protein interactions of the cytokinin-signaling system and provides a framework for further functional studies in planta.

Molecular simulation of the effect of cholesterol on lipid-mediated protein-protein interactions.

PubMed

de Meyer, Frédérick J-M; Rodgers, Jocelyn M; Willems, Thomas F; Smit, Berend

2010-12-01

Experiments and molecular simulations have shown that the hydrophobic mismatch between proteins and membranes contributes significantly to lipid-mediated protein-protein interactions. In this article, we discuss the effect of cholesterol on lipid-mediated protein-protein interactions as function of hydrophobic mismatch, protein diameter and protein cluster size, lipid tail length, and temperature. To do so, we study a mesoscopic model of a hydrated bilayer containing lipids and cholesterol in which proteins are embedded, with a hybrid dissipative particle dynamics-Monte Carlo method. We propose a mechanism by which cholesterol affects protein interactions: protein-induced, cholesterol-enriched, or cholesterol-depleted lipid shells surrounding the proteins affect the lipid-mediated protein-protein interactions. Our calculations of the potential of mean force between proteins and protein clusters show that the addition of cholesterol dramatically reduces repulsive lipid-mediated interactions between proteins (protein clusters) with positive mismatch, but does not affect attractive interactions between proteins with negative mismatch. Cholesterol has only a modest effect on the repulsive interactions between proteins with different mismatch. Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions.

PubMed

Yates, Christopher M; Sternberg, Michael J E

2013-11-01

Non-synonymous single nucleotide polymorphisms (nsSNPs) are single base changes leading to a change to the amino acid sequence of the encoded protein. Many of these variants are associated with disease, so nsSNPs have been well studied, with studies looking at the effects of nsSNPs on individual proteins, for example, on stability and enzyme active sites. In recent years, the impact of nsSNPs upon protein-protein interactions has also been investigated, giving a greater insight into the mechanisms by which nsSNPs can lead to disease. In this review, we summarize these studies, looking at the various mechanisms by which nsSNPs can affect protein-protein interactions. We focus on structural changes that can impair interaction, changes to disorder, gain of interaction, and post-translational modifications before looking at some examples of nsSNPs at human-pathogen protein-protein interfaces and the analysis of nsSNPs from a network perspective. © 2013.

Monitoring Protein–Protein Interactions Using Split Synthetic Renilla Luciferase Protein-Fragment-Assisted Complementation

PubMed Central

Paulmurugan, R.; Gambhir, S. S.

2014-01-01

In this study we developed an inducible synthetic renilla luciferase protein-fragment-assisted complementation-based bioluminescence assay to quantitatively measure real time protein–protein interactions in mammalian cells. We identified suitable sites to generate fragments of N and C portions of the protein that yield significant recovered activity through complementation. We validate complementation-based activation of split synthetic renilla luciferase protein driven by the interaction of two strongly interacting proteins, MyoD and Id, in five different cell lines utilizing transient transfection studies. The expression level of the system was also modulated by tumor necrosis factor α through NFκB-promoter/enhancer elements used to drive expression of the N portion of synthetic renilla luciferase reporter gene. This new system should help in studying protein–protein interactions and when used with other split reporters (e.g., split firefly luciferase) should help to monitor different components of an intracellular network. PMID:12705589

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

PubMed

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions

PubMed Central

Banks, Charles A. S.; Boanca, Gina; Lee, Zachary T.; Florens, Laurence; Washburn, Michael P.

2015-01-01

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine “cloning scar” present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected. PMID:25704442

Studies on interaction of insect repellent compounds with odorant binding receptor proteins by in silico molecular docking approach.

PubMed

Gopal, J Vinay; Kannabiran, K

2013-12-01

The aim of the study was to identify the interactions between insect repellent compounds and target olfactory proteins. Four compounds, camphor (C10H16O), carvacrol (C10H14O), oleic acid (C18H34O2) and firmotox (C22H28O5) were chosen as ligands. Seven olfactory proteins of insects with PDB IDs: 3K1E, 1QWV, 1TUJ, 1OOF, 2ERB, 3R1O and OBP1 were chosen for docking analysis. Patch dock was used and pymol for visualizing the structures. The interactions of these ligands with few odorant binding proteins showed binding energies. The ligand camphor had showed a binding energy of -136 kcal/mol with OBP1 protein. The ligand carvacrol interacted with 1QWV and 1TUJ proteins with a least binding energy of -117.45 kcal/mol and -21.78 kcal/mol respectively. The ligand oleic acid interacted with 1OOF, 2ERB, 3R1O and OBP1 with least binding energies. Ligand firmotox interacted with OBP1 and showed least binding energies. Three ligands (camphor, oleic acid and firmotox) had one, two, three interactions with a single protein OBP1 of Nilaparvatha lugens (Rice pest). From this in silico study we identified the interaction patterns for insect repellent compounds with the target insect odarant proteins. The results of our study revealed that the chosen ligands showed hydrogen bond interactions with the target olfactory receptor proteins.

Identification of structural protein-protein interactions of herpes simplex virus type 1.

PubMed

Lee, Jin H; Vittone, Valerio; Diefenbach, Eve; Cunningham, Anthony L; Diefenbach, Russell J

2008-09-01

In this study we have defined protein-protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument-tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566-9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35-pUL37 (capsid-tegument), pUL46-pUL37 (tegument-tegument) and pUL49 (VP22)-pUS9 (tegument-envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs.

Study and selection of in vivo protein interactions by coupling bimolecular fluorescence complementation and flow cytometry.

PubMed

Morell, Montse; Espargaro, Alba; Aviles, Francesc Xavier; Ventura, Salvador

2008-01-01

We present a high-throughput approach to study weak protein-protein interactions by coupling bimolecular fluorescent complementation (BiFC) to flow cytometry (FC). In BiFC, the interaction partners (bait and prey) are fused to two rationally designed fragments of a fluorescent protein, which recovers its function upon the binding of the interacting proteins. For weak protein-protein interactions, the detected fluorescence is proportional to the interaction strength, thereby allowing in vivo discrimination between closely related binders with different affinity for the bait protein. FC provides a method for high-speed multiparametric data acquisition and analysis; the assay is simple, thousands of cells can be analyzed in seconds and, if required, selected using fluorescence-activated cell sorting (FACS). The combination of both methods (BiFC-FC) provides a technically straightforward, fast and highly sensitive method to validate weak protein interactions and to screen and identify optimal ligands in biologically synthesized libraries. Once plasmids encoding the protein fusions have been obtained, the evaluation of a specific interaction, the generation of a library and selection of active partners using BiFC-FC can be accomplished in 5 weeks.

Dynamical analysis of yeast protein interaction network during the sake brewing process.

PubMed

Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

2011-12-01

Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

Visualization of protein interactions in living Drosophila embryos by the bimolecular fluorescence complementation assay

PubMed Central

2011-01-01

Background Protein interactions control the regulatory networks underlying developmental processes. The understanding of developmental complexity will, therefore, require the characterization of protein interactions within their proper environment. The bimolecular fluorescence complementation (BiFC) technology offers this possibility as it enables the direct visualization of protein interactions in living cells. However, its potential has rarely been applied in embryos of animal model organisms and was only performed under transient protein expression levels. Results Using a Hox protein partnership as a test case, we investigated the suitability of BiFC for the study of protein interactions in the living Drosophila embryo. Importantly, all BiFC parameters were established with constructs that were stably expressed under the control of endogenous promoters. Under these physiological conditions, we showed that BiFC is specific and sensitive enough to analyse dynamic protein interactions. We next used BiFC in a candidate interaction screen, which led to the identification of several Hox protein partners. Conclusion Our results establish the general suitability of BiFC for revealing and studying protein interactions in their physiological context during the rapid course of Drosophila embryonic development. PMID:21276241

Interactions of the α-subunits of heterotrimeric G-proteins with GPCRs, effectors and RGS proteins: a critical review and analysis of interacting surfaces, conformational shifts, structural diversity and electrostatic potentials.

PubMed

Baltoumas, Fotis A; Theodoropoulou, Margarita C; Hamodrakas, Stavros J

2013-06-01

G-protein coupled receptors (GPCRs) are one of the largest families of membrane receptors in eukaryotes. Heterotrimeric G-proteins, composed of α, β and γ subunits, are important molecular switches in the mediation of GPCR signaling. Receptor stimulation after the binding of a suitable ligand leads to G-protein heterotrimer activation and dissociation into the Gα subunit and Gβγ heterodimer. These subunits then interact with a large number of effectors, leading to several cell responses. We studied the interactions between Gα subunits and their binding partners, using information from structural, mutagenesis and Bioinformatics studies, and conducted a series of comparisons of sequence, structure, electrostatic properties and intermolecular energies among different Gα families and subfamilies. We identified a number of Gα surfaces that may, in several occasions, participate in interactions with receptors as well as effectors. The study of Gα interacting surfaces in terms of sequence, structure and electrostatic potential reveals features that may account for the Gα subunit's behavior towards its interacting partners. The electrostatic properties of the Gα subunits, which in some cases differ greatly not only between families but also between subfamilies, as well as the G-protein interacting surfaces of effectors and regulators of G-protein signaling (RGS) suggest that electrostatic complementarity may be an important factor in G-protein interactions. Energy calculations also support this notion. This information may be useful in future studies of G-protein interactions with GPCRs and effectors. Copyright © 2013 Elsevier Inc. All rights reserved.

Role for protein–protein interaction databases in human genetics

PubMed Central

Pattin, Kristine A; Moore, Jason H

2010-01-01

Proteomics and the study of protein–protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein–protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein–protein interactions in human genetics and genetic epidemiology. Since protein–protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies. PMID:19929610

TPPII, MYBBP1A and CDK2 form a protein-protein interaction network.

PubMed

Nahálková, Jarmila; Tomkinson, Birgitta

2014-12-15

Tripeptidyl-peptidase II (TPPII) is an aminopeptidase with suggested regulatory effects on cell cycle, apoptosis and senescence. A protein-protein interaction study revealed that TPPII physically interacts with the tumor suppressor MYBBP1A and the cell cycle regulator protein CDK2. Mutual protein-protein interaction was detected between MYBBP1A and CDK2 as well. In situ Proximity Ligation Assay (PLA) using HEK293 cells overexpressing TPPII forming highly enzymatically active oligomeric complexes showed that the cytoplasmic interaction frequency of TPPII with MYBBP1A increased with the protein expression of TPPII and using serum-free cell growth conditions. A specific reversible inhibitor of TPPII, butabindide, suppressed the cytoplasmic interactions of TPPII and MYBBP1A both in control HEK293 and the cells overexpressing murine TPPII. The interaction of MYBBP1A with CDK2 was confirmed by in situ PLA in two different mammalian cell lines. Functional link between TPPII and MYBBP1A has been verified by gene expression study during anoikis, where overexpression of TPP II decreased mRNA expression level of MYBBP1A at the cell detachment conditions. All three interacting proteins TPPII, MYBBP1A and CDK2 have been previously implicated in the research for development of tumor-suppressing agents. This is the first report presenting mutual protein-protein interaction network of these proteins. Copyright © 2014 Elsevier Inc. All rights reserved.

The interaction between NOLC1 and IAV NS1 protein promotes host cell apoptosis and reduces virus replication.

PubMed

Zhu, Chunyu; Zheng, Fangliang; Zhu, Junfeng; Liu, Meichen; Liu, Na; Li, Xue; Zhang, Li; Deng, Zaidong; Zhao, Qi; Liu, Hongsheng

2017-11-07

NS1 of the influenza virus plays an important role in the infection ability of the influenza virus. Our previous research found that NS1 protein interacts with the NOLC1 protein of host cells, however, the function of the interaction is unknown. In the present study, the role of the interaction between the two proteins in infection was further studied. Several analyses, including the use of a pull-down assay, Co-IP, western blot analysis, overexpression, RNAi, flow cytometry, etc., were used to demonstrate that the NS1 protein of H3N2 influenza virus interacts with host protein NOLC1 and reduces the quantity of NOLC1. The interaction also promotes apoptosis in A549 host cells, while the suppression of NOLC1 protein reduces the proliferation of the H3N2 virus. Based on these data, it was concluded that during the process of infection, NS1 protein interacts with NOLC1 protein, reducing the level of NOLC1, and that the interaction between the two proteins promotes apoptosis of host cells, thus reducing the proliferation of the virus. These findings provide new information on the biological function of the interaction between NS1 and NOLC1.

Predicting protein-protein interactions from protein domains using a set cover approach.

PubMed

Huang, Chengbang; Morcos, Faruck; Kanaan, Simon P; Wuchty, Stefan; Chen, Danny Z; Izaguirre, Jesús A

2007-01-01

One goal of contemporary proteome research is the elucidation of cellular protein interactions. Based on currently available protein-protein interaction and domain data, we introduce a novel method, Maximum Specificity Set Cover (MSSC), for the prediction of protein-protein interactions. In our approach, we map the relationship between interactions of proteins and their corresponding domain architectures to a generalized weighted set cover problem. The application of a greedy algorithm provides sets of domain interactions which explain the presence of protein interactions to the largest degree of specificity. Utilizing domain and protein interaction data of S. cerevisiae, MSSC enables prediction of previously unknown protein interactions, links that are well supported by a high tendency of coexpression and functional homogeneity of the corresponding proteins. Focusing on concrete examples, we show that MSSC reliably predicts protein interactions in well-studied molecular systems, such as the 26S proteasome and RNA polymerase II of S. cerevisiae. We also show that the quality of the predictions is comparable to the Maximum Likelihood Estimation while MSSC is faster. This new algorithm and all data sets used are accessible through a Web portal at http://ppi.cse.nd.edu.

The role of protein-protein interactions in the intracellular traffic of the potassium channels TASK-1 and TASK-3.

PubMed

Kilisch, Markus; Lytovchenko, Olga; Schwappach, Blanche; Renigunta, Vijay; Daut, Jürgen

2015-05-01

The intracellular transport of membrane proteins is controlled by trafficking signals: Short peptide motifs that mediate the contact with COPI, COPII or various clathrin-associated coat proteins. In addition, many membrane proteins interact with accessory proteins that are involved in the sorting of these proteins to different intracellular compartments. In the K2P channels, TASK-1 and TASK-3, the influence of protein-protein interactions on sorting decisions has been studied in some detail. Both TASK paralogues interact with the adaptor protein 14-3-3; TASK-1 interacts, in addition, with the adaptor protein p11 (S100A10) and the endosomal SNARE protein syntaxin-8. The role of these interacting proteins in controlling the intracellular traffic of the channels and the underlying molecular mechanisms are summarised in this review. In the case of 14-3-3, the interacting protein masks a retention signal in the C-terminus of the channel; in the case of p11, the interacting protein carries a retention signal that localises the channel to the endoplasmic reticulum; and in the case of syntaxin-8, the interacting protein carries an endocytosis signal that complements an endocytosis signal of the channel. These examples illustrate some of the mechanisms by which interacting proteins may determine the itinerary of a membrane protein within a cell and suggest that the intracellular traffic of membrane proteins may be adapted to the specific functions of that protein by multiple protein-protein interactions.

Molecular imaging of drug-modulated protein-protein interactions in living subjects.

PubMed

Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

2004-03-15

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

In silico prediction of protein-protein interactions in human macrophages

PubMed Central

2014-01-01

Background Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level. PMID:24636261

Examining post-translational modification-mediated protein–protein interactions using a chemical proteomics approach

PubMed Central

Li, Xiang; Foley, Emily A; Kawashima, Shigehiro A; Molloy, Kelly R; Li, Yinyin; Chait, Brian T; Kapoor, Tarun M

2013-01-01

Post-translational modifications (PTM) of proteins can control complex and dynamic cellular processes via regulating interactions between key proteins. To understand these regulatory mechanisms, it is critical that we can profile the PTM-dependent protein–protein interactions. However, identifying these interactions can be very difficult using available approaches, as PTMs can be dynamic and often mediate relatively weak protein–protein interactions. We have recently developed CLASPI (cross-linking-assisted and stable isotope labeling in cell culture-based protein identification), a chemical proteomics approach to examine protein–protein interactions mediated by methylation in human cell lysates. Here, we report three extensions of the CLASPI approach. First, we show that CLASPI can be used to analyze methylation-dependent protein–protein interactions in lysates of fission yeast, a genetically tractable model organism. For these studies, we examined trimethylated histone H3 lysine-9 (H3K9Me3)-dependent protein–protein interactions. Second, we demonstrate that CLASPI can be used to examine phosphorylation-dependent protein–protein interactions. In particular, we profile proteins recognizing phosphorylated histone H3 threonine-3 (H3T3-Phos), a mitotic histone “mark” appearing exclusively during cell division. Our approach identified survivin, the only known H3T3-Phos-binding protein, as well as other proteins, such as MCAK and KIF2A, that are likely to be involved in weak but selective interactions with this histone phosphorylation “mark”. Finally, we demonstrate that the CLASPI approach can be used to study the interplay between histone H3T3-Phos and trimethylation on the adjacent residue lysine 4 (H3K4Me3). Together, our findings indicate the CLASPI approach can be broadly applied to profile protein–protein interactions mediated by PTMs. PMID:23281010

Structural study of surfactant-dependent interaction with protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mehan, Sumit; Aswal, Vinod K., E-mail: vkaswal@barc.gov.in; Kohlbrecher, Joachim

2015-06-24

Small-angle neutron scattering (SANS) has been used to study the complex structure of anionic BSA protein with three different (cationic DTAB, anionic SDS and non-ionic C12E10) surfactants. These systems form very different surfactant-dependent complexes. We show that the structure of protein-surfactant complex is initiated by the site-specific electrostatic interaction between the components, followed by the hydrophobic interaction at high surfactant concentrations. It is also found that hydrophobic interaction is preferred over the electrostatic interaction in deciding the resultant structure of protein-surfactant complexes.

Structural study of surfactant-dependent interaction with protein

NASA Astrophysics Data System (ADS)

Mehan, Sumit; Aswal, Vinod K.; Kohlbrecher, Joachim

2015-06-01

Small-angle neutron scattering (SANS) has been used to study the complex structure of anionic BSA protein with three different (cationic DTAB, anionic SDS and non-ionic C12E10) surfactants. These systems form very different surfactant-dependent complexes. We show that the structure of protein-surfactant complex is initiated by the site-specific electrostatic interaction between the components, followed by the hydrophobic interaction at high surfactant concentrations. It is also found that hydrophobic interaction is preferred over the electrostatic interaction in deciding the resultant structure of protein-surfactant complexes.

Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes

PubMed Central

Mazloom, Amin R.; Dannenfelser, Ruth; Clark, Neil R.; Grigoryan, Arsen V.; Linder, Kathryn M.; Cardozo, Timothy J.; Bond, Julia C.; Boran, Aislyn D. W.; Iyengar, Ravi; Malovannaya, Anna; Lanz, Rainer B.; Ma'ayan, Avi

2011-01-01

Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/. PMID:22219718

Single Molecule Study of Metalloregulatory Protein-DNA Interactions

NASA Astrophysics Data System (ADS)

Sarkar, Susanta; Benitez, Jaime; Huang, Zhengxi; Wang, Qi; Chen, Peng

2007-03-01

Control of metal concentrations is essential for living body. Metalloregulatory proteins respond to metal concentrations by regulating transcriptions of metal resistance genes via protein-DNA interactions. It is thus necessary to understand interactions of metalloregulatory proteins with DNA. Ensemble measurements provide average behavior of a vast number of biomolecules. In contrast, single molecule spectroscopy can track single molecules individually and elucidate dynamics of processes of short time scales and intermediate structures not revealed by ensemble measurements. Here we present single molecule study of interactions between PbrR691, a MerR-family metalloregulatory protein and DNA. We presume that the dynamics of protein/DNA conformational changes and interactions are important for the transcription regulation and kinetics of these dynamic processes can provide useful information about the mechanisms of these metalloregulatory proteins.

Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein-Protein Interaction Inhibitors of CaV Function.

PubMed

Findeisen, Felix; Campiglio, Marta; Jo, Hyunil; Abderemane-Ali, Fayal; Rumpf, Christine H; Pope, Lianne; Rossen, Nathan D; Flucher, Bernhard E; DeGrado, William F; Minor, Daniel L

2017-06-21

For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (Ca V ) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (Ca V β). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:Ca V β interactions and reduce the entropic penalty associated with AID binding to Ca V β. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the Ca V α 1 :Ca V β interaction that modulate Ca V function in an Ca V β isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based Ca V modulator design.

Interaction of silver nanoparticles with proteins: a characteristic protein concentration dependent profile of SPR signal.

PubMed

Banerjee, Victor; Das, K P

2013-11-01

Silver nanoparticles are finding increasing applications in biological systems, for example as antimicrobial agents and potential candidates for control drug release systems. In all such applications, silver nanoparticles interact with proteins and other biomolecules. Hence, the study of such interactions is of considerable importance. While BSA has been extensively used as a model protein for the study of interaction with the silver nanoparticles, studies using other proteins are rather limited. The interaction of silver nanoparticles with light leads to collective oscillation of the conducting electrons giving rise to surface plasmon resonance (SPR). Here, we have studied the protein concentration dependence of the SPR band profiles for a number of proteins. We found that for all the proteins, with increase in concentration, the SPR band intensity initially decreased, reaching minima and then increased again leading to a characteristic "dip and rise" pattern. Minimum point of the pattern appeared to be related to the isoelectric point of the proteins. Detailed dynamic light scattering and transmission electron microscopy studies revealed that the consistency of SPR profile was dependent on the average particle size and state of association of the silver nanoparticles with the change in the protein concentration. Fluorescence spectroscopic studies showed the binding constants of the proteins with the silver nanoparticles were in the nano molar range with more than one nanoparticle binding to protein molecule. Structural studies demonstrate that protein retains its native-like structure on the nanoparticle surface unless the molar ratio of silver nanoparticles to protein exceeds 10. Our study reveals that nature of the protein concentration dependent profile of SPR signal is a general phenomena and mostly independent of the size and structure of the proteins. Copyright © 2013 Elsevier B.V. All rights reserved.

Identification of new protein interactions between dengue fever virus and its hosts, human and mosquito.

PubMed

Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann; Murali, Thilakam; Suriyaphol, Prapat; Malasit, Prida; Limjindaporn, Thawornchai; Finley, Russell L

2013-01-01

The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host - dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies.

Identification of New Protein Interactions between Dengue Fever Virus and Its Hosts, Human and Mosquito

PubMed Central

Mairiang, Dumrong; Zhang, Huamei; Sodja, Ann; Murali, Thilakam; Suriyaphol, Prapat; Malasit, Prida; Limjindaporn, Thawornchai; Finley, Russell L.

2013-01-01

The four divergent serotypes of dengue virus are the causative agents of dengue fever, dengue hemorrhagic fever and dengue shock syndrome. About two-fifths of the world's population live in areas where dengue is prevalent, and thousands of deaths are caused by the viruses every year. Dengue virus is transmitted from one person to another primarily by the yellow fever mosquito, Aedes aegypti. Recent studies have begun to define how the dengue viral proteins interact with host proteins to mediate viral replication and pathogenesis. A combined analysis of these studies, however, suggests that many virus-host protein interactions remain to be identified, especially for the mosquito host. In this study, we used high-throughput yeast two-hybrid screening to identify mosquito and human proteins that physically interact with dengue proteins. We tested each identified host protein against the proteins from all four serotypes of dengue to identify interactions that are conserved across serotypes. We further confirmed many of the interactions using co-affinity purification assays. As in other large-scale screens, we identified some previously detected interactions and many new ones, moving us closer to a complete host – dengue protein interactome. To help summarize and prioritize the data for further study, we combined our interactions with other published data and identified a subset of the host-dengue interactions that are now supported by multiple forms of evidence. These data should be useful for understanding the interplay between dengue and its hosts and may provide candidates for drug targets and vector control strategies. PMID:23326450

A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein-Protein Interaction Interfaces.

PubMed

Xu, David; Si, Yubing; Meroueh, Samy O

2017-09-25

The binding affinity of a protein-protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein-protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein-protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein-protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2•p53, Bcl-xL•Bak, and IL-2•IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein-protein interactions do not optimally mimic protein-ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials.

Research Techniques Made Simple: Emerging Methods to Elucidate Protein Interactions through Spatial Proximity.

PubMed

Che, Yonglu; Khavari, Paul A

2017-12-01

Interactions between proteins are essential for fundamental cellular processes, and the diversity of such interactions enables the vast variety of functions essential for life. A persistent goal in biological research is to develop assays that can faithfully capture different types of protein interactions to allow their study. A major step forward in this direction came with a family of methods that delineates spatial proximity of proteins as an indirect measure of protein-protein interaction. A variety of enzyme- and DNA ligation-based methods measure protein co-localization in space, capturing novel interactions that were previously too transient or low affinity to be identified. Here we review some of the methods that have been successfully used to measure spatially proximal protein-protein interactions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Specificity and non-specificity in RNA–protein interactions

PubMed Central

Jankowsky, Eckhard; Harris, Michael E.

2016-01-01

Gene expression is regulated by complex networks of interactions between RNAs and proteins. Proteins that interact with RNA have been traditionally viewed as either specific or non-specific; specific proteins interact preferentially with defined RNA sequence or structure motifs, whereas non-specific proteins interact with RNA sites devoid of such characteristics. Recent studies indicate that the binary “specific vs. non-specific” classification is insufficient to describe the full spectrum of RNA–protein interactions. Here, we review new methods that enable quantitative measurements of protein binding to large numbers of RNA variants, and the concepts aimed as describing resulting binding spectra: affinity distributions, comprehensive binding models and free energy landscapes. We discuss how these new methodologies and associated concepts enable work towards inclusive, quantitative models for specific and non-specific RNA–protein interactions. PMID:26285679

Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

PubMed

Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

2013-01-27

A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

HitPredict version 4: comprehensive reliability scoring of physical protein-protein interactions from more than 100 species.

PubMed

López, Yosvany; Nakai, Kenta; Patil, Ashwini

2015-01-01

HitPredict is a consolidated resource of experimentally identified, physical protein-protein interactions with confidence scores to indicate their reliability. The study of genes and their inter-relationships using methods such as network and pathway analysis requires high quality protein-protein interaction information. Extracting reliable interactions from most of the existing databases is challenging because they either contain only a subset of the available interactions, or a mixture of physical, genetic and predicted interactions. Automated integration of interactions is further complicated by varying levels of accuracy of database content and lack of adherence to standard formats. To address these issues, the latest version of HitPredict provides a manually curated dataset of 398 696 physical associations between 70 808 proteins from 105 species. Manual confirmation was used to resolve all issues encountered during data integration. For improved reliability assessment, this version combines a new score derived from the experimental information of the interactions with the original score based on the features of the interacting proteins. The combined interaction score performs better than either of the individual scores in HitPredict as well as the reliability score of another similar database. HitPredict provides a web interface to search proteins and visualize their interactions, and the data can be downloaded for offline analysis. Data usability has been enhanced by mapping protein identifiers across multiple reference databases. Thus, the latest version of HitPredict provides a significantly larger, more reliable and usable dataset of protein-protein interactions from several species for the study of gene groups. Database URL: http://hintdb.hgc.jp/htp. © The Author(s) 2015. Published by Oxford University Press.

Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology.

PubMed

DeBlasio, Stacy L; Chavez, Juan D; Alexander, Mariko M; Ramsey, John; Eng, Jimmy K; Mahoney, Jaclyn; Gray, Stewart M; Bruce, James E; Cilia, Michelle

2016-02-15

Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus [PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in the Luteoviridae and with unrelated viruses in the Herpesviridae and Adenoviridae. Functional analysis of three PLRV-interacting host proteins in planta using a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection-hallmarks of host-pathogen interactions-were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies. The exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used protein interaction reporter (PIR) technology to illustrate how viruses exploit host proteins during plant infection. PIR technology enabled our team to precisely describe the sites of functional virus-virus, virus-host, and host-host protein interactions using a mass spectrometry analysis that takes just a few hours. Applications of PIR technology in host-pathogen interactions will enable researchers studying recalcitrant pathogens, such as animal pathogens where host proteins are incorporated directly into the infectious agents, to investigate how proteins interact during infection and transmission as well as develop new tools for interdiction and therapy. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Detection of plum pox potyviral protein-protein interactions in planta using an optimized mRFP-based bimolecular fluorescence complementation system.

PubMed

Zilian, Eva; Maiss, Edgar

2011-12-01

In previous studies, protein interaction maps of different potyviruses have been generated using yeast two-hybrid (YTH) systems, and these maps have demonstrated a high diversity of interactions of potyviral proteins. Using an optimized bimolecular fluorescence complementation (BiFC) system, a complete interaction matrix for proteins of a potyvirus was developed for the first time under in planta conditions with ten proteins from plum pox virus (PPV). In total, 52 of 100 possible interactions were detected, including the self-interactions of CI, 6K2, VPg, NIa-Pro, NIb and CP, which is more interactions than have ever been detected for any other potyvirus in a YTH approach. Moreover, the BiFC system was shown to be able to localize the protein interactions, which was typified for the protein self-interactions indicated above. Additionally, experiments were carried out with the P3N-PIPO protein, revealing an interaction with CI but not with CP and supporting the involvement of P3N-PIPO in the cell-to-cell movement of potyviruses. No self-interaction of the PPV helper component-proteinase (HC-Pro) was detected using BiFC in planta. Therefore, additional experiments with turnip mosaic virus (TuMV) HC-Pro, PPV_HC-Pro and their mutants were conducted. The self-interaction of TuMV_HCpro, as recently demonstrated, and the self-interaction of the TuMV_ and PPV_HC-Pro mutants were shown by BiFC in planta, indicating that HC-Pro self-interactions may be species-specific. BiFC is a very useful and reliable method for the detection and localization of protein interactions in planta, thus enabling investigations under more natural conditions than studies in yeast cells.

Genome-Wide Protein Interaction Screens Reveal Functional Networks Involving Sm-Like Proteins

PubMed Central

Fromont-Racine, Micheline; Mayes, Andrew E.; Brunet-Simon, Adeline; Rain, Jean-Christophe; Colley, Alan; Dix, Ian; Decourty, Laurence; Joly, Nicolas; Ricard, Florence; Beggs, Jean D.

2000-01-01

A set of seven structurally related Sm proteins forms the core of the snRNP particles containing the spliceosomal U1, U2, U4 and U5 snRNAs. A search of the genomic sequence of Saccharomyces cerevisiae has identified a number of open reading frames that potentially encode structurally similar proteins termed Lsm (Like Sm) proteins. With the aim of analysing all possible interactions between the Lsm proteins and any protein encoded in the yeast genome, we performed exhaustive and iterative genomic two-hybrid screens, starting with the Lsm proteins as baits. Indeed, extensive interactions amongst eight Lsm proteins were found that suggest the existence of a Lsm complex or complexes. These Lsm interactions apparently involve the conserved Sm domain that also mediates interactions between the Sm proteins. The screens also reveal functionally significant interactions with splicing factors, in particular with Prp4 and Prp24, compatible with genetic studies and with the reported association of Lsm proteins with spliceosomal U6 and U4/U6 particles. In addition, interactions with proteins involved in mRNA turnover, such as Mrt1, Dcp1, Dcp2 and Xrn1, point to roles for Lsm complexes in distinct RNA metabolic processes, that are confirmed in independent functional studies. These results provide compelling evidence that two-hybrid screens yield functionally meaningful information about protein–protein interactions and can suggest functions for uncharacterized proteins, especially when they are performed on a genome-wide scale. PMID:10900456

Network-based study reveals potential infection pathways of hepatitis-C leading to various diseases.

PubMed

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement.

Network-Based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement. PMID:24743187

A combined database related and de novo MS-identification of yeast mannose-1-phosphate guanyltransferase PSA1 interaction partners at different phases of batch cultivation

NASA Astrophysics Data System (ADS)

Parviainen, Ville; Joenväärä, Sakari; Peltoniemi, Hannu; Mattila, Pirkko; Renkonen, Risto

2009-04-01

Mass spectrometry-based proteomic research has become one of the main methods in protein-protein interaction research. Several high throughput studies have established an interaction landscape of exponentially growing Baker's yeast culture. However, many of the protein-protein interactions are likely to change in different environmental conditions. In order to examine the dynamic nature of the protein interactions we isolated the protein complexes of mannose-1-phosphate guanyltransferase PSA1 from Saccharomyces cerevisiae at four different time points during batch cultivation. We used the tandem affinity purification (TAP)-method to purify the complexes and subjected the tryptic peptides to LC-MS/MS. The resulting peak lists were analyzed with two different methods: the database related protein identification program X!Tandem and the de novo sequencing program Lutefisk. We observed significant changes in the interactome of PSA1 during the batch cultivation and identified altogether 74 proteins interacting with PSA1 of which only six were found to interact during all time points. All the other proteins showed a more dynamic nature of binding activity. In this study we also demonstrate the benefit of using both database related and de novo methods in the protein interaction research to enhance both the quality and the quantity of observations.

A simple method to generate stable cell lines for the analysis of transient protein-protein interactions.

PubMed

Savage, Emilia Elizabeth; Wootten, Denise; Christopoulos, Arthur; Sexton, Patrick Michael; Furness, Sebastian George Barton

2013-04-01

Transient protein-protein interactions form the basis of signal transduction pathways in addition to many other biological processes. One tool for studying these interactions is bioluminescence resonance energy transfer (BRET). This technique has been widely applied to study signaling pathways, in particular those initiated by G protein-coupled receptors (GPCRs). These assays are routinely performed using transient transfection, a technique that has limitations in terms of assay cost and variability, overexpression of interacting proteins, vector uptake limited to cycling cells, and non-homogenous expression across cells within the assay. To address these issues, we developed bicistronic vectors for use with Life Technology's Gateway and flpIN systems. These vectors provide a means to generate isogenic cell lines for comparison of interacting proteins. They have the advantage of stable, single copy, isogenic, homogeneous expression with low inter-assay variation. We demonstrate their utility by assessing ligand-induced interactions between GPCRs and arrestin proteins.

Novel fusion protein approach for efficient high-throughput screening of small molecule-mediating protein-protein interactions in cells and living animals.

PubMed

Paulmurugan, Ramasamy; Gambhir, Sanjiv S

2005-08-15

Networks of protein interactions execute many different intracellular pathways. Small molecules either synthesized within the cell or obtained from the external environment mediate many of these protein-protein interactions. The study of these small molecule-mediated protein-protein interactions is important in understanding abnormal signal transduction pathways in a variety of disorders, as well as in optimizing the process of drug development and validation. In this study, we evaluated the rapamycin-mediated interaction of the human proteins FK506-binding protein (FKBP12) rapamycin-binding domain (FRB) and FKBP12 by constructing a fusion of these proteins with a split-Renilla luciferase or a split enhanced green fluorescent protein (split-EGFP) such that complementation of the reporter fragments occurs in the presence of rapamycin. Different linker peptides in the fusion protein were evaluated for the efficient maintenance of complemented reporter activity. This system was studied in both cell culture and xenografts in living animals. We found that peptide linkers with two or four EAAAR repeat showed higher protein-protein interaction-mediated signal with lower background signal compared with having no linker or linkers with amino acid sequences GGGGSGGGGS, ACGSLSCGSF, and ACGSLSCGSFACGSLSCGSF. A 9 +/- 2-fold increase in signal intensity both in cell culture and in living mice was seen compared with a system that expresses both reporter fragments and the interacting proteins separately. In this fusion system, rapamycin induced heterodimerization of the FRB and FKBP12 moieties occurred rapidly even at very lower concentrations (0.00001 nmol/L) of rapamycin. For a similar fusion system employing split-EGFP, flow cytometry analysis showed significant level of rapamycin-induced complementation.

Bacteriophage Protein–Protein Interactions

PubMed Central

Häuser, Roman; Blasche, Sonja; Dokland, Terje; Haggård-Ljungquist, Elisabeth; von Brunn, Albrecht; Salas, Margarita; Casjens, Sherwood; Molineux, Ian

2012-01-01

Bacteriophages T7, λ, P22, and P2/P4 (from Escherichia coli), as well as ϕ29 (from Bacillus subtilis), are among the best-studied bacterial viruses. This chapter summarizes published protein interaction data of intraviral protein interactions, as well as known phage–host protein interactions of these phages retrieved from the literature. We also review the published results of comprehensive protein interaction analyses of Pneumococcus phages Dp-1 and Cp-1, as well as coliphages λ and T7. For example, the ≈55 proteins encoded by the T7 genome are connected by ≈43 interactions with another ≈15 between the phage and its host. The chapter compiles published interactions for the well-studied phages λ (33 intra-phage/22 phage-host), P22 (38/9), P2/P4 (14/3), and ϕ29 (20/2). We discuss whether different interaction patterns reflect different phage lifestyles or whether they may be artifacts of sampling. Phages that infect the same host can interact with different host target proteins, as exemplified by E. coli phage λ and T7. Despite decades of intensive investigation, only a fraction of these phage interactomes are known. Technical limitations and a lack of depth in many studies explain the gaps in our knowledge. Strategies to complete current interactome maps are described. Although limited space precludes detailed overviews of phage molecular biology, this compilation will allow future studies to put interaction data into the context of phage biology. PMID:22748812

PACSAB: Coarse-Grained Force Field for the Study of Protein-Protein Interactions and Conformational Sampling in Multiprotein Systems.

PubMed

Emperador, Agustí; Sfriso, Pedro; Villarreal, Marcos Ariel; Gelpí, Josep Lluis; Orozco, Modesto

2015-12-08

Molecular dynamics simulations of proteins are usually performed on a single molecule, and coarse-grained protein models are calibrated using single-molecule simulations, therefore ignoring intermolecular interactions. We present here a new coarse-grained force field for the study of many protein systems. The force field, which is implemented in the context of the discrete molecular dynamics algorithm, is able to reproduce the properties of folded and unfolded proteins, in both isolation, complexed forming well-defined quaternary structures, or aggregated, thanks to its proper evaluation of protein-protein interactions. The accuracy and computational efficiency of the method makes it a universal tool for the study of the structure, dynamics, and association/dissociation of proteins.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-06-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed Central

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-01-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777

Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology

PubMed Central

DeBlasio, Stacy L.; Chavez, Juan D.; Alexander, Mariko M.; Ramsey, John; Eng, Jimmy K.; Mahoney, Jaclyn; Gray, Stewart M.; Bruce, James E.

2015-01-01

ABSTRACT Demonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus [PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in the Luteoviridae and with unrelated viruses in the Herpesviridae and Adenoviridae. Functional analysis of three PLRV-interacting host proteins in planta using a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection—hallmarks of host-pathogen interactions—were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies. IMPORTANCE The exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used protein interaction reporter (PIR) technology to illustrate how viruses exploit host proteins during plant infection. PIR technology enabled our team to precisely describe the sites of functional virus-virus, virus-host, and host-host protein interactions using a mass spectrometry analysis that takes just a few hours. Applications of PIR technology in host-pathogen interactions will enable researchers studying recalcitrant pathogens, such as animal pathogens where host proteins are incorporated directly into the infectious agents, to investigate how proteins interact during infection and transmission as well as develop new tools for interdiction and therapy. PMID:26656710

Density functional study of molecular interactions in secondary structures of proteins.

PubMed

Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

2016-01-01

Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

The light-harvesting antenna of Chlorobium tepidum: interactions between the FMO protein and the major chlorosome protein CsmA studied by surface plasmon resonance.

PubMed

Pedersen, Marie Østergaard; Borch, Jonas; Højrup, Peter; Cox, Raymond P; Miller, Mette

2006-09-01

Green sulfur bacteria possess two external light-harvesting antenna systems, the chlorosome and the FMO protein, which participate in a sequential energy transfer to the reaction centers embedded in the cytoplasmic membrane. However, little is known about the physical interaction between these two antenna systems. We have studied the interaction between the major chlorosome protein, CsmA, and the FMO protein in Chlorobium tepidum using surface plasmon resonance (SPR). Our results show an interaction between the FMO protein and an immobilized synthetic peptide corresponding to 17 amino acids at the C terminal of CsmA. This interaction is dependent on the presence of a motif comprising six amino acids that are highly conserved in all the currently available CsmA protein sequences.

Structure and expression of a novel compact myelin protein – Small VCP-interacting protein (SVIP)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Jiawen; Peng, Dungeng; Voehler, Markus

2013-10-11

Highlights: •SVIP (small p97/VCP-interacting protein) co-localizes with myelin basic protein (MBP) in compact myelin. •We determined that SVIP is an intrinsically disordered protein (IDP). •The helical content of SVIP increases dramatically during its interaction with negatively charged lipid membrane. •This study provides structural insight into interactions between SVIP and myelin membranes. -- Abstract: SVIP (small p97/VCP-interacting protein) was initially identified as one of many cofactors regulating the valosin containing protein (VCP), an AAA+ ATPase involved in endoplasmic-reticulum-associated protein degradation (ERAD). Our previous study showed that SVIP is expressed exclusively in the nervous system. In the present study, SVIP and VCPmore » were seen to be co-localized in neuronal cell bodies. Interestingly, we also observed that SVIP co-localizes with myelin basic protein (MBP) in compact myelin, where VCP was absent. Furthermore, using nuclear magnetic resonance (NMR) and circular dichroism (CD) spectroscopic measurements, we determined that SVIP is an intrinsically disordered protein (IDP). However, upon binding to the surface of membranes containing a net negative charge, the helical content of SVIP increases dramatically. These findings provide structural insight into interactions between SVIP and myelin membranes.« less

Optimizing immobilized enzyme performance in cell-free environments to produce liquid fuels.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Sanat

The overall goal of this project was to optimize enzyme performance for the production of bio-diesel fuel. Enzyme immobilization has attracted much attention as a means to increase productivity. Mesorporous silica materials have been known to be best suited for immobilizing enzymes. A major challenge is to ensure that the enzymatic activity is retained after immobilization. Two major factors which drive enzymatic deactivation are protein-surface and inter-protein interactions. Previously, we studied protein stability inside pores and how to optimize protein-surface interactions to minimize protein denaturation. In this work we studied eh effect of surface curvature and chemistry on inter-protein interactions.more » Our goal was to find suitable immobilization supports which minimize these inter-protein interactions. Our studies carried out in the frame work of Hydrophobic-Polar (HP) model showed that enzymes immobilized inside hydrophobic pores of optimal sizes are best suited to minimize these inter-protein interactions. Besides, this study is also of biological importance to understand the role of chaperonins in protein disaggregation. Both of these aspects profited immensely with collaborations with our experimental colleague, Prof. Georges Belfort (RPI), who performed the experimental analog of our theoretical works.« less

Interaction entropy for protein-protein binding.

PubMed

Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H

2017-03-28

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

Structural Interface Parameters Are Discriminatory in Recognising Near-Native Poses of Protein-Protein Interactions

PubMed Central

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. PMID:24498255

Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

PubMed

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

Emory University: Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Engineering Aromatic-Aromatic Interactions To Nucleate Folding in Intrinsically Disordered Regions of Proteins.

PubMed

Balakrishnan, Swati; Sarma, Siddhartha P

2017-08-22

Aromatic interactions are an important force in protein folding as they combine the stability of a hydrophobic interaction with the selectivity of a hydrogen bond. Much of our understanding of aromatic interactions comes from "bioinformatics" based analyses of protein structures and from the contribution of these interactions to stabilizing secondary structure motifs in model peptides. In this study, the structural consequences of aromatic interactions on protein folding have been explored in engineered mutants of the molten globule protein apo-cytochrome b 5 . Structural changes from disorder to order due to aromatic interactions in two variants of the protein, viz., WF-cytb5 and FF-cytb5, result in significant long-range secondary and tertiary structure. The results show that 54 and 52% of the residues in WF-cytb5 and FF-cytb5, respectively, occupy ordered regions versus 26% in apo-cytochrome b 5 . The interactions between the aromatic groups are offset-stacked and edge-to-face for the Trp-Phe and Phe-Phe mutants, respectively. Urea denaturation studies indicate that both mutants have a C m higher than that of apo-cytochrome b 5 and are more stable to chaotropic agents than apo-cytochrome b 5 . The introduction of these aromatic residues also results in "trimer" interactions with existing aromatic groups, reaffirming the selectivity of the aromatic interactions. These studies provide insights into the aromatic interactions that drive disorder-to-order transitions in intrinsically disordered regions of proteins and will aid in de novo protein design beyond small peptide scaffolds.

Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

PubMed

Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

2017-06-02

Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

Force spectroscopy studies on protein-ligand interactions: a single protein mechanics perspective.

PubMed

Hu, Xiaotang; Li, Hongbin

2014-10-01

Protein-ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein-ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein-ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein-ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Label-Free Proteomic Identification of Endogenous, Insulin-Stimulated Interaction Partners of Insulin Receptor Substrate-1

NASA Astrophysics Data System (ADS)

Geetha, Thangiah; Langlais, Paul; Luo, Moulun; Mapes, Rebekka; Lefort, Natalie; Chen, Shu-Chuan; Mandarino, Lawrence J.; Yi, Zhengping

2011-03-01

Protein-protein interactions are key to most cellular processes. Tandem mass spectrometry (MS/MS)-based proteomics combined with co-immunoprecipitation (CO-IP) has emerged as a powerful approach for studying protein complexes. However, a majority of systematic proteomics studies on protein-protein interactions involve the use of protein overexpression and/or epitope-tagged bait proteins, which might affect binding stoichiometry and lead to higher false positives. Here, we report an application of a straightforward, label-free CO-IP-MS/MS method, without the use of protein overexpression or protein tags, to the investigation of changes in the abundance of endogenous proteins associated with a bait protein, which is in this case insulin receptor substrate-1 (IRS-1), under basal and insulin stimulated conditions. IRS-1 plays a central role in the insulin signaling cascade. Defects in the protein-protein interactions involving IRS-1 may lead to the development of insulin resistance and type 2 diabetes. HPLC-ESI-MS/MS analyses identified eleven novel endogenous insulin-stimulated IRS-1 interaction partners in L6 myotubes reproducibly, including proteins play an important role in protein dephosphorylation [protein phosphatase 1 regulatory subunit 12A, (PPP1R12A)], muscle contraction and actin cytoskeleton rearrangement, endoplasmic reticulum stress, and protein folding, as well as protein synthesis. This novel application of label-free CO-IP-MS/MS quantification to assess endogenous interaction partners of a specific protein will prove useful for understanding how various cell stimuli regulate insulin signal transduction.

Protein-protein interactions in the regulation of WRKY transcription factors.

PubMed

Chi, Yingjun; Yang, Yan; Zhou, Yuan; Zhou, Jie; Fan, Baofang; Yu, Jing-Quan; Chen, Zhixiang

2013-03-01

It has been almost 20 years since the first report of a WRKY transcription factor, SPF1, from sweet potato. Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth, development, and responses to biotic and abiotic stress. Despite the functional diversity, almost all analyzed WRKY proteins recognize the TTGACC/T W-box sequences and, therefore, mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors. Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling, transcription, and chromatin remodeling. Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors. It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes. In this review, we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute, at different levels, to the establishment of the complex regulatory and functional network of WRKY transcription factors.

High-throughput analysis of peptide binding modules

PubMed Central

Liu, Bernard A.; Engelmann, Brett; Nash, Piers D.

2014-01-01

Modular protein interaction domains that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some protein interaction domains such as SH2, 14-3-3, Chromo and Bromo domains serve to recognize post-translational modification of amino acids (such as phosphorylation, acetylation, methylation etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PDZ domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High throughput analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry or other HTP techniques provides new insight into the potential protein-protein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls of high-throughput analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of protein interaction domains and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions. PMID:22610655

Polyamines: naturally occurring small molecule modulators of electrostatic protein-protein interactions.

PubMed

Berwanger, Anja; Eyrisch, Susanne; Schuster, Inge; Helms, Volkhard; Bernhardt, Rita

2010-02-01

Modulations of protein-protein interactions are a key step in regulating protein function, especially in networks. Modulators of these interactions are supposed to be candidates for the development of novel drugs. Here, we describe the role of the small, polycationic and highly abundant natural polyamines that could efficiently bind to charged spots at protein interfaces as modulators of such protein-protein interactions. Using the mitochondrial cytochrome P45011A1 (CYP11A1) electron transfer system as a model, we have analyzed the capability of putrescine, spermidine, and spermine at physiologically relevant concentrations to affect the protein-protein interactions between adrenodoxin reductase (AdR), adrenodoxin (Adx), and CYP11A1. The actions of polyamines on the individual components, on their association/dissociation, on electron transfer, and on substrate conversion were examined. These studies revealed modulating effects of polyamines on distinct interactions and on the entire system in a complex way. Modulation via changed protein-protein interactions appeared plausible from docking experiments that suggested favourable high-affinity binding sites of polyamines (spermine>spermidine>putrescine) at the AdR-Adx interface. Our findings imply for the first time that small endogenous compounds are capable of interfering with distinct components of transient protein complexes and might control protein functions by modulating electrostatic protein-protein interactions.

Identification of an interaction between calcium-dependent protein kinase 4 (EtCDPK4) and serine protease inhibitor (EtSerpin) in Eimeria tenella.

PubMed

Lv, Ling; Huang, Bing; Zhao, Qiping; Zhao, Zongping; Dong, Hui; Zhu, Shunhai; Chen, Ting; Yan, Ming; Han, Hongyu

2018-04-23

Eimeria tenella is an obligate intracellular apicomplexan protozoan parasite that has a complex life-cycle. Calcium ions, through various calcium-dependent protein kinases (CDPKs), regulate key events in parasite growth and development, including protein secretion, movement, differentiation, and invasion of and escape from host cells. In this study, we identified proteins that interact with EtCDPK4 to lay a foundation for clarifying the role of CDPKs in calcium channels. Eimeria tenella merozoites were collected to construct a yeast two-hybrid (Y2H) cDNA library. The Y2H system was used to identify proteins that interact with EtCDPK4. One of interacting proteins was confirmed using bimolecular fluorescence complementation and co-immunoprecipitation in vivo. Co-localization of proteins was performed using immunofluorescence assays. Eight proteins that interact with EtCDPK4 were identified using the Y2H system. One of the proteins, E. tenella serine protease inhibitor 1 (EtSerpin), was further confirmed. In this study, we screened for proteins that interact with EtCDPK4. An interaction between EtSerpin and EtCDPK4 was identified that may contribute to the invasion and development of E. tenella in host cells.

Network topological analysis reveals the functional cohesiveness for the newly discovered links by Yeast 2 Hybrid approach

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Pevzner, Sam; Rolland, Thomas; Tassan, Murat; Barabasi, Albert Laszlo; Vidal, Mark; CCNR, Northeastern University Collaboration; Dana Farber Cancer Institute Collaboration

2014-03-01

Protein-protein interaction maps and interactomes are the blueprint of Network Medicine and systems biology and are being experimentally studied by different groups. Despite the wide usage of Literature Curated Interactome (LCI), these sources are biased towards different parameters such as highly studied proteins. Yeast two hybrid method is a high throughput experimental setup which screens proteins in an unbiased fashion. Current knowledge of protein interactions is far from complete. In fact the previous offered data from Y2H method (2005), is estimated to offer only 5% of all potential protein interactions. Currently this coverage has increased to 20% of what is known as reference HI In this work we study the topological properties of Y2H protein-protein interactions network with LCI and show although they both agree on some properties, LCI shows a clear unbiased nature of interaction selections. Most importantly, we assess the properties of PPI as it evolves with increasing the coverage. We show that, the newly discovered interactions tend to connect proteins that have been closer than average in the previous PPI release. reinforcing the modular structure of PPI. Furthermore, we show, some unseen effects on PPI (as opposed to LCI) can be explained by its incompleteness.

Bimolecular fluorescence complementation (BiFC) analysis as a probe of protein interactions in living cells.

PubMed

Kerppola, Tom K

2008-01-01

Protein interactions are a fundamental mechanism for the generation of biological regulatory specificity. The study of protein interactions in living cells is of particular significance because the interactions that occur in a particular cell depend on the full complement of proteins present in the cell and the external stimuli that influence the cell. Bimolecular fluorescence complementation (BiFC) analysis enables direct visualization of protein interactions in living cells. The BiFC assay is based on the association between two nonfluorescent fragments of a fluorescent protein when they are brought in proximity to each other by an interaction between proteins fused to the fragments. Numerous protein interactions have been visualized using the BiFC assay in many different cell types and organisms. The BiFC assay is technically straightforward and can be performed using standard molecular biology and cell culture reagents and a regular fluorescence microscope or flow cytometer.

[Detection of protein-protein interactions by FRET and BRET methods].

PubMed

Matoulková, E; Vojtěšek, B

2014-01-01

Nowadays, in vivo protein-protein interaction studies have become preferable detecting meth-ods that enable to show or specify (already known) protein interactions and discover their inhibitors. They also facilitate detection of protein conformational changes and discovery or specification of signaling pathways in living cells. One group of in vivo methods enabling these findings is based on fluorescent resonance energy transfer (FRET) and its bio-luminescent modification (BRET). They are based on visualization of protein-protein interactions via light or enzymatic excitation of fluorescent or bio-luminescent proteins. These methods allow not only protein localization within the cell or its organelles (or small animals) but they also allow us to quantify fluorescent signals and to discover weak or strong interaction partners. In this review, we explain the principles of FRET and BRET, their applications in the characterization of protein-protein interactions and we describe several findings using these two methods that clarify molecular and cellular mechanisms and signals related to cancer biology.

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

PubMed Central

Roy, Sushmita; Martinez, Diego; Platero, Harriett; Lane, Terran; Werner-Washburne, Margaret

2009-01-01

Background Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information. Results AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins. Conclusion AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains. PMID:19936254

A simple and efficient method for predicting protein-protein interaction sites.

PubMed

Higa, R H; Tozzi, C L

2008-09-23

Computational methods for predicting protein-protein interaction sites based on structural data are characterized by an accuracy between 70 and 80%. Some experimental studies indicate that only a fraction of the residues, forming clusters in the center of the interaction site, are energetically important for binding. In addition, the analysis of amino acid composition has shown that residues located in the center of the interaction site can be better discriminated from the residues in other parts of the protein surface. In the present study, we implement a simple method to predict interaction site residues exploiting this fact and show that it achieves a very competitive performance compared to other methods using the same dataset and criteria for performance evaluation (success rate of 82.1%).

Molecular simulations of lipid-mediated protein-protein interactions.

PubMed

de Meyer, Frédérick Jean-Marie; Venturoli, Maddalena; Smit, Berend

2008-08-01

Recent experimental results revealed that lipid-mediated interactions due to hydrophobic forces may be important in determining the protein topology after insertion in the membrane, in regulating the protein activity, in protein aggregation and in signal transduction. To gain insight into the lipid-mediated interactions between two intrinsic membrane proteins, we developed a mesoscopic model of a lipid bilayer with embedded proteins, which we studied with dissipative particle dynamics. Our calculations of the potential of mean force between transmembrane proteins show that hydrophobic forces drive long-range protein-protein interactions and that the nature of these interactions depends on the length of the protein hydrophobic segment, on the three-dimensional structure of the protein and on the properties of the lipid bilayer. To understand the nature of the computed potentials of mean force, the concept of hydrophilic shielding is introduced. The observed protein interactions are interpreted as resulting from the dynamic reorganization of the system to maintain an optimal hydrophilic shielding of the protein and lipid hydrophobic parts, within the constraint of the flexibility of the components. Our results could lead to a better understanding of several membrane processes in which protein interactions are involved.

Utilizing Mechanistic Cross-Linking Technology to Study Protein-Protein Interactions: An Experiment Designed for an Undergraduate Biochemistry Lab

ERIC Educational Resources Information Center

Finzel, Kara; Beld, Joris; Burkart, Michael D.; Charkoudian, Louise K.

2017-01-01

Over the past decade, mechanistic cross-linking probes have been used to study protein-protein interactions in natural product biosynthetic pathways. This approach is highly interdisciplinary, combining elements of protein biochemistry, organic chemistry, and computational docking. Herein, we described the development of an experiment to engage…

Huntingtin-associated protein-1 (HAP1) regulates endocytosis and interacts with multiple trafficking-related proteins.

PubMed

Mackenzie, Kimberly D; Lim, Yoon; Duffield, Michael D; Chataway, Timothy; Zhou, Xin-Fu; Keating, Damien J

2017-07-01

Huntingtin-associated protein 1 (HAP1) was initially identified as a binding partner of huntingtin, mutations in which underlie Huntington's disease. Subcellular localization and protein interaction data indicate that HAP1 may be important in vesicle trafficking, cell signalling and receptor internalization. In this study, a proteomics approach was used for the identification of novel HAP1-interacting partners to attempt to shed light on the physiological function of HAP1. Using affinity chromatography with HAP1-GST protein fragments bound to Sepharose columns, this study identified a number of trafficking-related proteins that bind to HAP1. Interestingly, many of the proteins that were identified by mass spectrometry have trafficking-related functions and include the clathrin light chain B and Sec23A, an ER to Golgi trafficking vesicle coat component. Using co-immunoprecipitation and GST-binding assays the association between HAP1 and clathrin light chain B has been validated in vitro. This study also finds that HAP1 co-localizes with clathrin light chain B. In line with a physiological function of the HAP1-clathrin interaction this study detected a dramatic reduction in vesicle retrieval and endocytosis in adrenal chromaffin cells. Furthermore, through examination of transferrin endocytosis in HAP1 -/- cortical neurons, this study has determined that HAP1 regulates neuronal endocytosis. In this study, the interaction between HAP1 and Sec23A was also validated through endogenous co-immunoprecipitation in rat brain homogenate. Through the identification of novel HAP1 binding partners, many of which have putative trafficking roles, this study provides us with new insights into the mechanisms underlying the important physiological function of HAP1 as an intracellular trafficking protein through its protein-protein interactions. Copyright © 2017 Elsevier Inc. All rights reserved.

Specificity of molecular interactions in transient protein-protein interaction interfaces.

PubMed

Cho, Kyu-il; Lee, KiYoung; Lee, Kwang H; Kim, Dongsup; Lee, Doheon

2006-11-15

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of antibody-antigen complexes, the sign is somewhat ambiguous. From the evolutionary perspective, while protease-inhibitors and sig-naling proteins have optimized their interfaces to suit their biological functions, antibody-antigen interactions are the happenstance, implying that antibody-antigen complexes do not show distinctive interaction types. Persistent interaction types such as pi...pi, amide-carbonyl, and hydroxyl-carbonyl interaction, are also investigated. Analyzing the structural orientations of the pi...pi stacking interactions, we find that herringbone shape is a major configuration in transient protein-protein interfaces. This result is different from that of protein core, where parallel-displaced configurations are the major configuration. We also analyze overall trend of amide-carbonyl and hydroxyl-carbonyl interactions. It is noticeable that nearly 82% of the interfaces have at least one hydroxyl-carbonyl interactions. (c) 2006 Wiley-Liss, Inc.

A selection that reports on protein-protein interactions within a thermophilic bacterium.

PubMed

Nguyen, Peter Q; Silberg, Jonathan J

2010-07-01

Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein-protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein-protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AK(Tn)). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75 degrees C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78 degrees C by a vector that coexpresses polypeptides corresponding to residues 1-79 and 80-220 of AK(Tn). In contrast, PQN1 growth was not complemented by AK(Tn) fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein-protein interactions, since AK(Tn)-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein-protein interactions.

Study of Fluorinated Quantum Dots-Protein Interactions at the Oil/Water Interface by Interfacial Surface Tension Changes.

PubMed

Carrillo-Carrión, Carolina; Gallego, Marta; Parak, Wolfgang J; Carril, Mónica

2018-05-08

Understanding the interaction of nanoparticles with proteins and how this interaction modifies the nanoparticles’ surface is crucial before their use for biomedical applications. Since fluorinated materials are emerging as potential imaging probes and delivery vehicles, their interaction with proteins of biological interest must be studied in order to be able to predict their performance in real scenarios. It is known that fluorinated planar surfaces may repel the unspecific adsorption of proteins but little is known regarding the same process on fluorinated nanoparticles due to the scarce examples in the literature. In this context, the aim of this work is to propose a simple and fast methodology to study fluorinated nanoparticle-protein interactions based on interfacial surface tension (IFT) measurements. This technique is particularly interesting for fluorinated nanoparticles due to their increased hydrophobicity. Our study is based on the determination of IFT variations due to the interaction of quantum dots of ca. 5 nm inorganic core/shell diameter coated with fluorinated ligands (QD_F) with several proteins at the oil/water interface. Based on the results, we conclude that the presence of QD_F do not disrupt protein spontaneous film formation at the oil/water interface. Even if at very low concentrations of proteins the film formation in the presence of QD_F shows a slower rate, the final interfacial tension reached is similar to that obtained in the absence of QD_F. The differential behaviour of the studied proteins (bovine serum albumin, fibrinogen and apotransferrin) has been discussed on the basis of the adsorption affinity of each protein towards DCM/water interface and their different sizes. Additionally, it has been clearly demonstrated that the proposed methodology can serve as a complementary technique to other reported direct and indirect methods for the evaluation of nanoparticle-protein interactions at low protein concentrations.

From protein interaction profile to functional assignment: the human protein Ki-1/57 is associated with pre-mRNA splicing events.

PubMed

Bressan, Gustavo Costa; Kobarg, Jörg

2010-01-01

The mapping of protein-protein interactions of a determined organism is considered fundamental to assign protein function in the post-genomic era. As part of this effort, screenings for pairwise interactions by yeast two-hybrid system have been used popularly to reveal protein interaction networks in different biological systems. Through the identification of protein interaction partners we have successfully obtained interesting functional clues for Ki-1/57, a human protein with no previous functional annotation, in the context of RNA metabolism. We briefly discuss the way we approached protein-protein interaction data to conduct and interpret further molecular biological and cellular studies as well as structural analyses on this protein. Our data suggest that Ki-1/57 belongs to the family of intrinsically unstructured proteins and that the structural flexibility may be crucial for its capacity to interact with many different proteins. A large fraction of these proteins are involved in pre-mRNA splicing control. Finally, Ki-1/57 is localized to several subnuclear domains, all of which have been described to splicing and other RNA processing events.

Novel Fusion Protein Approach for Efficient High-Throughput Screening of Small Molecule–Mediating Protein-Protein Interactions in Cells and Living Animals

PubMed Central

Paulmurugan, Ramasamy; Gambhir, Sanjiv S.

2014-01-01

Networks of protein interactions execute many different intracellular pathways. Small molecules either synthesized within the cell or obtained from the external environment mediate many of these protein-protein interactions. The study of these small molecule–mediated protein-protein interactions is important in understanding abnormal signal transduction pathways in a variety of disorders, as well as in optimizing the process of drug development and validation. In this study, we evaluated the rapamycin-mediated interaction of the human proteins FK506-binding protein (FKBP12) rapamycin-binding domain (FRB) and FKBP12 by constructing a fusion of these proteins with a split-Renilla luciferase or a split enhanced green fluorescent protein (split-EGFP) such that complementation of the reporter fragments occurs in the presence of rapamycin. Different linker peptides in the fusion protein were evaluated for the efficient maintenance of complemented reporter activity. This system was studied in both cell culture and xenografts in living animals. We found that peptide linkers with two or four EAAAR repeat showed higher protein-protein interaction–mediated signal with lower background signal compared with having no linker or linkers with amino acid sequences GGGGSGGGGS, ACGSLSCGSF, and ACGSLSCGS-FACGSLSCGSF. A 9 ± 2-fold increase in signal intensity both in cell culture and in living mice was seen compared with a system that expresses both reporter fragments and the interacting proteins separately. In this fusion system, rapamycin induced heterodimerization of the FRB and FKBP12 moieties occurred rapidly even at very lower concentrations (0.00001 nmol/L) of rapamycin. For a similar fusion system employing split-EGFP, flow cytometry analysis showed significant level of rapamycin-induced complementation. PMID:16103094

Integrated web visualizations for protein-protein interaction databases.

PubMed

Jeanquartier, Fleur; Jean-Quartier, Claire; Holzinger, Andreas

2015-06-16

Understanding living systems is crucial for curing diseases. To achieve this task we have to understand biological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of databases and tools that support analysts in exploring protein-protein interactions on an integrated level for knowledge discovery. They provide predictions and correlations, indicate possibilities for future experimental research and fill the gaps to complete the picture of biochemical processes. There are numerous and huge databases of protein-protein interactions used to gain insights into answering some of the many questions of systems biology. Many computational resources integrate interaction data with additional information on molecular background. However, the vast number of diverse Bioinformatics resources poses an obstacle to the goal of understanding. We present a survey of databases that enable the visual analysis of protein networks. We selected M=10 out of N=53 resources supporting visualization, and we tested against the following set of criteria: interoperability, data integration, quantity of possible interactions, data visualization quality and data coverage. The study reveals differences in usability, visualization features and quality as well as the quantity of interactions. StringDB is the recommended first choice. CPDB presents a comprehensive dataset and IntAct lets the user change the network layout. A comprehensive comparison table is available via web. The supplementary table can be accessed on http://tinyurl.com/PPI-DB-Comparison-2015. Only some web resources featuring graph visualization can be successfully applied to interactive visual analysis of protein-protein interaction. Study results underline the necessity for further enhancements of visualization integration in biochemical analysis tools. Identified challenges are data comprehensiveness, confidence, interactive feature and visualization maturing.

Protein-protein interactions: an application of Tus-Ter mediated protein microarray system.

PubMed

Sitaraman, Kalavathy; Chatterjee, Deb K

2011-01-01

In this chapter, we present a novel, cost-effective microarray strategy that utilizes expression-ready plasmid DNAs to generate protein arrays on-demand and its use to validate protein-protein interactions. These expression plasmids were constructed in such a way so as to serve a dual purpose of synthesizing the protein of interest as well as capturing the synthesized protein. The microarray system is based on the high affinity binding of Escherichia coli "Tus" protein to "Ter," a 20 bp DNA sequence involved in the regulation of DNA replication. The protein expression is carried out in a cell-free protein synthesis system, with rabbit reticulocyte lysates, and the target proteins are detected either by labeled incorporated tag specific or by gene-specific antibodies. This microarray system has been successfully used for the detection of protein-protein interaction because both the target protein and the query protein can be transcribed and translated simultaneously in the microarray slides. The utility of this system for detecting protein-protein interaction is demonstrated by a few well-known examples: Jun/Fos, FRB/FKBP12, p53/MDM2, and CDK4/p16. In all these cases, the presence of protein complexes resulted in the localization of fluorophores at the specific sites of the immobilized target plasmids. Interestingly, during our interactions studies we also detected a previously unknown interaction between CDK2 and p16. Thus, this Tus-Ter based system of protein microarray can be used for the validation of known protein interactions as well as for identifying new protein-protein interactions. In addition, it can be used to examine and identify targets of nucleic acid-protein, ligand-receptor, enzyme-substrate, and drug-protein interactions.

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

Bacterial co-expression of human Tau protein with protein kinase A and 14-3-3 for studies of 14-3-3/phospho-Tau interaction

PubMed Central

Tugaeva, Kristina V.; Tsvetkov, Philipp O.

2017-01-01

Abundant regulatory 14-3-3 proteins have an extremely wide interactome and coordinate multiple cellular events via interaction with specifically phosphorylated partner proteins. Notwithstanding the key role of 14-3-3/phosphotarget interactions in many physiological and pathological processes, they are dramatically underexplored. Here, we focused on the 14-3-3 interaction with human Tau protein associated with the development of several neurodegenerative disorders, including Alzheimer’s and Parkinson’s diseases. Among many known phosphorylation sites within Tau, protein kinase A (PKA) phosphorylates several key residues of Tau and induces its tight interaction with 14-3-3 proteins. However, the stoichiometry and mechanism of 14-3-3 interaction with phosphorylated Tau (pTau) are not clearly elucidated. In this work, we describe a simple bacterial co-expression system aimed to facilitate biochemical and structural studies on the 14-3-3/pTau interaction. We show that dual co-expression of human fetal Tau with PKA in Escherichia coli results in multisite Tau phosphorylation including also naturally occurring sites which were not previously considered in the context of 14-3-3 binding. Tau protein co-expressed with PKA displays tight functional interaction with 14-3-3 isoforms of a different type. Upon triple co-expression with 14-3-3 and PKA, Tau protein could be co-purified with 14-3-3 and demonstrates complex which is similar to that formed in vitro between individual 14-3-3 and pTau obtained from dual co-expression. Although used in this study for the specific case of the previously known 14-3-3/pTau interaction, our co-expression system may be useful to study of other selected 14-3-3/phosphotarget interactions and for validations of 14-3-3 complexes identified by other methods. PMID:28575131

Computational prediction of virus-human protein-protein interactions using embedding kernelized heterogeneous data.

PubMed

Nourani, Esmaeil; Khunjush, Farshad; Durmuş, Saliha

2016-05-24

Pathogenic microorganisms exploit host cellular mechanisms and evade host defense mechanisms through molecular pathogen-host interactions (PHIs). Therefore, comprehensive analysis of these PHI networks should be an initial step for developing effective therapeutics against infectious diseases. Computational prediction of PHI data is gaining increasing demand because of scarcity of experimental data. Prediction of protein-protein interactions (PPIs) within PHI systems can be formulated as a classification problem, which requires the knowledge of non-interacting protein pairs. This is a restricting requirement since we lack datasets that report non-interacting protein pairs. In this study, we formulated the "computational prediction of PHI data" problem using kernel embedding of heterogeneous data. This eliminates the abovementioned requirement and enables us to predict new interactions without randomly labeling protein pairs as non-interacting. Domain-domain associations are used to filter the predicted results leading to 175 novel PHIs between 170 human proteins and 105 viral proteins. To compare our results with the state-of-the-art studies that use a binary classification formulation, we modified our settings to consider the same formulation. Detailed evaluations are conducted and our results provide more than 10 percent improvements for accuracy and AUC (area under the receiving operating curve) results in comparison with state-of-the-art methods.

Protein crowding in solution, frozen and freeze-dried states: small-angle neutron and X-ray scattering study of lysozyme/sorbitol/water systems

NASA Astrophysics Data System (ADS)

Krueger, Susan; Khodadadi, Sheila; Clark, Nicholas; McAuley, Arnold; Cristiglio, Viviana; Theyencheri, Narayanan; Curtis, Joseph; Shalaev, Evgenyi

2015-03-01

For effective preservation, proteins are often stored as frozen solutions or in glassy states using a freeze-drying process. However, aggregation is often observed after freeze-thaw or reconstitution of freeze-dried powder and the stability of the protein is no longer assured. In this study, small-angle neutron and X-ray scattering (SANS and SAXS) have been used to investigate changes in protein-protein interaction distances of a model protein/cryoprotectant system of lysozyme/sorbitol/water, under representative pharmaceutical processing conditions. The results demonstrate the utility of SAXS and SANS methods to monitor protein crowding at different stages of freezing and drying. The SANS measurements of solution samples showed at least one protein interaction peak corresponding to an interaction distance of ~ 90 Å. In the frozen state, two protein interaction peaks were observed by SANS with corresponding interaction distances at 40 Å as well as 90 Å. On the other hand, both SAXS and SANS data for freeze-dried samples showed three peaks, suggesting interaction distances ranging from ~ 15 Å to 170 Å. Possible interpretations of these interaction peaks will be discussed, as well as the role of sorbitol as a cryoprotectant during the freezing and drying process.

Protein–protein interactions and selection: yeast-based approaches that exploit guanine nucleotide-binding protein signaling.

PubMed

Ishii, Jun; Fukuda, Nobuo; Tanaka, Tsutomu; Ogino, Chiaki; Kondo, Akihiko

2010-05-01

For elucidating protein–protein interactions, many methodologies have been developed during the past two decades. For investigation of interactions inside cells under physiological conditions, yeast is an attractive organism with which to quickly screen for hopeful candidates using versatile genetic technologies, and various types of approaches are now available.Among them, a variety of unique systems using the guanine nucleotide-binding protein (G-protein) signaling pathway in yeast have been established to investigate the interactions of proteins for biological study and pharmaceutical research. G-proteins involved in various cellular processes are mainly divided into two groups: small monomeric G-proteins,and heterotrimeric G-proteins. In this minireview, we summarize the basic principles and applications of yeast-based screening systems, using these two types of G-protein, which are typically used for elucidating biological protein interactions but are differentiated from traditional yeast two-hybrid systems.

SNF1-related protein kinases 2 are negatively regulated by a plant-specific calcium sensor.

PubMed

Bucholc, Maria; Ciesielski, Arkadiusz; Goch, Grażyna; Anielska-Mazur, Anna; Kulik, Anna; Krzywińska, Ewa; Dobrowolska, Grażyna

2011-02-04

SNF1-related protein kinases 2 (SnRK2s) are plant-specific enzymes involved in environmental stress signaling and abscisic acid-regulated plant development. Here, we report that SnRK2s interact with and are regulated by a plant-specific calcium-binding protein. We screened a Nicotiana plumbaginifolia Matchmaker cDNA library for proteins interacting with Nicotiana tabacum osmotic stress-activated protein kinase (NtOSAK), a member of the SnRK2 family. A putative EF-hand calcium-binding protein was identified as a molecular partner of NtOSAK. To determine whether the identified protein interacts only with NtOSAK or with other SnRK2s as well, we studied the interaction of an Arabidopsis thaliana orthologue of the calcium-binding protein with selected Arabidopsis SnRK2s using a two-hybrid system. All kinases studied interacted with the protein. The interactions were confirmed by bimolecular fluorescence complementation assay, indicating that the binding occurs in planta, exclusively in the cytoplasm. Calcium binding properties of the protein were analyzed by fluorescence spectroscopy using Tb(3+) as a spectroscopic probe. The calcium binding constant, determined by the protein fluorescence titration, was 2.5 ± 0.9 × 10(5) M(-1). The CD spectrum indicated that the secondary structure of the protein changes significantly in the presence of calcium, suggesting its possible function as a calcium sensor in plant cells. In vitro studies revealed that the activity of SnRK2 kinases analyzed is inhibited in a calcium-dependent manner by the identified calcium sensor, which we named SCS (SnRK2-interacting calcium sensor). Our results suggest that SCS is involved in response to abscisic acid during seed germination most probably by negative regulation of SnRK2s activity.

Investigating the importance of Delaunay-based definition of atomic interactions in scoring of protein-protein docking results.

PubMed

Jafari, Rahim; Sadeghi, Mehdi; Mirzaie, Mehdi

2016-05-01

The approaches taken to represent and describe structural features of the macromolecules are of major importance when developing computational methods for studying and predicting their structures and interactions. This study attempts to explore the significance of Delaunay tessellation for the definition of atomic interactions by evaluating its impact on the performance of scoring protein-protein docking prediction. Two sets of knowledge-based scoring potentials are extracted from a training dataset of native protein-protein complexes. The potential of the first set is derived using atomic interactions extracted from Delaunay tessellated structures. The potential of the second set is calculated conventionally, that is, using atom pairs whose interactions were determined by their separation distances. The scoring potentials were tested against two different docking decoy sets and their performances were compared. The results show that, if properly optimized, the Delaunay-based scoring potentials can achieve higher success rate than the usual scoring potentials. These results and the results of a previous study on the use of Delaunay-based potentials in protein fold recognition, all point to the fact that Delaunay tessellation of protein structure can provide a more realistic definition of atomic interaction, and therefore, if appropriately utilized, may be able to improve the accuracy of pair potentials. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of A549 cell proteome alteration in response to recombinant influenza A virus nucleoprotein and its interaction with cellular proteins, a preliminary study.

PubMed

Kumar, D; Tiwari, K; Rajala, M S

Influenza A virus undergoes frequent changes of antigenicity and contributes to seasonal epidemics or unpredictable pandemics. Nucleoprotein, encoded by gene segment 5, is an internal protein of the virus and is conserved among strains of different host origins. In the current study, we analyzed the differentially expressed proteins in A549 cells transiently transfected with the recombinant nucleoprotein of influenza A virus by 2D gel electrophoresis. The resolved protein spots on gel were identified by MALDI-TOF/Mass spectrometry analysis. The majority of the host proteins detected to be differentially abundant in recombinant nucleoprotein-expressing cells as compared to vector-transfected cells are the proteins of metabolic pathways, glycolytic enzymes, molecular chaperones and cytoskeletal proteins. We further demonstrated the interaction of virus nucleoprotein with some of the identified host cellular proteins. In vitro binding assay carried out using the purified recombinant nucleoprotein (pET29a+NP-His) and A549 cell lysate confirmed the interaction between nucleoprotein and host proteins, such as alpha enolase 1, pyruvate kinase and β-actin. The preliminary data of our study provides the information on virus nucleoprotein interaction with proteins involved in glycolysis. However, studies are ongoing to understand the significance of these interactions in modulating the host factors during virus replication.

In Vitro Identification of Histatin 5 Salivary Complexes

PubMed Central

Moffa, Eduardo B.; Machado, Maria A. A. M.; Mussi, Maria C. M.; Xiao, Yizhi; Garrido, Saulo S.; Giampaolo, Eunice T.; Siqueira, Walter L.

2015-01-01

With recent progress in the analysis of the salivary proteome, the number of salivary proteins identified has increased dramatically. However, the physiological functions of many of the newly discovered proteins remain unclear. Closely related to the study of a protein’s function is the identification of its interaction partners. Although in saliva some proteins may act primarily as single monomeric units, a significant percentage of all salivary proteins, if not the majority, appear to act in complexes with partners to execute their diverse functions. Coimmunoprecipitation (Co-IP) and pull-down assays were used to identify the heterotypic complexes between histatin 5, a potent natural antifungal protein, and other salivary proteins in saliva. Classical protein–protein interaction methods in combination with high-throughput mass spectrometric techniques were carried out. Co-IP using protein G magnetic Sepharose TM beads suspension was able to capture salivary complexes formed between histatin 5 and its salivary protein partners. Pull-down assay was used to confirm histatin 5 protein partners. A total of 52 different proteins were identified to interact with histatin 5. The present study used proteomic approaches in conjunction with classical biochemical methods to investigate protein–protein interaction in human saliva. Our study demonstrated that when histatin 5 is complexed with salivary amylase, one of the 52 proteins identified as a histatin 5 partner, the antifungal activity of histatin 5 is reduced. We expected that our proteomic approach could serve as a basis for future studies on the mechanism and structural-characterization of those salivary protein interactions to understand their clinical significance. PMID:26544073

Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms.

PubMed

Lin, Xiaotong; Liu, Mei; Chen, Xue-wen

2009-04-29

Protein-protein interactions play vital roles in nearly all cellular processes and are involved in the construction of biological pathways such as metabolic and signal transduction pathways. Although large-scale experiments have enabled the discovery of thousands of previously unknown linkages among proteins in many organisms, the high-throughput interaction data is often associated with high error rates. Since protein interaction networks have been utilized in numerous biological inferences, the inclusive experimental errors inevitably affect the quality of such prediction. Thus, it is essential to assess the quality of the protein interaction data. In this paper, a novel Bayesian network-based integrative framework is proposed to assess the reliability of protein-protein interactions. We develop a cross-species in silico model that assigns likelihood scores to individual protein pairs based on the information entirely extracted from model organisms. Our proposed approach integrates multiple microarray datasets and novel features derived from gene ontology. Furthermore, the confidence scores for cross-species protein mappings are explicitly incorporated into our model. Applying our model to predict protein interactions in the human genome, we are able to achieve 80% in sensitivity and 70% in specificity. Finally, we assess the overall quality of the experimentally determined yeast protein-protein interaction dataset. We observe that the more high-throughput experiments confirming an interaction, the higher the likelihood score, which confirms the effectiveness of our approach. This study demonstrates that model organisms certainly provide important information for protein-protein interaction inference and assessment. The proposed method is able to assess not only the overall quality of an interaction dataset, but also the quality of individual protein-protein interactions. We expect the method to continually improve as more high quality interaction data from more model organisms becomes available and is readily scalable to a genome-wide application.

A traveling salesman approach for predicting protein functions.

PubMed

Johnson, Olin; Liu, Jing

2006-10-12

Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm 1 on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems.

A traveling salesman approach for predicting protein functions

PubMed Central

Johnson, Olin; Liu, Jing

2006-01-01

Background Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways. Results Here we present a new approach utilizing the classic Traveling Salesman Problem to study the protein-protein interactions and to predict protein functions in budding yeast Saccharomyces cerevisiae. We apply the global optimization tool from combinatorial optimization algorithms to cluster the yeast proteins based on the global protein interaction information. We then use this clustering information to help us predict protein functions. We use our algorithm together with the direct neighbor algorithm [1] on characterized proteins and compare the prediction accuracy of the two methods. We show our algorithm can produce better predictions than the direct neighbor algorithm, which only considers the immediate neighbors of the query protein. Conclusion Our method is a promising one to be used as a general tool to predict functions of uncharacterized proteins and a successful sample of using computer science knowledge and algorithms to study biological problems. PMID:17147783

Intuitive Density Functional Theory-Based Energy Decomposition Analysis for Protein-Ligand Interactions.

PubMed

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2017-04-11

First-principles quantum mechanical calculations with methods such as density functional theory (DFT) allow the accurate calculation of interaction energies between molecules. These interaction energies can be dissected into chemically relevant components such as electrostatics, polarization, and charge transfer using energy decomposition analysis (EDA) approaches. Typically EDA has been used to study interactions between small molecules; however, it has great potential to be applied to large biomolecular assemblies such as protein-protein and protein-ligand interactions. We present an application of EDA calculations to the study of ligands that bind to the thrombin protein, using the ONETEP program for linear-scaling DFT calculations. Our approach goes beyond simply providing the components of the interaction energy; we are also able to provide visual representations of the changes in density that happen as a result of polarization and charge transfer, thus pinpointing the functional groups between the ligand and protein that participate in each kind of interaction. We also demonstrate with this approach that we can focus on studying parts (fragments) of ligands. The method is relatively insensitive to the protocol that is used to prepare the structures, and the results obtained are therefore robust. This is an application to a real protein drug target of a whole new capability where accurate DFT calculations can produce both energetic and visual descriptors of interactions. These descriptors can be used to provide insights for tailoring interactions, as needed for example in drug design.

Identification of Histone Deacetylase (HDAC) as a drug target against MRSA via interolog method of protein-protein interaction prediction.

PubMed

Uddin, Reaz; Tariq, Syeda Sumayya; Azam, Syed Sikander; Wadood, Abdul; Moin, Syed Tarique

2017-08-30

Patently, Protein-Protein Interactions (PPIs) lie at the core of significant biological functions and make the foundation of host-pathogen relationships. Hence, the current study is aimed to use computational biology techniques to predict host-pathogen Protein-Protein Interactions (HP-PPIs) between MRSA and Humans as potential drug targets ultimately proposing new possible inhibitors against them. As a matter of fact this study is based on the Interolog method which implies that homologous proteins retain their ability to interact. A distant homolog approach based on Interolog method was employed to speculate MRSA protein homologs in Humans using PSI-BLAST. In addition the protein interaction partners of these homologs as listed in Database of Interacting Proteins (DIP) were predicted to interact with MRSA as well. Moreover, a direct approach using BLAST was also applied so as to attain further confidence in the strategy. Consequently, the common HP-PPIs predicted by both approaches are suggested as potential drug targets (22%) whereas, the unique HP-PPIs estimated only through distant homolog approach are presented as novel drug targets (12%). Furthermore, the most repeated entry in our results was found to be MRSA Histone Deacetylase (HDAC) which was then modeled using SWISS-MODEL. Eventually, small molecules from ZINC, selected randomly, were docked against HDAC using Auto Dock and are suggested as potential binders (inhibitors) based on their energetic profiles. Thus the current study provides basis for further in-depth analysis of such data which not only include MRSA but other deadly pathogens as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel protein interactions with an actin homolog (MreB) of Helicobacter pylori determined by bacterial two-hybrid system.

PubMed

Zepeda Gurrola, Reyna Cristina; Fu, Yajuan; Rodríguez Luna, Isabel Cristina; Benítez Cardoza, Claudia Guadalupe; López López, María de Jesús; López Vidal, Yolanda; Gutíerrez, Germán Rubén Aguilar; Rodríguez Pérez, Mario A; Guo, Xianwu

2017-08-01

The bacterium Helicobacter pylori infects more than 50% of the world population and causes several gastroduodenal diseases, including gastric cancer. Nevertheless, we still need to explore some protein interactions that may be involved in pathogenesis. MreB, an actin homolog, showed some special characteristics in previous studies, indicating that it could have different functions. Protein functions could be realized via protein-protein interactions. In the present study, the MreB protein from H. pylori 26695 fused with two tags 10×His and GST in tandem was overexpressed and purified from Escherchia coli. The purified recombinant protein was used to perform a pull-down assay with H. pylori 26695 cell lysate. The pulled-down proteins were identified by mass spectrometry (MALDI-TOF), in which the known important proteins related to morphogenesis were absent but several proteins related to pathogenesis process were observed. The bacterial two-hybrid system was further used to evaluate the protein interactions and showed that new interactions of MreB respectively with VacA, UreB, HydB, HylB and AddA were confirmed but the interaction MreB-MreC was not validated. These results indicated that the protein MreB in H. pylori has a distinct interactome, does not participate in cell morphogenesis via MreB-MreC but could be related to pathogenesis. Copyright © 2017 Elsevier GmbH. All rights reserved.

Split-luciferase complementary assay: applications, recent developments, and future perspectives.

PubMed

Azad, Taha; Tashakor, Amin; Hosseinkhani, Saman

2014-09-01

Bioluminescent systems are considered as potent reporter systems for bioanalysis since they have specific characteristics, such as relatively high quantum yields and photon emission over a wide range of colors from green to red. Biochemical events are mostly accomplished through large protein machines. These molecular complexes are built from a few to many proteins organized through their interactions. These protein-protein interactions are vital to facilitate the biological activity of cells. The split-luciferase complementation assay makes the study of two or more interacting proteins possible. In this technique, each of the two domains of luciferase is attached to each partner of two interacting proteins. On interaction of those proteins, luciferase fragments are placed close to each other and form a complemented luciferase, which produces a luminescent signal. Split luciferase is an effective tool for assaying biochemical metabolites, where a domain or an intact protein is inserted into an internally fragmented luciferase, resulting in ligand binding, which causes a change in the emitted signals. We review the various applications of this novel luminescent biosensor in studying protein-protein interactions and assaying metabolites involved in analytical biochemistry, cell communication and cell signaling, molecular biology, and the fate of the whole cell, and show that luciferase-based biosensors are powerful tools that can be applied for diagnostic and therapeutic purposes.

Comparative interactomics: analysis of arabidopsis 14-3-3 complexes reveals highly conserved 14-3-3 interactions between humans and plants.

PubMed

Paul, Anna-Lisa; Liu, Li; McClung, Scott; Laughner, Beth; Chen, Sixue; Ferl, Robert J

2009-04-01

As a first step in the broad characterization of plant 14-3-3 multiprotein complexes in vivo, stringent and specific antibody affinity purification was used to capture 14-3-3s together with their interacting proteins from extracts of Arabidopsis cell suspension cultures. Approximately 120 proteins were identified as potential in vivo 14-3-3 interacting proteins by mass spectrometry of the recovered complexes. Comparison of the proteins in this data set with the 14-3-3 interacting proteins from a similar study in human embryonic kidney cell cultures revealed eight interacting proteins that likely represent reasonably abundant, fundamental 14-3-3 interaction complexes that are highly conserved across all eukaryotes. The Arabidopsis 14-3-3 interaction data set was also compared to a yeast in vivo 14-3-3 interaction data set. Four 14-3-3 interacting proteins are conserved in yeast, humans, and Arabidopsis. Comparisons of the data sets based on biochemical function revealed many additional similarities in the human and Arabidopsis data sets that represent conserved functional interactions, while also leaving many proteins uniquely identified in either Arabidopsis or human cells. In particular, the Arabidopsis interaction data set is enriched for proteins involved in metabolism.

Interaction between Vaccinium bracteatum Thunb. leaf pigment and rice proteins.

PubMed

Wang, Li; Xu, Yuan; Zhou, Sumei; Qian, Haifeng; Zhang, Hui; Qi, Xiguang; Fan, Meihua

2016-03-01

In this study, we investigated the interaction of Vaccinium bracteatum Thunb. leaf (VBTL) pigment and rice proteins. In the presence of rice protein, VBTL pigment antioxidant activity and free polyphenol content decreased by 67.19% and 68.11%, respectively, and L(∗) of the protein-pigment complex decreased significantly over time. L(∗) values of albumin, globulin and glutelin during 60-min pigment exposure decreased by 55.00, 57.14, and 54.30%, respectively, indicating that these proteins had bound to the pigment. A significant difference in protein surface hydrophobicity was observed between rice proteins and pigment-protein complexes, indicating that hydrophobic interaction is a major binding mechanism between VBTL pigment and rice proteins. A significant difference in secondary structures between proteins and protein-pigment complexes was also uncovered, indicating that hydrogen bonding may be another mode of interaction between VBTL pigment and rice proteins. Our results indicate that VBTL pigment can stain rice proteins with hydrophobic and hydrogen interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Detecting protein-protein interactions using Renilla luciferase fusion proteins.

PubMed

Burbelo, Peter D; Kisailus, Adam E; Peck, Jeremy W

2002-11-01

We have developed a novel system designated the luciferase assay for protein detection (LAPD) to study protein-protein interactions. This method involves two protein fusions, a soluble reporter fusion and a fusion for immobilizing the target protein. The soluble reporter is an N-terminal Renilla luciferase fusion protein that exhibits high Renilla luciferase activity. Crude cleared lysates from transfected Cos1 cells that express the Renilla luciferase fusion protein can be used in binding assays with immobilized target proteins. Following incubation and washing, target-bound Renilla luciferase fusion proteins produce light from the coelenterazine substrate, indicating an interaction between the two proteins of interest. As proof of the principle, we reproduced known, transient protein-protein interactions between the Cdc42 GTPase and its effector proteins. GTPase Renilla fusion proteins produced in Cos1 cells were tested with immobilized recombinant GST-N-WASP and CEP5 effector proteins. Using this assay, we could detect specific interactions of Cdc42 with these effector proteins in approximately 50 min. The specificity of these interactions was demonstrated by showing that they were GTPase-specific and GTP-dependent and not seen with other unrelated target proteins. These results suggest that the LAPD method, which is both rapid and sensitive, may have research and practical applications.

Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

DOE PAGES

Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

2006-01-01

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

CH/π Interactions in Carbohydrate Recognition.

PubMed

Spiwok, Vojtěch

2017-06-23

Many carbohydrate-binding proteins contain aromatic amino acid residues in their binding sites. These residues interact with carbohydrates in a stacking geometry via CH/π interactions. These interactions can be found in carbohydrate-binding proteins, including lectins, enzymes and carbohydrate transporters. Besides this, many non-protein aromatic molecules (natural as well as artificial) can bind saccharides using these interactions. Recent computational and experimental studies have shown that carbohydrate-aromatic CH/π interactions are dispersion interactions, tuned by electrostatics and partially stabilized by a hydrophobic effect in solvated systems.

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Network organization of the human autophagy system.

PubMed

Behrends, Christian; Sowa, Mathew E; Gygi, Steven P; Harper, J Wade

2010-07-01

Autophagy, the process by which proteins and organelles are sequestered in autophagosomal vesicles and delivered to the lysosome/vacuole for degradation, provides a primary route for turnover of stable and defective cellular proteins. Defects in this system are linked with numerous human diseases. Although conserved protein kinase, lipid kinase and ubiquitin-like protein conjugation subnetworks controlling autophagosome formation and cargo recruitment have been defined, our understanding of the global organization of this system is limited. Here we report a proteomic analysis of the autophagy interaction network in human cells under conditions of ongoing (basal) autophagy, revealing a network of 751 interactions among 409 candidate interacting proteins with extensive connectivity among subnetworks. Many new autophagy interaction network components have roles in vesicle trafficking, protein or lipid phosphorylation and protein ubiquitination, and affect autophagosome number or flux when depleted by RNA interference. The six ATG8 orthologues in humans (MAP1LC3/GABARAP proteins) interact with a cohort of 67 proteins, with extensive binding partner overlap between family members, and frequent involvement of a conserved surface on ATG8 proteins known to interact with LC3-interacting regions in partner proteins. These studies provide a global view of the mammalian autophagy interaction landscape and a resource for mechanistic analysis of this critical protein homeostasis pathway.

Effect of fat content and homogenization under conventional or ultra-high-pressure conditions on interactions between proteins in rennet curds.

PubMed

Zamora, A; Trujillo, A J; Armaforte, E; Waldron, D S; Kelly, A L

2012-09-01

The objective of this study was to investigate the influence of conventional and ultra-high-pressure homogenization on interactions between proteins within drained rennet curds. The effect of fat content of milk (0.0, 1.8, or 3.6%) and homogenization treatment on dissociation of proteins by different chemical agents was thus studied. Increasing the fat content of raw milk increased levels of unbound whey proteins and calcium-bonded caseins in curds; in contrast, hydrophobic interactions and hydrogen bonds were inhibited. Both homogenization treatments triggered the incorporation of unbound whey proteins in the curd, and of caseins through ionic bonds involving calcium salts. Conventional homogenization-pasteurization enhanced interactions between caseins through hydrogen bonds and hydrophobic interactions. In contrast, ultra-high-pressure homogenization impaired hydrogen bonding, led to the incorporation of both whey proteins and caseins through hydrophobic interactions and increased the amount of unbound caseins. Thus, both homogenization treatments provoked changes in the protein interactions within rennet curds; however, the nature of the changes depended on the homogenization conditions. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Bifunctional fusion proteins of calmodulin and protein A as affinity ligands in protein purification and in the study of protein-protein interactions.

PubMed

Hentz, N G; Daunert, S

1996-11-15

An affinity chromatography system is described that incorporates a genetically designed bifunctional affinity ligand. The utility of the system in protein purification and in the study of protein-protein interactions is demonstrated by using the interaction between protein A and the heat shock protein DnaK as a model system. The bifunctional affinity ligand was developed by genetically fusing calmodulin (CaM) to protein A (ProtA). The dual functionality of protein A-calmodulin (ProtA-CaM) stems from the molecular recognition properties of the two components of the fusion protein. In particular, CaM serves as the anchoring component by virtue of its binding properties toward phenothiazine. Thus, the ProtA-CaM can be immobilized on a solid support containing phenothiazine from the C-terminal domain of the fusion protein. Protein A is at the N-terminal domain of the fusion protein and serves as the affinity site for DnaK. While DnaK binds specifically to the protein A domain of the bifunctional ligand, it is released upon addition of ATP and under very mild conditions (pH 7.0). In addition to obtaining highly purified DnaK, this system is very rugged in terms of its performance. The proteinaceous bifunctional affinity ligand can be easily removed by addition of EGTA, and fresh ProtA-CaM can be easily reloaded onto the column. This allows for a facile regeneration of the affinity column because the phenothiazine-silica support matrix is stable for long periods of time under a variety of conditions. This study also demonstrates that calmodulin fusions can provide a new approach to study protein-protein interactions. Indeed, the ProtA-CaM fusion protein identified DnaK as a cellular component that interacts with protein A from among the thousands of proteins present in Escherichia coli.

A Novel Biclustering Approach to Association Rule Mining for Predicting HIV-1–Human Protein Interactions

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal; Bandyopadhyay, Sanghamitra

2012-01-01

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed. PMID:22539940

Potential disruption of protein-protein interactions by graphene oxide

NASA Astrophysics Data System (ADS)

Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong

2016-06-01

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Potential disruption of protein-protein interactions by graphene oxide.

PubMed

Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong

2016-06-14

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Protein interactions in 3D: from interface evolution to drug discovery.

PubMed

Winter, Christof; Henschel, Andreas; Tuukkanen, Anne; Schroeder, Michael

2012-09-01

Over the past 10years, much research has been dedicated to the understanding of protein interactions. Large-scale experiments to elucidate the global structure of protein interaction networks have been complemented by detailed studies of protein interaction interfaces. Understanding the evolution of interfaces allows one to identify convergently evolved interfaces which are evolutionary unrelated but share a few key residues and hence have common binding partners. Understanding interaction interfaces and their evolution is an important basis for pharmaceutical applications in drug discovery. Here, we review the algorithms and databases on 3D protein interactions and discuss in detail applications in interface evolution, drug discovery, and interface prediction. Copyright © 2012 Elsevier Inc. All rights reserved.

Protein-Phospholipid Interactions in Nonclassical Protein Secretion: Problem and Methods of Study

PubMed Central

Prudovsky, Igor; Kumar, Thallapuranam Krishnaswamy Suresh; Sterling, Sarah; Neivandt, David

2013-01-01

Extracellular proteins devoid of signal peptides use nonclassical secretion mechanisms for their export. These mechanisms are independent of the endoplasmic reticulum and Golgi. Some nonclassically released proteins, particularly fibroblast growth factors (FGF) 1 and 2, are exported as a result of their direct translocation through the cell membrane. This process requires specific interactions of released proteins with membrane phospholipids. In this review written by a cell biologist, a structural biologist and two membrane engineers, we discuss the following subjects: (i) Phenomenon of nonclassical protein release and its biological significance; (ii) Composition of the FGF1 multiprotein release complex (MRC); (iii) The relationship between FGF1 export and acidic phospholipid externalization; (iv) Interactions of FGF1 MRC components with acidic phospholipids; (v) Methods to study the transmembrane translocation of proteins; (vi) Membrane models to study nonclassical protein release. PMID:23396106

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterization of the interactions between protein and carbon black.

PubMed

Chen, Tzu-Tao; Chuang, Kai-Jen; Chiang, Ling-Ling; Chen, Chun-Chao; Yeh, Chi-Tai; Wang, Liang-Shun; Gregory, Clive; Jones, Tim; BéruBé, Kelly; Lee, Chun-Nin; Chuang, Hsiao-Chi; Cheng, Tsun-Jen

2014-01-15

A considerable amount of studies have been conducted to investigate the interactions of biological fluids with nanoparticle surfaces, which exhibit a high affinity for proteins and particles. However, the mechanisms underlying these interactions have not been elucidated, particularly as they relate to human health. Using bovine serum albumin (BSA) and mice bronchoalveolar lavage fluid (BALF) as models for protein-particle conjugates, we characterized the physicochemical modifications of carbon blacks (CB) with 23nm or 65nm in diameter after protein treatment. Adsorbed BALF-containing proteins were quantified and identified by pathways, biological analyses and protein classification. Significant modifications of the physicochemistry of CB were induced by the addition of BSA. Enzyme modulators and hydrolase predominately interacted with CB, with protein-to-CB interactions that were associated with the coagulation pathways. Additionally, our results revealed that an acute-phase response could be activated by these proteins. With regard to human health, the present study revealed that the CB can react with proteins (∼55kDa and 70kDa) after inhalation and may modify the functional structures of lung proteins, leading to the activation of acute-inflammatory responses in the lungs. Copyright © 2013 Elsevier B.V. All rights reserved.

Population reversal driven by unrestrained interactions in molecular dynamics simulations: A dialanine model

NASA Astrophysics Data System (ADS)

Pullara, Filippo; Ignacio, J., General

2015-10-01

Standard Molecular Dynamics simulations (MD) are usually performed under periodic boundary conditions using the well-established "Ewald summation". This implies that the distance among each element in a given lattice cell and its corresponding element in another cell, as well as their relative orientations, are constant. Consequently, protein-protein interactions between proteins in different cells—important in many biological activities, such as protein cooperativity and physiological/pathological aggregation—are severely restricted, and features driven by protein-protein interactions are lost. The consequences of these restrictions, although conceptually understood and mentioned in the literature, have not been quantitatively studied before. The effect of protein-protein interactions on the free energy landscape of a model system, dialanine, is presented. This simple system features a free energy diagram with well-separated minima. It is found that, in the case of absence of peptide-peptide (p-p) interactions, the ψ = 150° dihedral angle determines the most energetically favored conformation (global free-energy minimum). When strong p-p interactions are induced, the global minimum switches to the ψ = 0° conformation. This shows that the free-energy landscape of an individual molecule is dramatically affected by the presence of other freely interacting molecules of its same type. Results of the study suggest how taking into account p-p interactions in MD allows having a more realistic picture of system activity and functional conformations.

Select host cell proteins coelute with monoclonal antibodies in protein A chromatography.

PubMed

Nogal, Bartek; Chhiba, Krishan; Emery, Jefferson C

2012-01-01

The most significant factor contributing to the presence of host cell protein (HCP) impurities in Protein A chromatography eluates is their association with the product monoclonal antibodies (mAbs) has been reported previously, and it has been suggested that more efficacious column washes may be developed by targeting the disruption of the mAbs-HCP interaction. However, characterization of this interaction is not straight forward as it is likely to involve multiple proteins and/or types of interaction. This work is an attempt to begin to understand the contribution of HCP subpopulations and/or mAb interaction propensity to the variability in HCP levels in the Protein A eluate. We performed a flowthrough (FT) recycling study with product respiking using two antibody molecules of apparently different HCP interaction propensities. In each case, the ELISA assay showed depletion of select subpopulations of HCP in Protein A eluates in subsequent column runs, while the feedstock HCP in the FTs remained unchanged from its native harvested cell culture fluid (HCCF) levels. In a separate study, the final FT from each molecule's recycling study was cross-spiked with various mAbs. In this case, Protein A eluate levels remained low for all but two molecules which were known as having high apparent HCP interaction propensity. The results of these studies suggest that mAbs may preferentially bind to select subsets of HCPs, and the degree of interaction and/or identity of the associated HCPs may vary depending on the mAb. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Quantitative study of protein-protein interactions by quartz nanopipettes.

PubMed

Tiwari, Purushottam Babu; Astudillo, Luisana; Miksovska, Jaroslava; Wang, Xuewen; Li, Wenzhi; Darici, Yesim; He, Jin

2014-09-07

In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions.

Toward a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chhabra, S.R.; Joachimiak, M.P.; Petzold, C.J.

Protein–protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study E. coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio 5 vulgaris Hildenborough, a model anaerobe and sulfate reducer. In this paper we present the first attempt to identify protein-protein interactions in an obligate anaerobic bacterium. We used suicide vector-assisted chromosomal modification of 12 open reading frames encoded by this sulfate reducer to append an eight amino acid affinity tag to themore » carboxy-terminus of the chosen proteins. Three biological replicates of the 10 ‘pulled-down’ proteins were separated and analyzed using liquid chromatography-mass spectrometry. Replicate agreement ranged between 35% and 69%. An interaction network among 12 bait and 90 prey proteins was reconstructed based on 134 bait-prey interactions computationally identified to be of high confidence. We discuss the biological significance of several unique metabolic features of D. vulgaris revealed by this protein-protein interaction data 15 and protein modifications that were observed. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.« less

Viruses are a dominant driver of protein adaptation in mammals.

PubMed

Enard, David; Cai, Le; Gwennap, Carina; Petrov, Dmitri A

2016-05-17

Viruses interact with hundreds to thousands of proteins in mammals, yet adaptation against viruses has only been studied in a few proteins specialized in antiviral defense. Whether adaptation to viruses typically involves only specialized antiviral proteins or affects a broad array of virus-interacting proteins is unknown. Here, we analyze adaptation in ~1300 virus-interacting proteins manually curated from a set of 9900 proteins conserved in all sequenced mammalian genomes. We show that viruses (i) use the more evolutionarily constrained proteins within the cellular functions they interact with and that (ii) despite this high constraint, virus-interacting proteins account for a high proportion of all protein adaptation in humans and other mammals. Adaptation is elevated in virus-interacting proteins across all functional categories, including both immune and non-immune functions. We conservatively estimate that viruses have driven close to 30% of all adaptive amino acid changes in the part of the human proteome conserved within mammals. Our results suggest that viruses are one of the most dominant drivers of evolutionary change across mammalian and human proteomes.

Viruses are a dominant driver of protein adaptation in mammals

PubMed Central

Enard, David; Cai, Le; Gwennap, Carina; Petrov, Dmitri A

2016-01-01

Viruses interact with hundreds to thousands of proteins in mammals, yet adaptation against viruses has only been studied in a few proteins specialized in antiviral defense. Whether adaptation to viruses typically involves only specialized antiviral proteins or affects a broad array of virus-interacting proteins is unknown. Here, we analyze adaptation in ~1300 virus-interacting proteins manually curated from a set of 9900 proteins conserved in all sequenced mammalian genomes. We show that viruses (i) use the more evolutionarily constrained proteins within the cellular functions they interact with and that (ii) despite this high constraint, virus-interacting proteins account for a high proportion of all protein adaptation in humans and other mammals. Adaptation is elevated in virus-interacting proteins across all functional categories, including both immune and non-immune functions. We conservatively estimate that viruses have driven close to 30% of all adaptive amino acid changes in the part of the human proteome conserved within mammals. Our results suggest that viruses are one of the most dominant drivers of evolutionary change across mammalian and human proteomes. DOI: http://dx.doi.org/10.7554/eLife.12469.001 PMID:27187613

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

Interactions of glycine betaine with proteins: insights from volume and compressibility measurements.

PubMed

Shek, Yuen Lai; Chalikian, Tigran V

2013-01-29

We report the first application of volume and compressibility measurements to characterization of interactions between cosolvents (osmolytes) and globular proteins. Specifically, we measure the partial molar volumes and adiabatic compressibilities of cytochrome c, ribonuclease A, lysozyme, and ovalbumin in aqueous solutions of the stabilizing osmolyte glycine betaine (GB) at concentrations between 0 and 4 M. The fact that globular proteins do not undergo any conformational transitions in the presence of GB provides an opportunity to study the interactions of GB with proteins in their native states within the entire range of experimentally accessible GB concentrations. We analyze our resulting volumetric data within the framework of a statistical thermodynamic model in which each instance of GB interaction with a protein is viewed as a binding reaction that is accompanied by release of four water molecules. From this analysis, we calculate the association constants, k, as well as changes in volume, ΔV(0), and adiabatic compressibility, ΔK(S0), accompanying each GB-protein association event in an ideal solution. By comparing these parameters with similar characteristics determined for low-molecular weight analogues of proteins, we conclude that there are no significant cooperative effects involved in interactions of GB with any of the proteins studied in this work. We also evaluate the free energies of direct GB-protein interactions. The energetic properties of GB-protein association appear to scale with the size of the protein. For all proteins, the highly favorable change in free energy associated with direct protein-cosolvent interactions is nearly compensated by an unfavorable free energy of cavity formation (excluded volume effect), yielding a modestly unfavorable free energy for the transfer of a protein from water to a GB/water mixture.

Adaptation of Tri-molecular fluorescence complementation allows assaying of regulatory Csr RNA-protein interactions in bacteria.

PubMed

Gelderman, Grant; Sivakumar, Anusha; Lipp, Sarah; Contreras, Lydia

2015-02-01

sRNAs play a significant role in controlling and regulating cellular metabolism. One of the more interesting aspects of certain sRNAs is their ability to make global changes in the cell by interacting with regulatory proteins. In this work, we demonstrate the use of an in vivo Tri-molecular Fluorescence Complementation assay to detect and visualize the central regulatory sRNA-protein interaction of the Carbon Storage Regulatory system in E. coli. The Carbon Storage Regulator consists primarily of an RNA binding protein, CsrA, that alters the activity of mRNA targets and of an sRNA, CsrB, that modulates the activity of CsrA. We describe the construction of a fluorescence complementation system that detects the interactions between CsrB and CsrA. Additionally, we demonstrate that the intensity of the fluorescence of this system is able to detect changes in the affinity of the CsrB-CsrA interaction, as caused by mutations in the protein sequence of CsrA. While previous methods have adopted this technique to study mRNA or RNA localization, this is the first attempt to use this technique to study the sRNA-protein interaction directly in bacteria. This method presents a potentially powerful tool to study complex bacterial RNA protein interactions in vivo. © 2014 Wiley Periodicals, Inc.

An efficient way of studying protein-protein interactions involving HIF-α, c-Myc, and Sp1.

PubMed

To, Kenneth K-W; Huang, L Eric

2013-01-01

Protein-protein interaction is an essential biochemical event that mediates various cellular processes including gene expression, intracellular signaling, and intercellular interaction. Understanding such interaction is key to the elucidation of mechanisms of cellular processes in biology and diseases. The hypoxia-inducible transcription factor HIF-1α possesses a non-transcriptional activity that competes with c-Myc for Sp1 binding, whereas its isoform HIF-2α lacks Sp1-binding activity due to phosphorylation. Here, we describe the use of in vitro translation to effectively investigate the dynamics of protein-protein interactions among HIF-1α, c-Myc, and Sp1 and to demonstrate protein phosphorylation as a molecular determinant that functionally distinguishes HIF-2α from HIF-1α.

Quantitative interactome reveals that porcine reproductive and respiratory syndrome virus nonstructural protein 2 forms a complex with viral nucleocapsid protein and cellular vimentin.

PubMed

Song, Tao; Fang, Liurong; Wang, Dang; Zhang, Ruoxi; Zeng, Songlin; An, Kang; Chen, Huanchun; Xiao, Shaobo

2016-06-16

Porcine reproductive and respiratory syndrome virus (PRRSV) is an Arterivirus that has heavily impacted the global swine industry. The PRRSV nonstructural protein 2 (nsp2) plays crucial roles in viral replication and host immune regulation, most likely by interacting with viral or cellular proteins that have not yet been identified. In this study, a quantitative interactome approach based on immunoprecipitation and stable isotope labeling with amino acids in cell culture (SILAC) was performed to identify nsp2-interacting proteins in PRRSV-infected cells with an nsp2-specific monoclonal antibody. Nine viral proteins and 62 cellular proteins were identified as potential nsp2-interacting partners. Our data demonstrate that the PRRSV nsp1α, nsp1β, and nucleocapsid proteins all interact directly with nsp2. Nsp2-interacting cellular proteins were classified into different functional groups and an interactome network of nsp2 was generated. Interestingly, cellular vimentin, a known receptor for PRRSV, forms a complex with nsp2 by using viral nucleocapsid protein as an intermediate. Taken together, the nsp2 interactome under the condition of virus infection clarifies a role of nsp2 in PRRSV replication and immune evasion. Viral proteins must interact with other virus-encoded proteins and/or host cellular proteins to function, and interactome analysis is an ideal approach for identifying such interacting proteins. In this study, we used the quantitative interactome methodology to identify the viral and cellular proteins that potentially interact with the nonstructural protein 2 (nsp2) of porcine reproductive and respiratory syndrome virus (PRRSV) under virus infection conditions, thus providing a rich source of potential viral and cellular interaction partners for PRRSV nsp2. Based on the interactome data, we further demonstrated that PRRSV nsp2 and nucleocapsid protein together with cellular vimentin, form a complex that may be essential for viral attachment and replication, which partly explains the role of nsp2 in PRRSV replication and immune evasion. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds.

PubMed

Chen, Lei; Zhang, Yu-Hang; Zheng, Mingyue; Huang, Tao; Cai, Yu-Dong

2016-12-01

Compound-protein interactions play important roles in every cell via the recognition and regulation of specific functional proteins. The correct identification of compound-protein interactions can lead to a good comprehension of this complicated system and provide useful input for the investigation of various attributes of compounds and proteins. In this study, we attempted to understand this system by extracting properties from both proteins and compounds, in which proteins were represented by gene ontology and KEGG pathway enrichment scores and compounds were represented by molecular fragments. Advanced feature selection methods, including minimum redundancy maximum relevance, incremental feature selection, and the basic machine learning algorithm random forest, were used to analyze these properties and extract core factors for the determination of actual compound-protein interactions. Compound-protein interactions reported in The Binding Databases were used as positive samples. To improve the reliability of the results, the analytic procedure was executed five times using different negative samples. Simultaneously, five optimal prediction methods based on a random forest and yielding maximum MCCs of approximately 77.55 % were constructed and may be useful tools for the prediction of compound-protein interactions. This work provides new clues to understanding the system of compound-protein interactions by analyzing extracted core features. Our results indicate that compound-protein interactions are related to biological processes involving immune, developmental and hormone-associated pathways.

Manipulating Protein-Protein Interactions in Nonribosomal Peptide Synthetase Type II Peptidyl Carrier Proteins.

PubMed

Jaremko, Matt J; Lee, D John; Patel, Ashay; Winslow, Victoria; Opella, Stanley J; McCammon, J Andrew; Burkart, Michael D

2017-10-10

In an effort to elucidate and engineer interactions in type II nonribosomal peptide synthetases, we analyzed biomolecular recognition between the essential peptidyl carrier proteins and adenylation domains using nuclear magnetic resonance (NMR) spectroscopy, molecular dynamics, and mutational studies. Three peptidyl carrier proteins, PigG, PltL, and RedO, in addition to their cognate adenylation domains, PigI, PltF, and RedM, were investigated for their cross-species activity. Of the three peptidyl carrier proteins, only PigG showed substantial cross-pathway activity. Characterization of the novel NMR solution structure of holo-PigG and molecular dynamics simulations of holo-PltL and holo-PigG revealed differences in structures and dynamics of these carrier proteins. NMR titration experiments revealed perturbations of the chemical shifts of the loop 1 residues of these peptidyl carrier proteins upon their interaction with the adenylation domain. These experiments revealed a key region for the protein-protein interaction. Mutational studies supported the role of loop 1 in molecular recognition, as mutations to this region of the peptidyl carrier proteins significantly modulated their activities.

Polypyrimidine tract-binding protein influences negative strand RNA synthesis of dengue virus.

PubMed

Jiang, Linbin; Yao, Huiling; Duan, Xiaoqun; Lu, Xi; Liu, Yongming

2009-07-24

Flavivirus non-structural protein 4A (NS4A) induces membrane rearrangements to form viral replication complex and functions as interferon antagonist. However, other non-structural roles of NS4A protein in relation to virus life-cycle are poorly defined. This study elucidated if dengue virus (DENV) NS4A protein interacts with host proteins and contributes to viral pathogenesis by screening human liver cDNA yeast-two-hybrid library. Our study identified polypyrimidine tract-binding protein (PTB) as a novel interacting partner of DENV NS4A protein. We reported for the first time that PTB influenced DENV production. Gene-silencing studies showed that PTB did not have an effect on DENV entry and DENV RNA translation. Further functional studies revealed that PTB influenced DENV production by modulating negative strand RNA synthesis. This is the first study that enlightens the interaction of DENV NS4A protein with PTB, in addition to demonstrating the novel role of PTB in relation to mosquito-borne flavivirus life-cycle.

Evidence for the interaction of the regulatory protein Ki-1/57 with p53 and its interacting proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nery, Flavia C.; Departamento de Genetica e Evolucao, Universidade Estadual de Campinas, Campinas, SP; Rui, Edmilson

Ki-1/57 is a cytoplasmic and nuclear phospho-protein of 57 kDa and interacts with the adaptor protein RACK1, the transcription factor MEF2C, and the chromatin remodeling factor CHD3, suggesting that it might be involved in the regulation of transcription. Here, we describe yeast two-hybrid studies that identified a total of 11 proteins interacting with Ki-1/57, all of which interact or are functionally associated with p53 or other members of the p53 family of proteins. We further found that Ki-1/57 is able to interact with p53 itself in the yeast two-hybrid system when the interaction was tested directly. This interaction could bemore » confirmed by pull down assays with purified proteins in vitro and by reciprocal co-immunoprecipitation assays from the human Hodgkin analogous lymphoma cell line L540. Furthermore, we found that the phosphorylation of p53 by PKC abolishes its interaction with Ki-1/57 in vitro.« less

Analysis of solute-protein interactions and solute-solute competition by zonal elution affinity chromatography.

PubMed

Tao, Pingyang; Poddar, Saumen; Sun, Zuchen; Hage, David S; Chen, Jianzhong

2018-02-02

Many biological processes involve solute-protein interactions and solute-solute competition for protein binding. One method that has been developed to examine these interactions is zonal elution affinity chromatography. This review discusses the theory and principles of zonal elution affinity chromatography, along with its general applications. Examples of applications that are examined include the use of this method to estimate the relative extent of solute-protein binding, to examine solute-solute competition and displacement from proteins, and to measure the strength of these interactions. It is also shown how zonal elution affinity chromatography can be used in solvent and temperature studies and to characterize the binding sites for solutes on proteins. In addition, several alternative applications of zonal elution affinity chromatography are discussed, which include the analysis of binding by a solute with a soluble binding agent and studies of allosteric effects. Other recent applications that are considered are the combined use of immunoextraction and zonal elution for drug-protein binding studies, and binding studies that are based on immobilized receptors or small targets. Copyright © 2018 Elsevier Inc. All rights reserved.

Detecting Coevolution in Mammalian Sperm–Egg Fusion Proteins

PubMed Central

CLAW, KATRINA G.; GEORGE, RENEE D.; SWANSON, WILLIE J.

2018-01-01

SUMMARY Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm–egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm–egg proteins; interacting sperm–egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm–egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm–egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm–egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm–egg protein pairs. PMID:24644026

Detecting coevolution in mammalian sperm-egg fusion proteins.

PubMed

Claw, Katrina G; George, Renee D; Swanson, Willie J

2014-06-01

Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm-egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm-egg proteins; interacting sperm-egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm-egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm-egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm-egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm-egg protein pairs. © 2014 Wiley Periodicals, Inc.

NOXclass: prediction of protein-protein interaction types.

PubMed

Zhu, Hongbo; Domingues, Francisco S; Sommer, Ingolf; Lengauer, Thomas

2006-01-19

Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. Six interface properties have been investigated on a dataset of 243 protein interactions. The six properties have been combined using a support vector machine algorithm, resulting in NOXclass, a classifier for distinguishing obligate, non-obligate and crystal packing interactions. We achieve an accuracy of 91.8% for the classification of these three types of interactions using a leave-one-out cross-validation procedure. NOXclass allows the interpretation and analysis of protein quaternary structures. In particular, it generates testable hypotheses regarding the nature of protein-protein interactions, when experimental results are not available. We expect this server will benefit the users of protein structural models, as well as protein crystallographers and NMR spectroscopists. A web server based on the method and the datasets used in this study are available at http://noxclass.bioinf.mpi-inf.mpg.de/.

Detection and characterization of protein interactions in vivo by a simple live-cell imaging method.

PubMed

Gallego, Oriol; Specht, Tanja; Brach, Thorsten; Kumar, Arun; Gavin, Anne-Claude; Kaksonen, Marko

2013-01-01

Over the last decades there has been an explosion of new methodologies to study protein complexes. However, most of the approaches currently used are based on in vitro assays (e.g. nuclear magnetic resonance, X-ray, electron microscopy, isothermal titration calorimetry etc). The accurate measurement of parameters that define protein complexes in a physiological context has been largely limited due to technical constrains. Here, we present PICT (Protein interactions from Imaging of Complexes after Translocation), a new method that provides a simple fluorescence microscopy readout for the study of protein complexes in living cells. We take advantage of the inducible dimerization of FK506-binding protein (FKBP) and FKBP-rapamycin binding (FRB) domain to translocate protein assemblies to membrane associated anchoring platforms in yeast. In this assay, GFP-tagged prey proteins interacting with the FRB-tagged bait will co-translocate to the FKBP-tagged anchor sites upon addition of rapamycin. The interactions are thus encoded into localization changes and can be detected by fluorescence live-cell imaging under different physiological conditions or upon perturbations. PICT can be automated for high-throughput studies and can be used to quantify dissociation rates of protein complexes in vivo. In this work we have used PICT to analyze protein-protein interactions from three biological pathways in the yeast Saccharomyces cerevisiae: Mitogen-activated protein kinase cascade (Ste5-Ste11-Ste50), exocytosis (exocyst complex) and endocytosis (Ede1-Syp1).

An "on-matrix" digestion procedure for AP-MS experiments dissects the interplay between complex-conserved and serotype-specific reactivities in Dengue virus-human plasma interactome.

PubMed

Ramos, Yassel; Huerta, Vivian; Martín, Dayron; Palomares, Sucel; Yero, Alexis; Pupo, Dianne; Gallien, Sebastien; Martín, Alejandro M; Pérez-Riverol, Yasset; Sarría, Mónica; Guirola, Osmany; Chinea, Glay; Domon, Bruno; González, Luis Javier

2017-07-13

The interactions between the four Dengue virus (DENV) serotypes and plasma proteins are crucial in the initial steps of viral infection to humans. Affinity purification combined with quantitative mass spectrometry analysis, has become one of the most powerful tools for the investigation on novel protein-protein interactions. Using this approach, we report here that a significant number of bait-interacting proteins do not dissociate under standard elution conditions, i.e. acid pH and chaotropic agents, and that this problem can be circumvented by using the "on-matrix" digestion procedure described here. This procedure enabled the identification of 16 human plasma proteins interacting with domain III from the envelope protein of DENV serotypes 1, 3 and 4 that would have not been detected otherwise and increased the known DIIIE interactors in human plasma to 59 proteins. Selected Reaction Monitoring analysis evidenced DENV interactome in human plasma is rather conserved although significant differences on the reactivity of viral serotypes with specific proteins do exist. A comparison between the serotype-dependent profile of reactivity and the conservation pattern of amino acid residues suggests an evolutionary selection of highly conserved interactions with the host and other interactions mediated for surface regions of higher variability. False negative results on the identification of interacting proteins in pull-down experiments compromise the subsequent interpretation of results and the formulation of a working hypothesis for the derived future work. In this study we demonstrate the presence of bait-interacting proteins reluctant to dissociate under elution conditions of acid pH and presence of chaotropics. We propose the direct proteolytic digestion of proteins while still bound to the affinity matrix ("on-matrix" digestion) and evaluate the impact of this methodology in the comparative study of the interactome of the four serotypes of Dengue virus mediated by the domain III of the viral envelope glycoprotein. Fifty nine proteins were identified as putative interaction partners of Dengue virus (IPs) either due to direct binding or by co-isolation with interacting proteins. Collectively the IPs identified from the pull-down with the recombinant domain III proteins representing the four viral serotypes, 29% were identified only after "on-matrix" digestion which demonstrate the usefulness of this method of recovering bait-bound proteins. Results highlight a particular importance of "on-matrix" digestion procedure for comparative studies where a stronger interaction with one of the interest baits could prevent a bound protein to elute under standard conditions thus leading to misinterpretation as absent in the interactome of this particular bait. The analysis of the Interaction Network indicates that Dengue virus interactome mediated by the domain III of the envelope protein is rather conserved in the viral complex suggesting a key role of these interactions for viral infection thus making candidates to explore for potential biomarkers of clinical outcome in DENV-caused disease. Interestingly, some particular IPs exhibit significant differences in the strength of the interaction with the viral serotypes representing interactions that involve more variable regions in the surface of the domain III. Since such variable regions are the consequence of the interaction with antibodies generated by human immune response; this result relates the interaction with proteins from human plasma with the interplay of the virus and the human immune system. Copyright © 2017 Elsevier B.V. All rights reserved.

Hexahistidine (6xHis) fusion-based assays for protein-protein interactions.

PubMed

Puckett, Mary C

2015-01-01

Fusion-protein tags provide a useful method to study protein-protein interactions. One widely used fusion tag is hexahistidine (6xHis). This tag has unique advantages over others due to its small size and the relatively low abundance of naturally occurring consecutive histidine repeats. 6xHis tags can interact with immobilized metal cations to provide for the capture of proteins and protein complexes of interest. In this chapter, a description of the benefits and uses of 6xHis-fusion proteins as well as a detailed method for performing a 6xHis-pulldown assay are described.

I-DIRT, a general method for distinguishing between specific and nonspecific protein interactions.

PubMed

Tackett, Alan J; DeGrasse, Jeffrey A; Sekedat, Matthew D; Oeffinger, Marlene; Rout, Michael P; Chait, Brian T

2005-01-01

Isolation of protein complexes via affinity-tagged proteins provides a powerful tool for studying biological systems, but the technique is often compromised by co-enrichment of nonspecifically interacting proteins. We describe a new technique (I-DIRT) that distinguishes contaminants from bona fide interactors in immunopurifications, overcoming this most challenging problem in defining protein complexes. I-DIRT will be of broad value for studying protein complexes in biological systems that can be metabolically labeled.

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study.

PubMed

A Santos, Jose C; Nassif, Houssam; Page, David; Muggleton, Stephen H; E Sternberg, Michael J

2012-07-11

There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. In addition to confirming literature results, ProGolem's model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners.

Quantitative study of protein-protein interactions by quartz nanopipettes

NASA Astrophysics Data System (ADS)

Tiwari, Purushottam Babu; Astudillo, Luisana; Miksovska, Jaroslava; Wang, Xuewen; Li, Wenzhi; Darici, Yesim; He, Jin

2014-08-01

In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions.In this report, protein-modified quartz nanopipettes were used to quantitatively study protein-protein interactions in attoliter sensing volumes. As shown by numerical simulations, the ionic current through the conical-shaped nanopipette is very sensitive to the surface charge variation near the pore mouth. With the appropriate modification of negatively charged human neuroglobin (hNgb) onto the inner surface of a nanopipette, we were able to detect concentration-dependent current change when the hNgb-modified nanopipette tip was exposed to positively charged cytochrome c (Cyt c) with a series of concentrations in the bath solution. Such current change is due to the adsorption of Cyt c to the inner surface of the nanopipette through specific interactions with hNgb. In contrast, a smaller current change with weak concentration dependence was observed when Cyt c was replaced with lysozyme, which does not specifically bind to hNgb. The equilibrium dissociation constant (KD) for the Cyt c-hNgb complex formation was derived and the value matched very well with the result from surface plasmon resonance measurement. This is the first quantitative study of protein-protein interactions by a conical-shaped nanopore based on charge sensing. Our results demonstrate that nanopipettes can potentially be used as a label-free analytical tool to quantitatively characterize protein-protein interactions. Electronic supplementary information (ESI) available: Determination of nanopipette diameter; surface modification scheme; numerical simulation; noise analysis; SPR experiments. See DOI: 10.1039/c4nr02964j

Human Dopamine Receptors Interaction Network (DRIN): a systems biology perspective on topology, stability and functionality of the network.

PubMed

Podder, Avijit; Jatana, Nidhi; Latha, N

2014-09-21

Dopamine receptors (DR) are one of the major neurotransmitter receptors present in human brain. Malfunctioning of these receptors is well established to trigger many neurological and psychiatric disorders. Taking into consideration that proteins function collectively in a network for most of the biological processes, the present study is aimed to depict the interactions between all dopamine receptors following a systems biology approach. To capture comprehensive interactions of candidate proteins associated with human dopamine receptors, we performed a protein-protein interaction network (PPIN) analysis of all five receptors and their protein partners by mapping them into human interactome and constructed a human Dopamine Receptors Interaction Network (DRIN). We explored the topology of dopamine receptors as molecular network, revealing their characteristics and the role of central network elements. More to the point, a sub-network analysis was done to determine major functional clusters in human DRIN that govern key neurological pathways. Besides, interacting proteins in a pathway were characterized and prioritized based on their affinity for utmost drug molecules. The vulnerability of different networks to the dysfunction of diverse combination of components was estimated under random and direct attack scenarios. To the best of our knowledge, the current study is unique to put all five dopamine receptors together in a common interaction network and to understand the functionality of interacting proteins collectively. Our study pinpointed distinctive topological and functional properties of human dopamine receptors that have helped in identifying potential therapeutic drug targets in the dopamine interaction network. Copyright © 2014 Elsevier Ltd. All rights reserved.

Exploration of protein-protein interaction effects on α-2-macroglobulin in an inhibition of serine protease through gene expression and molecular simulations studies.

PubMed

Sivakamavalli, Jeyachandran; Selvaraj, Chandrabose; Singh, Sanjeev Kumar; Vaseeharan, Baskaralingam

2014-01-01

In Prophenoloxidase (ProPO) cascade, two targets namely serine protease and α-2-macroglobulin are key regulators involved in the defense system of crustaceans. In biological systems, routine role of cell systems requires the understanding in protein-protein interactions through experimental and theoretical concepts, which might yield useful insights into the cellular responses. Response of cells to regulating the immune system is governed by the interactions-involved biomolecular simulations. Unfortunately, studies on the inhibitors (SP and α-2M) that negatively regulate the proPO system or melanization in penaeid shrimp are not yet available. In order to understand how these interactions change the proPO mechanism in Indian white shrimp Fenneropenaeus indicus was determined. In F. indicus, innate immune system is in a sensitive balance of intricate interactions; elucidating these interactions by the integration of in silico and in vitro has great potential. We have determined the expression of both the SP and α-2M enzymes in regulatory mechanism, which are analyzed through qRT-PCR, protein-protein docking, and simulation studies. From this work, we propose a novel approach for studying an organism at the systems level by integrating genome-wide computational analysis and the gene expression data.

Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs.

PubMed

Huo, Tong; Liu, Wei; Guo, Yu; Yang, Cheng; Lin, Jianping; Rao, Zihe

2015-03-26

Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.

A selection that reports on protein–protein interactions within a thermophilic bacterium

PubMed Central

Nguyen, Peter Q.; Silberg, Jonathan J.

2010-01-01

Many proteins can be split into fragments that exhibit enhanced function upon fusion to interacting proteins. While this strategy has been widely used to create protein-fragment complementation assays (PCAs) for discovering protein–protein interactions within mesophilic organisms, similar assays have not yet been developed for studying natural and engineered protein complexes at the temperatures where thermophilic microbes grow. We describe the development of a selection for protein–protein interactions within Thermus thermophilus that is based upon growth complementation by fragments of Thermotoga neapolitana adenylate kinase (AKTn). Complementation studies with an engineered thermophile (PQN1) that is not viable above 75°C because its adk gene has been replaced by a Geobacillus stearothermophilus ortholog revealed that growth could be restored at 78°C by a vector that coexpresses polypeptides corresponding to residues 1–79 and 80–220 of AKTn. In contrast, PQN1 growth was not complemented by AKTn fragments harboring a C156A mutation within the zinc-binding tetracysteine motif unless these fragments were fused to Thermotoga maritima chemotaxis proteins that heterodimerize (CheA and CheY) or homodimerize (CheX). This enhanced complementation is interpreted as arising from chemotaxis protein–protein interactions, since AKTn-C156A fragments having only one polypeptide fused to a chemotaxis protein did not complement PQN1 to the same extent. This selection increases the maximum temperature where a PCA can be used to engineer thermostable protein complexes and to map protein–protein interactions. PMID:20418388

Building biochips: a protein production pipeline

NASA Astrophysics Data System (ADS)

de Carvalho-Kavanagh, Marianne G. S.; Albala, Joanna S.

2004-06-01

Protein arrays are emerging as a practical format in which to study proteins in high-throughput using many of the same techniques as that of the DNA microarray. The key advantage to array-based methods for protein study is the potential for parallel analysis of thousands of samples in an automated, high-throughput fashion. Building protein arrays capable of this analysis capacity requires a robust expression and purification system capable of generating hundreds to thousands of purified recombinant proteins. We have developed a method to utilize LLNL-I.M.A.G.E. cDNAs to generate recombinant protein libraries using a baculovirus-insect cell expression system. We have used this strategy to produce proteins for analysis of protein/DNA and protein/protein interactions using protein microarrays in order to understand the complex interactions of proteins involved in homologous recombination and DNA repair. Using protein array techniques, a novel interaction between the DNA repair protein, Rad51B, and histones has been identified.

Interaction betwen Lead and Bone Protein to Affect Bone Calcium Level Using UV-Vis Spectroscopy

NASA Astrophysics Data System (ADS)

Noor, Z.; Azharuddin, A.; Aflanie, I.; Kania, N.; Suhartono, E.

2018-05-01

This present study aim to evaluate the interactions between lead (Pb) and with bone protein by UV-Vis approach. In addition, this prsent study also aim to investigate the effect of Pb on bone calcium (Ca) level. The present study was a true experimental study design to examine the impact of Pb exposure in bone of male rats (Rattus novergicus). The study involved 5 groups, P1 was the control group, while the other (P2-P5) were the case group with exposure of Pb in different concentration within 4 weeks. At the end of the exposure, the interaction between Pb and protein was determined using UV-Vis spectrophotometric method, and the Ca level was determined using permanganometric method. The results shows that that there is an interaction between Pb and bone protein. The result also shows that the value of the binding constant of Protein-Pb is 32.71. It means Pb have an high affinity to bind with bone protein, which promote a further reaction to induced the release of bone Ca from the bone protein. In conclusion, this present study found an obvious relationship between Pb and bone protein which promote a further reaction to increase the releasing of bone calcium.

Molecular dynamics simulations of β2-microglobulin interaction with hydrophobic surfaces.

PubMed

Dongmo Foumthuim, Cedrix J; Corazza, Alessandra; Esposito, Gennaro; Fogolari, Federico

2017-11-21

Hydrophobic surfaces are known to adsorb and unfold proteins, a process that has been studied only for a few proteins. Here we address the interaction of β2-microglobulin, a paradigmatic protein for the study of amyloidogenesis, with hydrophobic surfaces. A system with 27 copies of the protein surrounded by a model cubic hydrophobic box is studied by implicit solvent molecular dynamics simulations. Most proteins adsorb on the walls of the box without major distortions in local geometry, whereas free molecules maintain proper structures and fluctuations as observed in explicit solvent molecular dynamics simulations. The major conclusions from the simulations are as follows: (i) the adopted implicit solvent model is adequate to describe protein dynamics and thermodynamics; (ii) adsorption occurs readily and is irreversible on the simulated timescale; (iii) the regions most involved in molecular encounters and stable interactions with the walls are the same as those that are important in protein-protein and protein-nanoparticle interactions; (iv) unfolding following adsorption occurs at regions found to be flexible by both experiments and simulations; (v) thermodynamic analysis suggests a very large contribution from van der Waals interactions, whereas unfavorable electrostatic interactions are not found to contribute much to adsorption energy. Surfaces with different degrees of hydrophobicity may occur in vivo. Our simulations show that adsorption is a fast and irreversible process which is accompanied by partial unfolding. The results and the thermodynamic analysis presented here are consistent with and rationalize previous experimental work.

Abundance and Temperature Dependency of Protein-Protein Interaction Revealed by Interface Structure Analysis and Stability Evolution

PubMed Central

He, Yi-Ming; Ma, Bin-Guang

2016-01-01

Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophiles rather than mesophiles. Moreover, we found that the protein interaction strength in complexes is not only temperature-dependent but also abundance-dependent. The underlying mechanism for the observed correlation was explored by simulating the evolution of protein interface stability, which highlights the avoidance of misinteraction. Our findings make more complete the picture of the mechanisms for protein complex thermal adaptation and provide new insights into the principles of protein-protein interactions. PMID:27220911

Abundance and Temperature Dependency of Protein-Protein Interaction Revealed by Interface Structure Analysis and Stability Evolution

NASA Astrophysics Data System (ADS)

He, Yi-Ming; Ma, Bin-Guang

2016-05-01

Protein complexes are major forms of protein-protein interactions and implement essential biological functions. The subunit interface in a protein complex is related to its thermostability. Though the roles of interface properties in thermal adaptation have been investigated for protein complexes, the relationship between the interface size and the expression level of the subunits remains unknown. In the present work, we studied this relationship and found a positive correlation in thermophiles rather than mesophiles. Moreover, we found that the protein interaction strength in complexes is not only temperature-dependent but also abundance-dependent. The underlying mechanism for the observed correlation was explored by simulating the evolution of protein interface stability, which highlights the avoidance of misinteraction. Our findings make more complete the picture of the mechanisms for protein complex thermal adaptation and provide new insights into the principles of protein-protein interactions.

Dissecting protein:protein interactions between transcription factors with an RNA aptamer.

PubMed Central

Tian, Y; Adya, N; Wagner, S; Giam, C Z; Green, M R; Ellington, A D

1995-01-01

Nucleic acid aptamers isolated from random sequence pools have generally proven useful at inhibiting the interactions of nucleic acid binding proteins with their cognate nucleic acids. In order to develop reagents that could also be used to study protein:protein interactions, we have used in vitro selection to search for RNA aptamers that could interact with the transactivating protein Tax from human T-cell leukemia virus. Tax does not normally bind to nucleic acids, but instead stimulates transcription by interacting with a variety of cellular transcription factors, including the cyclic AMP-response element binding protein (CREB), NF-kappa B, and the serum response factor (SRF). Starting from a pool of greater than 10(13) different RNAs with a core of 120 random sequence positions, RNAs were selected for their ability to be co-retained on nitrocellulose filters with Tax. After five cycles of selection and amplification, a single nucleic acid species remained. This aptamer was found to bind Tax with high affinity and specificity, and could disrupt complex formation between Tax and NF-kappa B, but not with SRF. The differential effects of our aptamer probe on protein:protein interactions suggest a model for how the transcription factor binding sites on the surface of the Tax protein are organized. This model is consistent with data from a variety of other studies. PMID:7489503

Photonic-plasmonic hybrid single-molecule nanosensor measures the effect of fluorescent labels on DNA-protein dynamics

PubMed Central

Liang, Feng; Guo, Yuzheng; Hou, Shaocong; Quan, Qimin

2017-01-01

Current methods to study molecular interactions require labeling the subject molecules with fluorescent reporters. However, the effect of the fluorescent reporters on molecular dynamics has not been quantified because of a lack of alternative methods. We develop a hybrid photonic-plasmonic antenna-in-a-nanocavity single-molecule biosensor to study DNA-protein dynamics without using fluorescent labels. Our results indicate that the fluorescein and fluorescent protein labels decrease the interaction between a single DNA and a protein due to weakened electrostatic interaction. Although the study is performed on the DNA-XPA system, the conclusion has a general implication that the traditional fluorescent labeling methods might be misestimating the molecular interactions. PMID:28560341

Light-scattering studies of protein solutions: role of hydration in weak protein-protein interactions.

PubMed

Paliwal, A; Asthagiri, D; Abras, D; Lenhoff, A M; Paulaitis, M E

2005-09-01

We model the hydration contribution to short-range electrostatic/dispersion protein interactions embodied in the osmotic second virial coefficient, B(2), by adopting a quasi-chemical description in which water molecules associated with the protein are identified through explicit molecular dynamics simulations. These water molecules reduce the surface complementarity of highly favorable short-range interactions, and therefore can play an important role in mediating protein-protein interactions. Here we examine this quasi-chemical view of hydration by predicting the interaction part of B(2) and comparing our results with those derived from light-scattering measurements of B(2) for staphylococcal nuclease, lysozyme, and chymotrypsinogen at 25 degrees C as a function of solution pH and ionic strength. We find that short-range protein interactions are influenced by water molecules strongly associated with a relatively small fraction of the protein surface. However, the effect of these strongly associated water molecules on the surface complementarity of short-range protein interactions is significant, and must be taken into account for an accurate description of B(2). We also observe remarkably similar hydration behavior for these proteins despite substantial differences in their three-dimensional structures and spatial charge distributions, suggesting a general characterization of protein hydration.

Molecular recognition of a model globular protein apomyoglobin by synthetic receptor cyclodextrin: effect of fluorescence modification of the protein and cavity size of the receptor in the interaction.

PubMed

Saha, Ranajay; Rakshit, Surajit; Pal, Samir Kumar

2013-11-01

Labelling of proteins with some extrinsic probe is unavoidable in molecular biology research. Particularly, spectroscopic studies in the optical region require fluorescence modification of native proteins by attaching polycyclic aromatic fluoroprobe with the proteins under investigation. Our present study aims to address the consequence of the attachment of a fluoroprobe at the protein surface in the molecular recognition of the protein by selectively small model receptor. A spectroscopic study involving apomyoglobin (Apo-Mb) and cyclodextrin (CyD) of various cavity sizes as model globular protein and synthetic receptors, respectively, using steady-state and picosecond-resolved techniques, is detailed here. A study involving Förster resonance energy transfer, between intrinsic amino acid tryptophan (donor) and N, N-dimethyl naphthalene moiety of the extrinsic dansyl probes at the surface of Apo-Mb, precisely monitor changes in donor acceptor distance as a consequence of interaction of the protein with CyD having different cavity sizes (β and γ variety). Molecular modelling studies on the interaction of tryptophan and dansyl probe with β-CyD is reported here and found to be consistent with the experimental observations. In order to investigate structural aspects of the interacting protein, we have used circular dichroism spectroscopy. Temperature-dependent circular dichroism studies explore the change in the secondary structure of Apo-Mb in association with CyD, before and after fluorescence modification of the protein. Overall, the study well exemplifies approaches to protein recognition by CyD as a synthetic receptor and offers a cautionary note on the use of hydrophobic fluorescent labels for proteins in biochemical studies involving recognition of molecules. Copyright © 2013 John Wiley & Sons, Ltd.

CMP‑N‑acetylneuraminic acid synthetase interacts with fragile X related protein 1.

PubMed

Ma, Yun; Tian, Shuai; Wang, Zongbao; Wang, Changbo; Chen, Xiaowei; Li, Wei; Yang, Yang; He, Shuya

2016-08-01

Fragile X mental retardation protein (FMRP), fragile X related 1 protein (FXR1P) and FXR2P are the members of the FMR protein family. These proteins contain two KH domains and a RGG box, which are characteristic of RNA binding proteins. The absence of FMRP, causes fragile X syndrome (FXS), the leading cause of hereditary mental retardation. FXR1P is expressed throughout the body and important for normal muscle development, and its absence causes cardiac abnormality. To investigate the functions of FXR1P, a screen was performed to identify FXR1P‑interacting proteins and determine the biological effect of the interaction. The current study identified CMP‑N‑acetylneuraminic acid synthetase (CMAS) as an interacting protein using the yeast two‑hybrid system, and the interaction between FXR1P and CMAS was validated in yeast using a β‑galactosidase assay and growth studies with selective media. Furthermore, co‑immunoprecipitation was used to analyze the FXR1P/CMAS association and immunofluorescence microscopy was performed to detect expression and intracellular localization of the proteins. The results of the current study indicated that FXR1P and CMAS interact, and colocalize in the cytoplasm and the nucleus of HEK293T and HeLa cells. Accordingly, a fragile X related 1 (FXR1) gene overexpression vector was constructed to investigate the effect of FXR1 overexpression on the level of monosialotetrahexosylganglioside 1 (GM1). The results of the current study suggested that FXR1P is a tissue‑specific regulator of GM1 levels in SH‑SY5Y cells, but not in HEK293T cells. Taken together, the results initially indicate that FXR1P interacts with CMAS, and that FXR1P may enhance the activation of sialic acid via interaction with CMAS, and increase GM1 levels to affect the development of the nervous system, thus providing evidence for further research into the pathogenesis of FXS.

In Vivo Photo-Cross-Linking to Study T3S Interactions Demonstrated Using the Yersinia pestis T3S System.

PubMed

Henderson, Thomas A; Nilles, Matthew L

2017-01-01

Cross-linking of proteins is effective in determining protein-protein interactions. The use of photo-cross-linkers was developed to study protein interactions in several manners. One method involved the incorporation of photo-activatable cross-linking groups into chemically synthesized peptides. A second approach relies on incorporation of photo-activatable cross-linking groups into proteins using tRNAs with chemically bound photo-activatable amino acids with suppressor tRNAs translational systems to incorporate the tags into specific sites. A third system was made possible by the development of photoreactive amino acids that use the normal cellular tRNAs and aminoacyl tRNA synthetases. In this method, the third system is used to demonstrate its utility for the study of T3S system interactions. This method describes how two photo-activatable amino acids, photo-methionine and photo-leucine, that use the normal cellular machinery are incorporated into Yersinia pestis and used to study interactions in the T3S system. To demonstrate the system, the method was used to cross-link the T3S regulatory proteins LcrG and LcrV.

Protein-Protein Interactions (PPI) reagents: | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below.

The visible touch: in planta visualization of protein-protein interactions by fluorophore-based methods

PubMed Central

Bhat, Riyaz A; Lahaye, Thomas; Panstruga, Ralph

2006-01-01

Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this review, we address the individual strengths and weaknesses of both approaches and provide an outlook about new directions and possible future developments for both techniques. PMID:16800872

A rice kinase-protein interaction map.

PubMed

Ding, Xiaodong; Richter, Todd; Chen, Mei; Fujii, Hiroaki; Seo, Young Su; Xie, Mingtang; Zheng, Xianwu; Kanrar, Siddhartha; Stevenson, Rebecca A; Dardick, Christopher; Li, Ying; Jiang, Hao; Zhang, Yan; Yu, Fahong; Bartley, Laura E; Chern, Mawsheng; Bart, Rebecca; Chen, Xiuhua; Zhu, Lihuang; Farmerie, William G; Gribskov, Michael; Zhu, Jian-Kang; Fromm, Michael E; Ronald, Pamela C; Song, Wen-Yuan

2009-03-01

Plants uniquely contain large numbers of protein kinases, and for the vast majority of the 1,429 kinases predicted in the rice (Oryza sativa) genome, little is known of their functions. Genetic approaches often fail to produce observable phenotypes; thus, new strategies are needed to delineate kinase function. We previously developed a cost-effective high-throughput yeast two-hybrid system. Using this system, we have generated a protein interaction map of 116 representative rice kinases and 254 of their interacting proteins. Overall, the resulting interaction map supports a large number of known or predicted kinase-protein interactions from both plants and animals and reveals many new functional insights. Notably, we found a potential widespread role for E3 ubiquitin ligases in pathogen defense signaling mediated by receptor-like kinases, particularly by the kinases that may have evolved from recently expanded kinase subfamilies in rice. We anticipate that the data provided here will serve as a foundation for targeted functional studies in rice and other plants. The application of yeast two-hybrid and TAPtag analyses for large-scale plant protein interaction studies is also discussed.

Interaction and dynamics of homologous pairing protein 2 (HOP2) and DNA studied by MD simulation

NASA Astrophysics Data System (ADS)

Moktan, Hem; Pezza, Roberto; Zhou, Donghua

2015-03-01

The homologous pairing protein 2 (Hop2) plays an important role in meiosis and DNA repair. Together with protein Mnd1, Hop2 enhances the strand invasion activity of recombinase Dmc1 by over 30 times, facilitating proper synapsis of homologous chromosomes. We recently determined the NMR structure of the N-terminal domain of Hop2 and proposed a model of Protein-DNA complex based on NMR chemical shift perturbations and mutagenesis studies (Moktan, J Biol Chem 2014 10.1074/jbc.M114.548180). However structure and dynamics of the complex have not been studied at the atomic level yet. Here, we used classical MD simulations to study the interactions between the N-terminal HOP2 and DNA. The simulated results indicate that helix3 (H3) interacts with DNA in major groove and wing1 (W1) interacts mostly in minor groove mainly via direct hydrogen bonds. Also it is found that binding leads to reduced fluctuations in both protein and DNA. Several water bridge interactions have been identified. The residue-wise contributions to the interaction energy were evaluated. Also the functional motion of the protein is analyzed using principal component analysis. The results confirmed the importance of H3 and W1 for the stability of the complex, which is consistent with our previous experimental studies.

DOMMINO 2.0: integrating structurally resolved protein-, RNA-, and DNA-mediated macromolecular interactions

PubMed Central

Kuang, Xingyan; Dhroso, Andi; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry

2016-01-01

Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunctioning of macromolecular interactions is also linked to a number of diseases. Structural knowledge of the macromolecular interaction allows one to understand the interaction’s mechanism, determine its functional implications and characterize the effects of genetic variations, such as single nucleotide polymorphisms, on the interaction. Unfortunately, until now the interactions mediated by different types of macromolecules, e.g. protein–protein interactions or protein–DNA interactions, are collected into individual and unrelated structural databases. This presents a significant obstacle in the analysis of macromolecular interactions. For instance, the homogeneous structural interaction databases prevent scientists from studying structural interactions of different types but occurring in the same macromolecular complex. Here, we introduce DOMMINO 2.0, a structural Database Of Macro-Molecular INteractiOns. Compared to DOMMINO 1.0, a comprehensive database on protein-protein interactions, DOMMINO 2.0 includes the interactions between all three basic types of macromolecules extracted from PDB files. DOMMINO 2.0 is automatically updated on a weekly basis. It currently includes ∼1 040 000 interactions between two polypeptide subunits (e.g. domains, peptides, termini and interdomain linkers), ∼43 000 RNA-mediated interactions, and ∼12 000 DNA-mediated interactions. All protein structures in the database are annotated using SCOP and SUPERFAMILY family annotation. As a result, protein-mediated interactions involving protein domains, interdomain linkers, C- and N- termini, and peptides are identified. Our database provides an intuitive web interface, allowing one to investigate interactions at three different resolution levels: whole subunit network, binary interaction and interaction interface. Database URL: http://dommino.org PMID:26827237

Quantification of protein interaction kinetics in a micro droplet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, L. L.; College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044; Wang, S. P., E-mail: shaopeng.wang@asu.edu, E-mail: njtao@asu.edu

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the averagemore » SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.« less

Quantification of protein interaction kinetics in a micro droplet

NASA Astrophysics Data System (ADS)

Yin, L. L.; Wang, S. P.; Shan, X. N.; Zhang, S. T.; Tao, N. J.

2015-11-01

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.

Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

PubMed

Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

2018-01-16

"A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of bioinformatics tools to their full potential to analyse protein-protein interactions as a comprehensive network. Copyright © 2017 Elsevier B.V. All rights reserved.

Mapping differential interactomes by affinity purification coupled with data-independent mass spectrometry acquisition.

PubMed

Lambert, Jean-Philippe; Ivosev, Gordana; Couzens, Amber L; Larsen, Brett; Taipale, Mikko; Lin, Zhen-Yuan; Zhong, Quan; Lindquist, Susan; Vidal, Marc; Aebersold, Ruedi; Pawson, Tony; Bonner, Ron; Tate, Stephen; Gingras, Anne-Claude

2013-12-01

Characterizing changes in protein-protein interactions associated with sequence variants (e.g., disease-associated mutations or splice forms) or following exposure to drugs, growth factors or hormones is critical to understanding how protein complexes are built, localized and regulated. Affinity purification (AP) coupled with mass spectrometry permits the analysis of protein interactions under near-physiological conditions, yet monitoring interaction changes requires the development of a robust and sensitive quantitative approach, especially for large-scale studies in which cost and time are major considerations. We have coupled AP to data-independent mass spectrometric acquisition (sequential window acquisition of all theoretical spectra, SWATH) and implemented an automated data extraction and statistical analysis pipeline to score modulated interactions. We used AP-SWATH to characterize changes in protein-protein interactions imparted by the HSP90 inhibitor NVP-AUY922 or melanoma-associated mutations in the human kinase CDK4. We show that AP-SWATH is a robust label-free approach to characterize such changes and propose a scalable pipeline for systems biology studies.

A Library of Plasmodium vivax Recombinant Merozoite Proteins Reveals New Vaccine Candidates and Protein-Protein Interactions

PubMed Central

Hostetler, Jessica B.; Sharma, Sumana; Bartholdson, S. Josefin; Wright, Gavin J.; Fairhurst, Rick M.; Rayner, Julian C.

2015-01-01

Background A vaccine targeting Plasmodium vivax will be an essential component of any comprehensive malaria elimination program, but major gaps in our understanding of P. vivax biology, including the protein-protein interactions that mediate merozoite invasion of reticulocytes, hinder the search for candidate antigens. Only one ligand-receptor interaction has been identified, that between P. vivax Duffy Binding Protein (PvDBP) and the erythrocyte Duffy Antigen Receptor for Chemokines (DARC), and strain-specific immune responses to PvDBP make it a complex vaccine target. To broaden the repertoire of potential P. vivax merozoite-stage vaccine targets, we exploited a recent breakthrough in expressing full-length ectodomains of Plasmodium proteins in a functionally-active form in mammalian cells and initiated a large-scale study of P. vivax merozoite proteins that are potentially involved in reticulocyte binding and invasion. Methodology/Principal Findings We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further suggesting that the proteins are natively folded and functional. This screen also identified two novel protein-protein interactions, between P12 and PVX_110945, and between MSP3.10 and MSP7.1, the latter of which was confirmed by surface plasmon resonance. Conclusions/Significance We produced a new library of recombinant full-length P. vivax ectodomains, established that the majority of them contain tertiary structure, and used them to identify predicted and novel protein-protein interactions. As well as identifying new interactions for further biological studies, this library will be useful in identifying P. vivax proteins with vaccine potential, and studying P. vivax malaria pathogenesis and immunity. Trial Registration ClinicalTrials.gov NCT00663546 PMID:26701602

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

NASA Astrophysics Data System (ADS)

Han, Jing-Dong J.; Bertin, Nicolas; Hao, Tong; Goldberg, Debra S.; Berriz, Gabriel F.; Zhang, Lan V.; Dupuy, Denis; Walhout, Albertha J. M.; Cusick, Michael E.; Roth, Frederick P.; Vidal, Marc

2004-07-01

In apparently scale-free protein-protein interaction networks, or `interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the `hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: `party' hubs, which interact with most of their partners simultaneously, and `date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes-or modules -to each other, whereas party hubs function inside modules.

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

HIV-1 Nef binds with human GCC185 protein and regulates mannose 6 phosphate receptor recycling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Manjeet; Kaur, Supinder; Nazir, Aamir

HIV-1 Nef modulates cellular function that enhances viral replication in vivo which culminate into AIDS pathogenesis. With no enzymatic activity, Nef regulates cellular function through host protein interaction. Interestingly, trans-cellular introduction of recombinant Nef protein in Caenorhabditis elegans results in AIDS like pathogenesis which might share common pathophysiology because the gene sequence of C. elegans and humans share considerable homology. Therefore employing C. elegans based initial screen complemented with sequence based homology search we identified GCC185 as novel host protein interacting with HIV-1 Nef. The detailed molecular characterization revealed N-terminal EEEE{sub 65} acidic domain of Nef as key region for interaction. GCC185 ismore » a tethering protein that binds with Rab9 transport vesicles. Our results show that Nef-GCC185 interaction disrupts Rab9 interaction resulting in delocalization of CI-MPR (cation independent Mannose 6 phosphate receptor) resulting in elevated secretion of hexosaminidase. In agreement with this, our studies identified novel host GCC185 protein that interacts with Nef EEEE65 acidic domain interfering GCC185-Rab9 vesicle membrane fusion responsible for retrograde vesicular transport of CI-MPR from late endosomes to TGN. In light of existing report suggesting critical role of Nef-GCC185 interaction reveals valuable mechanistic insights affecting specific protein transport pathway in docking of late endosome derived Rab9 bearing transport vesicle at TGN elucidating role of Nef during viral pathogenesis. -- Highlights: •Nef, an accessory protein of HIV-1 interacts with host factor and culminates into AIDS pathogenesis. •Using Caenorhabditis elegans based screen system, novel Nef interacting cellular protein GCC185 was identified. •Molecular characterization of Nef and human protein GCC185 revealed Nef EEEE{sub 65} key region interacted with full length GCC185. •Nef impeded the GCC185-Rab 9 interaction and perturb the mannose 6 phosphate receptor recycling. •Our study identified novel Nef interacting human GCC185 protein and their role regulation of M6P receptor recycling.« less

Colloid-probe AFM studies of the interaction forces of proteins adsorbed on colloidal crystals.

PubMed

Singh, Gurvinder; Bremmell, Kristen E; Griesser, Hans J; Kingshott, Peter

2015-04-28

In recent years, colloid-probe AFM has been used to measure the direct interaction forces between colloidal particles of different size or surface functionality in aqueous media, as one can study different forces in symmerical systems (i.e., sphere-sphere geometry). The present study investigates the interaction between protein coatings on colloid probes and hydrophilic surfaces decorated with hexagonally close packed single particle layers that are either uncoated or coated with proteins. Controlled solvent evaporation from aqueous suspensions of colloidal particles (coated with or without lysozyme and albumin) produces single layers of close-packed colloidal crystals over large areas on a solid support. The measurements have been carried out in an aqueous medium at different salt concentrations and pH values. The results show changes in the interaction forces as the surface charge of the unmodified or modified particles, and ionic strength or pH of the solution is altered. At high ionic strength or pH, electrostatic interactions are screened, and a strong repulsive force at short separation below 5 nm dominates, suggesting structural changes in the absorbed protein layer on the particles. We also study the force of adhesion, which decreases with an increment in the salt concentration, and the interaction between two different proteins indicating a repulsive interaction on approach and adhesion on retraction.

Assessment of the reliability of protein-protein interactions and protein function prediction.

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex data. The supplementary information is available at the following Web site: http://www-hto.usc.edu/-msms/AssessInteraction/.

PCPPI: a comprehensive database for the prediction of Penicillium-crop protein-protein interactions.

PubMed

Yue, Junyang; Zhang, Danfeng; Ban, Rongjun; Ma, Xiaojing; Chen, Danyang; Li, Guangwei; Liu, Jia; Wisniewski, Michael; Droby, Samir; Liu, Yongsheng

2017-01-01

Penicillium expansum , the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium -crop interaction is a multifaceted process and mediated by pathogen- and host-derived proteins. Identification and characterization of the inter-species protein-protein interactions (PPIs) are fundamental to elucidating the molecular mechanisms underlying infection processes between P. expansum and plant crops. Here, we have developed PCPPI, the Penicillium -Crop Protein-Protein Interactions database, which is constructed based on the experimentally determined orthologous interactions in pathogen-plant systems and available domain-domain interactions (DDIs) in each PPI. Thus far, it stores information on 9911 proteins, 439 904 interactions and seven host species, including apple, kiwifruit, maize, pear, rice, strawberry and tomato. Further analysis through the gene ontology (GO) annotation indicated that proteins with more interacting partners tend to execute the essential function. Significantly, semantic statistics of the GO terms also provided strong support for the accuracy of our predicted interactions in PCPPI. We believe that all the PCPPI datasets are helpful to facilitate the study of pathogen-crop interactions and freely available to the research community. : http://bdg.hfut.edu.cn/pcppi/index.html. © The Author(s) 2017. Published by Oxford University Press.

Interaction of Tenebrio Molitor Antifreeze Protein with Ice Crystal: Insights from Molecular Dynamics Simulations.

PubMed

Ramya, L; Ramakrishnan, Vigneshwar

2016-07-01

Antifreeze proteins (AFP) observed in cold-adapting organisms bind to ice crystals and prevent further ice growth. However, the molecular mechanism of AFP-ice binding and AFP-inhibited ice growth remains unclear. Here we report the interaction of the insect antifreeze protein (Tenebrio molitor, TmAFP) with ice crystal by molecular dynamics simulation studies. Two sets of simulations were carried out at 263 K by placing the protein near the primary prism plane (PP) and basal plane (BL) of the ice crystal. To delineate the effect of temperatures, both the PP and BL simulations were carried out at 253 K as well. The analyses revealed that the protein interacts strongly with the ice crystal in BL simulation than in PP simulation both at 263 K and 253 K. Further, it was observed that the interactions are primarily mediated through the interface waters. We also observed that as the temperature decreases, the interaction between the protein and the ice increases which can be attributed to the decreased flexibility and the increased structuring of the protein at low temperature. In essence, our study has shed light on the interaction mechanism between the TmAFP antifreeze protein and the ice crystal. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Miscibility of binary monolayers at the air-water interface and interaction of protein with immobilized monolayers by surface plasmon resonance technique.

PubMed

Wang, Yuchun; Du, Xuezhong

2006-07-04

The miscibility and stability of the binary monolayers of zwitterionic dipalmitoylphosphatidylcholine (DPPC) and cationic dioctadecyldimethylammonium bromide (DOMA) at the air-water interface and the interaction of ferritin with the immobilized monolayers have been studied in detail using surface pressure-area isotherms and surface plasmon resonance technique, respectively. The surface pressure-area isotherms indicated that the binary monolayers of DPPC and DOMA at the air-water interface were miscible and more stable than the monolayers of the two individual components. The surface plasmon resonance studies indicated that ferritin binding to the immobilized monolayers was primarily driven by the electrostatic interaction and that the amount of adsorbed protein at saturation was closely related not only to the number of positive charges in the monolayers but also to the pattern of positive charges at a given mole fraction of DOMA. The protein adsorption kinetics was determined by the properties of the monolayers (i.e., the protein-monolayer interaction) and the structure of preadsorbed protein molecules (i.e., the protein-protein interaction).

Potential disruption of protein-protein interactions by graphene oxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Mei; Kang, Hongsuk; Luan, Binquan

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions andmore » eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.« less

Analysis of the STAT3 interactome using in-situ biotinylation and SILAC.

PubMed

Blumert, Conny; Kalkhof, Stefan; Brocke-Heidrich, Katja; Kohajda, Tibor; von Bergen, Martin; Horn, Friedemann

2013-12-06

Signal transducer and activator of transcription 3 (STAT3) is activated by a variety of cytokines and growth factors. To generate a comprehensive data set of proteins interacting specifically with STAT3, we applied stable isotope labeling with amino acids in cell culture (SILAC). For high-affinity pull-down using streptavidin, we fused STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag), which did not affect STAT3 functions. By this approach, 3642 coprecipitated proteins were detected in human embryonic kidney-293 cells. Filtering using statistical and functional criteria finally extracted 136 proteins as putative interaction partners of STAT3. Both, a physical interaction network analysis and the enrichment of known and predicted interaction partners suggested that our filtering criteria successfully enriched true STAT3 interactors. Our approach identified numerous novel interactors, including ones previously predicted to associate with STAT3. By reciprocal coprecipitation, we were able to verify the physical association between STAT3 and selected interactors, including the novel interaction with TOX4, a member of the TOX high mobility group box family. Applying the same method, we next investigated the activation-dependency of the STAT3 interactome. Again, we identified both known and novel interactions. Thus, our approach allows to study protein-protein interaction effectively and comprehensively. The location, activity, function, degradation, and synthesis of proteins are significantly regulated by interactions of proteins with other proteins, biopolymers and small molecules. Thus, the comprehensive characterization of interactions of proteins in a given proteome is the next milestone on the path to understanding the biochemistry of the cell. In order to generate a comprehensive interactome dataset of proteins specifically interacting with a selected bait protein, we fused our bait protein STAT3 with a short peptide tag allowing biotinylation in situ (bio-tag). This bio-tag allows an affinity pull-down using streptavidin but affected neither the activation of STAT3 by tyrosine phosphorylation nor its transactivating potential. We combined SILAC for accurate relative protein quantification, subcellular fractionation to increase the coverage of interacting proteins, high-affinity pull-down and a stringent filtering method to successfully analyze the interactome of STAT3. With our approach we confirmed several already known and identified numerous novel STAT3 interactors. The approach applied provides a rapid and effective method, which is broadly applicable for studying protein-protein interactions and their dependency on post-translational modifications. © 2013. Published by Elsevier B.V. All rights reserved.

Analysis of Protein Interactions with Picomolar Binding Affinity by Fluorescence-Detected Sedimentation Velocity

PubMed Central

2014-01-01

The study of high-affinity protein interactions with equilibrium dissociation constants (KD) in the picomolar range is of significant interest in many fields, but the characterization of stoichiometry and free energy of such high-affinity binding can be far from trivial. Analytical ultracentrifugation has long been considered a gold standard in the study of protein interactions but is typically applied to systems with micromolar KD. Here we present a new approach for the study of high-affinity interactions using fluorescence detected sedimentation velocity analytical ultracentrifugation (FDS-SV). Taking full advantage of the large data sets in FDS-SV by direct boundary modeling with sedimentation coefficient distributions c(s), we demonstrate detection and hydrodynamic resolution of protein complexes at low picomolar concentrations. We show how this permits the characterization of the antibody–antigen interactions with low picomolar binding constants, 2 orders of magnitude lower than previously achieved. The strongly size-dependent separation and quantitation by concentration, size, and shape of free and complex species in free solution by FDS-SV has significant potential for studying high-affinity multistep and multicomponent protein assemblies. PMID:24552356

Amyloid precursor protein interaction network in human testis: sentinel proteins for male reproduction.

PubMed

Silva, Joana Vieira; Yoon, Sooyeon; Domingues, Sara; Guimarães, Sofia; Goltsev, Alexander V; da Cruz E Silva, Edgar Figueiredo; Mendes, José Fernando F; da Cruz E Silva, Odete Abreu Beirão; Fardilha, Margarida

2015-01-16

Amyloid precursor protein (APP) is widely recognized for playing a central role in Alzheimer's disease pathogenesis. Although APP is expressed in several tissues outside the human central nervous system, the functions of APP and its family members in other tissues are still poorly understood. APP is involved in several biological functions which might be potentially important for male fertility, such as cell adhesion, cell motility, signaling, and apoptosis. Furthermore, APP superfamily members are known to be associated with fertility. Knowledge on the protein networks of APP in human testis and spermatozoa will shed light on the function of APP in the male reproductive system. We performed a Yeast Two-Hybrid screen and a database search to study the interaction network of APP in human testis and sperm. To gain insights into the role of APP superfamily members in fertility, the study was extended to APP-like protein 2 (APLP2). We analyzed several topological properties of the APP interaction network and the biological and physiological properties of the proteins in the APP interaction network were also specified by gene ontologyand pathways analyses. We classified significant features related to the human male reproduction for the APP interacting proteins and identified modules of proteins with similar functional roles which may show cooperative behavior for male fertility. The present work provides the first report on the APP interactome in human testis. Our approach allowed the identification of novel interactions and recognition of key APP interacting proteins for male reproduction, particularly in sperm-oocyte interaction.

Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

PubMed

Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

2007-08-01

INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

Studying Protein-Protein Interactions by Biotin AP-Tagged Pulldown and LTQ-Orbitrap Mass Spectrometry.

PubMed

Xie, Zhongqiu; Jia, Yuemeng; Li, Hui

2017-01-01

The study of protein-protein interactions represents a key aspect of biological research. Identifying unknown protein binding partners using mass spectrometry (MS)-based proteomics has evolved into an indispensable strategy in drug discovery. The classic approach of immunoprecipitation with specific antibodies against the proteins of interest has limitations, such as the need for immunoprecipitation-qualified antibody. The biotin AP-tag pull-down system has the advantage of high specificity, ease of use, and no requirement for antibody. It is based on the high specificity, high affinity interaction between biotin and streptavidin. After pulldown, in-gel tryptic digestion and tandem mass spectrometry (MS/MS) analysis of sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) protein bands can be performed. In this work, we provide protocols that can be used for the identification of proteins that interact with FOXM1, a protein that has recently emerged as a potential biomarker and drug target in oncotherapy, as an example. We focus on the pull-down procedure and assess the efficacy of the pulldown with known FOXM1 interactors such as β-catenin. We use a high performance LTQ Orbitrap MSn system that combines rapid LTQ ion trap data acquisition with high mass accuracy Orbitrap analysis to identify the interacting proteins.

Optimization of rhodanine scaffold for the development of protein-protein interaction inhibitors.

PubMed

Ferro, Stefania; De Luca, Laura; Agharbaoui, Fatima Ezzahra; Christ, Frauke; Debyser, Zeger; Gitto, Rosaria

2015-07-01

Searching for novel protein-protein interactions inhibitors (PPIs) herein we describe the identification of a new series of rhodanine derivatives. The selection was performed by means virtual-screening, docking studies, Molecular Dynamic (MD) simulations and synthetic approaches. All the new obtained compounds were tested in order to evaluate their ability to inhibit the interaction between the HIV-1 integrase (IN) enzyme and the nuclear protein lens epithelium growth factor LEDGF/p75. Copyright © 2015 Elsevier Ltd. All rights reserved.

Instrumental biosensors: new perspectives for the analysis of biomolecular interactions.

PubMed

Nice, E C; Catimel, B

1999-04-01

The use of instrumental biosensors in basic research to measure biomolecular interactions in real time is increasing exponentially. Applications include protein-protein, protein-peptide, DNA-protein, DNA-DNA, and lipid-protein interactions. Such techniques have been applied to, for example, antibody-antigen, receptor-ligand, signal transduction, and nuclear receptor studies. This review outlines the principles of two of the most commonly used instruments and highlights specific operating parameters that will assist in optimising experimental design, data generation, and analysis.

Design, synthesis and characterization of peptidomimetic conjugate of BODIPY targeting HER2 protein extracellular domain

PubMed Central

Banappagari, Sashikanth; McCall, Alecia; Fontenot, Krystal; Vicente, M. Graca H.; Gujar, Amit; Satyanarayanajois, Seetharama

2013-01-01

Among the EGFRs, HER2 is a major heterodimer partner and also has important implications in the formation of particular tumors. Interaction of HER2 protein with other EGFR proteins can be modulated by small molecule ligands and, hence, these protein-protein interactions play a key role in biochemical reactions related to control of cell growth. A peptidomimetic (compound 5-1) that binds to HER2 protein extracellular domain and inhibits protein-protein interactions of EGFRs was conjugated with BODIPY (4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene). Conjugation of BODIPY to the peptidomimetic was investigated by different approaches. The conjugate was characterized for its ability to bind to HER2 overexpressing SKBR-3 and BT-474 cells. Furthermore, cellular uptake of conjugate of BODIPY was studied in the presence of membrane tracker and Lyso tracker using confocal microscopy. Our results suggested that fluorescently labeled compound 5-7 binds to the extracellular domain and stays in the membrane for nearly 24 h. After 24 h there is an indication of internalization of the conjugate. Inhibition of protein-protein interaction and downstream signaling effect of compound 5-1 was also studied by proximity ligation assay and western blot analysis. Results suggested that compound 5-1 inhibits protein-protein interactions of HER2-HER3 and phosphorylation of HER2 in a time-dependent manner. PMID:23688700

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

PubMed

Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene-encoded proteins are attached to the core at more peripheral positions of the networks.

ROCS: a Reproducibility Index and Confidence Score for Interaction Proteomics Studies

PubMed Central

2012-01-01

Background Affinity-Purification Mass-Spectrometry (AP-MS) provides a powerful means of identifying protein complexes and interactions. Several important challenges exist in interpreting the results of AP-MS experiments. First, the reproducibility of AP-MS experimental replicates can be low, due both to technical variability and the dynamic nature of protein interactions in the cell. Second, the identification of true protein-protein interactions in AP-MS experiments is subject to inaccuracy due to high false negative and false positive rates. Several experimental approaches can be used to mitigate these drawbacks, including the use of replicated and control experiments and relative quantification to sensitively distinguish true interacting proteins from false ones. Methods To address the issues of reproducibility and accuracy of protein-protein interactions, we introduce a two-step method, called ROCS, which makes use of Indicator Prey Proteins to select reproducible AP-MS experiments, and of Confidence Scores to select specific protein-protein interactions. The Indicator Prey Proteins account for measures of protein identifiability as well as protein reproducibility, effectively allowing removal of outlier experiments that contribute noise and affect downstream inferences. The filtered set of experiments is then used in the Protein-Protein Interaction (PPI) scoring step. Prey protein scoring is done by computing a Confidence Score, which accounts for the probability of occurrence of prey proteins in the bait experiments relative to the control experiment, where the significance cutoff parameter is estimated by simultaneously controlling false positives and false negatives against metrics of false discovery rate and biological coherence respectively. In summary, the ROCS method relies on automatic objective criterions for parameter estimation and error-controlled procedures. Results We illustrate the performance of our method by applying it to five previously published AP-MS experiments, each containing well characterized protein interactions, allowing for systematic benchmarking of ROCS. We show that our method may be used on its own to make accurate identification of specific, biologically relevant protein-protein interactions, or in combination with other AP-MS scoring methods to significantly improve inferences. Conclusions Our method addresses important issues encountered in AP-MS datasets, making ROCS a very promising tool for this purpose, either on its own or in conjunction with other methods. We anticipate that our methodology may be used more generally in proteomics studies and databases, where experimental reproducibility issues arise. The method is implemented in the R language, and is available as an R package called “ROCS”, freely available from the CRAN repository http://cran.r-project.org/. PMID:22682516

Tuning of protein-surfactant interaction to modify the resultant structure.

PubMed

Mehan, Sumit; Aswal, Vinod K; Kohlbrecher, Joachim

2015-09-01

Small-angle neutron scattering and dynamic light scattering studies have been carried out to examine the interaction of bovine serum albumin (BSA) protein with different surfactants under varying solution conditions. We show that the interaction of anionic BSA protein (pH7) with surfactant and the resultant structure are strongly modified by the charge head group of the surfactant, ionic strength of the solution, and mixed surfactants. The protein-surfactant interaction is maximum when two components are oppositely charged, followed by components being similarly charged through the site-specific binding, and no interaction in the case of a nonionic surfactant. This interaction of protein with ionic surfactants is characterized by the fractal structure representing a bead-necklace structure of micellelike clusters adsorbed along the unfolded protein chain. The interaction is enhanced with ionic strength only in the case of site-specific binding of an anionic surfactant with an anionic protein, whereas it is almost unchanged for other complexes of cationic and nonionic surfactants with anionic proteins. Interestingly, the interaction of BSA protein with ionic surfactants is significantly suppressed in the presence of nonionic surfactant. These results with mixed surfactants thus can be used to fold back the unfolded protein as well as to prevent surfactant-induced protein unfolding. For different solution conditions, the results are interpreted in terms of a change in fractal dimension, the overall size of the protein-surfactant complex, and the number of micelles attached to the protein. The interplay of electrostatic and hydrophobic interactions is found to govern the resultant structure of complexes.

Tuning of protein-surfactant interaction to modify the resultant structure

NASA Astrophysics Data System (ADS)

Mehan, Sumit; Aswal, Vinod K.; Kohlbrecher, Joachim

2015-09-01

Small-angle neutron scattering and dynamic light scattering studies have been carried out to examine the interaction of bovine serum albumin (BSA) protein with different surfactants under varying solution conditions. We show that the interaction of anionic BSA protein (p H 7 ) with surfactant and the resultant structure are strongly modified by the charge head group of the surfactant, ionic strength of the solution, and mixed surfactants. The protein-surfactant interaction is maximum when two components are oppositely charged, followed by components being similarly charged through the site-specific binding, and no interaction in the case of a nonionic surfactant. This interaction of protein with ionic surfactants is characterized by the fractal structure representing a bead-necklace structure of micellelike clusters adsorbed along the unfolded protein chain. The interaction is enhanced with ionic strength only in the case of site-specific binding of an anionic surfactant with an anionic protein, whereas it is almost unchanged for other complexes of cationic and nonionic surfactants with anionic proteins. Interestingly, the interaction of BSA protein with ionic surfactants is significantly suppressed in the presence of nonionic surfactant. These results with mixed surfactants thus can be used to fold back the unfolded protein as well as to prevent surfactant-induced protein unfolding. For different solution conditions, the results are interpreted in terms of a change in fractal dimension, the overall size of the protein-surfactant complex, and the number of micelles attached to the protein. The interplay of electrostatic and hydrophobic interactions is found to govern the resultant structure of complexes.

Deciphering molecular interactions of native membrane proteins by single-molecule force spectroscopy.

PubMed

Kedrov, Alexej; Janovjak, Harald; Sapra, K Tanuj; Müller, Daniel J

2007-01-01

Molecular interactions are the basic language of biological processes. They establish the forces interacting between the building blocks of proteins and other macromolecules, thus determining their functional roles. Because molecular interactions trigger virtually every biological process, approaches to decipher their language are needed. Single-molecule force spectroscopy (SMFS) has been used to detect and characterize different types of molecular interactions that occur between and within native membrane proteins. The first experiments detected and localized molecular interactions that stabilized membrane proteins, including how these interactions were established during folding of alpha-helical secondary structure elements into the native protein and how they changed with oligomerization, temperature, and mutations. SMFS also enables investigators to detect and locate molecular interactions established during ligand and inhibitor binding. These exciting applications provide opportunities for studying the molecular forces of life. Further developments will elucidate the origins of molecular interactions encoded in their lifetimes, interaction ranges, interplay, and dynamics characteristic of biological systems.

Comparative analysis of protein-protein interactions in the defense response of rice and wheat.

PubMed

Cantu, Dario; Yang, Baoju; Ruan, Randy; Li, Kun; Menzo, Virginia; Fu, Daolin; Chern, Mawsheng; Ronald, Pamela C; Dubcovsky, Jorge

2013-03-12

Despite the importance of wheat as a major staple crop and the negative impact of diseases on its production worldwide, the genetic mechanisms and gene interactions involved in the resistance response in wheat are still poorly understood. The complete sequence of the rice genome has provided an extremely useful parallel road map for genetic and genomics studies in wheat. The recent construction of a defense response interactome in rice has the potential to further enhance the translation of advances in rice to wheat and other grasses. The objective of this study was to determine the degree of conservation in the protein-protein interactions in the rice and wheat defense response interactomes. As entry points we selected proteins that serve as key regulators of the rice defense response: the RAR1/SGT1/HSP90 protein complex, NPR1, XA21, and XB12 (XA21 interacting protein 12). Using available wheat sequence databases and phylogenetic analyses we identified and cloned the wheat orthologs of these four rice proteins, including recently duplicated paralogs, and their known direct interactors and tested 86 binary protein interactions using yeast-two-hybrid (Y2H) assays. All interactions between wheat proteins were further tested using in planta bimolecular fluorescence complementation (BiFC). Eighty three percent of the known rice interactions were confirmed when wheat proteins were tested with rice interactors and 76% were confirmed using wheat protein pairs. All interactions in the RAR1/SGT1/ HSP90, NPR1 and XB12 nodes were confirmed for the identified orthologous wheat proteins, whereas only forty four percent of the interactions were confirmed in the interactome node centered on XA21. We hypothesize that this reduction may be associated with a different sub-functionalization history of the multiple duplications that occurred in this gene family after the divergence of the wheat and rice lineages. The observed high conservation of interactions between proteins that serve as key regulators of the rice defense response suggests that the existing rice interactome can be used to predict interactions in wheat. Such predictions are less reliable for nodes that have undergone a different history of duplications and sub-functionalization in the two lineages.

Coherent microscopic picture for urea-induced denaturation of proteins.

PubMed

Yang, Zaixing; Xiu, Peng; Shi, Biyun; Hua, Lan; Zhou, Ruhong

2012-08-02

In a previous study, we explored the mechanism of urea-induced denaturation of proteins by performing molecular dynamics (MD) simulations of hen lysozyme in 8 M urea and supported the "direct interaction mechanism" whereby urea denatures protein via dispersion interaction (Hua, L.; Zhou, R. H.; Thirumalai, D.; Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 16928). Here we perform large scale MD simulations of five representative protein/peptide systems in aqueous urea to investigate if the above mechanism is common to other proteins. In all cases, accumulations of urea around proteins/peptide are observed, suggesting that urea denatures proteins by directly attacking protein backbones and side chains rather than indirectly disrupting water structure as a "water breaker". Consistent with our previous case study of lysozyme, the current energetic analyses with five protein/peptide systems reveal that urea's preferential binding to proteins mainly comes from urea's stronger dispersion interactions with proteins than with bulk solution, whereas the electrostatic (hydrogen-bonded) interactions only play a relatively minor (even negative) role during this denaturation process. Furthermore, the simulations of the peptide system at different urea concentrations (8 and 4.5 M), and with different force fields (CHARMM and OPLSAA) suggest that the above mechanism is robust, independent of the urea concentration and force field used. Last, we emphasize the importance of periodic boundary conditions in pairwise energetic analyses. This article provides a comprehensive study on the physical mechanism of urea-induced protein denaturation and suggests that the "dispersion-interaction-driven" mechanism should be general.

Structural principles within the human-virus protein-protein interaction network

PubMed Central

Franzosa, Eric A.; Xia, Yu

2011-01-01

General properties of the antagonistic biomolecular interactions between viruses and their hosts (exogenous interactions) remain poorly understood, and may differ significantly from known principles governing the cooperative interactions within the host (endogenous interactions). Systems biology approaches have been applied to study the combined interaction networks of virus and human proteins, but such efforts have so far revealed only low-resolution patterns of host-virus interaction. Here, we layer curated and predicted 3D structural models of human-virus and human-human protein complexes on top of traditional interaction networks to reconstruct the human-virus structural interaction network. This approach reveals atomic resolution, mechanistic patterns of host-virus interaction, and facilitates systematic comparison with the host’s endogenous interactions. We find that exogenous interfaces tend to overlap with and mimic endogenous interfaces, thereby competing with endogenous binding partners. The endogenous interfaces mimicked by viral proteins tend to participate in multiple endogenous interactions which are transient and regulatory in nature. While interface overlap in the endogenous network results largely from gene duplication followed by divergent evolution, viral proteins frequently achieve interface mimicry without any sequence or structural similarity to an endogenous binding partner. Finally, while endogenous interfaces tend to evolve more slowly than the rest of the protein surface, exogenous interfaces—including many sites of endogenous-exogenous overlap—tend to evolve faster, consistent with an evolutionary “arms race” between host and pathogen. These significant biophysical, functional, and evolutionary differences between host-pathogen and within-host protein-protein interactions highlight the distinct consequences of antagonism versus cooperation in biological networks. PMID:21680884

Molecular modelling of protein-protein/protein-solvent interactions

NASA Astrophysics Data System (ADS)

Luchko, Tyler

The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule destabilization. No conformational change was observed but a nucleotide dependent 'softening' of the interaction was found instead, suggesting that an entropic force in a microtubule configuration could be the mechanism of microtubule collapse. Finally, to overcome much of the computational costs associated with explicit soIvent calculations, a new combination of molecular dynamics with the 3D-reference interaction site model (3D-RISM) of solvation was integrated into the Amber molecular dynamics package. Our implementation of 3D-RISM shows excellent agreement with explicit solvent free energy calculations. Several optimisation techniques, including a new multiple time step method, provide a nearly 100 fold performance increase, giving similar computational performance to explicit solvent.

Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space

NASA Astrophysics Data System (ADS)

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-07-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.

Micro-Environmental Signature of The Interactions between Druggable Target Protein, Dipeptidyl Peptidase-IV, and Anti-Diabetic Drugs.

PubMed

Chakraborty, Chiranjib; Mallick, Bidyut; Sharma, Ashish Ranjan; Sharma, Garima; Jagga, Supriya; Doss, C George Priya; Nam, Ju-Suk; Lee, Sang-Soo

2017-01-01

Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV (DPP-4), and three anti-diabetic drugs (saxagliptin, linagliptin and vildagliptin). During the theoretical and bioinformatics analysis of micro-environmental properties, we performed drug-likeness study, protein active site predictions, docking analysis and residual interactions with the protein-drug interface. Micro-environmental landscape properties were evaluated through various parameters such as binding energy, intermolecular energy, electrostatic energy, van der Waals'+H-bond+desolvo energy (E VHD ) and ligand efficiency (LE) using different in silico methods. For this study, we have used several servers and software, such as Molsoft prediction server, CASTp server, AutoDock software and LIGPLOT server. Through micro-environmental study, highest log P value was observed for linagliptin (1.07). Lowest binding energy was also observed for linagliptin with DPP-4 in the binding plot. We also identified the number of H-bonds and residues involved in the hydrophobic interactions between the DPP-4 and the anti-diabetic drugs. During interaction, two H-bonds and nine residues, two H-bonds and eleven residues as well as four H-bonds and nine residues were found between the saxagliptin, linagliptin as well as vildagliptin cases and DPP-4, respectively. Our in silico data obtained for drug-target interactions and micro-environmental signature demonstrates linagliptin as the most stable interacting drug among the tested anti-diabetic medicines.

Modifications in nanoparticle-protein interactions by varying the protein conformation

NASA Astrophysics Data System (ADS)

Kumar, Sugam; Yadav, I.; Aswal, V. K.; Kohlbrecher, J.

2017-05-01

Small-angle neutron scattering has been used to study the interaction of silica nanoparticle with Bovine Serum Albumin (BSA) protein without and with a protein denaturing agent urea. The measurements have been carried out at pH 7 where both the components (nanoparticle and protein) are similarly charged. We show that the interactions in nanoparticle-protein system can be modified by changing the conformation of protein through the presence of urea. In the absence of urea, the strong electrostatic repulsion between the nanoparticle and protein prevents protein adsorption on nanoparticle surface. This non-adsorption, in turn gives rise to depletion attraction between nanoparticles. However, with addition of urea the depletion attraction is completely suppressed. Urea driven denaturation of protein is utilized to expose the positively charged patched of the BSA molecules which eventually leads to adsorption of BSA on nanoparticles eliminating the depletion interaction.

A novel microfluidics-based method for probing weak protein-protein interactions.

PubMed

Tan, Darren Cherng-wen; Wijaya, I Putu Mahendra; Andreasson-Ochsner, Mirjam; Vasina, Elena Nikolaevna; Nallani, Madhavan; Hunziker, Walter; Sinner, Eva-Kathrin

2012-08-07

We report the use of a novel microfluidics-based method to detect weak protein-protein interactions between membrane proteins. The tight junction protein, claudin-2, synthesised in vitro using a cell-free expression system in the presence of polymer vesicles as membrane scaffolds, was used as a model membrane protein. Individual claudin-2 molecules interact weakly, although the cumulative effect of these interactions is significant. This effect results in a transient decrease of average vesicle dispersivity and reduction in transport speed of claudin-2-functionalised vesicles. Polymer vesicles functionalised with claudin-2 were perfused through a microfluidic channel and the time taken to traverse a defined distance within the channel was measured. Functionalised vesicles took 1.19 to 1.69 times longer to traverse this distance than unfunctionalised ones. Coating the channel walls with protein A and incubating the vesicles with anti-claudin-2 antibodies prior to perfusion resulted in the functionalised vesicles taking 1.75 to 2.5 times longer to traverse this distance compared to the controls. The data show that our system is able to detect weak as well as strong protein-protein interactions. This system offers researchers a portable, easily operated and customizable platform for the study of weak protein-protein interactions, particularly between membrane proteins.

Interaction of murine macrophage-membrane proteins with components of the pathogenic fungus Histoplasma capsulatum

PubMed Central

Taylor, M L; Duarte-Escalante, E; Reyes-Montes, M R; Elizondo, N; Maldonado, G; Zenteno, E

1998-01-01

The interaction of macrophage-membrane proteins and histoplasmin, a crude antigen of the pathogenic fungus Histoplasma capsulatum, was studied using murine peritoneal macrophages. Membrane proteins were purified via membrane attachment to polycationic beads and solubilized in Tris–HCl/SDS/DTT/glycerol for protein extraction; afterwards they were adsorbed or not with H. capsulatum yeast or lectin binding-enriched by affinity chromatography. Membrane proteins and histoplasmin interactions were detected by ELISA and immunoblotting assays using anti-H. capsulatum human or mouse serum and biotinylated goat anti-human or anti-mouse IgG/streptavidin-peroxidase system to reveal the interaction. Results indicate that macrophage-membrane proteins and histoplasmin components interact in a dose-dependent reaction, and adsorption of macrophage-membrane proteins by yeast cells induces a critical decrease in the interaction. Macrophage-membrane glycoproteins with terminal d-galactosyl residues, purified by chromatography with Abrus precatorius lectin, bound to histoplasmin; and two bands of 68 kD and 180 kD of transferred membrane protein samples interacted with histoplasmin components, as revealed by immunoblot assays. Specificity for β-galactoside residues on the macrophage-membrane was confirmed by galactose inhibition of the interaction between macrophage-membrane proteins and histoplasmin components, in competitive ELISA using sugars, as well as by enzymatic cleavage of the galactoside residues. PMID:9737672

Protein interactions and ligand binding: from protein subfamilies to functional specificity.

PubMed

Rausell, Antonio; Juan, David; Pazos, Florencio; Valencia, Alfonso

2010-02-02

The divergence accumulated during the evolution of protein families translates into their internal organization as subfamilies, and it is directly reflected in the characteristic patterns of differentially conserved residues. These specifically conserved positions in protein subfamilies are known as "specificity determining positions" (SDPs). Previous studies have limited their analysis to the study of the relationship between these positions and ligand-binding specificity, demonstrating significant yet limited predictive capacity. We have systematically extended this observation to include the role of differential protein interactions in the segregation of protein subfamilies and explored in detail the structural distribution of SDPs at protein interfaces. Our results show the extensive influence of protein interactions in the evolution of protein families and the widespread association of SDPs with protein interfaces. The combined analysis of SDPs in interfaces and ligand-binding sites provides a more complete picture of the organization of protein families, constituting the necessary framework for a large scale analysis of the evolution of protein function.

Protein-Protein Interaction Reagents | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

Identification of interacting proteins of the TaFVE protein involved in spike development in bread wheat.

PubMed

Zheng, Yong-Sheng; Lu, Yu-Qing; Meng, Ying-Ying; Zhang, Rong-Zhi; Zhang, Han; Sun, Jia-Mei; Wang, Mu-Mu; Li, Li-Hui; Li, Ru-Yu

2017-05-01

WD-40 repeat-containing protein MSI4 (FVE)/MSI4 plays important roles in determining flowering time in Arabidopsis. However, its function is unexplored in wheat. In the present study, coimmunoprecipitation and nanoscale liquid chromatography coupled to MS/MS were used to identify FVE in wheat (TaFVE)-interacting or associated proteins. Altogether 89 differentially expressed proteins showed the same downregulated expression trends as TaFVE in wheat line 5660M. Among them, 62 proteins were further predicted to be involved in the interaction network of TaFVE and 11 proteins have been shown to be potential TaFVE interactors based on curated databases and experimentally determined in other species by the STRING. Both yeast two-hybrid assay and bimolecular fluorescence complementation assay showed that histone deacetylase 6 and histone deacetylase 15 directly interacted with TaFVE. Multiple chromatin-remodelling proteins and polycomb group proteins were also identified and predicted to interact with TaFVE. These results showed that TaFVE directly interacted with multiple proteins to form multiple complexes to regulate spike developmental process, e.g. histone deacetylate, chromatin-remodelling and polycomb repressive complex 2 complexes. In addition, multiple flower development regulation factors (e.g. flowering locus K homology domain, flowering time control protein FPA, FY, flowering time control protein FCA, APETALA 1) involved in floral transition were also identified in the present study. Taken together, these results further elucidate the regulatory functions of TaFVE and help reveal the genetic mechanisms underlying wheat spike differentiation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

PubMed Central

2012-01-01

Background There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. Results The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. Conclusions In addition to confirming literature results, ProGolem’s model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners. PMID:22783946

Photoactivatable protein labeling by singlet oxygen mediated reactions.

PubMed

To, Tsz-Leung; Medzihradszky, Katalin F; Burlingame, Alma L; DeGrado, William F; Jo, Hyunil; Shu, Xiaokun

2016-07-15

Protein-protein interactions regulate many biological processes. Identification of interacting proteins is thus an important step toward molecular understanding of cell signaling. The aim of this study was to investigate the use of photo-generated singlet oxygen and a small molecule for proximity labeling of interacting proteins in cellular environment. The protein of interest (POI) was fused with a small singlet oxygen photosensitizer (miniSOG), which generates singlet oxygen ((1)O2) upon irradiation. The locally generated singlet oxygen then activated a biotin-conjugated thiol molecule to form a covalent bond with the proteins nearby. The labeled proteins can then be separated and subsequently identified by mass spectrometry. To demonstrate the applicability of this labeling technology, we fused the miniSOG to Skp2, an F-box protein of the SCF ubiquitin ligase, and expressed the fusion protein in mammalian cells and identified that the surface cysteine of its interacting partner Skp1 was labeled by the biotin-thiol molecule. This photoactivatable protein labeling method may find important applications including identification of weak and transient protein-protein interactions in the native cellular context, as well as spatial and temporal control of protein labeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Physical Interaction Network of Dengue Virus and Human Proteins*

PubMed Central

Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

2011-01-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

A new protein-protein interaction sensor based on tripartite split-GFP association.

PubMed

Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

2013-10-04

Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

A New Protein-Protein Interaction Sensor Based on Tripartite Split-GFP Association

PubMed Central

Cabantous, Stéphanie; Nguyen, Hau B.; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A.; Favre, Gilles; Terwilliger, Thomas C.; Waldo, Geoffrey S.

2013-01-01

Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence. PMID:24092409

Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

PubMed Central

2011-01-01

Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally different groups of proteins and interactions. We conclude that it is a useful and important measure to be used in concert with gene co-expression correlation for further insights into the characteristics of proteins in the context of their interaction network. PMID:22369639

Protein 19F-labeling using transglutaminase for the NMR study of intermolecular interactions.

PubMed

Hattori, Yoshikazu; Heidenreich, David; Ono, Yuki; Sugiki, Toshihiko; Yokoyama, Kei-Ichi; Suzuki, Ei-Ichiro; Fujiwara, Toshimichi; Kojima, Chojiro

2017-08-01

The preparation of stable isotope-labeled proteins is important for NMR studies, however, it is often hampered in the case of eukaryotic proteins which are not readily expressed in Escherichia coli. Such proteins are often conveniently investigated following post-expression chemical isotope tagging. Enzymatic 15 N-labeling of glutamine side chains using transglutaminase (TGase) has been applied to several proteins for NMR studies. 19 F-labeling is useful for interaction studies due to its high NMR sensitivity and susceptibility. Here, 19 F-labeling of glutamine side chains using TGase and 2,2,2-trifluoroethylamine hydrochloride was established for use in an NMR study. This enzymatic 19 F-labeling readily provided NMR detection of protein-drug and protein-protein interactions with complexes of about 100 kDa since the surface residues provided a good substrate for TGase. The 19 F-labeling method was 3.5-fold more sensitive than 15 N-labeling, and could be combined with other chemical modification techniques such as lysine 13 C-methylation. 13 C-dimethylated- 19 F-labeled FKBP12 provided more accurate information concerning the FK506 binding site.

Incorporating water-release and lateral protein interactions in modeling equilibrium adsorption for ion-exchange chromatography.

PubMed

Thrash, Marvin E; Pinto, Neville G

2006-09-08

The equilibrium adsorption of two albumin proteins on a commercial ion exchanger has been studied using a colloidal model. The model accounts for electrostatic and van der Waals forces between proteins and the ion exchanger surface, the energy of interaction between adsorbed proteins, and the contribution of entropy from water-release accompanying protein adsorption. Protein-surface interactions were calculated using methods previously reported in the literature. Lateral interactions between adsorbed proteins were experimentally measured with microcalorimetry. Water-release was estimated by applying the preferential interaction approach to chromatographic retention data. The adsorption of ovalbumin and bovine serum albumin on an anion exchanger at solution pH>pI of protein was measured. The experimental isotherms have been modeled from the linear region to saturation, and the influence of three modulating alkali chlorides on capacity has been evaluated. The heat of adsorption is endothermic for all cases studied, despite the fact that the net charge on the protein is opposite that of the adsorbing surface. Strong repulsive forces between adsorbed proteins underlie the endothermic heat of adsorption, and these forces intensify with protein loading. It was found that the driving force for adsorption is the entropy increase due to the release of water from the protein and adsorbent surfaces. It is shown that the colloidal model predicts protein adsorption capacity in both the linear and non-linear isotherm regions, and can account for the effects of modulating salt.

Predicting permanent and transient protein-protein interfaces.

PubMed

La, David; Kong, Misun; Hoffman, William; Choi, Youn Im; Kihara, Daisuke

2013-05-01

Protein-protein interactions (PPIs) are involved in diverse functions in a cell. To optimize functional roles of interactions, proteins interact with a spectrum of binding affinities. Interactions are conventionally classified into permanent and transient, where the former denotes tight binding between proteins that result in strong complexes, whereas the latter compose of relatively weak interactions that can dissociate after binding to regulate functional activity at specific time point. Knowing the type of interactions has significant implications for understanding the nature and function of PPIs. In this study, we constructed amino acid substitution models that capture mutation patterns at permanent and transient type of protein interfaces, which were found to be different with statistical significance. Using the substitution models, we developed a novel computational method that predicts permanent and transient protein binding interfaces (PBIs) in protein surfaces. Without knowledge of the interacting partner, the method uses a single query protein structure and a multiple sequence alignment of the sequence family. Using a large dataset of permanent and transient proteins, we show that our method, BindML+, performs very well in protein interface classification. A very high area under the curve (AUC) value of 0.957 was observed when predicted protein binding sites were classified. Remarkably, near prefect accuracy was achieved with an AUC of 0.991 when actual binding sites were classified. The developed method will be also useful for protein design of permanent and transient PBIs. Copyright © 2013 Wiley Periodicals, Inc.

Bioluminescence resonance energy transfer system for measuring dynamic protein-protein interactions in bacteria.

PubMed

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong; Luo, Zhao-Qing; Shen, Xihui

2014-05-20

Protein-protein interactions are important for virtually every biological process, and a number of elegant approaches have been designed to detect and evaluate such interactions. However, few of these methods allow the detection of dynamic and real-time protein-protein interactions in bacteria. Here we describe a bioluminescence resonance energy transfer (BRET) system based on the bacterial luciferase LuxAB. We found that enhanced yellow fluorescent protein (eYFP) accepts the emission from LuxAB and emits yellow fluorescence. Importantly, BRET occurred when LuxAB and eYFP were fused, respectively, to the interacting protein pair FlgM and FliA. Furthermore, we observed sirolimus (i.e., rapamycin)-inducible interactions between FRB and FKBP12 and a dose-dependent abolishment of such interactions by FK506, the ligand of FKBP12. Using this system, we showed that osmotic stress or low pH efficiently induced multimerization of the regulatory protein OmpR and that the multimerization induced by low pH can be reversed by a neutralizing agent, further indicating the usefulness of this system in the measurement of dynamic interactions. This method can be adapted to analyze dynamic protein-protein interactions and the importance of such interactions in bacterial processes such as development and pathogenicity. Real-time measurement of protein-protein interactions in prokaryotes is highly desirable for determining the roles of protein complex in the development or virulence of bacteria, but methods that allow such measurement are not available. Here we describe the development of a bioluminescence resonance energy transfer (BRET) technology that meets this need. The use of endogenous excitation light in this strategy circumvents the requirement for the sophisticated instrument demanded by standard fluorescence resonance energy transfer (FRET). Furthermore, because the LuxAB substrate decanal is membrane permeable, the assay can be performed without lysing the bacterial cells, thus allowing the detection of protein-protein interactions in live bacterial cells. This BRET system added another useful tool to address important questions in microbiological studies. Copyright © 2014 Cui et al.

Membrane proteins from the cyanobacterium Synechocystis sp. PCC 6803 interacting with thioredoxin.

PubMed

Mata-Cabana, Alejandro; Florencio, Francisco J; Lindahl, Marika

2007-11-01

Cysteine dithiol/disulphide exchange forms the molecular basis for regulation of a wide variety of enzymatic activities and for transduction of cellular signals. Thus, the search for proteins with reactive, accessible cysteines is expected to contribute to the unravelling of new molecular mechanisms for enzyme regulation and signal transduction. Several methods have been designed for this purpose taking advantage of the interactions between thioredoxins and their protein substrates. Thioredoxins comprise a family of redox-active enzymes, which catalyse reduction of protein disulphides and sulphenic acids. Due to the inherent practical difficulties associated with studies of membrane proteins these have been largely overlooked in the many proteomic studies of thioredoxin-interacting proteins. In the present work, we have developed a procedure to isolate membrane proteins interacting with thioredoxin by binding in situ to a monocysteinic His-tagged thioredoxin added directly to the intact membranes. Following fractionation and solubilisation of the membranes, thioredoxin target proteins were isolated by Ni-affinity chromatography and 2-DE SDS-PAGE under nonreducing/reducing conditions. Applying this method to total membranes, including thylakoid and plasma membranes, from the cyanobacterium Synechocystis sp. PCC 6803 we have identified 50 thioredoxin-interacting proteins. Among the 38 newly identified thioredoxin targets are the ATP-binding subunits of several transporters and members of the AAA-family of ATPases.

Identification of host cellular proteins that interact with the M protein of a highly pathogenic porcine reproductive and respiratory syndrome virus vaccine strain.

PubMed

Wang, Qian; Li, Yanwei; Dong, Hong; Wang, Li; Peng, Jinmei; An, Tongqing; Yang, Xufu; Tian, Zhijun; Cai, Xuehui

2017-02-22

The highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) continues to pose one of the greatest threats to the swine industry. M protein is the most conserved and important structural protein of PRRSV. However, information about the host cellular proteins that interact with M protein remains limited. Host cellular proteins that interact with the M protein of HP-PRRSV were immunoprecipitated from MARC-145 cells infected with PRRSV HuN4-F112 using the M monoclonal antibody (mAb). The differentially expressed proteins were identified by LC-MS/MS. The screened proteins were used for bioinformatics analysis including Gene Ontology, the interaction network, and the enriched KEGG pathways. Some interested cellular proteins were validated to interact with M protein by CO-IP. The PRRSV HuN4-F112 infection group had 10 bands compared with the control group. The bands included 219 non-redundant cellular proteins that interact with M protein, which were identified by LC-MS/MS with high confidence. The gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway bioinformatic analyses indicated that the identified proteins could be assigned to several different subcellular locations and functional classes. Functional analysis of the interactome profile highlighted cellular pathways associated with protein translation, infectious disease, and signal transduction. Two interested cellular proteins-nuclear factor of activated T cells 45 kDa (NF45) and proliferating cell nuclear antigen (PCNA)-that could interact with M protein were validated by Co-IP and confocal analyses. The interactome data between PRRSV M protein and cellular proteins were identified and contribute to the understanding of the roles of M protein in the replication and pathogenesis of PRRSV. The interactome of M protein will aid studies of virus/host interactions and provide means to decrease the threat of PRRSV to the swine industry in the future.

Construction of reliable protein-protein interaction networks with a new interaction generality measure.

PubMed

Saito, Rintaro; Suzuki, Harukazu; Hayashizaki, Yoshihide

2003-04-12

Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed. We developed a new 'interaction generality' measure (IG2) to assess the reliability of protein-protein interactions using only the topological properties of their interaction-network structure. Using yeast protein-protein interaction data, we showed that reliable protein-protein interactions had significantly lower IG2 values than less-reliable interactions, suggesting that IG2 values can be used to evaluate and filter interaction data to enable the construction of reliable protein-protein interaction networks.

Fluorescence turn-on responses of anionic and cationic conjugated polymers toward proteins: effect of electrostatic and hydrophobic interactions.

PubMed

Pu, Kan-Yi; Liu, Bin

2010-03-11

Cationic and anionic poly(fluorenyleneethynylene-alt-benzothiadiazole)s (PFEBTs) are designed and synthesized via Sonagashira coupling reaction to show light-up signatures toward proteins. Due to the charge transfer character of the excited states, the fluorescence of PFEBTs is very weak in aqueous solution, while their yellow fluorescence can be enhanced by polymer aggregation. PFEBTs show fluorescence turn-on rather than fluorescence quenching upon complexation with proteins. Both electrostatic and hydrophobic interactions between PFEBTs and proteins are found to improve the polymer fluorescence, the extent of which is dependent on the nature of the polymer and the protein. Changes in solution pH adjust the net charges of proteins, providing an effective way to manipulate electrostatic interactions and in turn the increment in the polymer fluorescence. In addition, the effect of protein digestion on the fluorescence of polymer/protein complexes is probed. The results indicate that electrostatic interaction induced polymer fluorescence increase cannot be substantially reduced through cleaving protein into peptide fragments. In contrast, hydrophobic interactions, mainly determined by the hydrophobicity of proteins, can be minimized by digestion, imparting a light-off signature for the polymer/protein complexes. This study thus not only highlights the opportunities of exerting nonspecific interactions for protein sensing but also reveals significant implications for biosensor design.

Amino Acid Interaction (INTAA) web server.

PubMed

Galgonek, Jakub; Vymetal, Jirí; Jakubec, David; Vondrášek, Jirí

2017-07-03

Large biomolecules-proteins and nucleic acids-are composed of building blocks which define their identity, properties and binding capabilities. In order to shed light on the energetic side of interactions of amino acids between themselves and with deoxyribonucleotides, we present the Amino Acid Interaction web server (http://bioinfo.uochb.cas.cz/INTAA/). INTAA offers the calculation of the residue Interaction Energy Matrix for any protein structure (deposited in Protein Data Bank or submitted by the user) and a comprehensive analysis of the interfaces in protein-DNA complexes. The Interaction Energy Matrix web application aims to identify key residues within protein structures which contribute significantly to the stability of the protein. The application provides an interactive user interface enhanced by 3D structure viewer for efficient visualization of pairwise and net interaction energies of individual amino acids, side chains and backbones. The protein-DNA interaction analysis part of the web server allows the user to view the relative abundance of various configurations of amino acid-deoxyribonucleotide pairs found at the protein-DNA interface and the interaction energies corresponding to these configurations calculated using a molecular mechanical force field. The effects of the sugar-phosphate moiety and of the dielectric properties of the solvent on the interaction energies can be studied for the various configurations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

PubMed

Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

2010-07-01

The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

Lipid Interaction Sites on Channels, Transporters and Receptors: Recent Insights from Molecular Dynamics Simulations

PubMed Central

Hedger, George; Sansom, Mark S. P.

2017-01-01

Lipid molecules are able to selectively interact with specific sites on integral membrane proteins, and modulate their structure and function. Identification and characterisation of these sites is of importance for our understanding of the molecular basis of membrane protein function and stability, and may facilitate the design of lipid-like drug molecules. Molecular dynamics simulations provide a powerful tool for the identification of these sites, complementing advances in membrane protein structural biology and biophysics. We describe recent notable biomolecular simulation studies which have identified lipid interaction sites on a range of different membrane proteins. The sites identified in these simulation studies agree well with those identified by complementary experimental techniques. This demonstrates the power of the molecular dynamics approach in the prediction and characterization of lipid interaction sites on integral membrane proteins. PMID:26946244

Contribution of Hydrophobic Interactions to Protein Stability

PubMed Central

Pace, C. Nick; Fu, Hailong; Fryar, Katrina Lee; Landua, John; Trevino, Saul R.; Shirley, Bret A.; Hendricks, Marsha McNutt; Iimura, Satoshi; Gajiwala, Ketan; Scholtz, J. Martin; Grimsley, Gerald R.

2011-01-01

Our goal was to gain a better understanding of the contribution of hydrophobic interactions to protein stability. We measured the change in conformational stability, Δ(ΔG), for hydrophobic mutants of four proteins: villin head piece subdomain (VHP) with 36 residues, a surface protein from Borrelia burgdorferi (VlsE) with 341 residues, and two proteins previously studied in our laboratory, ribonucleases Sa and T1. We compare our results with previous studies and reach the following conclusions. 1. Hydrophobic interactions contribute less to the stability of a small protein, VHP (0.6 ± 0.3 kcal/mole per –CH2– group), than to the stability of a large protein, VlsE (1.6 ± 0.3 kcal/mol per –CH2– group). 2. Hydrophobic interactions make the major contribution to the stability of VHP (40 kcal/mol) and the major contributors are (in kcal/mol): Phe 18 (3.9), Met 13 (3.1), Phe 7 (2.9), Phe 11 (2.7), and Leu 21 (2.7). 3. Based on Δ(ΔG) values for 148 hydrophobic mutants in 13 proteins, burying a –CH2– group on folding contributes, on average, 1.1 ± 0.5 kcal/mol to protein stability. 4. The experimental Δ(ΔG) values for aliphatic side chains (Ala, Val, Ile, and Leu) are in good agreement with their ΔGtr values from water to cyclohexane. 5. For 22 proteins with 36 to 534 residues, hydrophobic interactions contribute 60 ± 4% and hydrogen bonds 40 ± 4% to protein stability. 6. Conformational entropy contributes about 2.4 kcal/mol per residue to protein instability. The globular conformation of proteins is stabilized predominately by hydrophobic interactions. PMID:21377472

The simulation approach to lipid-protein interactions.

PubMed

Paramo, Teresa; Garzón, Diana; Holdbrook, Daniel A; Khalid, Syma; Bond, Peter J

2013-01-01

The interactions between lipids and proteins are crucial for a range of biological processes, from the folding and stability of membrane proteins to signaling and metabolism facilitated by lipid-binding proteins. However, high-resolution structural details concerning functional lipid/protein interactions are scarce due to barriers in both experimental isolation of native lipid-bound complexes and subsequent biophysical characterization. The molecular dynamics (MD) simulation approach provides a means to complement available structural data, yielding dynamic, structural, and thermodynamic data for a protein embedded within a physiologically realistic, modelled lipid environment. In this chapter, we provide a guide to current methods for setting up and running simulations of membrane proteins and soluble, lipid-binding proteins, using standard atomistically detailed representations, as well as simplified, coarse-grained models. In addition, we outline recent studies that illustrate the power of the simulation approach in the context of biologically relevant lipid/protein interactions.

Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

PubMed Central

Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

2013-01-01

We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

A Luciferase-fragment Complementation Assay to Detect Lipid Droplet-associated Protein-Protein Interactions*

PubMed Central

Kolkhof, Petra; Werthebach, Michael; van de Venn, Anna; Poschmann, Gereon; Chen, Lili; Welte, Michael; Stühler, Kai; Beller, Mathias

2017-01-01

A critical challenge for all organisms is to carefully control the amount of lipids they store. An important node for this regulation is the protein coat present at the surface of lipid droplets (LDs), the intracellular organelles dedicated to lipid storage. Only limited aspects of this regulation are understood so far. For the probably best characterized case, the regulation of lipolysis in mammals, some of the major protein players have been identified, and it has been established that this process crucially depends on an orchestrated set of protein-protein interactions. Proteomic analysis has revealed that LDs are associated with dozens, if not hundreds, of different proteins, most of them poorly characterized, with even fewer data regarding which of them might physically interact. To comprehensively understand the mechanism of lipid storage regulation, it will likely be essential to define the interactome of LD-associated proteins. Previous studies of such interactions were hampered by technical limitations. Therefore, we have developed a split-luciferase based protein-protein interaction assay and test for interactions among 47 proteins from Drosophila and from mouse. We confirmed previously described interactions and identified many new ones. In 1561 complementation tests, we assayed for interactions among 487 protein pairs of which 92 (19%) resulted in a successful luciferase complementation. These results suggest that a prominent fraction of the LD-associated proteome participates in protein-protein interactions. In targeted experiments, we analyzed the two proteins Jabba and CG9186 in greater detail. Jabba mediates the sequestration of histones to LDs. We successfully applied our split luciferase complementation assay to learn more about this function as we were e.g. able to map the interaction between Jabba and histones. For CG9186, expression levels affect the positioning of LDs. Here, we reveal the ubiquitination of CG9186, and link this posttranslational modification to LD cluster induction. PMID:27956707

Molecular interactions between chondroitin-dermatan sulfate and growth factors/receptors/matrix proteins.

PubMed

Mizumoto, Shuji; Yamada, Shuhei; Sugahara, Kazuyuki

2015-10-01

Recent functional studies on chondroitin sulfate-dermatan sulfate (CS-DS) demonstrated its indispensable roles in various biological events including brain development and cancer. CS-DS proteoglycans exert their physiological activity through interactions with specific proteins including growth factors, cell surface receptors, and matrix proteins. The characterization of these interactions is essential for regulating the biological functions of CS-DS proteoglycans. Although amino acid sequences on the bioactive proteins required for these interactions have already been elucidated, the specific saccharide sequences involved in the binding of CS-DS to target proteins have not yet been sufficiently identified. In this review, recent findings are described on the interaction between CS-DS and some proteins which are especially involved in the central nervous system and cancer development/metastasis. Copyright © 2015. Published by Elsevier Ltd.

Influence of wine pectic polysaccharides on the interactions between condensed tannins and salivary proteins.

PubMed

Carvalho, Elisabete; Mateus, Nuno; Plet, Benoit; Pianet, Isabelle; Dufourc, Erick; De Freitas, Victor

2006-11-15

Alpha-amylase, a major human salivary protein, and IB8c, a representative of the proline-rich proteins, were obtained by isolation from saliva and by solid-phase synthesis, respectively. The interactions between these proteins and condensed tannins isolated from grape seeds were studied at different protein and tannin concentrations by measuring their aggregation. Pectic polysaccharides were isolated from wine, and their effect on protein tannin aggregation was assessed. The results presented in this study showed that the most acidic fractions of arabinogalactan proteins have the ability to inhibit the formation of aggregates between the grape seed tannins and the two different salivary proteins. Rhamnogalacturonan II has the same ability toward alpha-amylase but not IB8c under the conditions of the present study. Polysaccharides show effects at concentrations at which they are present in wine, which could mean an influence in wine astringency. The interaction between condensed tannins and alpha-amylase is differently affected by ionic strength when compared with IB8c.

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

A Protein Interaction Map of the Kalimantacin Biosynthesis Assembly Line

PubMed Central

Uytterhoeven, Birgit; Lathouwers, Thomas; Voet, Marleen; Michiels, Chris W.; Lavigne, Rob

2016-01-01

The antimicrobial secondary metabolite kalimantacin (also called batumin) is produced by a hybrid polyketide/non-ribosomal peptide system in Pseudomonas fluorescens BCCM_ID9359. In this study, the kalimantacin biosynthesis gene cluster is analyzed by yeast two-hybrid analysis, creating a protein–protein interaction map of the entire assembly line. In total, 28 potential interactions were identified, of which 13 could be confirmed further. These interactions include the dimerization of ketosynthase domains, a link between assembly line modules 9 and 10, and a specific interaction between the trans-acting enoyl reductase BatK and the carrier proteins of modules 8 and 10. These interactions reveal fundamental insight into the biosynthesis of secondary metabolites. This study is the first to reveal interactions in a complete biosynthetic pathway. Similar future studies could build a strong basis for engineering strategies in such clusters. PMID:27853452

A high-throughput and rapid computational method for screening of RNA post-transcriptional modifications that can be recognized by target proteins.

PubMed

Orr, Asuka A; Gonzalez-Rivera, Juan C; Wilson, Mark; Bhikha, P Reena; Wang, Daiqi; Contreras, Lydia M; Tamamis, Phanourios

2018-02-01

There are over 150 currently known, highly diverse chemically modified RNAs, which are dynamic, reversible, and can modulate RNA-protein interactions. Yet, little is known about the wealth of such interactions. This can be attributed to the lack of tools that allow the rapid study of all the potential RNA modifications that might mediate RNA-protein interactions. As a promising step toward this direction, here we present a computational protocol for the characterization of interactions between proteins and RNA containing post-transcriptional modifications. Given an RNA-protein complex structure, potential RNA modified ribonucleoside positions, and molecular mechanics parameters for capturing energetics of RNA modifications, our protocol operates in two stages. In the first stage, a decision-making tool, comprising short simulations and interaction energy calculations, performs a fast and efficient search in a high-throughput fashion, through a list of different types of RNA modifications categorized into trees according to their structural and physicochemical properties, and selects a subset of RNA modifications prone to interact with the target protein. In the second stage, RNA modifications that are selected as recognized by the protein are examined in-detail using all-atom simulations and free energy calculations. We implement and experimentally validate this protocol in a test case involving the study of RNA modifications in complex with Escherichia coli (E. coli) protein Polynucleotide Phosphorylase (PNPase), depicting the favorable interaction between 8-oxo-7,8-dihydroguanosine (8-oxoG) RNA modification and PNPase. Further advancement of the protocol can broaden our understanding of protein interactions with all known RNA modifications in several systems. Copyright © 2018 Elsevier Inc. All rights reserved.

Interaction of monomeric Ebola VP40 protein with a plasma membrane: A coarse-grained molecular dynamics (CGMD) simulation study.

PubMed

Mohamad Yusoff, Mohamad Ariff; Abdul Hamid, Azzmer Azzar; Mohammad Bunori, Noraslinda; Abd Halim, Khairul Bariyyah

2018-06-01

Ebola virus is a lipid-enveloped filamentous virus that affects human and non-human primates and consists of several types of protein: nucleoprotein, VP30, VP35, L protein, VP40, VP24, and transmembrane glycoprotein. Among the Ebola virus proteins, its matrix protein VP40 is abundantly expressed during infection and plays a number of critical roles in oligomerization, budding and egress from the host cell. VP40 exists predominantly as a monomer at the inner leaflet of the plasma membrane, and has been suggested to interact with negatively charged lipids such as phosphatidylinositol 4,5-bisphosphate (PIP 2 ) and phosphatidylserine (PS) via its cationic patch. The hydrophobic loop at the C-terminal domain has also been shown to be important in the interaction between the VP40 and the membrane. However, details of the molecular mechanisms underpinning their interactions are not fully understood. This study aimed at investigating the effects of mutation in the cationic patch and hydrophobic loop on the interaction between the VP40 monomer and the plasma membrane using coarse-grained molecular dynamics simulation (CGMD). Our simulations revealed that the interaction between VP40 and the plasma membrane is mediated by the cationic patch residues. This led to the clustering of PIP 2 around the protein in the inner leaflet as a result of interactions between some cationic residues including R52, K127, K221, K224, K225, K256, K270, K274, K275 and K279 and PIP 2 lipids via electrostatic interactions. Mutation of the cationic patch or hydrophobic loop amino acids caused the protein to bind at the inner leaflet of the plasma membrane in a different orientation, where no significant clustering of PIP 2 was observed around the mutated protein. This study provides basic understanding of the interaction of the VP40 monomer and its mutants with the plasma membrane. Copyright © 2018 Elsevier Inc. All rights reserved.

Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer.

PubMed

Shah, Anup D; Inder, Kerry L; Shah, Alok K; Cristino, Alexandre S; McKie, Arthur B; Gabra, Hani; Davis, Melissa J; Hill, Michelle M

2016-10-07

Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

Mechanisms of protein stabilization and prevention of protein aggregation by glycerol.

PubMed

Vagenende, Vincent; Yap, Miranda G S; Trout, Bernhardt L

2009-11-24

The stability of proteins in aqueous solution is routinely enhanced by cosolvents such as glycerol. Glycerol is known to shift the native protein ensemble to more compact states. Glycerol also inhibits protein aggregation during the refolding of many proteins. However, mechanistic insight into protein stabilization and prevention of protein aggregation by glycerol is still lacking. In this study, we derive mechanisms of glycerol-induced protein stabilization by combining the thermodynamic framework of preferential interactions with molecular-level insight into solvent-protein interactions gained from molecular simulations. Contrary to the common conception that preferential hydration of proteins in polyol/water mixtures is determined by the molecular size of the polyol and the surface area of the protein, we present evidence that preferential hydration of proteins in glycerol/water mixtures mainly originates from electrostatic interactions that induce orientations of glycerol molecules at the protein surface such that glycerol is further excluded. These interactions shift the native protein toward more compact conformations. Moreover, glycerol preferentially interacts with large patches of contiguous hydrophobicity where glycerol acts as an amphiphilic interface between the hydrophobic surface and the polar solvent. Accordingly, we propose that glycerol prevents protein aggregation by inhibiting protein unfolding and by stabilizing aggregation-prone intermediates through preferential interactions with hydrophobic surface regions that favor amphiphilic interface orientations of glycerol. These mechanisms agree well with experimental data available in the literature, and we discuss the extent to which these mechanisms apply to other cosolvents, including polyols, arginine, and urea.

Analyses of Coronavirus Assembly Interactions with Interspecies Membrane and Nucleocapsid Protein Chimeras

PubMed Central

Kuo, Lili; Hurst-Hess, Kelley R.; Koetzner, Cheri A.

2016-01-01

ABSTRACT The coronavirus membrane (M) protein is the central actor in virion morphogenesis. M organizes the components of the viral membrane, and interactions of M with itself and with the nucleocapsid (N) protein drive virus assembly and budding. In order to further define M-M and M-N interactions, we constructed mutants of the model coronavirus mouse hepatitis virus (MHV) in which all or part of the M protein was replaced by its phylogenetically divergent counterpart from severe acute respiratory syndrome coronavirus (SARS-CoV). We were able to obtain viable chimeras containing the entire SARS-CoV M protein as well as mutants with intramolecular substitutions that partitioned M protein at the boundaries between the ectodomain, transmembrane domains, or endodomain. Our results show that the carboxy-terminal domain of N protein, N3, is necessary and sufficient for interaction with M protein. However, despite some previous genetic and biochemical evidence that mapped interactions with N to the carboxy terminus of M, it was not possible to define a short linear region of M protein sufficient for assembly with N. Thus, interactions with N protein likely involve multiple linearly discontiguous regions of the M endodomain. The SARS-CoV M chimera exhibited a conditional growth defect that was partially suppressed by mutations in the envelope (E) protein. Moreover, virions of the M chimera were markedly deficient in spike (S) protein incorporation. These findings suggest that the interactions of M protein with both E and S protein are more complex than previously thought. IMPORTANCE The assembly of coronavirus virions entails concerted interactions among the viral structural proteins and the RNA genome. One strategy to study this process is through construction of interspecies chimeras that preserve or disrupt particular inter- or intramolecular associations. In this work, we replaced the membrane (M) protein of the model coronavirus mouse hepatitis virus with its counterpart from a heterologous coronavirus. The results clarify our understanding of the interaction between the coronavirus M protein and the nucleocapsid protein. At the same time, they reveal unanticipated complexities in the interactions of M with the viral spike and envelope proteins. PMID:26889024

Paramyxovirus V Proteins Interact with the RIG-I/TRIM25 Regulatory Complex and Inhibit RIG-I Signaling.

PubMed

Sánchez-Aparicio, Maria T; Feinman, Leighland J; García-Sastre, Adolfo; Shaw, Megan L

2018-03-15

Paramyxovirus V proteins are known antagonists of the RIG-I-like receptor (RLR)-mediated interferon induction pathway, interacting with and inhibiting the RLR MDA5. We report interactions between the Nipah virus V protein and both RIG-I regulatory protein TRIM25 and RIG-I. We also observed interactions between these host proteins and the V proteins of measles virus, Sendai virus, and parainfluenza virus. These interactions are mediated by the conserved C-terminal domain of the V protein, which binds to the tandem caspase activation and recruitment domains (CARDs) of RIG-I (the region of TRIM25 ubiquitination) and to the SPRY domain of TRIM25, which mediates TRIM25 interaction with the RIG-I CARDs. Furthermore, we show that V interaction with TRIM25 and RIG-I prevents TRIM25-mediated ubiquitination of RIG-I and disrupts downstream RIG-I signaling to the mitochondrial antiviral signaling protein. This is a novel mechanism for innate immune inhibition by paramyxovirus V proteins, distinct from other known V protein functions such as MDA5 and STAT1 antagonism. IMPORTANCE The host RIG-I signaling pathway is a key early obstacle to paramyxovirus infection, as it results in rapid induction of an antiviral response. This study shows that paramyxovirus V proteins interact with and inhibit the activation of RIG-I, thereby interrupting the antiviral signaling pathway and facilitating virus replication. Copyright © 2018 American Society for Microbiology.

Computational Methods to Predict Protein Interaction Partners

NASA Astrophysics Data System (ADS)

Valencia, Alfonso; Pazos, Florencio

In the new paradigm for studying biological phenomena represented by Systems Biology, cellular components are not considered in isolation but as forming complex networks of relationships. Protein interaction networks are among the first objects studied from this new point of view. Deciphering the interactome (the whole network of interactions for a given proteome) has been shown to be a very complex task. Computational techniques for detecting protein interactions have become standard tools for dealing with this problem, helping and complementing their experimental counterparts. Most of these techniques use genomic or sequence features intuitively related with protein interactions and are based on "first principles" in the sense that they do not involve training with examples. There are also other computational techniques that use other sources of information (i.e. structural information or even experimental data) or are based on training with examples.

Characterizing protein-protein-interaction in high-concentration monoclonal antibody systems with the quartz crystal microbalance.

PubMed

Hartl, Josef; Peschel, Astrid; Johannsmann, Diethelm; Garidel, Patrick

2017-12-13

Making use of a quartz crystal microbalance (QCM), concentrated solutions of therapeutic antibodies were studied with respect to their behavior under shear excitation with frequencies in the MHz range. At high protein concentration and neutral pH, viscoelastic behavior was found in the sense that the storage modulus, G', was nonzero. Fits of the frequency dependence of G'(ω) and G''(ω) (G'' being the loss modulus) using the Maxwell-model produced good agreement with the experimental data. The fit parameters were the relaxation time, τ, and the shear modulus at the inverse relaxation time, G* (at the "cross-over frequency" ω C = 1/τ). The influence of two different pharmaceutical excipients (histidine and citrate) was studied at variable concentrations of the antibody and variable pH. In cases, where viscoelasticity was observed, G* was in the range of a few kPa, consistent with entropy-driven interactions. τ was small at low pH, where the antibody carries a positive charge. τ increased with increasing pH. The relaxation time τ was found to be correlated with other parameters quantifying protein-protein interactions, namely the steady shear viscosity (η), the second osmotic virial coefficient as determined with both self-interaction chromatography (B 22,SIC ) and static light scattering (B 22,SLS ), and the diffusion interaction parameter as determined with dynamic light scattering (k D ). While B 22 and k D describe protein-protein interactions in diluted samples, the QCM can be applied to concentrated solutions, thereby being sensitive to higher-order protein-protein interactions.

Analysis of protein targets in pathogen-host interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network.

PubMed

Saha, Sovan; Sengupta, Kaustav; Chatterjee, Piyali; Basu, Subhadip; Nasipuri, Mita

2017-09-23

Infection and disease progression is the outcome of protein interactions between pathogen and host. Pathogen, the role player of Infection, is becoming a severe threat to life as because of its adaptability toward drugs and evolutionary dynamism in nature. Identifying protein targets by analyzing protein interactions between host and pathogen is the key point. Proteins with higher degree and possessing some topologically significant graph theoretical measures are found to be drug targets. On the other hand, exceptional nodes may be involved in infection mechanism because of some pathway process and biologically unknown factors. In this article, we attempt to investigate characteristics of host-pathogen protein interactions by presenting a comprehensive review of computational approaches applied on different infectious diseases. As an illustration, we have analyzed a case study on infectious disease malaria, with its causative agent Plasmodium falciparum acting as 'Bait' and host, Homo sapiens/human acting as 'Prey'. In this pathogen-host interaction network based on some interconnectivity and centrality properties, proteins are viewed as central, peripheral, hub and non-hub nodes and their significance on infection process. Besides, it is observed that because of sparseness of the pathogen and host interaction network, there may be some topologically unimportant but biologically significant proteins, which can also act as Bait/Prey. So, functional similarity or gene ontology mapping can help us in this case to identify these proteins. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Phenylboronate chromatography selectively separates glycoproteins through the manipulation of electrostatic, charge transfer, and cis-diol interactions.

PubMed

Carvalho, Rimenys J; Woo, James; Aires-Barros, M Raquel; Cramer, Steven M; Azevedo, Ana M

2014-10-01

Phenylboronate chromatography (PBC) has been applied for several years, however details regarding the mechanisms of interactions between the ligand and biomolecules are still scarce. The goal of this work is to investigate the various chemical interactions between proteins and their ligands, using a protein library containing both glycosylated and nonglycosylated proteins. Differences in the adsorption of these proteins over a pH range from 4 to 9 were related to two main properties: charge and presence of glycans. Acidic or neutral proteins were strongly adsorbed below pH 8 although the uncharged trigonal form of phenylboronate (PB) is less susceptible to forming electrostatic and cis-diol interactions with proteins. The glycosylated proteins were only adsorbed above pH 8 when the electrostatic repulsion between the boronate anion and the protein surface was mitigated (at 200 mM NaCl). All basic proteins were highly adsorbed above pH 8 with PB also acting as a cation-exchanger with binding occurring through electrostatic interactions. Batch adsorption performed at acidic conditions in the presence of Lewis base showed that charge-transfer interactions are critical for protein retention. This study demonstrates the multimodal interaction of PBC, which can be a selective tool for separation of different classes of proteins. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel approach using DNA-RNA hybrids in RNA nanotechnology | Center for Cancer Research

Cancer.gov

Developing simple approaches to detect interactions, modifications, and cellular locations of macromolecules is essential for understanding biochemical processes. The use of protein fragment complementation assays, also called split-protein systems, is a highly sensitive approach for studying protein interactions in biological systems. In this approach, functional proteins are

Partial molar volume of proteins studied by the three-dimensional reference interaction site model theory.

PubMed

Imai, Takashi; Kovalenko, Andriy; Hirata, Fumio

2005-04-14

The three-dimensional reference interaction site model (3D-RISM) theory is applied to the analysis of hydration effects on the partial molar volume of proteins. For the native structure of some proteins, the partial molar volume is decomposed into geometric and hydration contributions using the 3D-RISM theory combined with the geometric volume calculation. The hydration contributions are correlated with the surface properties of the protein. The thermal volume, which is the volume of voids around the protein induced by the thermal fluctuation of water molecules, is directly proportional to the accessible surface area of the protein. The interaction volume, which is the contribution of electrostatic interactions between the protein and water molecules, is apparently governed by the charged atomic groups on the protein surface. The polar atomic groups do not make any contribution to the interaction volume. The volume differences between low- and high-pressure structures of lysozyme are also analyzed by the present method.

Protein-surface interactions on stimuli-responsive polymeric biomaterials.

PubMed

Cross, Michael C; Toomey, Ryan G; Gallant, Nathan D

2016-03-04

Responsive surfaces: a review of the dependence of protein adsorption on the reversible volume phase transition in stimuli-responsive polymers. Specifically addressed are a widely studied subset: thermoresponsive polymers. Findings are also generalizable to other materials which undergo a similarly reversible volume phase transition. As of 2015, over 100,000 articles have been published on stimuli-responsive polymers and many more on protein-biomaterial interactions. Significantly, fewer than 100 of these have focused specifically on protein interactions with stimuli-responsive polymers. These report a clear trend of increased protein adsorption in the collapsed state compared to the swollen state. This control over protein interactions makes stimuli-responsive polymers highly useful in biomedical applications such as wound repair scaffolds, on-demand drug delivery, and antifouling surfaces. Outstanding questions are whether the protein adsorption is reversible with the volume phase transition and whether there is a time-dependence. A clear understanding of protein interactions with stimuli-responsive polymers will advance theoretical models, experimental results, and biomedical applications.

Characterization of the motion of membrane proteins using high-speed atomic force microscopy

NASA Astrophysics Data System (ADS)

Casuso, Ignacio; Khao, Jonathan; Chami, Mohamed; Paul-Gilloteaux, Perrine; Husain, Mohamed; Duneau, Jean-Pierre; Stahlberg, Henning; Sturgis, James N.; Scheuring, Simon

2012-08-01

For cells to function properly, membrane proteins must be able to diffuse within biological membranes. The functions of these membrane proteins depend on their position and also on protein-protein and protein-lipid interactions. However, so far, it has not been possible to study simultaneously the structure and dynamics of biological membranes. Here, we show that the motion of unlabelled membrane proteins can be characterized using high-speed atomic force microscopy. We find that the molecules of outer membrane protein F (OmpF) are widely distributed in the membrane as a result of diffusion-limited aggregation, and while the overall protein motion scales roughly with the local density of proteins in the membrane, individual protein molecules can also diffuse freely or become trapped by protein-protein interactions. Using these measurements, and the results of molecular dynamics simulations, we determine an interaction potential map and an interaction pathway for a membrane protein, which should provide new insights into the connection between the structures of individual proteins and the structures and dynamics of supramolecular membranes.

Observation of Water-Protein Interaction Dynamics with Broadband Two-Dimensional Infrared Spectroscopy

NASA Astrophysics Data System (ADS)

De Marco, Luigi; Haky, Andrew; Tokmakoff, Andrei

Two-dimensional infrared (2D IR) spectroscopy has proven itself an indispensable tool for studying molecular dynamics and intermolecular interactions on ultrafast timescales. Using a novel source of broadband mid-IR pulses, we have collected 2D IR spectra of protein films at varying levels of hydration. With 2D IR, we can directly observe coupling between water's motions and the protein's. Protein films provide us with the ability to discriminate hydration waters from bulk water and thus give us access to studying water dynamics along the protein backbone, fluctuations in the protein structure, and the interplay between the molecular dynamics of the two. We present two representative protein films: poly-L-proline (PLP) and hen egg-white lysozyme (HEWL). Having no N-H groups, PLP allows us to look at water dynamics without interference from resonant energy transfer between the protein N-H stretch and the water O-H stretch. We conclude that at low hydration levels water-protein interactions dominate, and the water's dynamics are tied to those of the protein. In HEWL films, we take advantage of the robust secondary structure to partially deuterate the film, allowing us to spectrally distinguish the protein core from the exterior. From this, we show that resonant energy transfer to water provides an effective means of dissipating excess energy within the protein, while maintaining the structure. These methods are general and can easily be extended to studying specific protein-water interactions.

Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasites.

PubMed

Liu, Xuewu; Huang, Yuxiao; Liang, Jiao; Zhang, Shuai; Li, Yinghui; Wang, Jun; Shen, Yan; Xu, Zhikai; Zhao, Ya

2014-11-30

The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Although several interactions between human and parasite proteins have been discovered, the mechanism related to invasion remains poorly understood because numerous human-parasite protein interactions have not yet been identified. High-throughput screening experiments are not feasible for malarial parasites due to difficulty in expressing the parasite proteins. Here, we performed computational prediction of the PPIs involved in malaria parasite invasion to elucidate the mechanism by which invasion occurs. In this study, an expectation maximization algorithm was used to estimate the probabilities of domain-domain interactions (DDIs). Estimates of DDI probabilities were then used to infer PPI probabilities. We found that our prediction performance was better than that based on the information of D. melanogaster alone when information related to the six species was used. Prediction performance was assessed using protein interaction data from S. cerevisiae, indicating that the predicted results were reliable. We then used the estimates of DDI probabilities to infer interactions between 490 parasite and 3,787 human membrane proteins. A small-scale dataset was used to illustrate the usability of our method in predicting interactions between human and parasite proteins. The positive predictive value (PPV) was lower than that observed in S. cerevisiae. We integrated gene expression data to improve prediction accuracy and to reduce false positives. We identified 80 membrane proteins highly expressed in the schizont stage by fast Fourier transform method. Approximately 221 erythrocyte membrane proteins were identified using published mass spectral datasets. A network consisting of 205 interactions was predicted. Results of network analysis suggest that SNARE proteins of parasites and APP of humans may function in the invasion of RBCs by parasites. We predicted a small-scale PPI network that may be involved in parasite invasion of RBCs by integrating DDI information and expression profiles. Experimental studies should be conducted to validate the predicted interactions. The predicted PPIs help elucidate the mechanism of parasite invasion and provide directions for future experimental investigations.

Dynamic nuclear protein interactions investigated using fluorescence lifetime and fluorescence fluctuation spectroscopy

NASA Astrophysics Data System (ADS)

Siegel, Amanda P.; Hays, Nicole M.; Day, Richard N.

2012-03-01

The discovery and engineering of novel fluorescent proteins (FPs) from diverse organisms is yielding fluorophores with exceptional characteristics for live-cell imaging. In particular, the development of FPs for Förster resonance energy transfer (FRET) microscopy and fluorescence fluctuation spectroscopy (FFS) provide important tools for monitoring dynamic protein interactions inside living cells. Fluorescence lifetime imaging microscopy (FLIM) quantitatively maps changes in the spatial distribution of donor FP lifetimes that result from FRET with acceptor FPs. FFS probes dynamic protein associations through its capacity to monitor localized protein diffusion. Here, we use FRET-FLIM combined with FFS in living cells to investigate changes in protein mobility due to protein-protein interactions involving transcription factors and chromatin modifying proteins that function in anterior pituitary gene regulation. The heterochromatin protein 1 alpha (HP1α) plays a key role in the establishment and maintenance of heterochromatin through its interactions with histone methyltransferases. Recent studies, however, also highlight the importance of HP1α as a positive regulator of active transcription in euchromatin. Intriguingly, we observed that the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) interacts with HP1α in regions of pericentromeric heterochromatin in mouse pituitary cells. These observations prompted us to investigate the relationship between HP1α dynamic interactions in pituitary specific gene regulation.

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

Network-based analysis of genotype-phenotype correlations between different inheritance modes.

PubMed

Hao, Dapeng; Li, Chuanxing; Zhang, Shaojun; Lu, Jianping; Jiang, Yongshuai; Wang, Shiyuan; Zhou, Meng

2014-11-15

Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease. We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations. haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Calcium/calmodulin-dependent serine protein kinase (CASK), a protein implicated in mental retardation and autism-spectrum disorders, interacts with T-Brain-1 (TBR1) to control extinction of associative memory in male mice.

PubMed

Huang, Tzyy-Nan; Hsueh, Yi-Ping

2017-01-01

Human genetic studies have indicated that mutations in calcium/calmodulin-dependent serine protein kinase ( CASK ) result in X-linked mental retardation and autism-spectrum disorders. We aimed to establish a mouse model to study how Cask regulates mental ability. Because Cask encodes a multidomain scaffold protein, a possible strategy to dissect how CASK regulates mental ability and cognition is to disrupt specific protein-protein interactions of CASK in vivo and then investigate the impact of individual specific protein interactions. Previous in vitro analyses indicated that a rat CASK T724A mutation reduces the interaction between CASK and T-brain-1 (TBR1) in transfected COS cells. Because TBR1 is critical for glutamate receptor, ionotropic, N -methyl-D-aspartate receptor subunit 2B ( Grin2b ) expression and is a causative gene for autism and intellectual disability, we then generated CASK T740A (corresponding to rat CASK T724A) mutant mice using a gene-targeting approach. Immunoblotting, coimmunoprecipitation, histological methods and behavioural assays (including home cage, open field, auditory and contextual fear conditioning and conditioned taste aversion) were applied to investigate expression of CASK and its related proteins, the protein-protein interactions of CASK, and anatomic and behavioural features of CASK T740A mice. The CASK T740A mutation attenuated the interaction between CASK and TBR1 in the brain. However, CASK T740A mice were generally healthy, without obvious defects in brain morphology. The most dramatic defect among the mutant mice was in extinction of associative memory, though acquisition was normal. The functions of other CASK protein interactions cannot be addressed using CASK T740A mice. Disruption of the CASK and TBR1 interaction impairs extinction, suggesting the involvement of CASK in cognitive flexibility.

An accurate binding interaction model in de novo computational protein design of interactions: if you build it, they will bind.

PubMed

London, Nir; Ambroggio, Xavier

2014-02-01

Computational protein design efforts aim to create novel proteins and functions in an automated manner and, in the process, these efforts shed light on the factors shaping natural proteins. The focus of these efforts has progressed from the interior of proteins to their surface and the design of functions, such as binding or catalysis. Here we examine progress in the development of robust methods for the computational design of non-natural interactions between proteins and molecular targets such as other proteins or small molecules. This problem is referred to as the de novo computational design of interactions. Recent successful efforts in de novo enzyme design and the de novo design of protein-protein interactions open a path towards solving this problem. We examine the common themes in these efforts, and review recent studies aimed at understanding the nature of successes and failures in the de novo computational design of interactions. While several approaches culminated in success, the use of a well-defined structural model for a specific binding interaction in particular has emerged as a key strategy for a successful design, and is therefore reviewed with special consideration. Copyright © 2013 Elsevier Inc. All rights reserved.

Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces.

PubMed

Engin, H Billur; Kreisberg, Jason F; Carter, Hannah

2016-01-01

Recently it has been shown that cancer mutations selectively target protein-protein interactions. We hypothesized that mutations affecting distinct protein interactions involving established cancer genes could contribute to tumor heterogeneity, and that novel mechanistic insights might be gained into tumorigenesis by investigating protein interactions under positive selection in cancer. To identify protein interactions under positive selection in cancer, we mapped over 1.2 million nonsynonymous somatic cancer mutations onto 4,896 experimentally determined protein structures and analyzed their spatial distribution. In total, 20% of mutations on the surface of known cancer genes perturbed protein-protein interactions (PPIs), and this enrichment for PPI interfaces was observed for both tumor suppressors (Odds Ratio 1.28, P-value < 10(-4)) and oncogenes (Odds Ratio 1.17, P-value < 10(-3)). To study this further, we constructed a bipartite network representing structurally resolved PPIs from all available human complexes in the Protein Data Bank (2,864 proteins, 3,072 PPIs). Analysis of frequently mutated cancer genes within this network revealed that tumor-suppressors, but not oncogenes, are significantly enriched with functional mutations in homo-oligomerization regions (Odds Ratio 3.68, P-Value < 10(-8)). We present two important examples, TP53 and beta-2-microglobulin, for which the patterns of somatic mutations at interfaces provide insights into specifically perturbed biological circuits. In patients with TP53 mutations, patient survival correlated with the specific interactions that were perturbed. Moreover, we investigated mutations at the interface of protein-nucleotide interactions and observed an unexpected number of missense mutations but not silent mutations occurring within DNA and RNA binding sites. Finally, we provide a resource of 3,072 PPI interfaces ranked according to their mutation rates. Analysis of this list highlights 282 novel candidate cancer genes that encode proteins participating in interactions that are perturbed recurrently across tumors. In summary, mutation of specific protein interactions is an important contributor to tumor heterogeneity and may have important implications for clinical outcomes.

The EICP22 Protein of Equine Herpesvirus 1 Physically Interacts with the Immediate-Early Protein and with Itself To Form Dimers and Higher-Order Complexes

PubMed Central

Derbigny, Wilbert A.; Kim, Seong K.; Caughman, Gretchen B.; O'Callaghan, Dennis J.

2000-01-01

The EICP22 protein (EICP22P) of Equine herpesvirus 1 (EHV-1) is an early protein that functions synergistically with other EHV-1 regulatory proteins to transactivate the expression of early and late viral genes. We have previously identified EICP22P as an accessory regulatory protein that has the ability to enhance the transactivating properties and the sequence-specific DNA-binding activity of the EHV-1 immediate-early protein (IEP). In the present study, we identify EICP22P as a self-associating protein able to form dimers and higher-order complexes during infection. Studies with the yeast two-hybrid system also indicate that physical interactions occur between EICP22P and IEP and that EICP22P self-aggregates. Results from in vitro and in vivo coimmunoprecipitation experiments and glutathione S-transferase (GST) pull-down studies confirmed a direct protein-protein interaction between EICP22P and IEP as well as self-interactions of EICP22P. Analyses of infected cells by laser-scanning confocal microscopy with antibodies specific for IEP and EICP22P revealed that these viral regulatory proteins colocalize in the nucleus at early times postinfection and form aggregates of dense nuclear structures within the nucleoplasm. Mutational analyses with a battery of EICP22P deletion mutants in both yeast two-hybrid and GST pull-down experiments implicated amino acids between positions 124 and 143 as the critical domain mediating the EICP22P self-interactions. Additional in vitro protein-binding assays with a library of GST-EICP22P deletion mutants identified amino acids mapping within region 2 (amino acids [aa] 65 to 196) and region 3 (aa 197 to 268) of EICP22P as residues that mediate its interaction with IEP. PMID:10627553

The CCDC55 couples cannabinoid receptor CNR1 to a putative DISC1 schizophrenia pathway.

PubMed

Xie, J; Gizatullin, R; Vukojevic, V; Leopardi, R

2015-12-03

Our previous study suggested that the coiled coil domain-containing 55 gene (CCDC55), also named as NSRP1 (nuclear speckle splicing regulatory protein 1 (NSRP1)), was encompassed in a haplotype block spanning over the serotonin transporter (5-HTT) gene in patients with schizophrenia (SCZ). However, the neurobiological function of CCDC55 gene remains unknown. This study aims to uncover the potential role of CCDC55 in SCZ-associated molecular pathways. Using molecular cloning, sequencing and immune blotting to identify basic properties, yeast two-hybrid screening and glutathione S-transferase (GST) pull-down assay to test protein-protein interaction, and confocal laser scanning microscopy (CSLM) to show intracellular interaction of proteins. (i) CCDC55 is expressed as a nuclear protein in human neuronal cells; (ii) Protein-protein interaction analyses showed CCDC55 physically interacted with Ran binding protein 9 (RanBP9) and disrupted in schizophrenia 1 (DISC1); (iii) CCDC55 and RanBP9 co-localized in the nucleus of human neuronal cells; (iv) CCDC55 also interacted with the cannabinoid receptor 1 (CNR1), and with the brain cannabinoid receptor-interacting protein 1a (CNRIP1a); (v) CNR1 activation in differentiated human neuronal cells resulted in an altered RanBP9 localization. CCDC55 may be involved in a functional bridging between the CNR1 activation and the DISC1/RanBP9-associated pathways. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Adaptability of Protein Structures to Enable Functional Interactions and Evolutionary Implications

PubMed Central

Haliloglu, Turkan; Bahar, Ivet

2015-01-01

Several studies in recent years have drawn attention to the ability of proteins to adapt to intermolecular interactions by conformational changes along structure-encoded collective modes of motions. These so-called soft modes, primarily driven by entropic effects, facilitate, if not enable, functional interactions. They represent excursions on the conformational space along principal low-ascent directions/paths away from the original free energy minimum, and they are accessible to the protein even prior to protein-protein/ligand interactions. An emerging concept from these studies is the evolution of structures or modular domains to favor such modes of motion that will be recruited or integrated for enabling functional interactions. Structural dynamics, including the allosteric switches in conformation that are often stabilized upon formation of complexes and multimeric assemblies, emerge as key properties that are evolutionarily maintained to accomplish biological activities, consistent with the paradigm sequence → structure → dynamics → function where ‘dynamics’ bridges structure and function. PMID:26254902

A Survey of Aspartate Phenylalanine and Glutamate Phenylalanine Interactions in the Protein Data Bank: Searching for Anion Pairs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Philip, Vivek M; Harris, Jason B; Adams, Rachel M

Protein structures are stabilized using noncovalent interactions. In addition to the traditional noncovalent interactions, newer types of interactions are thought to be present in proteins. One such interaction, an anion pair, in which the positively charged edge of an aromatic ring interacts with an anion, forming a favorable anion quadrupole interaction, has been previously proposed [Jackson, M. R., et al. (2007) J. Phys. Chem. B111, 8242 8249]. To study the role of anion interactions in stabilizing protein structure, we analyzed pairwise interactions between phenylalanine (Phe) and the anionic amino acids, aspartate (Asp) and glutamate (Glu). Particular emphasis was focused onmore » identification of Phe Asp or Glu pairs separated by less than 7 in the high-resolution, nonredundant Protein Data Bank. Simplifying Phe to benzene and Asp or Glu to formate molecules facilitated in silico analysis of the pairs. Kitaura Morokuma energy calculations were performed on roughly 19000 benzene formate pairs and the resulting energies analyzed as a function of distance and angle. Edgewise interactions typically produced strongly stabilizing interaction energies (2 to 7.3 kcal/mol), while interactions involving the ring face resulted in weakly stabilizing to repulsive interaction energies. The strongest, most stabilizing interactions were identified as preferentially occurring in buried residues. Anion pairs are found throughout protein structures, in helices as well as strands. Numerous pairs also had nearby cation interactions as well as potential stacking. While more than 1000 structures did not contain an anion pair, the 3134 remaining structures contained approximately 2.6 anion pairs per protein, suggesting it is a reasonably common motif that could contribute to the overall structural stability of a protein.« less

A Survey of Aspartate-Phenylalanine and Glutamate-Phenylalanine Interactions in the Protein Data Bank: Searching for Anion-pi Pairs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Philip, Vivek M; Harris, Jason B; Adams, Rachel M

Protein structures are stabilized using noncovalent interactions. In addition to the traditional noncovalent interactions, newer types of interactions are thought to be present in proteins. One such interaction, an anion-{pi} pair, in which the positively charged edge of an aromatic ring interacts with an anion, forming a favorable anion-quadrupole interaction, has been previously proposed [Jackson, M. R., et al. (2007) J. Phys. Chem. B111, 8242-8249]. To study the role of anion-{pi} interactions in stabilizing protein structure, we analyzed pairwise interactions between phenylalanine (Phe) and the anionic amino acids, aspartate (Asp) and glutamate (Glu). Particular emphasis was focused on identification ofmore » Phe-Asp or -Glu pairs separated by less than 7 {angstrom} in the high-resolution, nonredundant Protein Data Bank. Simplifying Phe to benzene and Asp or Glu to formate molecules facilitated in silico analysis of the pairs. Kitaura-Morokuma energy calculations were performed on roughly 19000 benzene-formate pairs and the resulting energies analyzed as a function of distance and angle. Edgewise interactions typically produced strongly stabilizing interaction energies (-2 to -7.3 kcal/mol), while interactions involving the ring face resulted in weakly stabilizing to repulsive interaction energies. The strongest, most stabilizing interactions were identified as preferentially occurring in buried residues. Anion-{pi} pairs are found throughout protein structures, in helices as well as {beta} strands. Numerous pairs also had nearby cation-{pi} interactions as well as potential {pi}-{pi} stacking. While more than 1000 structures did not contain an anion-{pi} pair, the 3134 remaining structures contained approximately 2.6 anion-{pi} pairs per protein, suggesting it is a reasonably common motif that could contribute to the overall structural stability of a protein.« less

A survey of aspartate-phenylalanine and glutamate-phenylalanine interactions in the protein data bank: searching for anion-π pairs.

PubMed

Philip, Vivek; Harris, Jason; Adams, Rachel; Nguyen, Don; Spiers, Jeremy; Baudry, Jerome; Howell, Elizabeth E; Hinde, Robert J

2011-04-12

Protein structures are stabilized using noncovalent interactions. In addition to the traditional noncovalent interactions, newer types of interactions are thought to be present in proteins. One such interaction, an anion-π pair, in which the positively charged edge of an aromatic ring interacts with an anion, forming a favorable anion-quadrupole interaction, has been previously proposed [Jackson, M. R., et al. (2007) J. Phys. Chem. B111, 8242-8249]. To study the role of anion-π interactions in stabilizing protein structure, we analyzed pairwise interactions between phenylalanine (Phe) and the anionic amino acids, aspartate (Asp) and glutamate (Glu). Particular emphasis was focused on identification of Phe-Asp or -Glu pairs separated by less than 7 Å in the high-resolution, nonredundant Protein Data Bank. Simplifying Phe to benzene and Asp or Glu to formate molecules facilitated in silico analysis of the pairs. Kitaura-Morokuma energy calculations were performed on roughly 19000 benzene-formate pairs and the resulting energies analyzed as a function of distance and angle. Edgewise interactions typically produced strongly stabilizing interaction energies (-2 to -7.3 kcal/mol), while interactions involving the ring face resulted in weakly stabilizing to repulsive interaction energies. The strongest, most stabilizing interactions were identified as preferentially occurring in buried residues. Anion-π pairs are found throughout protein structures, in helices as well as β strands. Numerous pairs also had nearby cation-π interactions as well as potential π-π stacking. While more than 1000 structures did not contain an anion-π pair, the 3134 remaining structures contained approximately 2.6 anion-π pairs per protein, suggesting it is a reasonably common motif that could contribute to the overall structural stability of a protein.

SNAPPI-DB: a database and API of Structures, iNterfaces and Alignments for Protein–Protein Interactions

PubMed Central

Jefferson, Emily R.; Walsh, Thomas P.; Roberts, Timothy J.; Barton, Geoffrey J.

2007-01-01

SNAPPI-DB, a high performance database of Structures, iNterfaces and Alignments of Protein–Protein Interactions, and its associated Java Application Programming Interface (API) is described. SNAPPI-DB contains structural data, down to the level of atom co-ordinates, for each structure in the Protein Data Bank (PDB) together with associated data including SCOP, CATH, Pfam, SWISSPROT, InterPro, GO terms, Protein Quaternary Structures (PQS) and secondary structure information. Domain–domain interactions are stored for multiple domain definitions and are classified by their Superfamily/Family pair and interaction interface. Each set of classified domain–domain interactions has an associated multiple structure alignment for each partner. The API facilitates data access via PDB entries, domains and domain–domain interactions. Rapid development, fast database access and the ability to perform advanced queries without the requirement for complex SQL statements are provided via an object oriented database and the Java Data Objects (JDO) API. SNAPPI-DB contains many features which are not available in other databases of structural protein–protein interactions. It has been applied in three studies on the properties of protein–protein interactions and is currently being employed to train a protein–protein interaction predictor and a functional residue predictor. The database, API and manual are available for download at: . PMID:17202171

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

PubMed Central

2013-01-01

Background The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. Results In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0.81 for VIRs, VAIRs, VBIRs, PLPIRs respectively, using PSSM-based evolutionary information. All the modules developed in this study have been trained and tested on non-redundant datasets and evaluated using five-fold cross-validation technique. The performances were also evaluated on the balanced and different independent datasets. Conclusions This study demonstrates that it is possible to predict VIRs, VAIRs, VBIRs and PLPIRs from evolutionary information of protein sequence. In order to provide service to the scientific community, we have developed web-server and standalone software VitaPred (http://crdd.osdd.net/raghava/vitapred/). PMID:23387468

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information.

PubMed

Panwar, Bharat; Gupta, Sudheer; Raghava, Gajendra P S

2013-02-07

The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0.81 for VIRs, VAIRs, VBIRs, PLPIRs respectively, using PSSM-based evolutionary information. All the modules developed in this study have been trained and tested on non-redundant datasets and evaluated using five-fold cross-validation technique. The performances were also evaluated on the balanced and different independent datasets. This study demonstrates that it is possible to predict VIRs, VAIRs, VBIRs and PLPIRs from evolutionary information of protein sequence. In order to provide service to the scientific community, we have developed web-server and standalone software VitaPred (http://crdd.osdd.net/raghava/vitapred/).

Cross dimerization of amyloid-β and αsynuclein proteins in aqueous environment: a molecular dynamics simulations study.

PubMed

Jose, Jaya C; Chatterjee, Prathit; Sengupta, Neelanjana

2014-01-01

Self-assembly of the intrinsically unstructured proteins, amyloid beta (Aβ) and alpha synclein (αSyn), are associated with Alzheimer's Disease, and Parkinson's and Lewy Body Diseases, respectively. Importantly, pathological overlaps between these neurodegenerative diseases, and the possibilities of interactions between Aβ and αSyn in biological milieu emerge from several recent clinical reports and in vitro studies. Nevertheless, there are very few molecular level studies that have probed the nature of spontaneous interactions between these two sequentially dissimilar proteins and key characteristics of the resulting cross complexes. In this study, we have used atomistic molecular dynamics simulations to probe the possibility of cross dimerization between αSyn1-95 and Aβ1-42, and thereby gain insights into their plausible early assembly pathways in aqueous environment. Our analyses indicate a strong probability of association between the two sequences, with inter-protein attractive electrostatic interactions playing dominant roles. Principal component analysis revealed significant heterogeneity in the strength and nature of the associations in the key interaction modes. In most, the interactions of repeating Lys residues, mainly in the imperfect repeats 'KTKEGV' present in αSyn1-95 were found to be essential for cross interactions and formation of inter-protein salt bridges. Additionally, a hydrophobicity driven interaction mode devoid of salt bridges, where the non-amyloid component (NAC) region of αSyn1-95 came in contact with the hydrophobic core of Aβ1-42 was observed. The existence of such hetero complexes, and therefore hetero assembly pathways may lead to polymorphic aggregates with variations in pathological attributes. Our results provide a perspective on development of therapeutic strategies for preventing pathogenic interactions between these proteins.

Amphipathic helical peptides hamper protein-protein interactions of the intrinsically disordered chromatin nuclear protein 1 (NUPR1).

PubMed

Santofimia-Castaño, Patricia; Rizzuti, Bruno; Abián, Olga; Velázquez-Campoy, Adrián; Iovanna, Juan L; Neira, José L

2018-06-01

NUPR1 is a multifunctional intrinsically disordered protein (IDP) involved, among other functions, in chromatin remodelling, and development of pancreatic ductal adenocarcinoma (PDAC). It interacts with several biomolecules through hydrophobic patches around residues Ala33 and Thr68. The drug trifluoperazine (TFP), which hampers PDAC development in xenografted mice, also binds to those regions. Because of the large size of the hot-spot interface of NUPR1, small molecules could not be adequate to modulate its functions. We explored how amphipathic helical-designed peptides were capable of interacting with wild-type NUPR1 and the Thr68Gln mutant, inhibiting the interaction with NUPR1 protein partners. We used in vitro biophysical techniques (fluorescence, circular dichroism (CD), nuclear magnetic resonance (NMR) and isothermal titration calorimetry (ITC)), in silico studies (docking and molecular dynamics (MD)), and in cellulo protein ligation assays (PLAs) to study the interaction. Peptide dissociation constants towards wild-type NUPR1 were ~ 3 μM, whereas no interaction was observed with the Thr68Gln mutant. Peptides interacted with wild-type NUPR1 residues around Ala33 and residues at the C terminus, as shown by NMR. The computational results clarified the main determinants of the interactions, providing a mechanism for the ligand-capture that explains why peptide binding was not observed for Thr68Gln mutant. Finally, the in cellulo assays indicated that two out of four peptides inhibited the interaction of NUPR1 with the C-terminal region of the Polycomb RING protein 1 (C-RING1B). Designed peptides can be used as lead compounds to inhibit NUPR1 interactions. Peptides may be exploited as drugs to target IDPs. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of surface compositional and structural heterogeneity on nanoparticle-protein interactions: different protein configurations.

PubMed

Huang, Rixiang; Carney, Randy P; Ikuma, Kaoru; Stellacci, Francesco; Lau, Boris L T

2014-06-24

As nanoparticles (NPs) enter into biological systems, they are immediately exposed to a variety and concentration of proteins. The physicochemical interactions between proteins and NPs are influenced by the surface properties of the NPs. To identify the effects of NP surface heterogeneity, the interactions between bovine serum albumin (BSA) and gold NPs (AuNPs) with similar chemical composition but different surface structures were investigated. Different interaction modes and BSA conformations were studied by dynamic light scattering, circular dichroism spectroscopy, fluorescence quenching and isothermal titration calorimetry (ITC). Depending on the surface structure of AuNPs, BSA seems to adopt either a "side-on" or an "end-on" conformation on AuNPs. ITC demonstrated that the adsorption of BSA onto AuNPs with randomly distributed polar and nonpolar groups was primarily driven by electrostatic interaction, and all BSA were adsorbed in the same process. The adsorption of BSA onto AuNPs covered with alternating domains of polar and nonpolar groups was a combination of different interactions. Overall, the results of this study point to the potential for utilizing nanoscale manipulation of NP surfaces to control the resulting NP-protein interactions.

GREEN: A program package for docking studies in rational drug design

NASA Astrophysics Data System (ADS)

Tomioka, Nobuo; Itai, Akiko

1994-08-01

A program package, GREEN, has been developed that enables docking studies between ligand molecules and a protein molecule. Based on the structure of the protein molecule, the physical and chemical environment of the ligand-binding site is expressed as three-dimensional grid-point data. The grid-point data are used for the real-time evaluation of the protein-ligand interaction energy, as well as for the graphical representation of the binding-site environment. The interactive docking operation is facilitated by various built-in functions, such as energy minimization, energy contribution analysis and logging of the manipulation trajectory. Interactive modeling functions are incorporated for designing new ligand molecules while considering the binding-site environment and the protein-ligand interaction. As an example of the application of GREEN, a docking study is presented on the complex between trypsin and a synthetic trypsin inhibitor. The program package will be useful for rational drug design, based on the 3D structure of the target protein.

Using genome-wide measurements for computational prediction of SH2–peptide interactions

PubMed Central

Wunderlich, Zeba; Mirny, Leonid A.

2009-01-01

Peptide-recognition modules (PRMs) are used throughout biology to mediate protein–protein interactions, and many PRMs are members of large protein domain families. Recent genome-wide measurements describe networks of peptide–PRM interactions. In these networks, very similar PRMs recognize distinct sets of peptides, raising the question of how peptide-recognition specificity is achieved using similar protein domains. The analysis of individual protein complex structures often gives answers that are not easily applicable to other members of the same PRM family. Bioinformatics-based approaches, one the other hand, may be difficult to interpret physically. Here we integrate structural information with a large, quantitative data set of SH2 domain–peptide interactions to study the physical origin of domain–peptide specificity. We develop an energy model, inspired by protein folding, based on interactions between the amino-acid positions in the domain and peptide. We use this model to successfully predict which SH2 domains and peptides interact and uncover the positions in each that are important for specificity. The energy model is general enough that it can be applied to other members of the SH2 family or to new peptides, and the cross-validation results suggest that these energy calculations will be useful for predicting binding interactions. It can also be adapted to study other PRM families, predict optimal peptides for a given SH2 domain, or study other biological interactions, e.g. protein–DNA interactions. PMID:19502496

Interaction Network of Proteins Associated with Human Cytomegalovirus IE2-p86 Protein during Infection: A Proteomic Analysis

PubMed Central

Du, Guixin; Stinski, Mark F.

2013-01-01

Human cytomegalovirus protein IE2-p86 exerts its functions through interaction with other viral and cellular proteins. To further delineate its protein interaction network, we generated a recombinant virus expressing SG-tagged IE2-p86 and used tandem affinity purification coupled with mass spectrometry. A total of 9 viral proteins and 75 cellular proteins were found to associate with IE2-p86 protein during the first 48 hours of infection. The protein profile at 8, 24, and 48 h post infection revealed that UL84 tightly associated with IE2-p86, and more viral and cellular proteins came into association with IE2-p86 with the progression of virus infection. A computational analysis of the protein-protein interaction network indicated that all of the 9 viral proteins and most of the cellular proteins identified in the study are interconnected to varying degrees. Of the cellular proteins that were confirmed to associate with IE2-p86 by immunoprecipitation, C1QBP was further shown to be upregulated by HCMV infection and colocalized with IE2-p86, UL84 and UL44 in the virus replication compartment of the nucleus. The IE2-p86 interactome network demonstrated the temporal development of stable and abundant protein complexes that associate with IE2-p86 and provided a framework to benefit future studies of various protein complexes during HCMV infection. PMID:24358118

Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein–Protein Interaction Inhibitors of CaV Function

PubMed Central

2017-01-01

For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein–protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein–protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein–protein interaction, the interaction between the voltage-gated calcium channel (CaV) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (CaVβ). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:CaVβ interactions and reduce the entropic penalty associated with AID binding to CaVβ. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the CaVα1:CaVβ interaction that modulate CaV function in an CaVβ isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein–protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based CaV modulator design. PMID:28278376

INTERSPIA: a web application for exploring the dynamics of protein-protein interactions among multiple species.

PubMed

Kwon, Daehong; Lee, Daehwan; Kim, Juyeon; Lee, Jongin; Sim, Mikang; Kim, Jaebum

2018-05-09

Proteins perform biological functions through cascading interactions with each other by forming protein complexes. As a result, interactions among proteins, called protein-protein interactions (PPIs) are not completely free from selection constraint during evolution. Therefore, the identification and analysis of PPI changes during evolution can give us new insight into the evolution of functions. Although many algorithms, databases and websites have been developed to help the study of PPIs, most of them are limited to visualize the structure and features of PPIs in a chosen single species with limited functions in the visualization perspective. This leads to difficulties in the identification of different patterns of PPIs in different species and their functional consequences. To resolve these issues, we developed a web application, called INTER-Species Protein Interaction Analysis (INTERSPIA). Given a set of proteins of user's interest, INTERSPIA first discovers additional proteins that are functionally associated with the input proteins and searches for different patterns of PPIs in multiple species through a server-side pipeline, and second visualizes the dynamics of PPIs in multiple species using an easy-to-use web interface. INTERSPIA is freely available at http://bioinfo.konkuk.ac.kr/INTERSPIA/.

The Use of Two-Photon FRET-FLIM to Study Protein Interactions During Nuclear Envelope Fusion In Vivo and In Vitro.

PubMed

Byrne, Richard D; Larijani, Banafshé; Poccia, Dominic L

2016-01-01

FRET-FLIM techniques have wide application in the study of protein and protein-lipid interactions in cells. We have pioneered an imaging platform for accurate detection of functional states of proteins and their interactions in fixed cells. This platform, two-site-amplified Förster resonance energy transfer (a-FRET), allows greater signal generation while retaining minimal noise thus enabling application of fluorescence lifetime imaging microscopy (FLIM) to be routinely deployed in different types of cells and tissue. We have used the method described here, time-resolved FRET monitored by two-photon FLIM, to demonstrate the direct interaction of Phospholipase Cγ (PLCγ) by Src Family Kinase 1 (SFK1) during nuclear envelope formation and during male and female pronuclear membrane fusion in fertilized sea urchin eggs. We describe here a generic method that can be applied to monitor any proteins of interest.

Lipid packing determines protein-membrane interactions: challenges for apolipoprotein A–I and High Density Lipoproteins

PubMed Central

Sánchez, Susana A.; Tricerri, M. Alejandra; Ossato, Giulia; Gratton, Enrico

2010-01-01

Summary Protein and protein-lipid interactions, with and within specific areas in the cell membrane, are critical in order to modulate the cell signaling events required to maintain cell functions and viability. Biological bilayers are complex, dynamic platforms, and thus in vivo observations usually need to be preceded by studies on model systems that simplify and discriminate the different factors involved in lipid-protein interactions. Fluorescence microscopy studies using giant unilamellar vesicles (GUVs) as membrane model systems provide a unique methodology to quantify protein binding, interaction and lipid solubilization in artificial bilayers. The large size of lipid domains obtainable on GUVs, together with fluorescence microscopy techniques, provides the possibility to localize and quantify molecular interactions. FCS (Fluorescence Correlation Spectroscopy) can be performed using the GUV model to extract information on mobility and concentration. Two-photon Laurdan GP (Generalized Polarization) reports on local changes in membrane water content (related to membrane fluidity) due to protein binding or lipid removal from a given lipid domain. In this review, we summarize the experimental microscopy methods used to study the interaction of human apolipoprotein A–I (apoA-I) in lipid-free and lipid-bound conformations with bilayers and natural membranes. Results described here help us to understand cholesterol homeostasis, and offer a methodological design suited to different biological systems. PMID:20347719

Conservation of hot regions in protein-protein interaction in evolution.

PubMed

Hu, Jing; Li, Jiarui; Chen, Nansheng; Zhang, Xiaolong

2016-11-01

The hot regions of protein-protein interactions refer to the active area which formed by those most important residues to protein combination process. With the research development on protein interactions, lots of predicted hot regions can be discovered efficiently by intelligent computing methods, while performing biology experiments to verify each every prediction is hardly to be done due to the time-cost and the complexity of the experiment. This study based on the research of hot spot residue conservations, the proposed method is used to verify authenticity of predicted hot regions that using machine learning algorithm combined with protein's biological features and sequence conservation, though multiple sequence alignment, module substitute matrix and sequence similarity to create conservation scoring algorithm, and then using threshold module to verify the conservation tendency of hot regions in evolution. This research work gives an effective method to verify predicted hot regions in protein-protein interactions, which also provides a useful way to deeply investigate the functional activities of protein hot regions. Copyright © 2016. Published by Elsevier Inc.

The amyloid interactome: Exploring protein aggregation

PubMed Central

Mastrokalou, Chara V.; Hamodrakas, Stavros J.

2017-01-01

Protein-protein interactions are the quintessence of physiological activities, but also participate in pathological conditions. Amyloid formation, an abnormal protein-protein interaction process, is a widespread phenomenon in divergent proteins and peptides, resulting in a variety of aggregation disorders. The complexity of the mechanisms underlying amyloid formation/amyloidogenicity is a matter of great scientific interest, since their revelation will provide important insight on principles governing protein misfolding, self-assembly and aggregation. The implication of more than one protein in the progression of different aggregation disorders, together with the cited synergistic occurrence between amyloidogenic proteins, highlights the necessity for a more universal approach, during the study of these proteins. In an attempt to address this pivotal need we constructed and analyzed the human amyloid interactome, a protein-protein interaction network of amyloidogenic proteins and their experimentally verified interactors. This network assembled known interconnections between well-characterized amyloidogenic proteins and proteins related to amyloid fibril formation. The consecutive extended computational analysis revealed significant topological characteristics and unraveled the functional roles of all constituent elements. This study introduces a detailed protein map of amyloidogenicity that will aid immensely towards separate intervention strategies, specifically targeting sub-networks of significant nodes, in an attempt to design possible novel therapeutics for aggregation disorders. PMID:28249044

The simulation study of protein-protein interfaces based on the 4-helix bundle structure

NASA Astrophysics Data System (ADS)

Fukuda, Masaki; Komatsu, Yu; Morikawa, Ryota; Miyakawa, Takeshi; Takasu, Masako; Akanuma, Satoshi; Yamagishi, Akihiko

2013-02-01

Docking of two protein molecules is induced by intermolecular interactions. Our purposes in this study are: designing binding interfaces on the two proteins, which specifically interact to each other; and inducing intermolecular interactions between the two proteins by mixing them. A 4-helix bundle structure was chosen as a scaffold on which binding interfaces were created. Based on this scaffold, we designed binding interfaces involving charged and nonpolar amino acid residues. We performed molecular dynamics (MD) simulation to identify suitable amino acid residues for the interfaces. We chose YciF protein as the scaffold for the protein-protein docking simulation. We observed the structure of two YciF protein molecules (I and II), and we calculated the distance between centroids (center of gravity) of the interfaces' surface planes of the molecules I and II. We found that the docking of the two protein molecules can be controlled by the number of hydrophobic and charged amino acid residues involved in the interfaces. Existence of six hydrophobic and five charged amino acid residues within an interface were most suitable for the protein-protein docking.

Characterization of Bufo arenarum oocyte plasma membrane proteins that interact with sperm.

PubMed

Coux, Gabriela; Cabada, Marcelo O

2006-04-28

Sperm-oocyte plasma membrane interaction is an essential step in fertilization. In amphibians, the molecules involved have not been identified. Our aim was to detect and characterize oocyte molecules with binding affinity for sperm. We isolated plasma membranes free from vitelline envelope and yolk proteins from surface-biotinylated Bufo arenarum oocytes. Using binding assays we detected a biotinylated 100 kDa plasma membrane protein that consistently bound to sperm. Chromatographic studies confirmed the 100 kDa protein and detected two additional oocyte molecules of 30 and 70 kDa with affinity for sperm. Competition studies with an integrin-interacting peptide and cross-reaction with an anti-HSP70 antibody suggested that the 100 and 70 kDa proteins are members of the integrin family and HSP70, respectively. MS/MS analysis suggested extra candidates for a role in this step of fertilization. In conclusion, we provide evidence for the involvement of several proteins, including integrins and HSP70, in B. arenarum sperm-oocyte plasma membrane interactions.

Observation of CH⋅⋅⋅π Interactions between Methyl and Carbonyl Groups in Proteins.

PubMed

Perras, Frédéric A; Marion, Dominique; Boisbouvier, Jérôme; Bryce, David L; Plevin, Michael J

2017-06-19

Protein structure and function is dependent on myriad noncovalent interactions. Direct detection and characterization of these weak interactions in large biomolecules, such as proteins, is experimentally challenging. Herein, we report the first observation and measurement of long-range "through-space" scalar couplings between methyl and backbone carbonyl groups in proteins. These J couplings are indicative of the presence of noncovalent C-H⋅⋅⋅π hydrogen-bond-like interactions involving the amide π network. Experimentally detected scalar couplings were corroborated by a natural bond orbital analysis, which revealed the orbital nature of the interaction and the origins of the through-space J couplings. The experimental observation of this type of CH⋅⋅⋅π interaction adds a new dimension to the study of protein structure, function, and dynamics by NMR spectroscopy. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular interaction networks in the analyses of sequence variation and proteomics data.

PubMed

Stelzl, Ulrich

2013-12-01

Protein-protein interaction networks are typically generated in standard cell lines or model organisms as it is prohibitively difficult to record large interaction datasets from specific tissues or disease models at a reasonable pace. Although the interaction data are of high confidence, they thus do not reflect in vivo relationships as such. A wealth of physiologically relevant protein information, obtained under different conditions and from different systems, is available including information on genetic variation, protein levels, and PTMs. However, these data are difficult to assess comprehensively because the relationships between the entities remain elusive from the measurements. Here, we exemplarily highlight recent studies that gained deeper insight from genetic variation, protein, and PTM measurements using interaction information pointing toward the importance and potential of interaction networks for the interpretation of sequencing and proteomics data. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using neighborhood cohesiveness to infer interactions between protein domains.

PubMed

Segura, Joan; Sorzano, C O S; Cuenca-Alba, Jesus; Aloy, Patrick; Carazo, J M

2015-08-01

In recent years, large-scale studies have been undertaken to describe, at least partially, protein-protein interaction maps, or interactomes, for a number of relevant organisms, including human. However, current interactomes provide a somehow limited picture of the molecular details involving protein interactions, mostly because essential experimental information, especially structural data, is lacking. Indeed, the gap between structural and interactomics information is enlarging and thus, for most interactions, key experimental information is missing. We elaborate on the observation that many interactions between proteins involve a pair of their constituent domains and, thus, the knowledge of how protein domains interact adds very significant information to any interactomic analysis. In this work, we describe a novel use of the neighborhood cohesiveness property to infer interactions between protein domains given a protein interaction network. We have shown that some clustering coefficients can be extended to measure a degree of cohesiveness between two sets of nodes within a network. Specifically, we used the meet/min coefficient to measure the proportion of interacting nodes between two sets of nodes and the fraction of common neighbors. This approach extends previous works where homolog coefficients were first defined around network nodes and later around edges. The proposed approach substantially increases both the number of predicted domain-domain interactions as well as its accuracy as compared with current methods. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The proteins interacting with C-terminal of μ receptor are identified by bacterial two-hybrid system from brain cDNA library in morphine-dependent rats.

PubMed

Zhou, Peilan; Jiang, Jiebing; Dong, Zhaoqi; Yan, Hui; You, Zhendong; Su, Ruibin; Gong, Zehui

2015-12-15

Opioid addiction is associated with long-term adaptive changes in the brain that involve protein expression. The carboxyl-terminal of the μ opioid receptor (MOR-C) is important for receptor signal transduction under opioid treatment. However, the proteins that interact with MOR-C after chronic morphine exposure remain unknown. The brain cDNA library of chronic morphine treatment rats was screened using rat MOR-C to investigate the regulator of opioids dependence in the present study. The brain cDNA library from chronic morphine-dependent rats was constructed using the SMART (Switching Mechanism At 5' end of RNA Transcript) technique. Bacterial two-hybrid system was used to screening the rat MOR-C interacting proteins from the cDNA library. RT-qPCR and immunoblotting were used to determine the variation of MOR-C interacting proteins in rat brain after chronic morphine treatment. Column overlay assays, immunocytochemistry and coimmunoprecipitation were used to demonstrate the interaction of MOR-C and p75NTR-associated cell death executor (NADE). 21 positive proteins, including 19 known proteins were screened to interact with rat MOR-C. Expression of several of these proteins was altered in specific rat brain regions after chronic morphine treatment. Among these proteins, NADE was confirmed to interact with rat MOR-C by in vitro protein-protein binding and coimmunoprecipitation in Chinese hamster ovary (CHO) cells and rat brain with or without chronic morphine treatment. Understanding the rat MOR-C interacting proteins and the proteins variation under chronic morphine treatment may be critical for determining the pathophysiological basis of opioid tolerance and addiction. Copyright © 2015. Published by Elsevier Inc.

Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

PubMed Central

Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

2016-01-01

Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

Prediction of Protein-Protein Interaction Sites by Random Forest Algorithm with mRMR and IFS

PubMed Central

Li, Bi-Qing; Feng, Kai-Yan; Chen, Lei; Huang, Tao; Cai, Yu-Dong

2012-01-01

Prediction of protein-protein interaction (PPI) sites is one of the most challenging problems in computational biology. Although great progress has been made by employing various machine learning approaches with numerous characteristic features, the problem is still far from being solved. In this study, we developed a novel predictor based on Random Forest (RF) algorithm with the Minimum Redundancy Maximal Relevance (mRMR) method followed by incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility. We also included five 3D structural features to predict protein-protein interaction sites and achieved an overall accuracy of 0.672997 and MCC of 0.347977. Feature analysis showed that 3D structural features such as Depth Index (DPX) and surface curvature (SC) contributed most to the prediction of protein-protein interaction sites. It was also shown via site-specific feature analysis that the features of individual residues from PPI sites contribute most to the determination of protein-protein interaction sites. It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction. PMID:22937126

Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data.

PubMed

Pokharel, Yuba Raj; Saarela, Jani; Szwajda, Agnieszka; Rupp, Christian; Rokka, Anne; Lal Kumar Karna, Shibendra; Teittinen, Kaisa; Corthals, Garry; Kallioniemi, Olli; Wennerberg, Krister; Aittokallio, Tero; Westermarck, Jukka

2015-12-01

High content protein interaction screens have revolutionized our understanding of protein complex assembly. However, one of the major challenges in translation of high content protein interaction data is identification of those interactions that are functionally relevant for a particular biological question. To address this challenge, we developed a relevance ranking platform (RRP), which consist of modular functional and bioinformatic filters to provide relevance rank among the interactome proteins. We demonstrate the versatility of RRP to enable a systematic prioritization of the most relevant interaction partners from high content data, highlighted by the analysis of cancer relevant protein interactions for oncoproteins Pin1 and PME-1. We validated the importance of selected interactions by demonstration of PTOV1 and CSKN2B as novel regulators of Pin1 target c-Jun phosphorylation and reveal previously unknown interacting proteins that may mediate PME-1 effects via PP2A-inhibition. The RRP framework is modular and can be modified to answer versatile research problems depending on the nature of the biological question under study. Based on comparison of RRP to other existing filtering tools, the presented data indicate that RRP offers added value especially for the analysis of interacting proteins for which there is no sufficient prior knowledge available. Finally, we encourage the use of RRP in combination with either SAINT or CRAPome computational tools for selecting the candidate interactors that fulfill the both important requirements, functional relevance, and high confidence interaction detection. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Structural modeling and molecular simulation analysis of HvAP2/EREBP from barley.

PubMed

Pandey, Bharati; Sharma, Pradeep; Tyagi, Chetna; Goyal, Sukriti; Grover, Abhinav; Sharma, Indu

2016-06-01

AP2/ERF transcription factors play a critical role in plant development and stress adaptation. This study reports the three-dimensional ab initio-based model of AP2/EREBP protein of barley and its interaction with DNA. Full-length coding sequence of HvAP2/EREBP gene isolated from two Indian barley cultivars, RD 2503 and RD 31, was used to model the protein. Of five protein models obtained, the one with lowest C-score was chosen for further analysis. The N- and C-terminal regions of HvAP2 protein were found to be highly disordered. The dynamic properties of AP2/EREBP and its interaction with DNA were investigated by molecular dynamics simulation. Analysis of trajectories from simulation yielded the equilibrated conformation between 2-10ns for protein and 7-15ns for protein-DNA complex. We established relationship between DNA having GCC box and DNA-binding domain of HvAP2/EREBP was established by modeling 11-base-pair-long nucleotide sequence and HvAP2/EREBP protein using ab initio method. Analysis of protein-DNA interaction showed that a β-sheet motif constituting amino acid residues THR105, ARG100, ARG93, and ARG83 seems to play important role in stabilizing the complex as they form strong hydrogen bond interactions with the DNA motif. Taken together, this study provides first-hand comprehensive information detailing structural conformation and interactions of HvAP2/EREBP proteins in barley. The study intensifies the role of computational approaches for preliminary examination of unknown proteins in the absence of experimental information. It also provides molecular insight into protein-DNA binding for understanding and enhancing abiotic stress resistance for improving the water use efficiency in crop plants.

Asymmetric scoring functions for proteins

NASA Astrophysics Data System (ADS)

Lezon, Timothy; Holter, Neal; Maritan, Amos; Banavar, Jayanth

2003-03-01

The protein folding problem entails the prediction of the native state structure of a protein given the sequence of amino acids. In a coarse-grained description of a protein, an important ingredient for attempting this task is the determination of the effective energies of interaction between amino acids. We will discuss a simple approach for determining such interaction potentials from a training set of protein sequences and their experimentally determined native state structures. The key new ingredient in our study is the incorporation of the lack of symmetry in the effective interactions between amino acids. Our results, obtained using a set of 513 proteins, and their implications will be discussed.

A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115

Specific interaction of capsid protein and importin-{alpha}/{beta} influences West Nile virus production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhuvanakantham, Raghavan; Chong, Mun-Keat; Ng, Mah-Lee, E-mail: micngml@nus.edu.sg

2009-11-06

West Nile virus (WNV) capsid (C) protein has been shown to enter the nucleus of infected cells. However, the mechanism by which C protein enters the nucleus is unknown. In this study, we have unveiled for the first time that nuclear transport of WNV and Dengue virus C protein is mediated by their direct association with importin-{alpha}. This interplay is mediated by the consensus sequences of bipartite nuclear localization signal located between amino acid residues 85-101 together with amino acid residues 42 and 43 of C protein. Elucidation of biological significance of importin-{alpha}/C protein interaction demonstrated that the binding efficiencymore » of this association influenced the nuclear entry of C protein and virus production. Collectively, this study illustrated the molecular mechanism by which the C protein of arthropod-borne flavivirus enters the nucleus and showed the importance of importin-{alpha}/C protein interaction in the context of flavivirus life-cycle.« less

Insights into the Nature of Anesthetic-Protein Interactions: An ONIOM Study.

PubMed

Qiu, Ling; Lin, Jianguo; Bertaccini, Edward J

2015-10-08

Anesthetics have been employed widely to relieve surgical suffering, but their mechanism of action is not yet clear. For over a century, the mechanism of anesthesia was previously thought to be via lipid bilayer interactions. In the present work, a rigorous three-layer ONIOM(M06-2X/6-31+G*:PM6:AMBER) method was utilized to investigate the nature of interactions between several anesthetics and actual protein binding sites. According to the calculated structural features, interaction energies, atomic charges, and electrostatic potential surfaces, the amphiphilic nature of anesthetic-protein interactions was demonstrated for both inhalational and injectable anesthetics. The existence of hydrogen and halogen bonding interactions between anesthetics and proteins was clearly identified, and these interactions served to assist ligand recognition and binding by the protein. Within all complexes of inhalational or injectable anesthetics, the polarization effects play a dominant role over the steric effects and induce a significant asymmetry in the otherwise symmetric atomic charge distributions of the free ligands in vacuo. This study provides new insight into the mechanism of action of general anesthetics in a more rigorous way than previously described. Future rational design of safer anesthetics for an aging and more physiologically vulnerable population will be predicated on this greater understanding of such specific interactions.

CD4-gp120 interaction interface - a gateway for HIV-1 infection in human: molecular network, modeling and docking studies.

PubMed

Pandey, Deeksha; Podder, Avijit; Pandit, Mansi; Latha, Narayanan

2017-09-01

The major causative agent for Acquired Immune Deficiency Syndrome (AIDS) is Human Immunodeficiency Virus-1 (HIV-1). HIV-1 is a predominant subtype of HIV which counts on human cellular mechanism virtually in every aspect of its life cycle. Binding of viral envelope glycoprotein-gp120 with human cell surface CD4 receptor triggers the early infection stage of HIV-1. This study focuses on the interaction interface between these two proteins that play a crucial role for viral infectivity. The CD4-gp120 interaction interface has been studied through a comprehensive protein-protein interaction network (PPIN) analysis and highlighted as a useful step towards identifying potential therapeutic drug targets against HIV-1 infection. We prioritized gp41, Nef and Tat proteins of HIV-1 as valuable drug targets at early stage of viral infection. Lack of crystal structure has made it difficult to understand the biological implication of these proteins during disease progression. Here, computational protein modeling techniques and molecular dynamics simulations were performed to generate three-dimensional models of these targets. Besides, molecular docking was initiated to determine the desirability of these target proteins for already available HIV-1 specific drugs which indicates the usefulness of these protein structures to identify an effective drug combination therapy against AIDS.

Predicting Protein-Protein Interactions by Combing Various Sequence-Derived.

PubMed

Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

2011-09-20

Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

Two potato proteins, including a novel RING finger protein (HIP1), interact with the potyviral multifunctional protein HCpro.

PubMed

Guo, Deyin; Spetz, Carl; Saarma, Mart; Valkonen, Jari P T

2003-05-01

Potyviral helper-component proteinase (HCpro) is a multifunctional protein exerting its cellular functions in interaction with putative host proteins. In this study, cellular protein partners of the HCpro encoded by Potato virus A (PVA) (genus Potyvirus) were screened in a potato leaf cDNA library using a yeast two-hybrid system. Two cellular proteins were obtained that interact specifically with PVA HCpro in yeast and in the two in vitro binding assays used. Both proteins are encoded by single-copy genes in the potato genome. Analysis of the deduced amino acid sequences revealed that one (HIP1) of the two HCpro interactors is a novel RING finger protein. The sequence of the other protein (HIP2) showed no resemblance to the protein sequences available from databanks and has known biological functions.

Dilution of protein-surfactant complexes: a fluorescence study.

PubMed

Azadi, Glareh; Chauhan, Anuj; Tripathi, Anubhav

2013-09-01

Dilution of protein-surfactant complexes is an integrated step in microfluidic protein sizing, where the contribution of free micelles to the overall fluorescence is reduced by dilution. This process can be further improved by establishing an optimum surfactant concentration and quantifying the amount of protein based on the fluorescence intensity. To this end, we study the interaction of proteins with anionic sodium dodecyl sulfate (SDS) and cationic hexadecyl trimethyl ammonium bromide (CTAB) using a hydrophobic fluorescent dye (sypro orange). We analyze these interactions fluourometrically with bovine serum albumin, carbonic anhydrase, and beta-galactosidase as model proteins. The fluorescent signature of protein-surfactant complexes at various dilution points shows three distinct regions, surfactant dominant, breakdown, and protein dominant region. Based on the dilution behavior of protein-surfactant complexes, we propose a fluorescence model to explain the contribution of free and bound micelles to the overall fluorescence. Our results show that protein peak is observed at 3 mM SDS as the optimum dilution concentration. Furthermore, we study the effect of protein concentration on fluorescence intensity. In a single protein model with a constant dye quantum yield, the peak height increases with protein concentration. Finally, addition of CTAB to the protein-SDS complex at mole fractions above 0.1 shifts the protein peak from 3 mM to 4 mM SDS. The knowledge of protein-surfactant interactions obtained from these studies provides significant insights for novel detection and quantification techniques in microfluidics. © 2013 The Protein Society.

Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

PubMed

Rezende, Antonio M; Folador, Edson L; Resende, Daniela de M; Ruiz, Jeronimo C

2012-01-01

The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI) study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping) and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks received some degree of functional annotation which represents an important contribution since approximately 60% of Leishmania predicted proteomes has no predicted function.

CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

PubMed

Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

2017-09-01

Due to Ca 2+ -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

Protein-protein interaction networks (PPI) and complex diseases

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

2014-01-01

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094

The Rice Tungro Bacilliform Virus Gene II Product Interacts with the Coat Protein Domain of the Viral Gene III Polyprotein

PubMed Central

Herzog, Etienne; Guerra-Peraza, Orlene; Hohn, Thomas

2000-01-01

Rice tungro bacilliform virus (RTBV) is a plant pararetrovirus whose DNA genome contains four genes encoding three proteins and a large polyprotein. The function of most of the viral proteins is still unknown. To investigate the role of the gene II product (P2), we searched for interactions between this protein and other RTBV proteins. P2 was shown to interact with the coat protein (CP) domain of the viral gene III polyprotein (P3) both in the yeast two-hybrid system and in vitro. Domains involved in the P2-CP association have been identified and mapped on both proteins. To determine the importance of this interaction for viral multiplication, the infectivity of RTBV gene II mutants was investigated by agroinoculation of rice plants. The results showed that virus viability correlates with the ability of P2 to interact with the CP domain of P3. This study suggests that P2 could participate in RTBV capsid assembly. PMID:10666237

HyCCAPP as a tool to characterize promoter DNA-protein interactions in Saccharomyces cerevisiae.

PubMed

Guillen-Ahlers, Hector; Rao, Prahlad K; Levenstein, Mark E; Kennedy-Darling, Julia; Perumalla, Danu S; Jadhav, Avinash Y L; Glenn, Jeremy P; Ludwig-Kubinski, Amy; Drigalenko, Eugene; Montoya, Maria J; Göring, Harald H; Anderson, Corianna D; Scalf, Mark; Gildersleeve, Heidi I S; Cole, Regina; Greene, Alexandra M; Oduro, Akua K; Lazarova, Katarina; Cesnik, Anthony J; Barfknecht, Jared; Cirillo, Lisa A; Gasch, Audrey P; Shortreed, Michael R; Smith, Lloyd M; Olivier, Michael

2016-06-01

Currently available methods for interrogating DNA-protein interactions at individual genomic loci have significant limitations, and make it difficult to work with unmodified cells or examine single-copy regions without specific antibodies. In this study, we describe a physiological application of the Hybridization Capture of Chromatin-Associated Proteins for Proteomics (HyCCAPP) methodology we have developed. Both novel and known locus-specific DNA-protein interactions were identified at the ENO2 and GAL1 promoter regions of Saccharomyces cerevisiae, and revealed subgroups of proteins present in significantly different levels at the loci in cells grown on glucose versus galactose as the carbon source. Results were validated using chromatin immunoprecipitation. Overall, our analysis demonstrates that HyCCAPP is an effective and flexible technology that does not require specific antibodies nor prior knowledge of locally occurring DNA-protein interactions and can now be used to identify changes in protein interactions at target regions in the genome in response to physiological challenges. Copyright © 2016 Elsevier Inc. All rights reserved.

A genetic analysis of an important hydrophobic interaction at the P22 tailspike protein N-terminal domain.

PubMed

Williams, Jeremie; Venkatesan, Karthikeya; Ayariga, Joseph Atia; Jackson, Doba; Wu, Hongzhuan; Villafane, Robert

2018-06-01

P22 bacteriophage has been studied extensively and has served as a model for many important processes such as in vivo protein folding, protein aggregation and protein-protein interactions. The trimeric tailspike protein (TSP) serves as the receptor-binding protein for the P22 bacteriophage to the bacterial host. The homotrimeric P22 tail consists of three chains of 666aa in which the first 108aa form a trimeric dome-like structure which is called the N-terminal domain (NTD) and is responsible for attachment of the tailspike protein to the rest of the phage particle structure in the phage assembly pathway. Knowledge of this interaction requires information on what amino acids are interacting in the interface and how the NTD structure is maintained. The first 23aa form the "stem peptide" which originates at the dome top and terminates at the dome bottom. It contains a hydrophobic valine patch (V8-V9-V10) located within the dome structure. It is hypothesized that the interaction between the hydrophobic valine patch located on stem peptide and the adjacent polypeptide is critical for the interchain interaction which should be important for the stability of the P22 TSP NTD itself. To test this hypothesis, each amino acid in the valine residues is substituted by an acid, a basic, and a hydrophobic amino acid. The results of such substitutions are presented as well as associated studies. The data strongly suggest that the valine patch is of critical importance in the hydrophobic interaction between stem peptide valine patch and an adjacent chain.

Structural and Functional Analysis of VQ Motif-Containing Proteins in Arabidopsis as Interacting Proteins of WRKY Transcription Factors1[W][OA

PubMed Central

Cheng, Yuan; Zhou, Yuan; Yang, Yan; Chi, Ying-Jun; Zhou, Jie; Chen, Jian-Ye; Wang, Fei; Fan, Baofang; Shi, Kai; Zhou, Yan-Hong; Yu, Jing-Quan; Chen, Zhixiang

2012-01-01

WRKY transcription factors are encoded by a large gene superfamily with a broad range of roles in plants. Recently, several groups have reported that proteins containing a short VQ (FxxxVQxLTG) motif interact with WRKY proteins. We have recently discovered that two VQ proteins from Arabidopsis (Arabidopsis thaliana), SIGMA FACTOR-INTERACTING PROTEIN1 and SIGMA FACTOR-INTERACTING PROTEIN2, act as coactivators of WRKY33 in plant defense by specifically recognizing the C-terminal WRKY domain and stimulating the DNA-binding activity of WRKY33. In this study, we have analyzed the entire family of 34 structurally divergent VQ proteins from Arabidopsis. Yeast (Saccharomyces cerevisiae) two-hybrid assays showed that Arabidopsis VQ proteins interacted specifically with the C-terminal WRKY domains of group I and the sole WRKY domains of group IIc WRKY proteins. Using site-directed mutagenesis, we identified structural features of these two closely related groups of WRKY domains that are critical for interaction with VQ proteins. Quantitative reverse transcription polymerase chain reaction revealed that expression of a majority of Arabidopsis VQ genes was responsive to pathogen infection and salicylic acid treatment. Functional analysis using both knockout mutants and overexpression lines revealed strong phenotypes in growth, development, and susceptibility to pathogen infection. Altered phenotypes were substantially enhanced through cooverexpression of genes encoding interacting VQ and WRKY proteins. These findings indicate that VQ proteins play an important role in plant growth, development, and response to environmental conditions, most likely by acting as cofactors of group I and IIc WRKY transcription factors. PMID:22535423

Structural and functional analysis of VQ motif-containing proteins in Arabidopsis as interacting proteins of WRKY transcription factors.

PubMed

Cheng, Yuan; Zhou, Yuan; Yang, Yan; Chi, Ying-Jun; Zhou, Jie; Chen, Jian-Ye; Wang, Fei; Fan, Baofang; Shi, Kai; Zhou, Yan-Hong; Yu, Jing-Quan; Chen, Zhixiang

2012-06-01

WRKY transcription factors are encoded by a large gene superfamily with a broad range of roles in plants. Recently, several groups have reported that proteins containing a short VQ (FxxxVQxLTG) motif interact with WRKY proteins. We have recently discovered that two VQ proteins from Arabidopsis (Arabidopsis thaliana), SIGMA FACTOR-INTERACTING PROTEIN1 and SIGMA FACTOR-INTERACTING PROTEIN2, act as coactivators of WRKY33 in plant defense by specifically recognizing the C-terminal WRKY domain and stimulating the DNA-binding activity of WRKY33. In this study, we have analyzed the entire family of 34 structurally divergent VQ proteins from Arabidopsis. Yeast (Saccharomyces cerevisiae) two-hybrid assays showed that Arabidopsis VQ proteins interacted specifically with the C-terminal WRKY domains of group I and the sole WRKY domains of group IIc WRKY proteins. Using site-directed mutagenesis, we identified structural features of these two closely related groups of WRKY domains that are critical for interaction with VQ proteins. Quantitative reverse transcription polymerase chain reaction revealed that expression of a majority of Arabidopsis VQ genes was responsive to pathogen infection and salicylic acid treatment. Functional analysis using both knockout mutants and overexpression lines revealed strong phenotypes in growth, development, and susceptibility to pathogen infection. Altered phenotypes were substantially enhanced through cooverexpression of genes encoding interacting VQ and WRKY proteins. These findings indicate that VQ proteins play an important role in plant growth, development, and response to environmental conditions, most likely by acting as cofactors of group I and IIc WRKY transcription factors.

A physiologically required G protein-coupled receptor (GPCR)-regulator of G protein signaling (RGS) interaction that compartmentalizes RGS activity.

PubMed

Croft, Wayne; Hill, Claire; McCann, Eilish; Bond, Michael; Esparza-Franco, Manuel; Bennett, Jeannette; Rand, David; Davey, John; Ladds, Graham

2013-09-20

G protein-coupled receptors (GPCRs) can interact with regulator of G protein signaling (RGS) proteins. However, the effects of such interactions on signal transduction and their physiological relevance have been largely undetermined. Ligand-bound GPCRs initiate by promoting exchange of GDP for GTP on the Gα subunit of heterotrimeric G proteins. Signaling is terminated by hydrolysis of GTP to GDP through intrinsic GTPase activity of the Gα subunit, a reaction catalyzed by RGS proteins. Using yeast as a tool to study GPCR signaling in isolation, we define an interaction between the cognate GPCR (Mam2) and RGS (Rgs1), mapping the interaction domains. This reaction tethers Rgs1 at the plasma membrane and is essential for physiological signaling response. In vivo quantitative data inform the development of a kinetic model of the GTPase cycle, which extends previous attempts by including GPCR-RGS interactions. In vivo and in silico data confirm that GPCR-RGS interactions can impose an additional layer of regulation through mediating RGS subcellular localization to compartmentalize RGS activity within a cell, thus highlighting their importance as potential targets to modulate GPCR signaling pathways.

PREFACE: Protein protein interactions: principles and predictions

NASA Astrophysics Data System (ADS)

Nussinov, Ruth; Tsai, Chung-Jung

2005-06-01

Proteins are the `workhorses' of the cell. Their roles span functions as diverse as being molecular machines and signalling. They carry out catalytic reactions, transport, form viral capsids, traverse membranes and form regulated channels, transmit information from DNA to RNA, making possible the synthesis of new proteins, and they are responsible for the degradation of unnecessary proteins and nucleic acids. They are the vehicles of the immune response and are responsible for viral entry into the cell. Given their importance, considerable effort has been centered on the prediction of protein function. A prime way to do this is through identification of binding partners. If the function of at least one of the components with which the protein interacts is known, that should let us assign its function(s) and the pathway(s) in which it plays a role. This holds since the vast majority of their chores in the living cell involve protein-protein interactions. Hence, through the intricate network of these interactions we can map cellular pathways, their interconnectivities and their dynamic regulation. Their identification is at the heart of functional genomics; their prediction is crucial for drug discovery. Knowledge of the pathway, its topology, length, and dynamics may provide useful information for forecasting side effects. The goal of predicting protein-protein interactions is daunting. Some associations are obligatory, others are continuously forming and dissociating. In principle, from the physical standpoint, any two proteins can interact, but under what conditions and at which strength? The principles of protein-protein interactions are general: the non-covalent interactions of two proteins are largely the outcome of the hydrophobic effect, which drives the interactions. In addition, hydrogen bonds and electrostatic interactions play important roles. Thus, many of the interactions observed in vitro are the outcome of experimental overexpression. Protein disorder is important in protein-protein association. It has been estimated that a large fraction of cellular proteins are `natively disordered', i.e., unstable in solution. The disordered state has a significant residual structure. In this state, a protein exists in an ensemble of rapidly interconverting conformers. They play roles in cell-cycle control, signal transduction, transcriptional and translational regulation, and in large macromolecular complexes. It has been suggested that natively disordered proteins are more `adaptive', and thus advantageous in regulation and in binding diverse ligands. Alternatively, since the native conformation is still likely to be the most abundant within the ensemble, disordered proteins, which typically have larger interface to size ratios, lead to smaller protein, genome and cell sizes, and thus are functionally advantageous. To be able to predict protein-protein interactions, we need to discern various aspects of their associations: from their shape complementarity to the organization and relative contributions of the different physical components to their stability. They involve the static and the dynamic. Proteins interact through their surfaces. Thus, to analyze their interactions, we typically study residues (or atoms) which are in contact across the two-chain interface. In addition, we often inspect the residues in their vicinity, exploring their supporting matrix. The hope is that through the understanding of the principles and mechanisms of the interactions, we shall eventually be able to solve the protein-protein interaction puzzle.

Understanding Protein-Interface Interactions of a Fusion Protein at Silicone Oil-Water Interface Probed by Sum Frequency Generation Vibrational Spectroscopy.

PubMed

Li, Yaoxin; Pan, Duohai; Nashine, Vishal; Deshmukh, Smeet; Vig, Balvinder; Chen, Zhan

2018-02-01

Protein adsorbed at the silicone oil-water interface can undergo a conformational change that has the potential to induce protein aggregation on storage. Characterization of the protein structures at interface is therefore critical for understanding the protein-interface interactions. In this article, we have applied sum frequency generation (SFG) spectroscopy for studying the secondary structures of a fusion protein at interface and the surfactant effect on protein adsorption to silicone oil-water interface. SFG and chiral SFG spectra from adsorbed protein in the amide I region were analyzed. The presence of beta-sheet vibrational band at 1635 cm -1 implies the protein secondary structure was likely perturbed when protein adsorbed at silicone oil interface. The time-dependent SFG study showed a significant reduction in the SFG signal of preadsorbed protein when polysorbate 20 was introduced, suggesting surfactant has stronger interaction with the interface leading to desorption of protein from the interface. In the preadsorbed surfactant and a mixture of protein/polysorbate 20, SFG analysis confirmed that surfactant can dramatically prevent the protein adsorption to silicone oil surface. This study has demonstrated the potential of SFG for providing the detailed molecular level understanding of protein conformation at interface and assessing the influence of surfactant on protein adsorption behavior. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Probing the surface of a sweet protein: NMR study of MNEI with a paramagnetic probe

PubMed Central

Niccolai, Neri; Spadaccini, Roberta; Scarselli, Maria; Bernini, Andrea; Crescenzi, Orlando; Spiga, Ottavia; Ciutti, Arianna; Di Maro, Daniela; Bracci, Luisa; Dalvit, Claudio; Temussi, Piero A.

2001-01-01

The design of safe sweeteners is very important for people who are affected by diabetes, hyperlipemia, and caries and other diseases that are linked to the consumption of sugars. Sweet proteins, which are found in several tropical plants, are many times sweeter than sucrose on a molar basis. A good understanding of their structure–function relationship can complement traditional SAR studies on small molecular weight sweeteners and thus help in the design of safe sweeteners. However, there is virtually no sequence homology and very little structural similarity among known sweet proteins. Studies on mutants of monellin, the best characterized of sweet proteins, proved not decisive in the localization of the main interaction points of monellin with its receptor. Accordingly, we resorted to an unbiased approach to restrict the search of likely areas of interaction on the surface of a typical sweet protein. It has been recently shown that an accurate survey of the surface of proteins by appropriate paramagnetic probes may locate interaction points on protein surface. Here we report the survey of the surface of MNEI, a single chain monellin, by means of a paramagnetic probe, and a direct assessment of bound water based on an application of ePHOGSY, an NMR experiment that is ideally suited to detect interactions of small ligands to a protein. Detailed surface mapping reveals the presence, on the surface of MNEI, of interaction points that include residues previously predicted by ELISA tests and by mutagenesis. PMID:11468346

System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells.

PubMed

Malina, Halina Z

2011-01-19

The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules in disease development. In the knockout cells, incorrect interactions between proteins were observed without the protein modification by small molecules, indicating the abnormality of the protein network in the transgenic system. The irreversible protein-protein interactions lead to protein aggregation and cell degeneration, which are observed in all aging-associated diseases.

System in biology leading to cell pathology: stable protein-protein interactions after covalent modifications by small molecules or in transgenic cells

PubMed Central

2011-01-01

Background The physiological processes in the cell are regulated by reversible, electrostatic protein-protein interactions. Apoptosis is such a regulated process, which is critically important in tissue homeostasis and development and leads to complete disintegration of the cell. Pathological apoptosis, a process similar to apoptosis, is associated with aging and infection. The current study shows that pathological apoptosis is a process caused by the covalent interactions between the signaling proteins, and a characteristic of this pathological network is the covalent binding of calmodulin to regulatory sequences. Results Small molecules able to bind covalently to the amino group of lysine, histidine, arginine, or glutamine modify the regulatory sequences of the proteins. The present study analyzed the interaction of calmodulin with the BH3 sequence of Bax, and the calmodulin-binding sequence of myristoylated alanine-rich C-kinase substrate in the presence of xanthurenic acid in primary retinal epithelium cell cultures and murine epithelial fibroblast cell lines transformed with SV40 (wild type [WT], Bid knockout [Bid-/-], and Bax-/-/Bak-/- double knockout [DKO]). Cell death was observed to be associated with the covalent binding of calmodulin, in parallel, to the regulatory sequences of proteins. Xanthurenic acid is known to activate caspase-3 in primary cell cultures, and the results showed that this activation is also observed in WT and Bid-/- cells, but not in DKO cells. However, DKO cells were not protected against death, but high rates of cell death occurred by detachment. Conclusions The results showed that small molecules modify the basic amino acids in the regulatory sequences of proteins leading to covalent interactions between the modified sequences (e.g., calmodulin to calmodulin-binding sites). The formation of these polymers (aggregates) leads to an unregulated and, consequently, pathological protein network. The results suggest a mechanism for the involvement of small molecules in disease development. In the knockout cells, incorrect interactions between proteins were observed without the protein modification by small molecules, indicating the abnormality of the protein network in the transgenic system. The irreversible protein-protein interactions lead to protein aggregation and cell degeneration, which are observed in all aging-associated diseases. PMID:21247434

Individual N-Glycans Added at Intervals along the Stalk of the Nipah Virus G Protein Prevent Fusion but Do Not Block the Interaction with the Homologous F Protein

PubMed Central

Zhu, Qiyun; Biering, Scott B.; Mirza, Anne M.; Grasseschi, Brittany A.; Mahon, Paul J.; Lee, Benhur; Aguilar, Hector C.

2013-01-01

The promotion of membrane fusion by most paramyxoviruses requires an interaction between the viral attachment and fusion (F) proteins to enable receptor binding by the former to trigger the activation of the latter for fusion. Numerous studies demonstrate that the F-interactive sites on the Newcastle disease virus (NDV) hemagglutinin-neuraminidase (HN) and measles virus (MV) hemagglutinin (H) proteins reside entirely within the stalk regions of those proteins. Indeed, stalk residues of NDV HN and MV H that likely mediate the F interaction have been identified. However, despite extensive efforts, the F-interactive site(s) on the Nipah virus (NiV) G attachment glycoprotein has not been identified. In this study, we have introduced individual N-linked glycosylation sites at several positions spaced at intervals along the stalk of the NiV G protein. Five of the seven introduced sites are utilized as established by a retardation of electrophoretic mobility. Despite surface expression, ephrinB2 binding, and oligomerization comparable to those of the wild-type protein, four of the five added N-glycans completely eliminate the ability of the G protein to complement the homologous F protein in the promotion of fusion. The most membrane-proximal added N-glycan reduces fusion by 80%. However, unlike similar NDV HN and MV H mutants, the NiV G glycosylation stalk mutants retain the ability to bind F, indicating that the fusion deficiency of these mutants is not due to prevention of the G-F interaction. These findings suggest that the G-F interaction is not mediated entirely by the stalk domain of G and may be more complex than that of HN/H-F. PMID:23283956

Identification of Protein–Excipient Interaction Hotspots Using Computational Approaches

PubMed Central

Barata, Teresa S.; Zhang, Cheng; Dalby, Paul A.; Brocchini, Steve; Zloh, Mire

2016-01-01

Protein formulation development relies on the selection of excipients that inhibit protein–protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations using force degradation studies. Such methods do not readily provide information on intermolecular interactions responsible for the protective effects of excipients. This study describes a molecular docking approach to screen and rank interactions allowing for the identification of protein–excipient hotspots to aid in the selection of excipients to be experimentally screened. Previously published work with Drosophila Su(dx) was used to develop and validate the computational methodology, which was then used to determine the formulation hotspots for Fab A33. Commonly used excipients were examined and compared to the regions in Fab A33 prone to protein–protein interactions that could lead to aggregation. This approach could provide information on a molecular level about the protective interactions of excipients in protein formulations to aid the more rational development of future formulations. PMID:27258262

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Interaction study on bovine serum albumin physically binding to silver nanoparticles: Evolution from discrete conjugates to protein coronas

NASA Astrophysics Data System (ADS)

Guo, Jun; Zhong, Ruibo; Li, Wanrong; Liu, Yushuang; Bai, Zhijun; Yin, Jun; Liu, Jingran; Gong, Pei; Zhao, Xinmin; Zhang, Feng

2015-12-01

The nanostructures formed by inorganic nanoparticles together with organic molecules especially biomolecules have attracted increasing attention from both industries and researching fields due to their unique hybrid properties. In this paper, we systemically studied the interactions between amphiphilic polymer coated silver nanoparticles and bovine serum albumins by employing the fluorescence quenching approach in combination with the Stern-Volmer and Hill equations. The binding affinity was determined to 1.30 × 107 M-1 and the interaction was spontaneously driven by mainly the van der Waals force and hydrogen-bond mediated interactions, and negatively cooperative from the point of view of thermodynamics. With the non-uniform coating of amphiphilic polymer, the silver nanoparticles can form protein coronas which can become discrete protein-nanoparticle conjugates when controlling their molar ratios of mixing. The protein's conformational changes upon binding nanoparticles was also studied by using the three-dimensional fluorescence spectroscopy.

Exploring Strong Interactions in Proteins with Quantum Chemistry and Examples of Their Applications in Drug Design.

PubMed

Xie, Neng-Zhong; Du, Qi-Shi; Li, Jian-Xiu; Huang, Ri-Bo

2015-01-01

Three strong interactions between amino acid side chains (salt bridge, cation-π, and amide bridge) are studied that are stronger than (or comparable to) the common hydrogen bond interactions, and play important roles in protein-protein interactions. Quantum chemical methods MP2 and CCSD(T) are used in calculations of interaction energies and structural optimizations. The energies of three types of amino acid side chain interactions in gaseous phase and in aqueous solutions are calculated using high level quantum chemical methods and basis sets. Typical examples of amino acid salt bridge, cation-π, and amide bridge interactions are analyzed, including the inhibitor design targeting neuraminidase (NA) enzyme of influenza A virus, and the ligand binding interactions in the HCV p7 ion channel. The inhibition mechanism of the M2 proton channel in the influenza A virus is analyzed based on strong amino acid interactions. (1) The salt bridge interactions between acidic amino acids (Glu- and Asp-) and alkaline amino acids (Arg+, Lys+ and His+) are the strongest residue-residue interactions. However, this type of interaction may be weakened by solvation effects and broken by lower pH conditions. (2) The cation- interactions between protonated amino acids (Arg+, Lys+ and His+) and aromatic amino acids (Phe, Tyr, Trp and His) are 2.5 to 5-fold stronger than common hydrogen bond interactions and are less affected by the solvation environment. (3) The amide bridge interactions between the two amide-containing amino acids (Asn and Gln) are three times stronger than hydrogen bond interactions, which are less influenced by the pH of the solution. (4) Ten of the twenty natural amino acids are involved in salt bridge, or cation-, or amide bridge interactions that often play important roles in protein-protein, protein-peptide, protein-ligand, and protein-DNA interactions.

Novel approach using DNA-RNA hybrids in RNA nanotechnology | Center for Cancer Research

Cancer.gov

Developing simple approaches to detect interactions, modifications, and cellular locations of macromolecules is essential for understanding biochemical processes. The use of protein fragment complementation assays, also called split-protein systems, is a highly sensitive approach for studying protein interactions in biological systems. In this approach, functional proteins are split into non-functional fragments, and when attached to possible interacting partners, can reassemble and become functional again. Use of split-protein assays can establish differences between a healthy and a diseased state in the cell as well as determine the outcome of a therapeutic intervention.

Imaging Erg and Jun transcription factor interaction in living cells using fluorescence resonance energy transfer analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Camuzeaux, Barbara; Spriet, Corentin; Heliot, Laurent

2005-07-15

Physical interactions between transcription factors play important roles in modulating gene expression. Previous in vitro studies have shown a transcriptional synergy between Erg protein, an Ets family member, and Jun/Fos heterodimer, members of the bZip family, which requires direct Erg-Jun protein interactions. Visualization of protein interactions in living cells is a new challenge in biology. For this purpose, we generated fusion proteins of Erg, Fos, and Jun with yellow and cyan fluorescent proteins, YFP and CFP, respectively. After transient expression in HeLa cells, interactions of the resulting fusion proteins were explored by fluorescence resonance energy transfer microscopy (FRET) in fixedmore » and living cells. FRET between YFP-Erg and CFP-Jun was monitored by using photobleaching FRET and fluorescence lifetime imaging microscopy. Both techniques revealed the occurrence of intermolecular FRET between YFP-Erg and CFP-Jun. This is stressed by loss of FRET with an YFP-Erg version carrying a point mutation in its ETS domain. These results provide evidence for the interaction of Erg and Jun proteins in living cells as a critical prerequisite of their transcriptional synergy, but also for the essential role of the Y371 residue, conserved in most Ets proteins, in this interaction.« less

Interaction between Paracoccidioides brasiliensis conidia and the coagulation system: involvement of fibrinogen

PubMed Central

Tamayo, Diana; Hernández, Orville; Muñoz-Cadavid, Cesar; Cano, Luz Elena; González, Angel

2013-01-01

The infectious process starts with an initial contact between pathogen and host. We have previously demonstrated that Paracoccidioides brasiliensis conidia interact with plasma proteins including fibrinogen, which is considered the major component of the coagulation system. In this study, we evaluated the in vitro capacity of P. brasiliensis conidia to aggregate with plasma proteins and compounds involved in the coagulation system. We assessed the aggregation of P. brasiliensis conidia after incubation with human serum or plasma in the presence or absence of anticoagulants, extracellular matrix (ECM) proteins, metabolic and protein inhibitors, monosaccharides and other compounds. Additionally, prothrombin and partial thromboplastin times were determined after the interaction of P. brasiliensis conidia with human plasma. ECM proteins, monosaccharides and human plasma significantly induced P. brasiliensis conidial aggregation; however, anticoagulants and metabolic and protein inhibitors diminished the aggregation process. The extrinsic coagulation pathway was not affected by the interaction between P. brasiliensis conidia and plasma proteins, while the intrinsic pathway was markedly altered. These results indicate that P. brasiliensis conidia interact with proteins involved in the coagulation system. This interaction may play an important role in the initial inflammatory response, as well as fungal disease progression caused by P. brasiliensis dissemination. PMID:23827999

[POSSIBILITIES OF APPLICATION OF MALDI-TOF MASS-SPECTROMETRY FOR STUDY OF CARBOHYDRATE-SPECIFIC RECEPTORS FOR DIAGNOSTIC BACTERIOPHAGE EL TOR].

PubMed

Telesmanich, N R; Goncharenko, E V; Chaika, S O; Chaika, I A; Telicheva, V O

2016-01-01

Study mechanisms of interaction of diagnostic bacteriophage El Tor with sensitive strain Vibrio cholerae El Tor 18507 using direct protein profiling, identification of constant and variable proteins, taking part in interaction of the phage and cell, as well as carbohydrate-specific phage receptors. . A commercial preparation of cholera diagnostic bacteriophage El Tor, strain V. cholerae El Tor 18507 were used. Effect of carbohydrates on bacteriophage activity was determined in experiments with phage by a classic and modified by us method. Protein profiles of the studied objects were studied using MSP-analysis method. Sucrose was shown to inhibit lytic activity of bacteriophage. Proteome profiles of El Tor bacteriophage and sensitive indicator strains were studied, identification of constant and variable proteins of the studied objects by MSP Peak-list program was carried out. Analysis of changes of profiles of phage and microbial cell during interaction with sucrose gave a basis for assuming, that sucrose in the mixture of culture-phage enters interaction namely with phage protein receptors, blocking receptors specific for cholera vibrio, that subsequently manifests in a sharp decrease of phage activity against the sensitive strain.

Solid-state NMR studies of proteins immobilized on inorganic surfaces

DOE PAGES

Shaw, Wendy J.

2014-10-29

Solid state NMR is the primary tool for studying the quantitative, site-specific structure, orientation, and dynamics of biomineralization proteins under biologically relevant conditions. Two calcium phosphate proteins, statherin and leucine rich amelogenin protein (LRAP), have been studied in depth and have different features, challenging our ability to extract design principles. More recent studies of the significantly larger full-length amelogenin represent a challenging but necessary step to ultimately investigate the full diversity of biomineralization proteins. Interactions of amino acids and silaffin peptide with silica are also being studied, along with qualitative studies of proteins interacting with calcium carbonate. Dipolar recoupling techniquesmore » have formed the core of the quantitative studies, yet, the need for isolated spin pairs makes this approach costly and time intensive. The use of multi-dimensional techniques is advancing, methodology which, despite its challenges with these difficult-to-study proteins, will continue to drive future advancements in this area.« less

Exploring the interaction network of the Bacillus subtilis outer coat and crust proteins.

PubMed

Krajčíková, Daniela; Forgáč, Vladimír; Szabo, Adam; Barák, Imrich

2017-11-01

Bacillus subtilis spores, representatives of an exceptionally resistant dormant cell type, are encircled by a thick proteinaceous layer called the spore coat. More than 80 proteins assemble into four distinct coat layers: a basement layer, an inner coat, an outer coat and a crust. As the spore develops inside the mother cell, spore coat proteins synthesized in the cytoplasm are gradually deposited onto the prespore surface. A small set of morphogenetic proteins necessary for spore coat morphogenesis are thought to form a scaffold to which the rest of the coat proteins are attached. Extensive localization and proteomic studies using wild type and mutant spores have revealed the arrangement of individual proteins within the spore coat layers. In this study we examined the interactions between the proteins localized to the outer coat and crust using a bacterial two hybrid system. These two layers are composed of at least 25 components. Self-interactions were observed for most proteins and numerous novel interactions were identified. The most interesting contacts are those made with the morphogenetic proteins CotE, CotY and CotZ; these could serve as a basis for understanding the specific roles of particular proteins in spore coat morphogenesis. Copyright © 2017 Elsevier GmbH. All rights reserved.

Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free Energy.

PubMed

Duan, Lili; Liu, Xiao; Zhang, John Z H

2016-05-04

Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.

Prediction of physical protein protein interactions

NASA Astrophysics Data System (ADS)

Szilágyi, András; Grimm, Vera; Arakaki, Adrián K.; Skolnick, Jeffrey

2005-06-01

Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry.

PubMed

Pflieger, Delphine; Gonnet, Florence; de la Fuente van Bentem, Sergio; Hirt, Heribert; de la Fuente, Alberto

2011-01-01

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks. Copyright © 2010 Wiley Periodicals, Inc.

STUDIES OF METABOLITE-PROTEIN INTERACTIONS: A REVIEW

PubMed Central

Matsuda, Ryan; Bi, Cong; Anguizola, Jeanethe; Sobansky, Matthew; Rodriquez, Elliot; Badilla, John Vargas; Zheng, Xiwei; Hage, Benjamin; Hage, David S.

2014-01-01

The study of metabolomics can provide valuable information about biochemical pathways and processes at the molecular level. There have been many reports that have examined the structure, identity and concentrations of metabolites in biological systems. However, the binding of metabolites with proteins is also of growing interest. This review examines past reports that have looked at the binding of various types of metabolites with proteins. An overview of the techniques that have been used to characterize and study metabolite-protein binding is first provided. This is followed by examples of studies that have investigated the binding of hormones, fatty acids, drugs or other xenobiotics, and their metabolites with transport proteins and receptors. These examples include reports that have considered the structure of the resulting solute-protein complexes, the nature of the binding sites, the strength of these interactions, the variations in these interactions with solute structure, and the kinetics of these reactions. The possible effects of metabolic diseases on these processes, including the impact of alterations in the structure and function of proteins, are also considered. PMID:24321277

Label-free quantitative 1H NMR spectroscopy to study low-affinity ligand–protein interactions in solution: A contribution to the mechanism of polyphenol-mediated astringency

PubMed Central

Delius, Judith; Frank, Oliver

2017-01-01

Nuclear magnetic resonance (NMR) spectroscopy is well-established in assessing the binding affinity between low molecular weight ligands and proteins. However, conventional NMR-based binding assays are often limited to small proteins of high purity and may require elaborate isotopic labeling of one of the potential binding partners. As protein–polyphenol complexation is assumed to be a key event in polyphenol-mediated oral astringency, here we introduce a label-free, ligand-focused 1H NMR titration assay to estimate binding affinities and characterize soluble complex formation between proteins and low molecular weight polyphenols. The method makes use of the effects of NMR line broadening due to protein–ligand interactions and quantitation of the non-bound ligand at varying protein concentrations by quantitative 1H NMR spectroscopy (qHNMR) using electronic reference to access in vivo concentration (ERETIC 2). This technique is applied to assess the interaction kinetics of selected astringent tasting polyphenols and purified mucin, a major lubricating glycoprotein of human saliva, as well as human whole saliva. The protein affinity values (BC50) obtained are subsequently correlated with the intrinsic mouth-puckering, astringent oral sensation imparted by these compounds. The quantitative NMR method is further exploited to study the effect of carboxymethyl cellulose, a candidate “anti-astringent” protein binding antagonist, on the polyphenol–protein interaction. Consequently, the NMR approach presented here proves to be a versatile tool to study the interactions between proteins and low-affinity ligands in solution and may find promising applications in the discovery of bioactives. PMID:28886151

A mass spectrometry-based proteomic analysis of Homer2-interacting proteins in the mouse brain.

PubMed

Goulding, Scott P; Szumlinski, Karen K; Contet, Candice; MacCoss, Michael J; Wu, Christine C

2017-08-23

In the brain, the Homer protein family modulates excitatory signal transduction and receptor plasticity through interactions with other proteins in dendritic spines. Homer proteins are implicated in a variety of psychiatric disorders such as schizophrenia and addiction. Since long Homers serve as scaffolding proteins, identifying their interacting partners is an important first step in understanding their biological function and could help to guide the design of new therapeutic strategies. The present study set out to document Homer2-interacting proteins in the mouse brain using a co-immunoprecipitation-based mass spectrometry approach where Homer2 knockout samples were used to filter out non-specific interactors. We found that in the mouse brain, Homer2 interacts with a limited subset of its previously reported interacting partners (3 out of 31). Importantly, we detected an additional 15 novel Homer2-interacting proteins, most of which are part of the N-methyl-D-aspartate receptor signaling pathway. These results corroborate the central role Homer2 plays in glutamatergic transmission and expand the network of proteins potentially contributing to the behavioral abnormalities associated with altered Homer2 expression. Long Homer proteins are scaffolding proteins that regulate signal transduction in neurons. Identifying their interacting partners is key to understanding their function. We used co-immunoprecipitation in combination with mass spectrometry to establish the first comprehensive list of Homer2-interacting partners in the mouse brain. The specificity of interactions was evaluated using Homer2 knockout brain tissue as a negative control. The set of proteins that we identified minimally overlaps with previously reported interacting partners of Homer2; however, we identified novel interactors that are part of a signaling cascade activated by glutamatergic transmission, which improves our mechanistic understanding of the role of Homer2 in behavior. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying the Molecular Origins of Opposite Solvent Effects on Protein-Protein Interactions

PubMed Central

Vagenende, Vincent; Han, Alvin X.; Pek, Han B.; Loo, Bernard L. W.

2013-01-01

Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments. PMID:23696727

Quantifying the molecular origins of opposite solvent effects on protein-protein interactions.

PubMed

Vagenende, Vincent; Han, Alvin X; Pek, Han B; Loo, Bernard L W

2013-01-01

Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on the thermodynamic principles of preferential interaction theory and the quantitative characterization of local protein solvation from molecular dynamics simulations. We find that changes of preferential solvent interactions at the protein-protein interface quantitatively account for the opposite effects of glycerol on the antibody-antigen association constants. Detailed characterization of local protein solvation in the free and associated protein states reveals how opposite solvent effects on protein-protein interactions depend on the extent of dewetting of the protein-protein contact region and on structural changes that alter cooperative solvent-protein interactions at the periphery of the protein-protein interface. These results demonstrate the direct relationship between macroscopic solvent effects on protein-protein interactions and atom-scale solvent-protein interactions, and establish a general methodology for predicting and understanding solvent effects on protein-protein interactions in diverse biological environments.

Symmetric and asymmetric squarylium dyes as noncovalent protein labels: a study by fluorimetry and capillary electrophoresis.

PubMed

Welder, Frank; Paul, Beverly; Nakazumi, Hiroyuki; Yagi, Shigeyuki; Colyer, Christa L

2003-08-05

Noncovalent interactions between two squarylium dyes and various model proteins have been explored. NN127 and SQ-3 are symmetric and asymmetric squarylium dyes, respectively, the fluorescence emissions of which have been shown to be enhanced upon complexation with proteins such as bovine serum albumin (BSA), human serum albumin (HSA), beta-lactoglobulin A, and trypsinogen. Although these dyes are poorly soluble in aqueous solution, they can be dissolved first in methanol followed by dilution with aqueous buffer without precipitation, and are then suitable for use as fluorescent labels in protein determination studies. The nature of interactions between these dyes and proteins was studied using a variety of buffer systems, and it was found that electrostatic interactions are involved but not dominant. Dye/protein stoichiometries in the noncovalent complexes were found to be 1:1 for SQ-3, although various possible stoichiometries were found for NN127 depending upon pH and protein. Association constants on the order of 10(5) and 10(7) were found for noncovalent complexes of SQ-3 and NN127, respectively, with HSA, indicating stronger interactions of the symmetric dye with proteins. Finally, HSA complexes with NN127 were determined by capillary electrophoresis with laser-induced fluorescence detection (CE-LIF). In particular, NN127 shows promise as a reagent capable of fluorescently labeling analyte proteins for analysis by CE-LIF without itself being significantly fluorescent under the aqueous solution conditions studied herein.

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions.

PubMed

Agarwal, Shashank; Liu, Feifan; Yu, Hong

2011-10-03

Protein-protein interaction (PPI) is an important biomedical phenomenon. Automatically detecting PPI-relevant articles and identifying methods that are used to study PPI are important text mining tasks. In this study, we have explored domain independent features to develop two open source machine learning frameworks. One performs binary classification to determine whether the given article is PPI relevant or not, named "Simple Classifier", and the other one maps the PPI relevant articles with corresponding interaction method nodes in a standardized PSI-MI (Proteomics Standards Initiative-Molecular Interactions) ontology, named "OntoNorm". We evaluated our system in the context of BioCreative challenge competition using the standardized data set. Our systems are amongst the top systems reported by the organizers, attaining 60.8% F1-score for identifying relevant documents, and 52.3% F1-score for mapping articles to interaction method ontology. Our results show that domain-independent machine learning frameworks can perform competitively well at the tasks of detecting PPI relevant articles and identifying the methods that were used to study the interaction in such articles. Simple Classifier is available at http://sourceforge.net/p/simpleclassify/home/ and OntoNorm at http://sourceforge.net/p/ontonorm/home/.

Protective effect of surfactant protein d in pulmonary vaccinia virus infection: implication of A27 viral protein.

PubMed

Perino, Julien; Thielens, Nicole M; Crouch, Erika; Spehner, Danièle; Crance, Jean-Marc; Favier, Anne-Laure

2013-03-21

Vaccinia virus (VACV) was used as a surrogate of variola virus (VARV) (genus Orthopoxvirus), the causative agent of smallpox, to study Orthopoxvirus infection. VARV is principally transmitted between humans by aerosol droplets. Once inhaled, VARV first infects the respiratory tract where it could encounter surfactant components, such as soluble pattern recognition receptors. Surfactant protein D (SP-D), constitutively present in the lining fluids of the respiratory tract, plays important roles in innate host defense against virus infection. We investigated the role of SP-D in VACV infection and studied the A27 viral protein involvement in the interaction with SP-D. Interaction between SP-D and VACV caused viral inhibition in a lung cell model. Interaction of SP-D with VACV was mediated by the A27 viral protein. Binding required Ca2+ and interactions were blocked in the presence of excess of SP-D saccharide ligands. A27, which lacks glycosylation, directly interacted with SP-D. The interaction between SP-D and the viral particle was also observed using electron microscopy. Infection of mice lacking SP-D (SP-D-/-) resulted in increased mortality compared to SP-D+/+ mice. Altogether, our data show that SP-D participates in host defense against the vaccinia virus infection and that the interaction occurs with the viral surface protein A27.

The Homeodomain of PDX-1 Mediates Multiple Protein-Protein Interactions in the Formation of a Transcriptional Activation Complex on the Insulin Promoter

PubMed Central

Ohneda, Kinuko; Mirmira, Raghavendra G.; Wang, Juehu; Johnson, Jeffrey D.; German, Michael S.

2000-01-01

Activation of insulin gene transcription specifically in the pancreatic β cells depends on multiple nuclear proteins that interact with each other and with sequences on the insulin gene promoter to build a transcriptional activation complex. The homeodomain protein PDX-1 exemplifies such interactions by binding to the A3/4 region of the rat insulin I promoter and activating insulin gene transcription by cooperating with the basic-helix-loop-helix (bHLH) protein E47/Pan1, which binds to the adjacent E2 site. The present study provides evidence that the homeodomain of PDX-1 acts as a protein-protein interaction domain to recruit multiple proteins, including E47/Pan1, BETA2/NeuroD1, and high-mobility group protein I(Y), to an activation complex on the E2A3/4 minienhancer. The transcriptional activity of this complex results from the clustering of multiple activation domains capable of interacting with coactivators and the basal transcriptional machinery. These interactions are not common to all homeodomain proteins: the LIM homeodomain protein Lmx1.1 can also activate the E2A3/4 minienhancer in cooperation with E47/Pan1 but does so through different interactions. Cooperation between Lmx1.1 and E47/Pan1 results not only in the aggregation of multiple activation domains but also in the unmasking of a potent activation domain on E47/Pan1 that is normally silent in non-β cells. While more than one activation complex may be capable of activating insulin gene transcription through the E2A3/4 minienhancer, each is dependent on multiple specific interactions among a unique set of nuclear proteins. PMID:10629047

Biophysics of protein-DNA interactions and chromosome organization

PubMed Central

Marko, John F.

2014-01-01

The function of DNA in cells depends on its interactions with protein molecules, which recognize and act on base sequence patterns along the double helix. These notes aim to introduce basic polymer physics of DNA molecules, biophysics of protein-DNA interactions and their study in single-DNA experiments, and some aspects of large-scale chromosome structure. Mechanisms for control of chromosome topology will also be discussed. PMID:25419039

Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells.

PubMed

Tan, Chris Soon Heng; Go, Ka Diam; Bisteau, Xavier; Dai, Lingyun; Yong, Chern Han; Prabhu, Nayana; Ozturk, Mert Burak; Lim, Yan Ting; Sreekumar, Lekshmy; Lengqvist, Johan; Tergaonkar, Vinay; Kaldis, Philipp; Sobota, Radoslaw M; Nordlund, Pär

2018-03-09

Proteins differentially interact with each other across cellular states and conditions, but an efficient proteome-wide strategy to monitor them is lacking. We report the application of thermal proximity coaggregation (TPCA) for high-throughput intracellular monitoring of protein complex dynamics. Significant TPCA signatures observed among well-validated protein-protein interactions correlate positively with interaction stoichiometry and are statistically observable in more than 350 annotated human protein complexes. Using TPCA, we identified many complexes without detectable differential protein expression, including chromatin-associated complexes, modulated in S phase of the cell cycle. Comparison of six cell lines by TPCA revealed cell-specific interactions even in fundamental cellular processes. TPCA constitutes an approach for system-wide studies of protein complexes in nonengineered cells and tissues and might be used to identify protein complexes that are modulated in diseases. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

PubMed

Sardiu, Mihaela E; Gilmore, Joshua M; Carrozza, Michael J; Li, Bing; Workman, Jerry L; Florens, Laurence; Washburn, Michael P

2009-10-06

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

A Single-Cell Biochemistry Approach Reveals PAR Complex Dynamics during Cell Polarization.

PubMed

Dickinson, Daniel J; Schwager, Francoise; Pintard, Lionel; Gotta, Monica; Goldstein, Bob

2017-08-21

Regulated protein-protein interactions are critical for cell signaling, differentiation, and development. For the study of dynamic regulation of protein interactions in vivo, there is a need for techniques that can yield time-resolved information and probe multiple protein binding partners simultaneously, using small amounts of starting material. Here we describe a single-cell protein interaction assay. Single-cell lysates are generated at defined time points and analyzed using single-molecule pull-down, yielding information about dynamic protein complex regulation in vivo. We established the utility of this approach by studying PAR polarity proteins, which mediate polarization of many animal cell types. We uncovered striking regulation of PAR complex composition and stoichiometry during Caenorhabditis elegans zygote polarization, which takes place in less than 20 min. PAR complex dynamics are linked to the cell cycle by Polo-like kinase 1 and govern the movement of PAR proteins to establish polarity. Our results demonstrate an approach to study dynamic biochemical events in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

Interaction of classical platinum agents with the monomeric and dimeric Atox1 proteins: a molecular dynamics simulation study.

PubMed

Wang, Xiaolei; Li, Chaoqun; Wang, Yan; Chen, Guangju

2013-12-20

We carried out molecular dynamics simulations and free energy calculations for a series of binary and ternary models of the cisplatin, transplatin and oxaliplatin agents binding to a monomeric Atox1 protein and a dimeric Atox1 protein to investigate their interaction mechanisms. All three platinum agents could respectively combine with the monomeric Atox1 protein and the dimeric Atox1 protein to form a stable binary and ternary complex due to the covalent interaction of the platinum center with the Atox1 protein. The results suggested that the extra interaction from the oxaliplatin ligand-Atox1 protein interface increases its affinity only for the OxaliPt + Atox1 model. The binding of the oxaliplatin agent to the Atox1 protein might cause larger deformation of the protein than those of the cisplatin and transplatin agents due to the larger size of the oxaliplatin ligand. However, the extra interactions to facilitate the stabilities of the ternary CisPt + 2Atox1 and OxaliPt + 2Atox1 models come from the α1 helices and α2-β4 loops of the Atox1 protein-Atox1 protein interface due to the cis conformation of the platinum agents. The combinations of two Atox1 proteins in an asymmetric way in the three ternary models were analyzed. These investigations might provide detailed information for understanding the interaction mechanism of the platinum agents binding to the Atox1 protein in the cytoplasm.

Monitoring glycolipid transfer protein activity and membrane interaction with the surface plasmon resonance technique.

PubMed

Ohvo-Rekilä, Henna; Mattjus, Peter

2011-01-01

The glycolipid transfer protein (GLTP) is a protein capable of binding and transferring glycolipids. GLTP is cytosolic and it can interact through its FFAT-like (two phenylalanines in an acidic tract) motif with proteins localized on the surface of the endoplasmic reticulum. Previous in vitro work with GLTP has focused mainly on the complete transfer reaction of the protein, that is, binding and subsequent removal of the glycolipid from the donor membrane, transfer through the aqueous environment, and the final release of the glycolipid to an acceptor membrane. Using bilayer vesicles and surface plasmon resonance spectroscopy, we have now, for the first time, analyzed the binding and lipid removal capacity of GLTP with a completely label-free technique. This technique is focused on the initial steps in GLTP-mediated transfer and the parameters affecting these steps can be more precisely determined. We used the new approach for detailed structure-function studies of GLTP by examining the glycolipid transfer capacity of specific GLTP tryptophan mutants. Tryptophan 96 is crucial for the transfer activity of the protein and tryptophan 142 is an important part of the proteins membrane interacting domain. Further, we varied the composition of the used lipid vesicles and gained information on the effect of membrane properties on GLTP activity. GLTP prefers to interact with more tightly packed membranes, although GLTP-mediated transfer is faster from more fluid membranes. This technique is very useful for the study of membrane-protein interactions and lipid-transfer rates and it can easily be adapted to other membrane-interacting proteins. Copyright © 2010 Elsevier B.V. All rights reserved.

Metabotropic Glutamate Receptors and Interacting Proteins in Epileptogenesis

PubMed Central

Qian, Feng; Tang, Feng-Ru

2016-01-01

Neurotransmitter and receptor systems are involved in different neurological and neuropsychological disorders such as Parkinson's disease, depression, Alzheimer’s disease and epilepsy. Recent advances in studies of signal transduction pathways or interacting proteins of neurotransmitter receptor systems suggest that different receptor systems may share the common signal transduction pathways or interacting proteins which may be better therapeutic targets for development of drugs to effectively control brain diseases. In this paper, we reviewed metabotropic glutamate receptors (mGluRs) and their related signal transduction pathways or interacting proteins in status epilepticus and temporal lobe epilepsy, and proposed some novel therapeutical drug targets for controlling epilepsy and epileptogenesis. PMID:27030135

Quenching interaction of BSA with DTAB is dynamic in nature: A spectroscopic insight

NASA Astrophysics Data System (ADS)

Das, Nirmal Kumar; Pawar, Lavanya; Kumar, Naveen; Mukherjee, Saptarshi

2015-08-01

The role of electrostatic interactions between the protein, Bovine Serum Albumin (BSA) and the cationic surfactant, dodecyltrimethylammonium bromide (DTAB) has been substantiated using spectroscopic approaches. The primary mechanism of fluorescence quenching of the tryptophan of BSA is most probably dynamic in nature as the complex formation resulting in a protein-surfactant assembly is not very spontaneous. The weak interaction buries the tryptophan amino acid residue inside the protein scaffolds which have been quantitatively proved by our acrylamide quenching studies. The loss in the secondary structure of the protein as a result of interaction with DTAB has been elucidated by CD spectroscopy.

HExpoChem: a systems biology resource to explore human exposure to chemicals.

PubMed

Taboureau, Olivier; Jacobsen, Ulrik Plesner; Kalhauge, Christian; Edsgärd, Daniel; Rigina, Olga; Gupta, Ramneek; Audouze, Karine

2013-05-01

Humans are exposed to diverse hazardous chemicals daily. Although an exposure to these chemicals is suspected to have adverse effects on human health, mechanistic insights into how they interact with the human body are still limited. Therefore, acquisition of curated data and development of computational biology approaches are needed to assess the health risks of chemical exposure. Here we present HExpoChem, a tool based on environmental chemicals and their bioactivities on human proteins with the objective of aiding the qualitative exploration of human exposure to chemicals. The chemical-protein interactions have been enriched with a quality-scored human protein-protein interaction network, a protein-protein association network and a chemical-chemical interaction network, thus allowing the study of environmental chemicals through formation of protein complexes and phenotypic outcomes enrichment. HExpoChem is available at http://www.cbs.dtu.dk/services/HExpoChem-1.0/.

Influence of homology and node age on the growth of protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Bottinelli, Arianna; Bassetti, Bruno; Lagomarsino, Marco Cosentino; Gherardi, Marco

2012-10-01

Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so the dynamics of the two objects are intrinsically linked. Here we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions through the definition of three different node wiring or divergence schemes. A comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition and topology observables.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Prediction of glycolipid-binding domains from the amino acid sequence of lipid raft-associated proteins: application to HpaA, a protein involved in the adhesion of Helicobacter pylori to gastrointestinal cells.

PubMed

Fantini, Jacques; Garmy, Nicolas; Yahi, Nouara

2006-09-12

Protein-glycolipid interactions mediate the attachment of various pathogens to the host cell surface as well as the association of numerous cellular proteins with lipid rafts. Thus, it is of primary importance to identify the protein domains involved in glycolipid recognition. Using structure similarity searches, we could identify a common glycolipid-binding domain in the three-dimensional structure of several proteins known to interact with lipid rafts. Yet the three-dimensional structure of most raft-targeted proteins is still unknown. In the present study, we have identified a glycolipid-binding domain in the amino acid sequence of a bacterial adhesin (Helicobacter pylori adhesin A, HpaA). The prediction was based on the major properties of the glycolipid-binding domains previously characterized by structural searches. A short (15-mer) synthetic peptide corresponding to this putative glycolipid-binding domain was synthesized, and we studied its interaction with glycolipid monolayers at the air-water interface. The synthetic HpaA peptide recognized LacCer but not Gb3. This glycolipid specificity was in line with that of the whole bacterium. Molecular modeling studies gave some insights into this high selectivity of interaction. It also suggested that Phe147 in HpaA played a key role in LacCer recognition, through sugar-aromatic CH-pi stacking interactions with the hydrophobic side of the galactose ring of LacCer. Correspondingly, the replacement of Phe147 with Ala strongly affected LacCer recognition, whereas substitution with Trp did not. Our method could be used to identify glycolipid-binding domains in microbial and cellular proteins interacting with lipid shells, rafts, and other specialized membrane microdomains.

Reconstruction of the bifidobacterial pan-secretome reveals the network of extracellular interactions between bifidobacteria and the infant gut.

PubMed

Lugli, Gabriele Andrea; Mancino, Walter; Milani, Christian; Duranti, Sabrina; Turroni, Francesca; van Sinderen, Douwe; Ventura, Marco

2018-06-08

The repertoire of secreted proteins decoded by a microorganism represents proteins released from or associated with the cell's surface. In gut commensals, such as bifidobacteria, these proteins are perceived to be functionally relevant as they regulate the interaction with the gut environment. In the current study, we have screened the predicted proteome of over 300 bifidobacterial strains amongst the currently recognized bifidobacterial species to generate a comprehensive database encompassing bifidobacterial extracellular proteins. A glycobiome analysis of this predicted bifidobacterial secretome revealed that a correlation exists between particular bifidobacterial species and their capability to hydrolyze HMOs and intestinal glyconjugates such as mucin. Furthermore, exploration of metatranscriptomic datasets of the infant gut microbiota allowed the evaluation of the expression of bifidobacterial genes encoding extracellular proteins, represented by ABC transporter substrate-binding proteins and glycoside hydrolases enzymes involved in the degradation of human milk oligosaccharides and mucin. Overall, this study provides insights into how bifidobacteria interact with their natural yet highly complex environment, the infant gut. Importance The ecological success of bifidobacteria relies on the activity of extracellular proteins that are involved in the metabolism of nutrients and the interaction with the environment. To date, information on secreted proteins encoded by bifidobacteria are incomplete and just related to few species. In this study, we reconstructed the bifidobacterial pan-secretome, revealing extracellular proteins that modulate the interaction of bifidobacteria with their natural environment. Furthermore, a survey of secretion system between bifidobacterial genomes allowed the identification of a conserved Sec-dependent secretion machinery in all the analyzed genomes and the Tat protein translocation system in the chromosomes of 23 strains belonging to Bifidobacterium longum subsp. longum and Bifidobacterium aesculapii . Copyright © 2018 American Society for Microbiology.

Phosphorylation of Tat-interactive protein 60 kDa by protein kinase C epsilon is important for its subcellular localisation.

PubMed

Sapountzi, Vasileia; Logan, Ian R; Nelson, Glyn; Cook, Susan; Robson, Craig N

2008-01-01

Tat-interactive protein 60 kDa is a nuclear acetyltransferase that both coactivates and corepresses transcription factors and has a definitive function in the DNA damage response. Here, we provide evidence that Tat-interactive protein 60 kDa is phosphorylated by protein kinase C epsilon. In vitro, protein kinase C epsilon phosphorylates Tat-interactive protein 60 kDa on at least two sites within the acetyltransferase domain. In whole cells, activation of protein kinase C increases the levels of phosphorylated Tat-interactive protein 60 kDa and the interaction of Tat-interactive protein 60 kDa with protein kinase C epsilon. A phosphomimetic mutant Tat-interactive protein 60 kDa has distinct subcellular localisation compared to the wild-type protein in whole cells. Taken together, these findings suggest that the protein kinase C epsilon phosphorylation sites on Tat-interactive protein 60 kDa are important for its subcellular localisation. Regulation of the subcellular localisation of Tat-interactive protein 60 kDa via phosphorylation provides a novel means of controlling Tat-interactive protein 60 kDa function.

Protein modeling and molecular dynamics simulation of the two novel surfactant proteins SP-G and SP-H.

PubMed

Rausch, Felix; Schicht, Martin; Bräuer, Lars; Paulsen, Friedrich; Brandt, Wolfgang

2014-11-01

Surfactant proteins are well known from the human lung where they are responsible for the stability and flexibility of the pulmonary surfactant system. They are able to influence the surface tension of the gas-liquid interface specifically by directly interacting with single lipids. This work describes the generation of reliable protein structure models to support the experimental characterization of two novel putative surfactant proteins called SP-G and SP-H. The obtained protein models were complemented by predicted posttranslational modifications and placed in a lipid model system mimicking the pulmonary surface. Molecular dynamics simulations of these protein-lipid systems showed the stability of the protein models and the formation of interactions between protein surface and lipid head groups on an atomic scale. Thereby, interaction interface and strength seem to be dependent on orientation and posttranslational modification of the protein. The here presented modeling was fundamental for experimental localization studies and the simulations showed that SP-G and SP-H are theoretically able to interact with lipid systems and thus are members of the surfactant protein family.

Role of Urea-Aromatic Stacking Interactions in Stabilizing the Aromatic Residues of the Protein in Urea-Induced Denatured State.

PubMed

Goyal, Siddharth; Chattopadhyay, Aditya; Kasavajhala, Koushik; Priyakumar, U Deva

2017-10-25

A delicate balance of different types of intramolecular interactions makes the folded states of proteins marginally more stable than the unfolded states. Experiments use thermal, chemical, or mechanical stress to perturb the folding equilibrium for examining protein stability and the protein folding process. Elucidation of the mechanism by which chemical denaturants unfold proteins is crucial; this study explores the nature of urea-aromatic interactions relevant in urea-assisted protein denaturation. Free energy profiles corresponding to the unfolding of Trp-cage miniprotein in the presence and absence of urea at three different temperatures demonstrate the distortion of the hydrophobic core to be a crucial step. Exposure of the Trp6 residue to the solvent is found to be favored in the presence of urea. Previous experiments showed that urea has a high affinity for aromatic groups of proteins. We show here that this is due to the remarkable ability of urea to form stacking and NH-π interactions with aromatic groups of proteins. Urea-nucleobase stacking interactions have been shown to be crucial in urea-assisted RNA unfolding. Examination of these interactions using microsecond-long unrestrained simulations shows that urea-aromatic stacking interactions are stabilizing and long lasting. Further MD simulations, thermodynamic integration, and quantum mechanical calculations on aromatic model systems reveal that such interactions are possible for all the aromatic amino acid side-chains. Finally, we validate the ubiquitous nature of urea-aromatic stacking interactions by analyzing experimental structures of urea transporters and proteins crystallized in the presence of urea or urea derivatives.

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean.

PubMed

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla ) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein-protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.

Sunitinib: from charge-density studies to interaction with proteins.

PubMed

Malińska, Maura; Jarzembska, Katarzyna N; Goral, Anna M; Kutner, Andrzej; Woźniak, Krzysztof; Dominiak, Paulina M

2014-05-01

Protein kinases are targets for the treatment of a number of diseases. Sunitinib malate is a type I inhibitor of tyrosine kinases and was approved as a drug in 2006. This contribution constitutes the first comprehensive analysis of the crystal structures of sunitinib malate and of complexes of sunitinib with a series of protein kinases. The high-resolution single-crystal X-ray measurement and aspherical atom databank approach served as a basis for reconstruction of the charge-density distribution of sunitinib and its protein complexes. Hirshfeld surface and topological analyses revealed a similar interaction pattern in the sunitinib malate crystal structure to that in the protein binding pockets. Sunitinib forms nine preserved bond paths corresponding to hydrogen bonds and also to the C-H···O and C-H···π contacts common to the VEGRF2, CDK2, G2, KIT and IT kinases. In general, sunitinib interacts with the studied proteins with a similar electrostatic interaction energy and can adjust its conformation to fit the binding pocket in such a way as to enhance the electrostatic interactions, e.g. hydrogen bonds in ligand-kinase complexes. Such behaviour may be responsible for the broad spectrum of action of sunitinib as a kinase inhibitor.

Mapping a Noncovalent Protein-Peptide Interface by Top-Down FTICR Mass Spectrometry Using Electron Capture Dissociation

NASA Astrophysics Data System (ADS)

Clarke, David J.; Murray, Euan; Hupp, Ted; Mackay, C. Logan; Langridge-Smith, Pat R. R.

2011-08-01

Noncovalent protein-ligand and protein-protein complexes are readily detected using electrospray ionization mass spectrometry (ESI MS). Furthermore, recent reports have demonstrated that careful use of electron capture dissociation (ECD) fragmentation allows covalent backbone bonds of protein complexes to be dissociated without disruption of noncovalent protein-ligand interactions. In this way the site of protein-ligand interfaces can be identified. To date, protein-ligand complexes, which have proven tractable to this technique, have been mediated by ionic electrostatic interactions, i.e., ion pair interactions or salt bridging. Here we extend this methodology by applying ECD to study a protein-peptide complex that contains no electrostatics interactions. We analyzed the complex between the 21 kDa p53-inhibitor protein anterior gradient-2 and its hexapeptide binding ligand (PTTIYY). ECD fragmentation of the 1:1 complex occurs with retention of protein-peptide binding and analysis of the resulting fragments allows the binding interface to be localized to a C-terminal region between residues 109 and 175. These finding are supported by a solution-phase competition assay, which implicates the region between residues 108 and 122 within AGR2 as the PTTIYY binding interface. Our study expands previous findings by demonstrating that top-down ECD mass spectrometry can be used to determine directly the sites of peptide-protein interfaces. This highlights the growing potential of using ECD and related top-down fragmentation techniques for interrogation of protein-protein interfaces.

Prioritization of orphan disease-causing genes using topological feature and GO similarity between proteins in interaction networks.

PubMed

Li, Min; Li, Qi; Ganegoda, Gamage Upeksha; Wang, JianXin; Wu, FangXiang; Pan, Yi

2014-11-01

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease studies. However, it is still time-consuming and laborious to determine the real disease-causing genes by biological experiments. With the advances of the high-throughput techniques, a large number of protein-protein interactions have been produced. Therefore, to address this issue, several methods based on protein interaction network have been proposed. In this paper, we propose a shortest path-based algorithm, named SPranker, to prioritize disease-causing genes in protein interaction networks. Considering the fact that diseases with similar phenotypes are generally caused by functionally related genes, we further propose an improved algorithm SPGOranker by integrating the semantic similarity of GO annotations. SPGOranker not only considers the topological similarity between protein pairs in a protein interaction network but also takes their functional similarity into account. The proposed algorithms SPranker and SPGOranker were applied to 1598 known orphan disease-causing genes from 172 orphan diseases and compared with three state-of-the-art approaches, ICN, VS and RWR. The experimental results show that SPranker and SPGOranker outperform ICN, VS, and RWR for the prioritization of orphan disease-causing genes. Importantly, for the case study of severe combined immunodeficiency, SPranker and SPGOranker predict several novel causal genes.

Atopic dermatitis-associated protein interaction network lead to new insights in chronic sulfur mustard skin lesion mechanisms.

PubMed

Amiri, Mojtaba; Jafari, Mohieddin; Azimzadeh Jamalkandi, Sadegh; Davoodi, Seyed-Masoud

2013-10-01

Chronic sulfur mustard skin lesions (CSMSLs) are the most common complications of sulfur mustard exposure; however, its mechanism is not completely understood.According to clinical signs, there are similarities between CSMSL and atopic dermatitis (AD). In this study, proteomic results of AD were reviewed and the AD-associated protein-protein interaction network (PIN) was analyzed. According to centrality measurements, 16 proteins were designated as pivotal elements in AD mechanisms. Interestingly, most of these proteins had been reported in some sulfur mustard-related studies in late and acute phases separately. Based on the gene enrichment analysis, aging, cell response to stress, cancer, Toll- and NOD-like receptor and apoptosis signaling pathways have the greatest impact on the disease. By the analysis of directed protein interaction networks, it is concluded that TNF, IL-6, AKT1, NOS3 and CDKN1A are the most important proteins. It is possible that these proteins play role in the shared complications of AD and CSMSL including xerosis and itching.

Patterns of amino acid conservation in human and animal immunodeficiency viruses.

PubMed

Voitenko, Olga S; Dhroso, Andi; Feldmann, Anna; Korkin, Dmitry; Kalinina, Olga V

2016-09-01

Due to their high genomic variability, RNA viruses and retroviruses present a unique opportunity for detailed study of molecular evolution. Lentiviruses, with HIV being a notable example, are one of the best studied viral groups: hundreds of thousands of sequences are available together with experimentally resolved three-dimensional structures for most viral proteins. In this work, we use these data to study specific patterns of evolution of the viral proteins, and their relationship to protein interactions and immunogenicity. We propose a method for identification of two types of surface residues clusters with abnormal conservation: extremely conserved and extremely variable clusters. We identify them on the surface of proteins from HIV and other animal immunodeficiency viruses. Both types of clusters are overrepresented on the interaction interfaces of viral proteins with other proteins, nucleic acids or low molecular-weight ligands, both in the viral particle and between the virus and its host. In the immunodeficiency viruses, the interaction interfaces are not more conserved than the corresponding proteins on an average, and we show that extremely conserved clusters coincide with protein-protein interaction hotspots, predicted as the residues with the largest energetic contribution to the interaction. Extremely variable clusters have been identified here for the first time. In the HIV-1 envelope protein gp120, they overlap with known antigenic sites. These antigenic sites also contain many residues from extremely conserved clusters, hence representing a unique interacting interface enriched both in extremely conserved and in extremely variable clusters of residues. This observation may have important implication for antiretroviral vaccine development. A Python package is available at https://bioinf.mpi-inf.mpg.de/publications/viral-ppi-pred/ voitenko@mpi-inf.mpg.de or kalinina@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Discovery Proteomics Identifies a Molecular Link between the Coatomer Protein Complex I and Androgen Receptor-dependent Transcription*

PubMed Central

Hsiao, Jordy J.; Smits, Melinda M.; Ng, Brandon H.; Lee, Jinhee; Wright, Michael E.

2016-01-01

Aberrant androgen receptor (AR)-dependent transcription is a hallmark of human prostate cancers. At the molecular level, ligand-mediated AR activation is coordinated through spatial and temporal protein-protein interactions involving AR-interacting proteins, which we designate the “AR-interactome.” Despite many years of research, the ligand-sensitive protein complexes involved in ligand-mediated AR activation in prostate tumor cells have not been clearly defined. Here, we describe the development, characterization, and utilization of a novel human LNCaP prostate tumor cell line, N-AR, which stably expresses wild-type AR tagged at its N terminus with the streptavidin-binding peptide epitope (streptavidin-binding peptide-tagged wild-type androgen receptor; SBP-AR). A bioanalytical workflow involving streptavidin chromatography and label-free quantitative mass spectrometry was used to identify SBP-AR and associated ligand-sensitive cytosolic proteins/protein complexes linked to AR activation in prostate tumor cells. Functional studies verified that ligand-sensitive proteins identified in the proteomic screen encoded modulators of AR-mediated transcription, suggesting that these novel proteins were putative SBP-AR-interacting proteins in N-AR cells. This was supported by biochemical associations between recombinant SBP-AR and the ligand-sensitive coatomer protein complex I (COPI) retrograde trafficking complex in vitro. Extensive biochemical and molecular experiments showed that the COPI retrograde complex regulates ligand-mediated AR transcriptional activation, which correlated with the mobilization of the Golgi-localized ARA160 coactivator to the nuclear compartment of prostate tumor cells. Collectively, this study provides a bioanalytical strategy to validate the AR-interactome and define novel AR-interacting proteins involved in ligand-mediated AR activation in prostate tumor cells. Moreover, we describe a cellular system to study how compartment-specific AR-interacting proteins influence AR activation and contribute to aberrant AR-dependent transcription that underlies the majority of human prostate cancers. PMID:27365400

Interactome of E. piscicida and grouper liver proteins reveals strategies of bacterial infection and host immune response.

PubMed

Li, Hui; Zhu, Qing-Feng; Peng, Xuan-Xian; Peng, Bo

2017-01-03

The occurrence of infectious diseases is related to heterogeneous protein interactions between a host and a microbe. Therefore, elucidating the host-pathogen interplay is essential. We previously revealed the protein interactome between Edwardsiella piscicida and fish gill cells, and the present study identified the protein interactome between E. piscicida and E. drummondhayi liver cells. E. drummondhayi liver cells and bacterial pull-down approaches were used to identify E. piscicida outer membrane proteins that bind to liver cells and fish liver cell proteins that interact with bacterial cells, respectively. Eight bacterial proteins and 11 fish proteins were characterized. Heterogeneous protein-protein interactions between these bacterial cells and fish liver cells were investigated through far-Western blotting and co-immunoprecipitation. A network was constructed based on 42 heterogeneous protein-protein interactions between seven bacterial proteins and 10 fish proteins. A comparison of the new interactome with the previously reported interactome showed that four bacterial proteins overlapped, whereas all of the identified fish proteins were new, suggesting a difference between bacterial tricks for evading host immunity and the host strategy for combating bacterial infection. Furthermore, these bacterial proteins were found to regulate the expression of host innate immune-related proteins. These findings indicate that the interactome contributes to bacterial infection and host immunity.

Protein electrostatics: a review of the equations and methods used to model electrostatic equations in biomolecules--applications in biotechnology.

PubMed

Neves-Petersen, Maria Teresa; Petersen, Steffen B

2003-01-01

The molecular understanding of the initial interaction between a protein and, e.g., its substrate, a surface or an inhibitor is essentially an understanding of the role of electrostatics in intermolecular interactions. When studying biomolecules it is becoming increasingly evident that electrostatic interactions play a role in folding, conformational stability, enzyme activity and binding energies as well as in protein-protein interactions. In this chapter we present the key basic equations of electrostatics necessary to derive the equations used to model electrostatic interactions in biomolecules. We will also address how to solve such equations. This chapter is divided into two major sections. In the first part we will review the basic Maxwell equations of electrostatics equations called the Laws of Electrostatics that combined will result in the Poisson equation. This equation is the starting point of the Poisson-Boltzmann (PB) equation used to model electrostatic interactions in biomolecules. Concepts as electric field lines, equipotential surfaces, electrostatic energy and when can electrostatics be applied to study interactions between charges will be addressed. In the second part we will arrive at the electrostatic equations for dielectric media such as a protein. We will address the theory of dielectrics and arrive at the Poisson equation for dielectric media and at the PB equation, the main equation used to model electrostatic interactions in biomolecules (e.g., proteins, DNA). It will be shown how to compute forces and potentials in a dielectric medium. In order to solve the PB equation we will present the continuum electrostatic models, namely the Tanford-Kirkwood and the modified Tandord-Kirkwood methods. Priority will be given to finding the protonation state of proteins prior to solving the PB equation. We also present some methods that can be used to map and study the electrostatic potential distribution on the molecular surface of proteins. The combination of graphical visualisation of the electrostatic fields combined with knowledge about the location of key residues on the protein surface allows us to envision atomic models for enzyme function. Finally, we exemplify the use of some of these methods on the enzymes of the lipase family.

The RSV F and G glycoproteins interact to form a complex on the surface of infected cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Low, Kit-Wei; Tan, Timothy; Ng, Ken

2008-02-08

In this study, the interaction between the respiratory syncytial virus (RSV) fusion (F) protein, attachment (G) protein, and small hydrophobic (SH) proteins was examined. Immunoprecipitation analysis suggested that the F and G proteins exist as a protein complex on the surface of RSV-infected cells, and this conclusion was supported by ultracentrifugation analysis that demonstrated co-migration of surface-expressed F and G proteins. Although our analysis provided evidence for an interaction between the G and SH proteins, no evidence was obtained for a single protein complex involving all three of the virus proteins. These data suggest the existence of multiple virus glycoproteinmore » complexes within the RSV envelope. Although the stimulus that drives RSV-mediated membrane fusion is unknown, the association between the G and F proteins suggest an indirect role for the G protein in this process.« less

Gγ recruitment system incorporating a novel signal amplification circuit to screen transient protein-protein interactions.

PubMed

Fukuda, Nobuo; Ishii, Jun; Kondo, Akihiko

2011-09-01

Weak and transient protein-protein interactions are associated with biological processes, but many are still undefined because of the difficulties in their identification. Here, we describe a redesigned method to screen transient protein-protein interactions by using a novel signal amplification circuit, which is incorporated into yeast to artificially magnify the signal responding to the interactions. This refined method is based on the previously established Gγ recruitment system, which utilizes yeast G-protein signaling and mating growth selection to screen interacting protein pairs. In the current study, to test the capability of our method, we chose mutants of the Z-domain derived from Staphylococcus aureus protein A as candidate proteins, and the Fc region of human IgG as the counterpart. By introduction of an artificial signal amplifier into the previous Gγ recruitment system, the signal transduction responding to transient interactions between Z-domain mutants and the Fc region with significantly low affinity (8.0 × 10(3) M(-1)) was successfully amplified in recombinant haploid yeast cells. As a result of zygosis with the opposite mating type of wild-type haploid cells, diploid colonies were vigorously and selectively generated on the screening plates, whereas our previous system rarely produced positive colonies. This new approach will be useful for exploring the numerous transient interactions that remain undefined because of the lack of powerful screening tools for their identification. © 2011 The Authors Journal compilation © 2011 FEBS.

Proof of concept of a "greener" protein purification/enrichment method based on carboxylate-terminated carbosilane dendrimer-protein interactions.

PubMed

González-García, Estefanía; Maly, Marek; de la Mata, Francisco Javier; Gómez, Rafael; Marina, María Luisa; García, María Concepción

2016-11-01

Protein sample preparation is a critical and an unsustainable step since it involves the use of tedious methods that usually require high amount of solvents. The development of new materials offers additional opportunities in protein sample preparation. This work explores, for the first time, the potential application of carboxylate-terminated carbosilane dendrimers to the purification/enrichment of proteins. Studies on dendrimer binding to proteins, based on protein fluorescence intensity and emission wavelengths measurements, demonstrated the interaction between carboxylate-terminated carbosilane dendrimers and proteins at all tested pH levels. Interactions were greatly affected by the protein itself, pH, and dendrimer concentration and generation. Especially interesting was the interaction at acidic pH since it resulted in a significant protein precipitation. Dendrimer-protein interactions were modeled observing stable complexes for all proteins. Carboxylate-terminated carbosilane dendrimers at acidic pH were successfully used in the purification/enrichment of proteins extracted from a complex sample. Graphical Abstract Images showing the growing turbidity of solutions containing a mixture of proteins (lysozyme, myoglobin, and BSA) at different protein:dendrimer ratios (1:0, 1:1, 1:8, and 1:20) at acidic pH and SDS-PAGE profiles of the corresponsing supernatants. Comparison of SDS-PAGE profiles for the pellets obtained during the purification of proteins present in a complex sample using a conventional "no-clean" method based on acetone precipitation and the proposed "greener" method using carboxylate-terminated carbosilane dendrimer at a 1:20 protein:dendrimer ratio.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Interaction of Tim23 with Tim50 Is essential for protein translocation by the mitochondrial TIM23 complex.

PubMed

Gevorkyan-Airapetov, Lada; Zohary, Keren; Popov-Celeketic, Dusan; Mapa, Koyeli; Hell, Kai; Neupert, Walter; Azem, Abdussalam; Mokranjac, Dejana

2009-02-20

The TIM23 complex is the major translocase of the mitochondrial inner membrane responsible for the import of essentially all matrix proteins and a number of inner membrane proteins. Tim23 and Tim50, two essential proteins of the complex, expose conserved domains into the intermembrane space that interact with each other. Here, we describe in vitro reconstitution of this interaction using recombinantly expressed and purified intermembrane space domains of Tim50 and Tim23. We established two independent methods, chemical cross-linking and surface plasmon resonance, to track their interaction. In addition, we identified mutations in Tim23 that abolish its interaction with Tim50 in vitro. These mutations also destabilized the interaction between the two proteins in vivo, leading to defective import of preproteins via the TIM23 complex and to cell death at higher temperatures. This is the first study to describe the reconstitution of the Tim50-Tim23 interaction in vitro and to identify specific residues of Tim23 that are vital for the interaction with Tim50.

Magnetic field effect corroborated with docking study to explore photoinduced electron transfer in drug-protein interaction.

PubMed

Chakraborty, Brotati; Roy, Atanu Singha; Dasgupta, Swagata; Basu, Samita

2010-12-30

Conventional spectroscopic tools such as absorption, fluorescence, and circular dichroism spectroscopy used in the study of photoinduced drug-protein interactions can yield useful information about ground-state and excited-state phenomena. However, photoinduced electron transfer (PET) may be a possible phenomenon in the drug-protein interaction, which may go unnoticed if only conventional spectroscopic observations are taken into account. Laser flash photolysis coupled with an external magnetic field can be utilized to confirm the occurrence of PET and authenticate the spin states of the radicals/radical ions formed. In the study of interaction of the model protein human serum albumin (HSA) with acridine derivatives, acridine yellow (AY) and proflavin (PF(+)), conventional spectroscopic tools along with docking study have been used to decipher the binding mechanism, and laser flash photolysis technique with an associated magnetic field (MF) has been used to explore PET. The results of fluorescence study indicate that fluorescence resonance energy transfer takes place from the protein to the acridine-based drugs. Docking study unveils the crucial role of Ser 232 residue of HSA in explaining the differential behavior of the two drugs towards the model protein. Laser flash photolysis experiments help to identify the radicals/radical ions formed in the due course of PET (PF(•), AY(•-), TrpH(•+), Trp(•)), and the application of an external MF has been used to characterize their initial spin-state. Owing to its distance dependence, MF effect gives an idea about the proximity of the radicals/radical ions during interaction in the system and also helps to elucidate the reaction mechanisms. A prominent MF effect is observed in homogeneous buffer medium owing to the pseudoconfinement of the radicals/radical ions provided by the complex structure of the protein.

Predicting protein-protein interactions by combing various sequence- derived features into the general form of Chou's Pseudo amino acid composition.

PubMed

Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

2012-05-01

Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

On the Importance of Polar Interactions for Complexes Containing Intrinsically Disordered Proteins

PubMed Central

Wong, Eric T. C.; Na, Dokyun; Gsponer, Jörg

2013-01-01

There is a growing recognition for the importance of proteins with large intrinsically disordered (ID) segments in cell signaling and regulation. ID segments in these proteins often harbor regions that mediate molecular recognition. Coupled folding and binding of the recognition regions has been proposed to confer high specificity to interactions involving ID segments. However, researchers recently questioned the origin of the interaction specificity of ID proteins because of the overrepresentation of hydrophobic residues in their interaction interfaces. Here, we focused on the role of polar and charged residues in interactions mediated by ID segments. Making use of the extended nature of most ID segments when in complex with globular proteins, we first identified large numbers of complexes between globular proteins and ID segments by using radius-of-gyration-based selection criteria. Consistent with previous studies, we found the interfaces of these complexes to be enriched in hydrophobic residues, and that these residues contribute significantly to the stability of the interaction interface. However, our analyses also show that polar interactions play a larger role in these complexes than in structured protein complexes. Computational alanine scanning and salt-bridge analysis indicate that interfaces in ID complexes are highly complementary with respect to electrostatics, more so than interfaces of globular proteins. Follow-up calculations of the electrostatic contributions to the free energy of binding uncovered significantly stronger Coulombic interactions in complexes harbouring ID segments than in structured protein complexes. However, they are counter-balanced by even higher polar-desolvation penalties. We propose that polar interactions are a key contributing factor to the observed high specificity of ID segment-mediated interactions. PMID:23990768

IC-tagged proteins are able to interact with each other and perform complex reactions when integrated into muNS-derived inclusions.

PubMed

Brandariz-Nuñez, Alberto; Otero-Romero, Iria; Benavente, Javier; Martinez-Costas, Jose M

2011-09-20

We have recently developed a versatile tagging system (IC-tagging) that causes relocation of the tagged proteins to ARV muNS-derived intracellular globular inclusions. In the present study we demonstrate (i) that the IC-tag can be successfully fused either to the amino or carboxyl terminus of the protein to be tagged and (ii) that IC-tagged proteins are able to interact between them and perform complex reactions that require such interactions while integrated into muNS inclusions, increasing the versatility of the IC-tagging system. Also, our studies with the DsRed protein add some light on the structure/function relationship of the evolution of DsRed chromophore. Copyright © 2011 Elsevier B.V. All rights reserved.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Interaction study of rice stripe virus proteins reveals a region of the nucleocapsid protein (NP) required for NP self-interaction and nuclear localization.

PubMed

Lian, Sen; Cho, Won Kyong; Jo, Yeonhwa; Kim, Sang-Min; Kim, Kook-Hyung

2014-04-01

Rice stripe virus (RSV), which belongs to the genus Tenuivirus, is an emergent virus problem. The RSV genome is composed of four single-strand RNAs (RNA1-RNA4) and encodes seven proteins. We investigated interactions between six of the RSV proteins by yeast-two hybrid (Y2H) assay in vitro and by bimolecular fluorescence complementation (BiFC) in planta. Y2H identified self-interaction of the nucleocapsid protein (NP) and NS3, while BiFC revealed self-interaction of NP, NS3, and NCP. To identify regions(s) and/or crucial amino acid (aa) residues required for NP self-interaction, we generated various truncated and aa substitution mutants. Y2H assay showed that the N-terminal region of NP (aa 1-56) is necessary for NP self-interaction. Further analysis with substitution mutants demonstrated that additional aa residues located at 42-47 affected their interaction with full-length NP. These results indicate that the N-terminal region (aa 1-36 and 42-47) is required for NP self-interaction. BiFC and co-localization studies showed that the region required for NP self-interaction is also required for NP localization at the nucleus. Overall, our results indicate that the N-terminal region (aa 1-47) of the NP is important for NP self-interaction and that six aa residues (42-47) are essential for both NP self-interaction and nuclear localization. Copyright © 2014 Elsevier B.V. All rights reserved.

Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

PubMed

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.

Phthalic acid chemical probes synthesized for protein-protein interaction analysis.

PubMed

Liang, Shih-Shin; Liao, Wei-Ting; Kuo, Chao-Jen; Chou, Chi-Hsien; Wu, Chin-Jen; Wang, Hui-Min

2013-06-24

Plasticizers are additives that are used to increase the flexibility of plastic during manufacturing. However, in injection molding processes, plasticizers cannot be generated with monomers because they can peel off from the plastics into the surrounding environment, water, or food, or become attached to skin. Among the various plasticizers that are used, 1,2-benzenedicarboxylic acid (phthalic acid) is a typical precursor to generate phthalates. In addition, phthalic acid is a metabolite of diethylhexyl phthalate (DEHP). According to Gene_Ontology gene/protein database, phthalates can cause genital diseases, cardiotoxicity, hepatotoxicity, nephrotoxicity, etc. In this study, a silanized linker (3-aminopropyl triethoxyslane, APTES) was deposited on silicon dioxides (SiO2) particles and phthalate chemical probes were manufactured from phthalic acid and APTES-SiO2. These probes could be used for detecting proteins that targeted phthalic acid and for protein-protein interactions. The phthalic acid chemical probes we produced were incubated with epithelioid cell lysates of normal rat kidney (NRK-52E cells) to detect the interactions between phthalic acid and NRK-52E extracted proteins. These chemical probes interacted with a number of chaperones such as protein disulfide-isomerase A6, heat shock proteins, and Serpin H1. Ingenuity Pathways Analysis (IPA) software showed that these chemical probes were a practical technique for protein-protein interaction analysis.

Prediction of GCRV virus-host protein interactome based on structural motif-domain interactions.

PubMed

Zhang, Aidi; He, Libo; Wang, Yaping

2017-03-02

Grass carp hemorrhagic disease, caused by grass carp reovirus (GCRV), is the most fatal causative agent in grass carp aquaculture. Protein-protein interactions between virus and host are one avenue through which GCRV can trigger infection and induce disease. Experimental approaches for the detection of host-virus interactome have many inherent limitations, and studies on protein-protein interactions between GCRV and its host remain rare. In this study, based on known motif-domain interaction information, we systematically predicted the GCRV virus-host protein interactome by using motif-domain interaction pair searching strategy. These proteins derived from different domain families and were predicted to interact with different motif patterns in GCRV. JAM-A protein was successfully predicted to interact with motifs of GCRV Sigma1-like protein, and shared the similar binding mode compared with orthoreovirus. Differentially expressed genes during GCRV infection process were extracted and mapped to our predicted interactome, the overlapped genes displayed different tissue expression distributions on the whole, the overall expression level in intestinal is higher than that of other three tissues, which may suggest that the functions of these genes are more active in intestinal. Function annotation and pathway enrichment analysis revealed that the host targets were largely involved in signaling pathway and immune pathway, such as interferon-gamma signaling pathway, VEGF signaling pathway, EGF receptor signaling pathway, B cell activation, and T cell activation. Although the predicted PPIs may contain some false positives due to limited data resource and poor research background in non-model species, the computational method still provide reasonable amount of interactions, which can be further validated by high throughput experiments. The findings of this work will contribute to the development of system biology for GCRV infectious diseases, and help guide the identification of novel receptors of GCRV in its host.

Precise control of surface electrostatic forces on polymer brush layers with opposite charges for resistance to protein adsorption.

PubMed

Sakata, Sho; Inoue, Yuuki; Ishihara, Kazuhiko

2016-10-01

Various molecular interaction forces are generated during protein adsorption process on material surfaces. Thus, it is necessary to control them to suppress protein adsorption and the subsequent cell and tissue responses. A series of binary copolymer brush layers were prepared via surface-initiated atom transfer radical polymerization, by mixing the cationic monomer unit and anionic monomer unit randomly in various ratios. Surface characterization revealed that the constructed copolymer brush layers exhibited an uniform super-hydrophilic nature and different surface potentials. The strength of the electrostatic interaction forces operating on these mixed-charge copolymer brush surfaces was evaluated quantitatively using force-versus-distance (f-d) curve measurements by atomic force microscopy (AFM) and probes modified by negatively charged carboxyl groups or positively charged amino groups. The electrostatic interaction forces were determined based on the charge ratios of the copolymer brush layers. Notably, the surface containing equivalent cationic/anionic monomer units hardly interacted with both the charged groups. Furthermore, the protein adsorption force and the protein adsorption mass on these surfaces were examined by AFM f-d curve measurement and surface plasmon resonance measurement, respectively. To clarify the influence of the electrostatic interaction on the protein adsorption behavior on the surface, three kinds of proteins having negative, positive, and relatively neutral net charges under physiological conditions were used in this study. We quantitatively demonstrated that the amount of adsorbed proteins on the surfaces would have a strong correlation with the strength of surface-protein interaction forces, and that the strength of surface-protein interaction forces would be determined from the combination between the properties of the electrostatic interaction forces on the surfaces and the charge properties of the proteins. Especially, the copolymer brush surface composed of equivalent cationic/anionic monomer units exhibited no significant interaction forces, and dramatically suppressed the adsorption of proteins regardless of their charge properties. We conclude that the established methodology could elucidate relationship between the protein adsorption behavior and molecular interaction, especially the electrostatic interaction forces, and demonstrated that the suppression of the electrostatic interactions with the ionic functional groups would be important for the development of new polymeric biomaterials with a high repellency of protein adsorption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Noroviruses Co-opt the Function of Host Proteins VAPA and VAPB for Replication via a Phenylalanine-Phenylalanine-Acidic-Tract-Motif Mimic in Nonstructural Viral Protein NS1/2.

PubMed

McCune, Broc T; Tang, Wei; Lu, Jia; Eaglesham, James B; Thorne, Lucy; Mayer, Anne E; Condiff, Emily; Nice, Timothy J; Goodfellow, Ian; Krezel, Andrzej M; Virgin, Herbert W

2017-07-11

The Norovirus genus contains important human pathogens, but the role of host pathways in norovirus replication is largely unknown. Murine noroviruses provide the opportunity to study norovirus replication in cell culture and in small animals. The human norovirus nonstructural protein NS1/2 interacts with the host protein VAMP-associated protein A (VAPA), but the significance of the NS1/2-VAPA interaction is unexplored. Here we report decreased murine norovirus replication in VAPA- and VAPB-deficient cells. We characterized the role of VAPA in detail. VAPA was required for the efficiency of a step(s) in the viral replication cycle after entry of viral RNA into the cytoplasm but before the synthesis of viral minus-sense RNA. The interaction of VAPA with viral NS1/2 proteins is conserved between murine and human noroviruses. Murine norovirus NS1/2 directly bound the major sperm protein (MSP) domain of VAPA through its NS1 domain. Mutations within NS1 that disrupted interaction with VAPA inhibited viral replication. Structural analysis revealed that the viral NS1 domain contains a mimic of the phenylalanine-phenylalanine-acidic-tract (FFAT) motif that enables host proteins to bind to the VAPA MSP domain. The NS1/2-FFAT mimic region interacted with the VAPA-MSP domain in a manner similar to that seen with bona fide host FFAT motifs. Amino acids in the FFAT mimic region of the NS1 domain that are important for viral replication are highly conserved across murine norovirus strains. Thus, VAPA interaction with a norovirus protein that functionally mimics host FFAT motifs is important for murine norovirus replication. IMPORTANCE Human noroviruses are a leading cause of gastroenteritis worldwide, but host factors involved in norovirus replication are incompletely understood. Murine noroviruses have been studied to define mechanisms of norovirus replication. Here we defined the importance of the interaction between the hitherto poorly studied NS1/2 norovirus protein and the VAPA host protein. The NS1/2-VAPA interaction is conserved between murine and human noroviruses and was important for early steps in murine norovirus replication. Using structure-function analysis, we found that NS1/2 contains a short sequence that molecularly mimics the FFAT motif that is found in multiple host proteins that bind VAPA. This represents to our knowledge the first example of functionally important mimicry of a host FFAT motif by a microbial protein. Copyright © 2017 McCune et al.

Altered Protein Interactions of the Endogenous Interactome of PTPIP51 towards MAPK Signaling

PubMed Central

Brobeil, Alexander; Chehab, Rajaa; Dietel, Eric; Gattenlöhner, Stefan; Wimmer, Monika

2017-01-01

Protein–protein interactions play a pivotal role in normal cellular functions as well as in carcinogenesis. The protein–protein interactions form functional clusters during signal transduction. To elucidate the fine calibration of the protein–protein interactions of protein tyrosine phosphatase interacting protein 51 (PTPIP51) a small molecule drug, namely LDC-3, directly targeting PTPIP51 is now available. Therefore, LDC-3 allows for the studying of the regulation of the endogenous interactome by modulating PTPIP51 binding capacity. Small interfering ribonucleic acid (siRNA) experiments show that the modification in PTPIP51 binding capacity is induced by LDC-3. Application of LDC-3 annuls the known regulatory phosphorylation mechanisms for PTPIP51 and consequently, significantly alters the assembly of the PTPIP51 associated protein complexes. The treatment of human keratinocytes (HaCaT cells) with LDC-3 induces an altered protein–protein interaction profile of the endogenous interactome of PTPIP51. In addition, LDC-3 stabilizes PTPIP51 within a mitogen activated protein kinase (MAPK) complex composed of Raf-1 and the scaffold protein 14-3-3, independent of the phosphorylation status of PTPIP51. Of note, under LDC-3 treatment the regulatory function of the PTP1B on PTPIP51 fails to impact the PTPIP51 interaction characteristics, as reported for the HaCaT cell line. In summary, LDC-3 gives the unique opportunity to directly modulate PTPIP51 in malignant cells, thus targeting potential dysregulated signal transduction pathways such as the MAPK cascade. The provided data give critical insights in the therapeutic potential of PTPIP51 protein interactions and thus are basic for possible targeted therapy regimens. PMID:28754031

Using porphyrin-amino acid pairs to model the electrochemistry of heme proteins: experimental and theoretical investigations.

PubMed

Samajdar, Rudra N; Manogaran, Dhivya; Yashonath, S; Bhattacharyya, Aninda J

2018-04-18

Quasi reversibility in electrochemical cycling between different oxidation states of iron is an often seen characteristic of iron containing heme proteins that bind dioxygen. Surprisingly, the system becomes fully reversible in the bare iron-porphyrin complex: hemin. This leads to the speculation that the polypeptide bulk (globin) around the iron-porphyrin active site in these heme proteins is probably responsible for the electrochemical quasi reversibility. To understand the effect of such polypeptide bulk on iron-porphyrin, we study the interaction of specific amino acids with the hemin center in solution. We choose three representative amino acids-histidine (a well-known iron coordinator in bio-inorganic systems), tryptophan (a well-known fluoroprobe for proteins), and cysteine (a redox-active organic molecule). The interactions of these amino acids with hemin are studied using electrochemistry, spectroscopy, and density functional theory. The results indicate that among these three, the interaction of histidine with the iron center is strongest. Further, histidine maintains the electrochemical reversibility of iron. On the other hand, tryptophan and cysteine interact weakly with the iron center but disturb the electrochemical reversibility by contributing their own redox active processes to the system. Put together, this study attempts to understand the molecular interactions that can control electrochemical reversibility in heme proteins. The results obtained here from the three representative amino acids can be scaled up to build a heme-amino acid interaction database that may predict the electrochemical properties of any protein with a defined polypeptide sequence.

Molecular origins of osmotic second virial coefficients of proteins.

PubMed Central

Neal, B L; Asthagiri, D; Lenhoff, A M

1998-01-01

The thermodynamic properties of protein solutions are determined by the molecular interactions involving both solvent and solute molecules. A quantitative understanding of the relationship would facilitate more systematic procedures for manipulating the properties in a process environment. In this work the molecular basis for the osmotic second virial coefficient, B22, is studied; osmotic effects are critical in membrane transport, and the value of B22 has also been shown to correlate with protein crystallization behavior. The calculations here account for steric, electrostatic, and short-range interactions, with the structural and functional anisotropy of the protein molecules explicitly accounted for. The orientational dependence of the protein interactions is seen to have a pronounced effect on the calculations; in particular, the relatively few protein-protein configurations in which the apposing surfaces display geometric complementarity contribute disproportionately strongly to B22. The importance of electrostatic interactions is also amplified in these high-complementarity configurations. The significance of molecular recognition in determining B22 can explain the correlation with crystallization behavior, and it suggests that alteration of local molecular geometry can help in manipulating protein solution behavior. The results also have implications for the role of protein interactions in biological self-organization. PMID:9788942

Protein sequences insight into heavy metal tolerance in Cronobacter sakazakii BAA-894 encoded by plasmid pESA3.

PubMed

Chaturvedi, Navaneet; Kajsik, Michal; Forsythe, Stephen; Pandey, Paras Nath

2015-12-01

The recently annotated genome of the bacterium Cronobacter sakazakii BAA-894 suggests that the organism has the ability to bind heavy metals. This study demonstrates heavy metal tolerance in C. sakazakii, in which proteins with the heavy metal interaction were recognized by computational and experimental study. As the result, approximately one-fourth of proteins encoded on the plasmid pESA3 are proposed to have potential interaction with heavy metals. Interaction between heavy metals and predicted proteins was further corroborated using protein crystal structures from protein data bank database and comparison of metal-binding ligands. In addition, a phylogenetic study was undertaken for the toxic heavy metals, arsenic, cadmium, lead and mercury, which generated relatedness clustering for lead, cadmium and arsenic. Laboratory studies confirmed the organism's tolerance to tellurite, copper and silver. These experimental and computational study data extend our understanding of the genes encoding for proteins of this important neonatal pathogen and provide further insights into the genotypes associated with features that can contribute to its persistence in the environment. The information will be of value for future environmental protection from heavy toxic metals.

Identification of potential novel interaction partners of the sodium-activated potassium channels Slick and Slack in mouse brain.

PubMed

Rizzi, Sandra; Schwarzer, Christoph; Kremser, Leopold; Lindner, Herbert H; Knaus, Hans-Günther

2015-12-01

The sodium-activated potassium channels Slick (Slo2.1, KCNT2) and Slack (Slo2.2, KCNT1) are paralogous channels of the Slo family of high-conductance potassium channels. Slick and Slack channels are widely distributed in the mammalian CNS and they play a role in slow afterhyperpolarization, generation of depolarizing afterpotentials and in setting and stabilizing the resting potential. In the present study we used a combined approach of (co)-immunoprecipitation studies, Western blot analysis, double immunofluorescence and mass spectrometric sequencing in order to investigate protein-protein interactions of the Slick and Slack channels. The data strongly suggest that Slick and Slack channels co-assemble into identical cellular complexes. Double immunofluorescence experiments revealed that Slick and Slack channels co-localize in distinct mouse brain regions. Moreover, we identified the small cytoplasmic protein beta-synuclein and the transmembrane protein 263 (TMEM 263) as novel interaction partners of both, native Slick and Slack channels. In addition, the inactive dipeptidyl-peptidase (DPP 10) and the synapse associated protein 102 (SAP 102) were identified as constituents of the native Slick and Slack channel complexes in the mouse brain. This study presents new insights into protein-protein interactions of native Slick and Slack channels in the mouse brain.

Cytochrome c conjugated to ZnO-MAA nanoparticles: the study of interaction and influence on protein structure.

PubMed

Simšíková, Michaela; Antalík, Marián; Kaňuchová, Mária; Skvarla, Jiří

2013-08-01

Nanoparticle-protein conjugates have potential for numerous applications due to the combination of the properties of both components. In this paper we studied the conjugation of horse heart cytochrome c with ZnO nanoparticles modified by mercaptoacetic acid (MAA) which may be a material with great potential in anticancer therapy as a consequence of synergic effect of both components. Cyt c adsorption to the ZnO-MAA NPs surface was studied by UV-vis spectroscopy and by a dynamic light scattering in various pH. The results indicate that the optimal pH for the association of protein with modified nanoparticles is in range 5.8-8.5 where 90-96% of cytochrome c was assembled on ZnO-MAA nanoparticles. The interaction of proteins with nanoparticles often results in denaturation or loss of protein function. Our observations from UV-vis spectroscopy and circular dichroism performed preserved protein structure after the interaction with modified nanoparticles. Copyright © 2013 Elsevier B.V. All rights reserved.

Bacterial adhesion to protein-coated surfaces: An AFM and QCM-D study

NASA Astrophysics Data System (ADS)

Strauss, Joshua; Liu, Yatao; Camesano, Terri A.

2009-09-01

Bacterial adhesion to biomaterials, mineral surfaces, or other industrial surfaces is strongly controlled by the way bacteria interact with protein layers or organic matter and other biomolecules that coat the materials. Despite this knowledge, many studies of bacterial adhesion are performed under clean conditions, instead of in the presence of proteins or organic molecules. We chose fetal bovine serum (FBS) as a model protein, and prepared FBS films on quartz crystals. The thickness of the FBS layer was characterized using atomic force microscopy (AFM) imaging under liquid and quartz crystal microbalance with dissipation (QCM-D). Next, we characterized how the model biomaterial surface would interact with the nocosomial pathogen Staphylococcus epidermidis. An AFM probe was coated with S. epidermidis cells and used to probe a gold slide that had been coated with FBS or another protein, fibronectin (FN). These experiments show that AFM and QCM-D can be used in complementary ways to study the complex interactions between bacteria, proteins, and surfaces.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

PubMed

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.

PubMed

Frenkel-Morgenstern, Milana; Gorohovski, Alessandro; Tagore, Somnath; Sekar, Vaishnovi; Vazquez, Miguel; Valencia, Alfonso

2017-07-07

Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein-protein interactions (ChiPPI) that uses the domain-domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF β), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Structural insight into GRIP1-PDZ6 in Alzheimer's disease: study from protein expression data to molecular dynamics simulations.

PubMed

Chatterjee, Paulami; Roy, Debjani

2017-08-01

Protein-protein interaction domain, PDZ, plays a critical role in efficient synaptic transmission in brain. Dysfunction of synaptic transmission is thought to be the underlying basis of many neuropsychiatric and neurodegenerative disorders including Alzheimer's disease (AD). In this study, Glutamate Receptor Interacting Protein1 (GRIP1) was identified as one of the most important differentially expressed, topologically significant proteins in the protein-protein interaction network. To date, very few studies have analyzed the detailed structural basis of PDZ-mediated protein interaction of GRIP1. In order to gain better understanding of structural and dynamic basis of these interactions, we employed molecular dynamics (MD) simulations of GRIP1-PDZ6 dimer bound with Liprin-alpha and GRIP1-PDZ6 dimer alone each with 100 ns simulations. The analyses of MD simulations of Liprin-alpha bound GRIP1-PDZ6 dimer show considerable conformational differences than that of peptide-free dimer in terms of SASA, hydrogen bonding patterns, and along principal component 1 (PC1). Our study also furnishes insight into the structural attunement of the PDZ6 domains of Liprin-alpha bound GRIP1 that is attributed by significant shift of the Liprin-alpha recognition helix in the simulated peptide-bound dimer compared to the crystal structure and simulated peptide-free dimer. It is evident that PDZ6 domains of peptide-bound dimer show differential movements along PC1 than that of peptide-free dimers. Thus, Liprin-alpha also serves an important role in conferring conformational changes along the dimeric interface of the peptide-bound dimer. Results reported here provide information that may lead to novel therapeutic approaches in AD.

Expression and Association of the Yersinia pestis Translocon Proteins, YopB and YopD, Are Facilitated by Nanolipoprotein Particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Matthew A.; Cappuccio, Jenny A.; Blanchette, Craig D.

Yersinia pestis enters host cells and evades host defenses, in part, through interactions between Yersinia pestis proteins and host membranes. One such interaction is through the type III secretion system, which uses a highly conserved and ordered complex for Yersinia pestis outer membrane effector protein translocation called the injectisome. The portion of the injectisome that interacts directly with host cell membranes is referred to as the translocon. The translocon is believed to form a pore allowing effector molecules to enter host cells. To facilitate mechanistic studies of the translocon, we have developed a cell-free approach for expressing translocon pore proteinsmore » as a complex supported in a bilayer membrane mimetic nano-scaffold known as a nanolipoprotein particle (NLP) Initial results show cell-free expression of Yersinia pestis outer membrane proteins YopB and YopD was enhanced in the presence of liposomes. However, these complexes tended to aggregate and precipitate. With the addition of co-expressed (NLP) forming components, the YopB and/or YopD complex was rendered soluble, increasing the yield of protein for biophysical studies. Biophysical methods such as Atomic Force Microscopy and Fluorescence Correlation Spectroscopy were used to confirm that the soluble YopB/D complex was associated with NLPs. An interaction between the YopB/D complex and NLP was validated by immunoprecipitation. The YopB/D translocon complex embedded in a NLP provides a platform for protein interaction studies between pathogen and host proteins. Ultimately, these studies will help elucidate the poorly understood mechanism which enables this pathogen to inject effector proteins into host cells, thus evading host defenses.« less

Expression and Association of the Yersinia pestis Translocon Proteins, YopB and YopD, Are Facilitated by Nanolipoprotein Particles

DOE PAGES

Coleman, Matthew A.; Cappuccio, Jenny A.; Blanchette, Craig D.; ...

2016-03-25

Yersinia pestis enters host cells and evades host defenses, in part, through interactions between Yersinia pestis proteins and host membranes. One such interaction is through the type III secretion system, which uses a highly conserved and ordered complex for Yersinia pestis outer membrane effector protein translocation called the injectisome. The portion of the injectisome that interacts directly with host cell membranes is referred to as the translocon. The translocon is believed to form a pore allowing effector molecules to enter host cells. To facilitate mechanistic studies of the translocon, we have developed a cell-free approach for expressing translocon pore proteinsmore » as a complex supported in a bilayer membrane mimetic nano-scaffold known as a nanolipoprotein particle (NLP) Initial results show cell-free expression of Yersinia pestis outer membrane proteins YopB and YopD was enhanced in the presence of liposomes. However, these complexes tended to aggregate and precipitate. With the addition of co-expressed (NLP) forming components, the YopB and/or YopD complex was rendered soluble, increasing the yield of protein for biophysical studies. Biophysical methods such as Atomic Force Microscopy and Fluorescence Correlation Spectroscopy were used to confirm that the soluble YopB/D complex was associated with NLPs. An interaction between the YopB/D complex and NLP was validated by immunoprecipitation. The YopB/D translocon complex embedded in a NLP provides a platform for protein interaction studies between pathogen and host proteins. Ultimately, these studies will help elucidate the poorly understood mechanism which enables this pathogen to inject effector proteins into host cells, thus evading host defenses.« less

Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

PubMed Central

Bhattacharyya, Sanchari; Bershtein, Shimon; Yan, Jin; Argun, Tijda; Gilson, Amy I; Trauger, Sunia A; Shakhnovich, Eugene I

2016-01-01

Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization – molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between ‘E. coli’s self’ and ‘foreign’ proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness. DOI: http://dx.doi.org/10.7554/eLife.20309.001 PMID:27938662

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

PubMed Central

Hu, Jianfei; Neiswinger, Johnathan; Zhang, Jin; Zhu, Heng; Qian, Jiang

2015-01-01

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process. PMID:26393507

Calcium-dependent interaction of monomeric S100P protein with serum albumin.

PubMed

Kazakov, Alexei S; Shevelyova, Marina P; Ismailov, Ramis G; Permyakova, Maria E; Litus, Ekaterina A; Permyakov, Eugene A; Permyakov, Sergei E

2018-03-01

S100 proteins are multifunctional (intra/extra)cellular mostly dimeric calcium-binding proteins engaged into numerous diseases. We have found that monomeric recombinant human S100P protein interacts with intact human serum albumin (HSA) in excess of calcium ions with equilibrium dissociation constant of 25-50nM, as evidenced by surface plasmon resonance spectroscopy and fluorescent titration by HSA of S100P labelled by fluorescein isothiocyanate. Calcium removal or S100P dimerization abolish the S100P-HSA interaction. The interaction is selective, since S100P does not bind bovine serum albumin and monomeric human S100B lacks interaction with HSA. In vitro glycation of HSA disables its binding to S100P. The revealed selective and highly specific conformation-dependent interaction between S100P and HSA shows that functional properties of monomeric and dimeric forms of S100 proteins are different, and raises concerns on validity of cell-based assays and animal models used for studies of (patho)physiological roles of extracellular S100 proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Adsorption Kinetics, Conformation, and Mobility of the Growth Hormone and Lysozyme on Solid Surfaces, Studied with TIRF

PubMed

Buijs; Hlady

1997-06-01

Interactions of recombinant human growth hormone and lysozyme with solid surfaces are studied using total internal reflection fluorescence (TIRF) and monitoring the protein's intrinsic tryptophan fluorescence. The intensity, spectra, quenching, and polarization of the fluorescence emitted by the adsorbed proteins are monitored and related to adsorption kinetics, protein conformation, and fluorophore rotational mobility. To study the influence of electrostatic and hydrophobic interactions on the adsorption process, three sorbent surfaces are used which differ in charge and hydrophobicity. The chemical surface groups are silanol, methyl, and quaternary amine. Results indicate that adsorption of hGH is dominated by hydrophobic interactions. Lysozyme adsoption is strongly affected by the ionic strength. This effect is probably caused by an ionic strength dependent conformational state in solution which, in turn, influences the affinity for adsorption. Both proteins are more strongly bound to hydrophobic surfaces and this strong interaction is accompanied by a less compact conformation. Furthermore, it was seen that regardless of the characteristics of the sorbent surface, the rotational mobility of both proteins' tryptophans is largely reduced upon adsorption.

A Conserved Deubiquitinating Enzyme Uses Intrinsically Disordered Regions to Scaffold Multiple Protein Interaction Sites*

PubMed Central

Reed, Benjamin J.; Locke, Melissa N.; Gardner, Richard G.

2015-01-01

In the canonical view of protein function, it is generally accepted that the three-dimensional structure of a protein determines its function. However, the past decade has seen a dramatic growth in the identification of proteins with extensive intrinsically disordered regions (IDRs), which are conformationally plastic and do not appear to adopt single three-dimensional structures. One current paradigm for IDR function is that disorder enables IDRs to adopt multiple conformations, expanding the ability of a protein to interact with a wide variety of disparate proteins. The capacity for many interactions is an important feature of proteins that occupy the hubs of protein networks, in particular protein-modifying enzymes that usually have a broad spectrum of substrates. One such protein modification is ubiquitination, where ubiquitin is attached to proteins through ubiquitin ligases (E3s) and removed through deubiquitinating enzymes. Numerous proteomic studies have found that thousands of proteins are dynamically regulated by cycles of ubiquitination and deubiquitination. Thus, how these enzymes target their wide array of substrates is of considerable importance for understanding the function of the cell's diverse ubiquitination networks. Here, we characterize a yeast deubiquitinating enzyme, Ubp10, that possesses IDRs flanking its catalytic protease domain. We show that Ubp10 possesses multiple, distinct binding modules within its IDRs that are necessary and sufficient for directing protein interactions important for Ubp10's known roles in gene silencing and ribosome biogenesis. The human homolog of Ubp10, USP36, also has IDRs flanking its catalytic domain, and these IDRs similarly contain binding modules important for protein interactions. This work highlights the significant protein interaction scaffolding abilities of IDRs in the regulation of dynamic protein ubiquitination. PMID:26149687

An Evolutionarily Conserved Innate Immunity Protein Interaction Network*

PubMed Central

De Arras, Lesly; Seng, Amara; Lackford, Brad; Keikhaee, Mohammad R.; Bowerman, Bruce; Freedman, Jonathan H.; Schwartz, David A.; Alper, Scott

2013-01-01

The innate immune response plays a critical role in fighting infection; however, innate immunity also can affect the pathogenesis of a variety of diseases, including sepsis, asthma, cancer, and atherosclerosis. To identify novel regulators of innate immunity, we performed comparative genomics RNA interference screens in the nematode Caenorhabditis elegans and mouse macrophages. These screens have uncovered many candidate regulators of the response to lipopolysaccharide (LPS), several of which interact physically in multiple species to form an innate immunity protein interaction network. This protein interaction network contains several proteins in the canonical LPS-responsive TLR4 pathway as well as many novel interacting proteins. Using RNAi and overexpression studies, we show that almost every gene in this network can modulate the innate immune response in mouse cell lines. We validate the importance of this network in innate immunity regulation in vivo using available mutants in C. elegans and mice. PMID:23209288

Defining the human deubiquitinating enzyme interaction landscape.

PubMed

Sowa, Mathew E; Bennett, Eric J; Gygi, Steven P; Harper, J Wade

2009-07-23

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

Defining the Human Deubiquitinating Enzyme Interaction Landscape

PubMed Central

Sowa, Mathew E.; Bennett, Eric J.; Gygi, Steven P.; Harper, J. Wade

2009-01-01

Summary Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform, called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel non-reciprocal proteomic datasets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, sub-cellular localization and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway. PMID:19615732

Molecular dynamics simulations and statistical coupling analysis reveal functional coevolution network of oncogenic mutations in the CDKN2A-CDK6 complex.

PubMed

Wang, Jingwen; Zhao, Yuqi; Wang, Yanjie; Huang, Jingfei

2013-01-16

Coevolution between proteins is crucial for understanding protein-protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural-functional integrity. In this study, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on the CDK6-CDKN2A protein complex to evaluate coevolution between proteins. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37 interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in the CDK6-CDKN2A complex can be helpful for designing protein engineering experiments. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Strong Ligand-Protein Interactions Derived from Diffuse Ligand Interactions with Loose Binding Sites.

PubMed

Marsh, Lorraine

2015-01-01

Many systems in biology rely on binding of ligands to target proteins in a single high-affinity conformation with a favorable ΔG. Alternatively, interactions of ligands with protein regions that allow diffuse binding, distributed over multiple sites and conformations, can exhibit favorable ΔG because of their higher entropy. Diffuse binding may be biologically important for multidrug transporters and carrier proteins. A fine-grained computational method for numerical integration of total binding ΔG arising from diffuse regional interaction of a ligand in multiple conformations using a Markov Chain Monte Carlo (MCMC) approach is presented. This method yields a metric that quantifies the influence on overall ligand affinity of ligand binding to multiple, distinct sites within a protein binding region. This metric is essentially a measure of dispersion in equilibrium ligand binding and depends on both the number of potential sites of interaction and the distribution of their individual predicted affinities. Analysis of test cases indicates that, for some ligand/protein pairs involving transporters and carrier proteins, diffuse binding contributes greatly to total affinity, whereas in other cases the influence is modest. This approach may be useful for studying situations where "nonspecific" interactions contribute to biological function.

The modular architecture of protein-protein binding interfaces.

PubMed

Reichmann, D; Rahat, O; Albeck, S; Meged, R; Dym, O; Schreiber, G

2005-01-04

Protein-protein interactions are essential for life. Yet, our understanding of the general principles governing binding is not complete. In the present study, we show that the interface between proteins is built in a modular fashion; each module is comprised of a number of closely interacting residues, with few interactions between the modules. The boundaries between modules are defined by clustering the contact map of the interface. We show that mutations in one module do not affect residues located in a neighboring module. As a result, the structural and energetic consequences of the deletion of entire modules are surprisingly small. To the contrary, within their module, mutations cause complex energetic and structural consequences. Experimentally, this phenomenon is shown on the interaction between TEM1-beta-lactamase and beta-lactamase inhibitor protein (BLIP) by using multiple-mutant analysis and x-ray crystallography. Replacing an entire module of five interface residues with Ala created a large cavity in the interface, with no effect on the detailed structure of the remaining interface. The modular architecture of binding sites, which resembles human engineering design, greatly simplifies the design of new protein interactions and provides a feasible view of how these interactions evolved.

Aggregation of polyglutamine-expanded ataxin-3 sequesters its specific interacting partners into inclusions: Implication in a loss-of-function pathology

PubMed Central

Yang, Hui; Li, Jing-Jing; Liu, Shuai; Zhao, Jian; Jiang, Ya-Jun; Song, Ai-Xin; Hu, Hong-Yu

2014-01-01

Expansion of polyglutamine (polyQ) tract may cause protein misfolding and aggregation that lead to cytotoxicity and neurodegeneration, but the underlying mechanism remains to be elucidated. We applied ataxin-3 (Atx3), a polyQ tract-containing protein, as a model to study sequestration of normal cellular proteins. We found that the aggregates formed by polyQ-expanded Atx3 sequester its interacting partners, such as P97/VCP and ubiquitin conjugates, into the protein inclusions through specific interactions both in vitro and in cells. Moreover, this specific sequestration impairs the normal cellular function of P97 in down-regulating neddylation. However, expansion of polyQ tract in Atx3 does not alter the conformation of its surrounding regions and the interaction affinities with the interacting partners, although it indeed facilitates misfolding and aggregation of the Atx3 protein. Thus, we propose a loss-of-function pathology for polyQ diseases that sequestration of the cellular essential proteins via specific interactions into inclusions by the polyQ aggregates causes dysfunction of the corresponding proteins, and consequently leads to neurodegeneration. PMID:25231079

Protein Condensation

NASA Astrophysics Data System (ADS)

Gunton, James D.; Shiryayev, Andrey; Pagan, Daniel L.

2007-09-01

Preface; 1. Introduction; 2. Globular protein structure; 3. Experimental methods; 4. Thermodynamics and statistical mechanics; 5. Protein-protein interactions; 6. Theoretical studies of equilibrium; 7. Nucleation theory; 8. Experimental studies of nucleation; 9. Lysozyme; 10. Some other globular proteins; 11. Membrane proteins; 12. Crystallins and cataracts; 13. Sickle hemoglobin and sickle cell anemia; 14, Alzheimer's disease; Index.

Protein Condensation

NASA Astrophysics Data System (ADS)

Gunton, James D.; Shiryayev, Andrey; Pagan, Daniel L.

2014-07-01

Preface; 1. Introduction; 2. Globular protein structure; 3. Experimental methods; 4. Thermodynamics and statistical mechanics; 5. Protein-protein interactions; 6. Theoretical studies of equilibrium; 7. Nucleation theory; 8. Experimental studies of nucleation; 9. Lysozyme; 10. Some other globular proteins; 11. Membrane proteins; 12. Crystallins and cataracts; 13. Sickle hemoglobin and sickle cell anemia; 14, Alzheimer's disease; Index.

Atomic force microscopy and force spectroscopy on the assessment of protein folding and functionality.

PubMed

Carvalho, Filomena A; Martins, Ivo C; Santos, Nuno C

2013-03-01

Atomic force microscopy (AFM) applied to biological systems can, besides generating high-quality and well-resolved images, be employed to study protein folding via AFM-based force spectroscopy. This approach allowed remarkable advances in the measurement of inter- and intramolecular interaction forces with piconewton resolution. The detection of specific interaction forces between molecules based on the AFM sensitivity and the manipulation of individual molecules greatly advanced the understanding of intra-protein and protein-ligand interactions. Apart from the academic interest in the resolution of basic scientific questions, this technique has also key importance on the clarification of several biological questions of immediate biomedical relevance. Force spectroscopy is an especially appropriate technique for "mechanical proteins" that can provide crucial information on single protein molecules and/or domains. Importantly, it also has the potential of combining in a single experiment spatial and kinetic measurements. Here, the main principles of this methodology are described, after which the ability to measure interactions at the single-molecule level is discussed, in the context of relevant protein-folding examples. We intend to demonstrate the potential of AFM-based force spectroscopy in the study of protein folding, especially since this technique is able to circumvent some of the difficulties typically encountered in classical thermal/chemical denaturation studies. Copyright © 2012 Elsevier Inc. All rights reserved.

[Drosophila melanogaster as a model for studying the function of animal viral proteins].

PubMed

Omelianchuk, L V; Iudina, O S

2011-07-01

Studies in which Drosophila melanogaster individuals carrying transgenes of animal viruses were used to analyze the action of animal viral proteins on the cell are reviewed. The data presented suggest that host specificity of viruses is determined by their proteins responsible for the penetration of the virus into the cell, while viral proteins responsible for interactions with the host cell are much less host-specific. Due to this, the model of Drosophila with its developed system of searching for genetic interactions can be used to find intracellular targets for the action of viral proteins of the second group.

Genome-wide Mapping of Cellular Protein–RNA Interactions Enabled by Chemical Crosslinking

PubMed Central

Li, Xiaoyu; Song, Jinghui; Yi, Chengqi

2014-01-01

RNA–protein interactions influence many biological processes. Identifying the binding sites of RNA-binding proteins (RBPs) remains one of the most fundamental and important challenges to the studies of such interactions. Capturing RNA and RBPs via chemical crosslinking allows stringent purification procedures that significantly remove the non-specific RNA and protein interactions. Two major types of chemical crosslinking strategies have been developed to date, i.e., UV-enabled crosslinking and enzymatic mechanism-based covalent capture. In this review, we compare such strategies and their current applications, with an emphasis on the technologies themselves rather than the biology that has been revealed. We hope such methods could benefit broader audience and also urge for the development of new methods to study RNA−RBP interactions. PMID:24747191

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

PubMed

Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

Deciphering RNA-Recognition Patterns of Intrinsically Disordered Proteins.

PubMed

Srivastava, Ambuj; Ahmad, Shandar; Gromiha, M Michael

2018-05-29

Intrinsically disordered regions (IDRs) and protein (IDPs) are highly flexible owing to their lack of well-defined structures. A subset of such proteins interacts with various substrates; including RNA; frequently adopting regular structures in the final complex. In this work; we have analysed a dataset of protein⁻RNA complexes undergoing disorder-to-order transition (DOT) upon binding. We found that DOT regions are generally small in size (less than 3 residues) for RNA binding proteins. Like structured proteins; positively charged residues are found to interact with RNA molecules; indicating the dominance of electrostatic and cation-π interactions. However, a comparison of binding frequency shows that interface hydrophobic and aromatic residues have more interactions in only DOT regions than in a protein. Further; DOT regions have significantly higher exposure to water than their structured counterparts. Interactions of DOT regions with RNA increase the sheet formation with minor changes in helix forming residues. We have computed the interaction energy for amino acids⁻nucleotide pairs; which showed the preference of His⁻G; Asn⁻U and Ser⁻U at for the interface of DOT regions. This study provides insights to understand protein⁻RNA interactions and the results could also be used for developing a tool for identifying DOT regions in RNA binding proteins.

Liquid-Liquid Phase Separation in a Dual Variable Domain Immunoglobulin Protein Solution: Effect of Formulation Factors and Protein-Protein Interactions.

PubMed

Raut, Ashlesha S; Kalonia, Devendra S

2015-09-08

Dual variable domain immunoglobulin proteins (DVD-Ig proteins) are large molecules (MW ∼ 200 kDa) with increased asymmetry because of their extended Y-like shape, which results in increased formulation challenges. Liquid-liquid phase separation (LLPS) of protein solutions into protein-rich and protein-poor phases reduces solution stability at intermediate concentrations and lower temperatures, and is a serious concern in formulation development as therapeutic proteins are generally stored at refrigerated conditions. In the current work, LLPS was studied for a DVD-Ig protein molecule as a function of solution conditions by measuring solution opalescence. LLPS of the protein was confirmed by equilibrium studies and by visually observing under microscope. The protein does not undergo any structural change after phase separation. Protein-protein interactions were measured by light scattering (kD) and Tcloud (temperature that marks the onset of phase separation). There is a good agreement between kD measured in dilute solution with Tcloud measured in the critical concentration range. Results indicate that the increased complexity of the molecule (with respect to size, shape, and charge distribution on the molecule) increases contribution of specific and nonspecific interactions in solution, which are affected by formulation factors, resulting in LLPS for DVD-Ig protein.

Interaction between holo transferrin and HSA-PPIX complex in the presence of lomefloxacin: An evaluation of PPIX aggregation in protein-protein interactions

NASA Astrophysics Data System (ADS)

Sattar, Zohreh; Iranfar, Hediye; Asoodeh, Ahmad; Saberi, Mohammad Reza; Mazhari, Mahboobeh; Chamani, Jamshidkhan

2012-11-01

Human serum albumin (HSA) and holo transferrin (TF) are two serum carrier proteins that are able to interact with each other, thereby altering their binding behavior toward their ligands. During the course of this study, the interaction between HSA-PPIX and TF, in the presence and absence of lomefloxacin (LMF), was for the first time investigated using different spectroscopic and molecular modeling techniques. Fluorescence spectroscopy experiments were performed in order to study conformational changes of proteins. The RLS technique was utilized to investigate the effect of LMF on J-aggregation of PPIX, which is the first report of its kind. Our findings present clear-cut evidence for the alteration of interactions between HSA and TF in the presence of PPIX and changes in drug-binding to HSA and HSA-PPIX complex upon interaction with TF. Moreover, molecular modeling studies suggested that the binding site for LMF became switched in the presence of PPIX, and that LMF bound to the site IIA of HSA. The obtained results should give new insight into research in this field and may cast some light on the dynamics of drugs in biological systems.

Hydrogen Bond Networks and Hydrophobic Effects in the Amyloid β30-35 Chain in Water: A Molecular Dynamics Study.

PubMed

Jong, KwangHyok; Grisanti, Luca; Hassanali, Ali

2017-07-24

We have studied the conformational landscape of the C-terminal fragment of the amyloid protein Aβ 30-35 in water using well-tempered metadynamics simulations and found that it resembles an intrinsically disordered protein. The conformational fluctuations of the protein are facilitated by a collective reorganization of both protein and water hydrogen bond networks, combined with electrostatic interactions between termini as well as hydrophobic interactions of the side chains. The stabilization of hydrophobic interactions in one of the conformers involves a collective collapse of the side chains along with a squeeze-out of water sandwiched between them. The charged N- and C-termini play a critical role in stabilizing different types of protein conformations, including those involving contact-ion salt bridges as well as solvent-mediated interactions of the termini and the amide backbone. We have examined this by probing the distribution of directed water wires forming the hydrogen bond network enveloping the polypeptide. Water wires and their fluctuations form an integral part of structural signature of the protein conformation.

In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks.

PubMed

Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques; Ferreira, Rafaela Salgado; Silva, Artur; Gromiha, Michael; Ghosh, Preetam; Barh, Debmalya; Azevedo, Vasco; Röttger, Richard

2016-11-04

Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.

Characterizing carbohydrate-protein interactions by NMR

PubMed Central

Bewley, Carole A.; Shahzad-ul-Hussan, Syed

2013-01-01

Interactions between proteins and soluble carbohydrates and/or surface displayed glycans are central to countless recognition, attachment and signaling events in biology. The physical chemical features associated with these binding events vary considerably, depending on the biological system of interest. For example, carbohydrate-protein interactions can be stoichiometric or multivalent, the protein receptors can be monomeric or oligomeric, and the specificity of recognition can be highly stringent or rather promiscuous. Equilibrium dissociation constants for carbohydrate binding are known to vary from micromolar to millimolar, with weak interactions being far more prevalent; and individual carbohydrate binding sites can be truly symmetrical or merely homologous, and hence, the affinities of individual sites within a single protein can vary, as can the order of binding. Several factors, including the weak affinities with which glycans bind their protein receptors, the dynamic nature of the glycans themselves, and the non-equivalent interactions among oligomeric carbohydrate receptors, have made NMR an especially powerful tool for studying and defining carbohydrate-protein interactions. Here we describe those NMR approaches that have proven to be the most robust in characterizing these systems, and explain what type of information can (or cannot) be obtained from each. Our goal is to provide to the reader the information necessary for selecting the correct experiment or sets of experiments to characterize their carbohydrate-protein interaction of interest. PMID:23784792

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

PubMed

Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Bimolecular interaction of argpyrimidine (a Maillard reaction product) in in vitro non-enzymatic protein glycation model and its potential role as an antiglycating agent.

PubMed

Bhattacherjee, Abhishek; Dhara, Kaliprasanna; Chakraborti, Abhay Sankar

2017-09-01

Non- enzymatic glycation, also known as Maillard reaction, is one of the most important and investigated reactions in biochemistry. Maillard reaction products (MRPs) like protein-derived advanced glycation end products (AGEs) are often referred to cause pathophysiological complications in human systems. On contrary, several MRPs are exogenously used as antioxidant, antimicrobial and flavouring agents. In the preset study, we have shown that argpyrimidine, a well-established AGE, interacts with bovine serum albumin (BSA) and glucose individually in standard BSA-glucose model system and successfully inhibits glycation of the protein. Bimolecular interaction of argpyrimidine with glucose or BSA has been studied independently. Chromatographic purification, different spectroscopic studies and molecular modeling have been used to evaluate the nature and pattern of interactions. Binding of argpyrimidine with BSA prevents incorporation of glucose inside the native protein. Argpyrimidine can also directly entrap glucose. Both these interactions may be associated with the antiglycation potential of argpyrimidine, indicating a beneficial function of an AGE. Copyright © 2017 Elsevier B.V. All rights reserved.

Time-course, negative-stain electron microscopy-based analysis for investigating protein-protein interactions at the single-molecule level.

PubMed

Nogal, Bartek; Bowman, Charles A; Ward, Andrew B

2017-11-24

Several biophysical approaches are available to study protein-protein interactions. Most approaches are conducted in bulk solution, and are therefore limited to an average measurement of the ensemble of molecular interactions. Here, we show how single-particle EM can enrich our understanding of protein-protein interactions at the single-molecule level and potentially capture states that are unobservable with ensemble methods because they are below the limit of detection or not conducted on an appropriate time scale. Using the HIV-1 envelope glycoprotein (Env) and its interaction with receptor CD4-binding site neutralizing antibodies as a model system, we both corroborate ensemble kinetics-derived parameters and demonstrate how time-course EM can further dissect stoichiometric states of complexes that are not readily observable with other methods. Visualization of the kinetics and stoichiometry of Env-antibody complexes demonstrated the applicability of our approach to qualitatively and semi-quantitatively differentiate two highly similar neutralizing antibodies. Furthermore, implementation of machine-learning techniques for sorting class averages of these complexes into discrete subclasses of particles helped reduce human bias. Our data provide proof of concept that single-particle EM can be used to generate a "visual" kinetic profile that should be amenable to studying many other protein-protein interactions, is relatively simple and complementary to well-established biophysical approaches. Moreover, our method provides critical insights into broadly neutralizing antibody recognition of Env, which may inform vaccine immunogen design and immunotherapeutic development. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors

PubMed Central

Hsing, Michael; Byler, Kendall; Cherkasov, Artem

2009-01-01

Hub proteins (those engaged in most physical interactions in a protein interaction network (PIN) have recently gained much research interest due to their essential role in mediating cellular processes and their potential therapeutic value. It is straightforward to identify hubs if the underlying PIN is experimentally determined; however, theoretical hub prediction remains a very challenging task, as physicochemical properties that differentiate hubs from less connected proteins remain mostly uncharacterized. To adequately distinguish hubs from non-hub proteins we have utilized over 1300 protein descriptors, some of which represent QSAR (quantitative structure-activity relationship) parameters, and some reflect sequence-derived characteristics of proteins including domain composition and functional annotations. Those protein descriptors, together with available protein interaction data have been processed by a machine learning method (boosting trees) and resulted in the development of hub classifiers that are capable of predicting highly interacting proteins for four model organisms: Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens. More importantly, through the analyses of the most relevant protein descriptors, we are able to demonstrate that hub proteins not only share certain common physicochemical and structural characteristics that make them different from non-hub counterparts, but they also exhibit species-specific characteristics that should be taken into account when analyzing different PINs. The developed prediction models can be used for determining highly interacting proteins in the four studied species to assist future proteomics experiments and PIN analyses. Availability The source code and executable program of the hub classifier are available for download at: http://www.cnbi2.ca/hub-analysis/ PMID:20198194

Structures of the human Pals1 PDZ domain with and without ligand suggest gated access of Crb to the PDZ peptide-binding groove

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanova, Marina E.; Fletcher, Georgina C.; O’Reilly, Nicola

2015-03-01

This study characterizes the interaction between the carboxy-terminal (ERLI) motif of the essential polarity protein Crb and the Pals1/Stardust PDZ-domain protein. Structures of human Pals1 PDZ with and without a Crb peptide are described, explaining the highly conserved nature of the ERLI motif and revealing a sterically blocked peptide-binding groove in the absence of ligand. Many components of epithelial polarity protein complexes possess PDZ domains that are required for protein interaction and recruitment to the apical plasma membrane. Apical localization of the Crumbs (Crb) transmembrane protein requires a PDZ-mediated interaction with Pals1 (protein-associated with Lin7, Stardust, MPP5), a member ofmore » the p55 family of membrane-associated guanylate kinases (MAGUKs). This study describes the molecular interaction between the Crb carboxy-terminal motif (ERLI), which is required for Drosophila cell polarity, and the Pals1 PDZ domain using crystallography and fluorescence polarization. Only the last four Crb residues contribute to Pals1 PDZ-domain binding affinity, with specificity contributed by conserved charged interactions. Comparison of the Crb-bound Pals1 PDZ structure with an apo Pals1 structure reveals a key Phe side chain that gates access to the PDZ peptide-binding groove. Removal of this side chain enhances the binding affinity by more than fivefold, suggesting that access of Crb to Pals1 may be regulated by intradomain contacts or by protein–protein interaction.« less

Expression and purification of recombinant polyomavirus VP2 protein and its interactions with polyomavirus proteins

NASA Technical Reports Server (NTRS)

Cai, X.; Chang, D.; Rottinghaus, S.; Consigli, R. A.; Spooner, B. S. (Principal Investigator)

1994-01-01

Recombinant polyomavirus VP2 protein was expressed in Escherichia coli (RK1448), using the recombinant expression system pFPYV2. Recombinant VP2 was purified to near homogeneity by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, electroelution, and Extracti-Gel chromatography. Polyclonal serum to this protein which reacted specifically with recombinant VP2 as well as polyomavirus virion VP2 and VP3 on Western blots (immunoblots) was produced. Purified VP2 was used to establish an in vitro protein-protein interaction assay with polyomavirus structural proteins and purified recombinant VP1. Recombinant VP2 interacted with recombinant VP1, virion VP1, and the four virion histones. Recombinant VP1 coimmunoprecipitated with recombinant VP2 or truncated VP2 (delta C12VP2), which lacked the carboxy-terminal 12 amino acids. These experiments confirmed the interaction between VP1 and VP2 and revealed that the carboxyterminal 12 amino acids of VP2 and VP3 were not necessary for formation of this interaction. In vivo VP1-VP2 interaction study accomplished by cotransfection of COS-7 cells with VP2 and truncated VP1 (delta N11VP1) lacking the nuclear localization signal demonstrated that VP2 was capable of translocating delta N11VP1 into the nucleus. These studies suggest that complexes of VP1 and VP2 may be formed in the cytoplasm and cotransported to the nucleus for virion assembly to occur.

0610009K11Rik, a testis-specific and germ cell nuclear receptor-interacting protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Heng; Denhard, Leslie A.; Zhou Huaxin

Using an in silico approach, a putative nuclear receptor-interacting protein 0610009K11Rik was identified in mouse testis. We named this gene testis-specific nuclear receptor-interacting protein-1 (Tnrip-1). Tnrip-1 was predominantly expressed in the testis of adult mouse tissues. Expression of Tnrip-1 in the testis was regulated during postnatal development, with robust expression in 14-day-old or older testes. In situ hybridization analyses showed that Tnrip-1 is highly expressed in pachytene spermatocytes and spermatids. Consistent with its mRNA expression, Tnrip-1 protein was detected in adult mouse testes. Immunohistochemical studies showed that Tnrip-1 is a nuclear protein and mainly expressed in pachytene spermatocytes and roundmore » spermatids. Moreover, co-immunoprecipitation analyses showed that endogenous Tnrip-1 protein can interact with germ cell nuclear receptor (GCNF) in adult mouse testes. Our results suggest that Tnrip-1 is a testis-specific and GCNF-interacting protein which may be involved in the modulation of GCNF-mediated gene transcription in spermatogenic cells within the testis.« less

Structural analysis of intermolecular interactions in the kinesin adaptor complex fasciculation and elongation protein zeta 1/ short coiled-coil protein (FEZ1/SCOCO).

PubMed

Alborghetti, Marcos Rodrigo; Furlan, Ariane da Silva; da Silva, Júlio César; Sforça, Maurício Luís; Honorato, Rodrigo Vargas; Granato, Daniela Campos; dos Santos Migueleti, Deivid Lucas; Neves, Jorge L; de Oliveira, Paulo Sergio Lopes; Paes-Leme, Adriana Franco; Zeri, Ana Carolina de Mattos; de Torriani, Iris Concepcion Linares; Kobarg, Jörg

2013-01-01

Cytoskeleton and protein trafficking processes, including vesicle transport to synapses, are key processes in neuronal differentiation and axon outgrowth. The human protein FEZ1 (fasciculation and elongation protein zeta 1 / UNC-76, in C. elegans), SCOCO (short coiled-coil protein / UNC-69) and kinesins (e.g. kinesin heavy chain / UNC116) are involved in these processes. Exploiting the feature of FEZ1 protein as a bivalent adapter of transport mediated by kinesins and FEZ1 protein interaction with SCOCO (proteins involved in the same path of axonal growth), we investigated the structural aspects of intermolecular interactions involved in this complex formation by NMR (Nuclear Magnetic Resonance), cross-linking coupled with mass spectrometry (MS), SAXS (Small Angle X-ray Scattering) and molecular modelling. The topology of homodimerization was accessed through NMR (Nuclear Magnetic Resonance) studies of the region involved in this process, corresponding to FEZ1 (92-194). Through studies involving the protein in its monomeric configuration (reduced) and dimeric state, we propose that homodimerization occurs with FEZ1 chains oriented in an anti-parallel topology. We demonstrate that the interaction interface of FEZ1 and SCOCO defined by MS and computational modelling is in accordance with that previously demonstrated for UNC-76 and UNC-69. SAXS and literature data support a heterotetrameric complex model. These data provide details about the interaction interfaces probably involved in the transport machinery assembly and open perspectives to understand and interfere in this assembly and its involvement in neuronal differentiation and axon outgrowth.

Structural Analysis of Intermolecular Interactions in the Kinesin Adaptor Complex Fasciculation and Elongation Protein Zeta 1/ Short Coiled-Coil Protein (FEZ1/SCOCO)

PubMed Central

da Silva, Júlio César; Sforça, Maurício Luís; Honorato, Rodrigo Vargas; Granato, Daniela Campos; dos Santos Migueleti, Deivid Lucas; Neves, Jorge L.; de Oliveira, Paulo Sergio Lopes; Paes-Leme, Adriana Franco; Zeri, Ana Carolina de Mattos; de Torriani, Iris Concepcion Linares; Kobarg, Jörg

2013-01-01

Cytoskeleton and protein trafficking processes, including vesicle transport to synapses, are key processes in neuronal differentiation and axon outgrowth. The human protein FEZ1 (fasciculation and elongation protein zeta 1 / UNC-76, in C. elegans), SCOCO (short coiled-coil protein / UNC-69) and kinesins (e.g. kinesin heavy chain / UNC116) are involved in these processes. Exploiting the feature of FEZ1 protein as a bivalent adapter of transport mediated by kinesins and FEZ1 protein interaction with SCOCO (proteins involved in the same path of axonal growth), we investigated the structural aspects of intermolecular interactions involved in this complex formation by NMR (Nuclear Magnetic Resonance), cross-linking coupled with mass spectrometry (MS), SAXS (Small Angle X-ray Scattering) and molecular modelling. The topology of homodimerization was accessed through NMR (Nuclear Magnetic Resonance) studies of the region involved in this process, corresponding to FEZ1 (92-194). Through studies involving the protein in its monomeric configuration (reduced) and dimeric state, we propose that homodimerization occurs with FEZ1 chains oriented in an anti-parallel topology. We demonstrate that the interaction interface of FEZ1 and SCOCO defined by MS and computational modelling is in accordance with that previously demonstrated for UNC-76 and UNC-69. SAXS and literature data support a heterotetrameric complex model. These data provide details about the interaction interfaces probably involved in the transport machinery assembly and open perspectives to understand and interfere in this assembly and its involvement in neuronal differentiation and axon outgrowth. PMID:24116125

Ab initio folding of proteins using all-atom discrete molecular dynamics

PubMed Central

Ding, Feng; Tsao, Douglas; Nie, Huifen; Dokholyan, Nikolay V.

2008-01-01

Summary Discrete molecular dynamics (DMD) is a rapid sampling method used in protein folding and aggregation studies. Until now, DMD was used to perform simulations of simplified protein models in conjunction with structure-based force fields. Here, we develop an all-atom protein model and a transferable force field featuring packing, solvation, and environment-dependent hydrogen bond interactions. Using the replica exchange method, we perform folding simulations of six small proteins (20–60 residues) with distinct native structures. In all cases, native or near-native states are reached in simulations. For three small proteins, multiple folding transitions are observed and the computationally-characterized thermodynamics are in quantitative agreement with experiments. The predictive power of all-atom DMD highlights the importance of environment-dependent hydrogen bond interactions in modeling protein folding. The developed approach can be used for accurate and rapid sampling of conformational spaces of proteins and protein-protein complexes, and applied to protein engineering and design of protein-protein interactions. PMID:18611374

Interactions of polyphenols with carbohydrates, lipids and proteins.

PubMed

Jakobek, Lidija

2015-05-15

Polyphenols are secondary metabolites in plants, investigated intensively because of their potential positive effects on human health. Their bioavailability and mechanism of positive effects have been studied, in vitro and in vivo. Lately, a high number of studies takes into account the interactions of polyphenols with compounds present in foods, like carbohydrates, proteins or lipids, because these food constituents can have significant effects on the activity of phenolic compounds. This paper reviews the interactions between phenolic compounds and lipids, carbohydrates and proteins and their impact on polyphenol activity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Recent Progress in CFTR Interactome Mapping and Its Importance for Cystic Fibrosis.

PubMed

Lim, Sang Hyun; Legere, Elizabeth-Ann; Snider, Jamie; Stagljar, Igor

2017-01-01

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride channel found in secretory epithelia with a plethora of known interacting proteins. Mutations in the CFTR gene cause cystic fibrosis (CF), a disease that leads to progressive respiratory illness and other complications of phenotypic variance resulting from perturbations of this protein interaction network. Studying the collection of CFTR interacting proteins and the differences between the interactomes of mutant and wild type CFTR provides insight into the molecular machinery of the disease and highlights possible therapeutic targets. This mini review focuses on functional genomics and proteomics approaches used for systematic, high-throughput identification of CFTR-interacting proteins to provide comprehensive insight into CFTR regulation and function.

Host cell interactome of PA protein of H5N1 influenza A virus in chicken cells.

PubMed

Wang, Qiao; Li, Qinghe; Liu, Ranran; Zheng, Maiqing; Wen, Jie; Zhao, Guiping

2016-03-16

Influenza A virus (IAV) heavily depends on viral-host protein interactions in order to replicate and spread. Identification of host factors that interact with viral proteins plays crucial roles in understanding the mechanism of IAV infection. Here we report the interaction landscape of H5N1 IAV PA protein in chicken cells through the use of affinity purification and mass spectrometry. PA protein was expressed in chicken cells and PA interacting complexes were captured by co-immunoprecipitation and analyzed by mass spectrometry. A total of 134 proteins were identified as PA-host interacting factors. Protein complexes including the minichromosome maintenance complex (MCM), 26S proteasome and the coat protein I (COPI) complex associated with PA in chicken cells, indicating the essential roles of these functional protein complexes during the course of IAV infection. Gene Ontology and pathway enrichment analysis both showed strong enrichment of PA interacting proteins in the category of DNA replication, covering genes such as PCNA, MCM2, MCM3, MCM4, MCM5 and MCM7. This study has uncovered the comprehensive interactome of H5N1 IAV PA protein in its chicken host and helps to establish the foundation for further investigation into the newly identified viral-host interactions. Influenza A virus (IAV) is a great threat to public health and avian production. However, the manner in which avian IAV recruits the host cellular machinery for replication and how the host antagonizes the IAV infection was previously poorly understood. Here we present the viral-host interactome of the H5N1 IAV PA protein and reveal the comprehensive association of host factors with PA. Copyright © 2016 Elsevier B.V. All rights reserved.

3D model for Cancerous Inhibitor of Protein Phosphatase 2A armadillo domain unveils highly conserved protein-protein interaction characteristics.

PubMed

Dahlström, Käthe M; Salminen, Tiina A

2015-12-07

Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) is a human oncoprotein, which exerts its cancer-promoting function through interaction with other proteins, for example Protein Phosphatase 2A (PP2A) and MYC. The lack of structural information for CIP2A significantly prevents the design of anti-cancer therapeutics targeting this protein. In an attempt to counteract this fact, we modeled the three-dimensional structure of the N-terminal domain (CIP2A-ArmRP), analyzed key areas and amino acids, and coupled the results to the existing literature. The model reliably shows a stable armadillo repeat fold with a positively charged groove. The fact that this conserved groove highly likely binds peptides is corroborated by the presence of a conserved polar ladder, which is essential for the proper peptide-binding mode of armadillo repeat proteins and, according to our results, several known CIP2A interaction partners appropriately possess an ArmRP-binding consensus motif. Moreover, we show that Arg229Gln, which has been linked to the development of cancer, causes a significant change in charge and surface properties of CIP2A-ArmRP. In conclusion, our results reveal that CIP2A-ArmRP shares the typical fold, protein-protein interaction site and interaction patterns with other natural armadillo proteins and that, presumably, several interaction partners bind into the central groove of the modeled CIP2A-ArmRP. By providing essential structural characteristics of CIP2A, the present study significantly increases our knowledge on how CIP2A interacts with other proteins in cancer progression and how to develop new therapeutics targeting CIP2A. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Noninvasive imaging of protein-protein interactions in living organisms.

PubMed

Haberkorn, Uwe; Altmann, Annette

2003-06-01

Genomic research is expected to generate new types of complex observational data, changing the types of experiments as well as our understanding of biological processes. The investigation and definition of relationships among proteins is essential for understanding the function of each gene and the mechanisms of biological processes that specific genes are involved in. Recently, a study by Paulmurugan et al. demonstrated a tool for in vivo noninvasive imaging of protein-protein interactions and intracellular networks.

In Cell Footprinting Coupled with Mass Spectrometry for the Structural Analysis of Proteins in Live Cells.

PubMed

Espino, Jessica A; Mali, Vishaal S; Jones, Lisa M

2015-08-04

Protein footprinting coupled with mass spectrometry has become a widely used tool for the study of protein-protein and protein-ligand interactions and protein conformational change. These methods provide residue-level analysis on protein interaction sites and have been successful in studying proteins in vitro. The extension of these methods for in cell footprinting would open an avenue to study proteins that are not amenable for in vitro studies and would probe proteins in their native environment. Here we describe the application of an oxidative-based footprinting approach inside cells in which hydroxyl radicals are used to oxidatively modify proteins. Mass spectrometry is used to detect modification sites and to calculate modification levels. The method is probing biologically relevant proteins in live cells, and proteins in various cellular compartments can be oxdiatively modified. Several different amino acid residues are modified making the method a general labeling strategy for the study of a variety of proteins. Further, comparison of the extent of oxidative modification with solvent accessible surface area reveals the method successfully probes solvent accessibility. This marks the first time protein footprinting has been performed in live cells.

Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein.

PubMed

Khamina, Kseniya; Lercher, Alexander; Caldera, Michael; Schliehe, Christopher; Vilagos, Bojan; Sahin, Mehmet; Kosack, Lindsay; Bhattacharya, Anannya; Májek, Peter; Stukalov, Alexey; Sacco, Roberto; James, Leo C; Pinschewer, Daniel D; Bennett, Keiryn L; Menche, Jörg; Bergthaler, Andreas

2017-12-01

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/- mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host.

DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

PubMed Central

Sagendorf, Jared M.

2017-01-01

Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

Prediction of cancer proteins by integrating protein interaction, domain frequency, and domain interaction data using machine learning algorithms.

PubMed

Huang, Chien-Hung; Peng, Huai-Shun; Ng, Ka-Lok

2015-01-01

Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues's method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins. Performances were benchmarked based on three kinds of experiments as follows: (I) using individual algorithm, (II) combining algorithms, and (III) combining the same classification types of algorithms. When compared with Aragues's method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures. We demonstrated the accuracy of the proposed method on two independent datasets. The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively. It is anticipated that the current research could help understand disease mechanisms and diagnosis.

No Interactions of Stacked Bt Maize with the Non-target Aphid Rhopalosiphum padi and the Spider Mite Tetranychus urticae.

PubMed

Shu, Yinghua; Romeis, Jörg; Meissle, Michael

2018-01-01

In the agroecosystem, genetically engineered plants producing insecticidal Cry proteins from Bacillus thuringiensis (Bt) interact with non-target herbivores and other elements of the food web. Stacked Bt crops expose herbivores to multiple Cry proteins simultaneously. In this study, the direct interactions between SmartStax ® Bt maize producing six different Cry proteins and two herbivores with different feeding modes were investigated. Feeding on leaves of Bt maize had no effects on development time, fecundity, or longevity of the aphid Rhopalosiphum padi (Hemiptera: Aphididae), and no effects on the egg hatching time, development time, sex ratio, fecundity, and survival of the spider mite Tetranychus urticae (Acari: Tetranychidae). The results thus confirm the lack of effects on those species reported previously for some of the individual Cry proteins. In the Bt maize leaves, herbivore infestation did not result in a consistent change of Cry protein concentrations. However, occasional statistical differences between infested and non-infested leaves were observed for some Cry proteins and experimental repetitions. Overall, the study provides evidence that the Cry proteins in stacked Bt maize do not interact with two common non-target herbivores.

Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms

PubMed Central

2015-01-01

Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues's method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins. Performances were benchmarked based on three kinds of experiments as follows: (I) using individual algorithm, (II) combining algorithms, and (III) combining the same classification types of algorithms. When compared with Aragues's method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures. We demonstrated the accuracy of the proposed method on two independent datasets. The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively. It is anticipated that the current research could help understand disease mechanisms and diagnosis. PMID:25866773

Interactions between subunits of Saccharomyces cerevisiae RNase MRP support a conserved eukaryotic RNase P/MRP architecture.

PubMed

Aspinall, Tanya V; Gordon, James M B; Bennett, Hayley J; Karahalios, Panagiotis; Bukowski, John-Paul; Walker, Scott C; Engelke, David R; Avis, Johanna M

2007-01-01

Ribonuclease MRP is an endonuclease, related to RNase P, which functions in eukaryotic pre-rRNA processing. In Saccharomyces cerevisiae, RNase MRP comprises an RNA subunit and ten proteins. To improve our understanding of subunit roles and enzyme architecture, we have examined protein-protein and protein-RNA interactions in vitro, complementing existing yeast two-hybrid data. In total, 31 direct protein-protein interactions were identified, each protein interacting with at least three others. Furthermore, seven proteins self-interact, four strongly, pointing to subunit multiplicity in the holoenzyme. Six protein subunits interact directly with MRP RNA and four with pre-rRNA. A comparative analysis with existing data for the yeast and human RNase P/MRP systems enables confident identification of Pop1p, Pop4p and Rpp1p as subunits that lie at the enzyme core, with probable addition of Pop5p and Pop3p. Rmp1p is confirmed as an integral subunit, presumably associating preferentially with RNase MRP, rather than RNase P, via interactions with Snm1p and MRP RNA. Snm1p and Rmp1p may act together to assist enzyme specificity, though roles in substrate binding are also indicated for Pop4p and Pop6p. The results provide further evidence of a conserved eukaryotic RNase P/MRP architecture and provide a strong basis for studies of enzyme assembly and subunit function.

The Molecular Basis of Polyunsaturated Fatty Acid Interactions with the Shaker Voltage-Gated Potassium Channel

PubMed Central

Yazdi, Samira; Stein, Matthias; Elinder, Fredrik; Andersson, Magnus; Lindahl, Erik

2016-01-01

Voltage-gated potassium (KV) channels are membrane proteins that respond to changes in membrane potential by enabling K+ ion flux across the membrane. Polyunsaturated fatty acids (PUFAs) induce channel opening by modulating the voltage-sensitivity, which can provide effective treatment against refractory epilepsy by means of a ketogenic diet. While PUFAs have been reported to influence the gating mechanism by electrostatic interactions to the voltage-sensor domain (VSD), the exact PUFA-protein interactions are still elusive. In this study, we report on the interactions between the Shaker KV channel in open and closed states and a PUFA-enriched lipid bilayer using microsecond molecular dynamics simulations. We determined a putative PUFA binding site in the open state of the channel located at the protein-lipid interface in the vicinity of the extracellular halves of the S3 and S4 helices of the VSD. In particular, the lipophilic PUFA tail covered a wide range of non-specific hydrophobic interactions in the hydrophobic central core of the protein-lipid interface, while the carboxylic head group displayed more specific interactions to polar/charged residues at the extracellular regions of the S3 and S4 helices, encompassing the S3-S4 linker. Moreover, by studying the interactions between saturated fatty acids (SFA) and the Shaker KV channel, our study confirmed an increased conformational flexibility in the polyunsaturated carbon tails compared to saturated carbon chains, which may explain the specificity of PUFA action on channel proteins. PMID:26751683

Influence of structure properties on protein-protein interactions-QSAR modeling of changes in diffusion coefficients.

PubMed

Bauer, Katharina Christin; Hämmerling, Frank; Kittelmann, Jörg; Dürr, Cathrin; Görlich, Fabian; Hubbuch, Jürgen

2017-04-01

Information about protein-protein interactions provides valuable knowledge about the phase behavior of protein solutions during the biopharmaceutical production process. Up to date it is possible to capture their overall impact by an experimentally determined potential of mean force. For the description of this potential, the second virial coefficient B22, the diffusion interaction parameter kD, the storage modulus G', or the diffusion coefficient D is applied. In silico methods do not only have the potential to predict these parameters, but also to provide deeper understanding of the molecular origin of the protein-protein interactions by correlating the data to the protein's three-dimensional structure. This methodology furthermore allows a lower sample consumption and less experimental effort. Of all in silico methods, QSAR modeling, which correlates the properties of the molecule's structure with the experimental behavior, seems to be particularly suitable for this purpose. To verify this, the study reported here dealt with the determination of a QSAR model for the diffusion coefficient of proteins. This model consisted of diffusion coefficients for six different model proteins at various pH values and NaCl concentrations. The generated QSAR model showed a good correlation between experimental and predicted data with a coefficient of determination R2 = 0.9 and a good predictability for an external test set with R2 = 0.91. The information about the properties affecting protein-protein interactions present in solution was in agreement with experiment and theory. Furthermore, the model was able to give a more detailed picture of the protein properties influencing the diffusion coefficient and the acting protein-protein interactions. Biotechnol. Bioeng. 2017;114: 821-831. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach.

PubMed

Ramu, Venkatesh; Venkatarangaiah, Krishna; Krishnappa, Pradeepa; Shimoga Rajanna, Santosh Kumar; Deeplanaik, Nagaraja; Chandra Pal, Anup; Kini, Kukkundoor Ramachandra

2016-02-24

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (-6.48 kcal/mol) and docking energy (-8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases.

Identification of Biomarkers for Resistance to Fusarium oxysporum f. sp. cubense Infection and in Silico Studies in Musa paradisiaca Cultivar Puttabale through Proteomic Approach

PubMed Central

Ramu, Venkatesh; Venkatarangaiah, Krishna; Krishnappa, Pradeepa; Shimoga Rajanna, Santosh Kumar; Deeplanaik, Nagaraja; Chandra Pal, Anup; Kini, Kukkundoor Ramachandra

2016-01-01

Panama wilt caused by Fusarium oxysporum f. sp. cubense (Foc) is one of the major disease constraints of banana production. Previously, we reported the disease resistance Musa paradisiaca cv. puttabale clones developed from Ethylmethanesulfonate and Foc culture filtrate against Foc inoculation. Here, the same resistant clones and susceptible clones were used for the study of protein accumulation against Foc inoculation by two-dimensional gel electrophoresis (2-DE), their expression pattern and an in silico approach. The present investigation revealed mass-spectrometry identified 16 proteins that were over accumulated and 5 proteins that were under accumulated as compared to the control. The polyphosphoinositide binding protein ssh2p (PBPssh2p) and Indoleacetic acid-induced-like (IAA) protein showed significant up-regulation and down-regulation. The docking of the pathogenesis-related protein (PR) with the fungal protein endopolygalacturonase (PG) exemplify the three ionic interactions and seven hydrophobic residues that tends to good interaction at the active site of PG with free energy of assembly dissociation (1.5 kcal/mol). The protein-ligand docking of the Peptide methionine sulfoxide reductase chloroplastic-like protein (PMSRc) with the ligand β-1,3 glucan showed minimum binding energy (−6.48 kcal/mol) and docking energy (−8.2 kcal/mol) with an interaction of nine amino-acid residues. These explorations accelerate the research in designing the host pathogen interaction studies for the better management of diseases. PMID:28248219

Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems

PubMed Central

MacPherson, Jamie I.; Dickerson, Jonathan E.; Pinney, John W.; Robertson, David L.

2010-01-01

Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection. PMID:20686668

Noncovalent Ubiquitin Interactions Regulate the Catalytic Activity of Ubiquitin Writers.

PubMed

Wright, Joshua D; Mace, Peter D; Day, Catherine L

2016-11-01

Covalent modification of substrate proteins with ubiquitin is the end result of an intricate network of protein-protein interactions. The inherent ability of the E1, E2, and E3 proteins of the ubiquitylation cascade (the ubiquitin writers) to interact with ubiquitin facilitates this process. Importantly, contact between ubiquitin and the E2/E3 writers is required for catalysis and the assembly of chains of a given linkage. However, ubiquitin is also an activator of ubiquitin-writing enzymes, with many recent studies highlighting the ability of ubiquitin to regulate activity and substrate modification. Here, we review the interactions between ubiquitin-writing enzymes and regulatory ubiquitin molecules that promote activity, and highlight the potential of these interactions to promote processive ubiquitin transfer. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

PubMed Central

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms. PMID:29666630

A study on the nature of interactions of mixed-mode ligands HEA and PPA HyperCel using phenylglyoxal modified lysozyme.

PubMed

Pezzini, J; Cabanne, C; Dupuy, J-W; Gantier, R; Santarelli, X

2014-06-01

Mixed mode chromatography, or multimodal chromatography, involves the exploitation of combinations of several interactions in a controlled manner, to facilitate the rapid capture of proteins. Mixed-mode ligands like HEA and PPA HyperCel™ facilitate different kinds of interactions (hydrophobic, ionic, etc.) under different conditions. In order to better characterize the nature of this multi-modal interaction, we sought to study a protein, lysozyme, which is normally not retained by these mixed mode resins under normal binding conditions. Lysozyme was modified specifically at Arginine residues by the action of phenylglyoxal, and was extensively studied in this work to better characterize the mixed-mode interactions of HEA HyperCel™ and PPA HyperCel™ chromatographic supports. We show here that the adsorption behaviour of lysozyme on HEA and PPA HyperCel™ mixed mode sorbents varies depending on the degree of charge modification at the surface of the protein. Experiments using conventional cation exchange and hydrophobic interaction chromatography confirm that both charge and hydrophobicity modification occurs at the surface of the protein after lysozyme reaction with phenylglyoxal. The results emanating from this work using HEA and PPA HyperCel sorbents strongly suggest that mixed mode chromatography can efficiently separate closely related proteins of only minor surface charge and/or hydrophobicity differences. Copyright © 2014 Elsevier B.V. All rights reserved.

Biophysical studies of interaction between hydrolysable tannins isolated from Oenothera gigas and Geranium sanguineum with human serum albumin.

PubMed

Sekowski, Szymon; Ionov, Maksim; Kaszuba, Mateusz; Mavlyanov, Saidmukhtar; Bryszewska, Maria; Zamaraeva, Maria

2014-11-01

Tannins, secondary plant metabolites, possess diverse biological activities and can interact with biopolymers such as lipids or proteins. Interactions between tannins and proteins depend on the structures of both and can result in changes in protein structure and activity. Because human serum albumin is the most abundant protein in plasma and responsible for interactions with important biological compounds (e.g. bilirubin) and proper blood pressure, therefore, it is very important to investigate reactions between HSA and tannins. This paper describes the interaction between human serum albumin (HSA) and two tannins: bihexahydroxydiphenoyl-trigalloylglucose (BDTG) and 1-O-galloyl-4,6-hexahydroxydiphenoyl-β-d-glucose (OGβDG), isolated from Geranium sanguineum and Oenothera gigas leafs, respectively. Optical (spectrofluorimetric) and chiral optical (circular dichroism) methods were used in this study. Fluorescence analysis demonstrated that OGβDG quenched HSA fluorescence more strongly than BDTG. Both OGβDG and BDTG formed complexes with albumin and caused a red shift of the fluorescence spectra but did not significantly change the protein secondary structure. Our studies clearly demonstrate that the tested tannins interact very strongly with human serum albumin (quenching constant K=88,277.26±407.04 M(-1) and K=55,552.67±583.07 M(-1) respectively for OGβDG and BDTG) in a manner depending on their chemical structure. Copyright © 2014 Elsevier B.V. All rights reserved.

The rhodopsin-arrestin-1 interaction in bicelles.

PubMed

Chen, Qiuyan; Vishnivetskiy, Sergey A; Zhuang, Tiandi; Cho, Min-Kyu; Thaker, Tarjani M; Sanders, Charles R; Gurevich, Vsevolod V; Iverson, T M

2015-01-01

G-protein-coupled receptors (GPCRs) are essential mediators of information transfer in eukaryotic cells. Interactions between GPCRs and their binding partners modulate the signaling process. For example, the interaction between GPCR and cognate G protein initiates the signal, while the interaction with cognate arrestin terminates G-protein-mediated signaling. In visual signal transduction, arrestin-1 selectively binds to the phosphorylated light-activated GPCR rhodopsin to terminate rhodopsin signaling. Under physiological conditions, the rhodopsin-arrestin-1 interaction occurs in highly specialized disk membrane in which rhodopsin resides. This membrane is replaced with mimetics when working with purified proteins. While detergents are commonly used as membrane mimetics, most detergents denature arrestin-1, preventing biochemical studies of this interaction. In contrast, bicelles provide a suitable alternative medium. An advantage of bicelles is that they contain lipids, which have been shown to be necessary for normal rhodopsin-arrestin-1 interaction. Here we describe how to reconstitute rhodopsin into bicelles, and how bicelle properties affect the rhodopsin-arrestin-1 interaction.

The Rhodopsin-Arrestin-1 Interaction in Bicelles

PubMed Central

Chen, Qiuyan; Vishnivetskiy, Sergey A.; Zhuang, Tiandi; Cho, Min-Kyu; Thaker, Tarjani M.; Sanders, Charles R.; Gurevich, Vsevolod V.; Iverson, T. M.

2015-01-01

G-protein-coupled receptors (GPCRs) are essential mediators of information transfer in eukaryotic cells. Interactions between GPCRs and their binding partners modulate the signaling process. For example, the interaction between GPCR and cognate G protein initiates the signal, while the interaction with cognate arrestin terminates G-protein-mediated signaling. In visual signal transduction, arrestin-1 selectively binds to the phosphorylated light-activated GPCR rhodopsin to terminate rhodopsin signaling. Under physiological conditions, the rhodopsin-arrestin-1 interaction occurs in highly specialized disk membrane in which rhodopsin resides. This membrane is replaced with mimetics when working with purified proteins. While detergents are commonly used as membrane mimetics, most detergents denature arrestin-1, preventing biochemical studies of this interaction. In contrast, bicelles provide a suitable alternative medium. An advantage of bicelles is that they contain lipids, which have been shown to be necessary for normal rhodopsin-arrestin-1 interaction. Here we describe how to reconstitute rhodopsin into bicelles, and how bicelle properties affect the rhodopsin-arrestin-1 interaction. PMID:25697518

Ectromelia virus encodes a novel family of F-box proteins that interact with the SCF complex.

PubMed

van Buuren, Nick; Couturier, Brianne; Xiong, Yue; Barry, Michele

2008-10-01

Poxviruses are notorious for encoding multiple proteins that regulate cellular signaling pathways, including the ubiquitin-proteasome system. Bioinformatics indicated that ectromelia virus, the causative agent of lethal mousepox, encoded four proteins, EVM002, EVM005, EVM154, and EVM165, containing putative F-box domains. In contrast to cellular F-box proteins, the ectromelia virus proteins contain C-terminal F-box domains in conjunction with N-terminal ankyrin repeats, a combination that has not been previously reported for cellular proteins. These observations suggested that the ectromelia virus F-box proteins interact with SCF (Skp1, cullin-1, and F-box) ubiquitin ligases. We focused our studies on EVM005, since this protein had only one ortholog in cowpox virus. Using mass spectrometry, we identified cullin-1 as a binding partner for EVM005, and this interaction was confirmed by overexpression of hemagglutinin (HA)-cullin-1. During infection, Flag-EVM005 and HA-cullin-1 colocalized to distinct cellular bodies. Significantly, EVM005 coprecipitated with endogenous Skp1, cullin-1, and Roc1 and associated with conjugated ubiquitin, suggesting that EVM005 interacted with the components of a functional ubiquitin ligase. Interaction of EVM005 with cullin-1 and Skp1 was abolished upon deletion of the F-box, indicating that the F-box played a crucial role in interaction with the SCF complex. Additionally, EVM002 and EVM154 interacted with Skp1 and conjugated ubiquitin, suggesting that ectromelia virus encodes multiple F-box-containing proteins that regulate the SCF complex. Our results indicate that ectromelia virus has evolved multiple proteins that interact with the SCF complex.

"Features of two proteins of Leptospira interrogans with potential role in host-pathogen interactions"

PubMed Central

2012-01-01

Background Leptospirosis is considered a re-emerging infectious disease caused by pathogenic spirochaetes of the genus Leptospira. Pathogenic leptospires have the ability to survive and disseminate to multiple organs after penetrating the host. Leptospires were shown to express surface proteins that interact with the extracellular matrix (ECM) and to plasminogen (PLG). This study examined the interaction of two putative leptospiral proteins with laminin, collagen Type I, collagen Type IV, cellular fibronectin, plasma fibronectin, PLG, factor H and C4bp. Results We show that two leptospiral proteins encoded by LIC11834 and LIC12253 genes interact with laminin in a dose - dependent and saturable mode, with dissociation equilibrium constants (KD) of 367.5 and 415.4 nM, respectively. These proteins were named Lsa33 and Lsa25 (Leptospiral surface adhesin) for LIC11834 and LIC12253, respectively. Metaperiodate - treated laminin reduced Lsa25 - laminin interaction, suggesting that sugar moieties of this ligand participate in this interaction. The Lsa33 is also PLG - binding receptor, with a KD of 23.53 nM, capable of generating plasmin in the presence of an activator. Although in a weak manner, both proteins interact with C4bp, a regulator of complement classical route. In silico analysis together with proteinase K and immunoflorescence data suggest that these proteins might be surface exposed. Moreover, the recombinant proteins partially inhibited leptospiral adherence to immobilized laminin and PLG. Conclusions We believe that these multifunctional proteins have the potential to participate in the interaction of leptospires to hosts by mediating adhesion and by helping the bacteria to escape the immune system and to overcome tissue barriers. To our knowledge, Lsa33 is the first leptospiral protein described to date with the capability of binding laminin, PLG and C4bp in vitro. PMID:22463075

Statistical models for detecting differential chromatin interactions mediated by a protein.

PubMed

Niu, Liang; Li, Guoliang; Lin, Shili

2014-01-01

Chromatin interactions mediated by a protein of interest are of great scientific interest. Recent studies show that protein-mediated chromatin interactions can have different intensities in different types of cells or in different developmental stages of a cell. Such differences can be associated with a disease or with the development of a cell. Thus, it is of great importance to detect protein-mediated chromatin interactions with different intensities in different cells. A recent molecular technique, Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET), which uses formaldehyde cross-linking and paired-end sequencing, is able to detect genome-wide chromatin interactions mediated by a protein of interest. Here we proposed two models (One-Step Model and Two-Step Model) for two sample ChIA-PET count data (one biological replicate in each sample) to identify differential chromatin interactions mediated by a protein of interest. Both models incorporate the data dependency and the extent to which a fragment pair is related to a pair of DNA loci of interest to make accurate identifications. The One-Step Model makes use of the data more efficiently but is more computationally intensive. An extensive simulation study showed that the models can detect those differentially interacted chromatins and there is a good agreement between each classification result and the truth. Application of the method to a two-sample ChIA-PET data set illustrates its utility. The two models are implemented as an R package MDM (available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM).

Statistical Models for Detecting Differential Chromatin Interactions Mediated by a Protein

PubMed Central

Niu, Liang; Li, Guoliang; Lin, Shili

2014-01-01

Chromatin interactions mediated by a protein of interest are of great scientific interest. Recent studies show that protein-mediated chromatin interactions can have different intensities in different types of cells or in different developmental stages of a cell. Such differences can be associated with a disease or with the development of a cell. Thus, it is of great importance to detect protein-mediated chromatin interactions with different intensities in different cells. A recent molecular technique, Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET), which uses formaldehyde cross-linking and paired-end sequencing, is able to detect genome-wide chromatin interactions mediated by a protein of interest. Here we proposed two models (One-Step Model and Two-Step Model) for two sample ChIA-PET count data (one biological replicate in each sample) to identify differential chromatin interactions mediated by a protein of interest. Both models incorporate the data dependency and the extent to which a fragment pair is related to a pair of DNA loci of interest to make accurate identifications. The One-Step Model makes use of the data more efficiently but is more computationally intensive. An extensive simulation study showed that the models can detect those differentially interacted chromatins and there is a good agreement between each classification result and the truth. Application of the method to a two-sample ChIA-PET data set illustrates its utility. The two models are implemented as an R package MDM (available at http://www.stat.osu.edu/~statgen/SOFTWARE/MDM). PMID:24835279

Hydrogen-deuterium exchange mass spectrometry reveals folding and allostery in protein-protein interactions.

PubMed

Ramirez-Sarmiento, Cesar A; Komives, Elizabeth A

2018-04-06

Hydrogen-deuterium exchange mass spectrometry (HDXMS) has emerged as a powerful approach for revealing folding and allostery in protein-protein interactions. The advent of higher resolution mass spectrometers combined with ion mobility separation and ultra performance liquid chromatographic separations have allowed the complete coverage of large protein sequences and multi-protein complexes. Liquid-handling robots have improved the reproducibility and accurate temperature control of the sample preparation. Many researchers are also appreciating the power of combining biophysical approaches such as stopped-flow fluorescence, single molecule FRET, and molecular dynamics simulations with HDXMS. In this review, we focus on studies that have used a combination of approaches to reveal (re)folding of proteins as well as on long-distance allosteric changes upon interaction. Copyright © 2018 Elsevier Inc. All rights reserved.

iRefWeb: interactive analysis of consolidated protein interaction data and their supporting evidence

PubMed Central

Turner, Brian; Razick, Sabry; Turinsky, Andrei L.; Vlasblom, James; Crowdy, Edgard K.; Cho, Emerson; Morrison, Kyle; Wodak, Shoshana J.

2010-01-01

We present iRefWeb, a web interface to protein interaction data consolidated from 10 public databases: BIND, BioGRID, CORUM, DIP, IntAct, HPRD, MINT, MPact, MPPI and OPHID. iRefWeb enables users to examine aggregated interactions for a protein of interest, and presents various statistical summaries of the data across databases, such as the number of organism-specific interactions, proteins and cited publications. Through links to source databases and supporting evidence, researchers may gauge the reliability of an interaction using simple criteria, such as the detection methods, the scale of the study (high- or low-throughput) or the number of cited publications. Furthermore, iRefWeb compares the information extracted from the same publication by different databases, and offers means to follow-up possible inconsistencies. We provide an overview of the consolidated protein–protein interaction landscape and show how it can be automatically cropped to aid the generation of meaningful organism-specific interactomes. iRefWeb can be accessed at: http://wodaklab.org/iRefWeb. Database URL: http://wodaklab.org/iRefWeb/ PMID:20940177

Atomic detail brownian dynamics simulations of concentrated protein solutions with a mean field treatment of hydrodynamic interactions.

PubMed

Mereghetti, Paolo; Wade, Rebecca C

2012-07-26

High macromolecular concentrations are a distinguishing feature of living organisms. Understanding how the high concentration of solutes affects the dynamic properties of biological macromolecules is fundamental for the comprehension of biological processes in living systems. In this paper, we describe the implementation of mean field models of translational and rotational hydrodynamic interactions into an atomically detailed many-protein brownian dynamics simulation method. Concentrated solutions (30-40% volume fraction) of myoglobin, hemoglobin A, and sickle cell hemoglobin S were simulated, and static structure factors, oligomer formation, and translational and rotational self-diffusion coefficients were computed. Good agreement of computed properties with available experimental data was obtained. The results show the importance of both solvent mediated interactions and weak protein-protein interactions for accurately describing the dynamics and the association properties of concentrated protein solutions. Specifically, they show a qualitative difference in the translational and rotational dynamics of the systems studied. Although the translational diffusion coefficient is controlled by macromolecular shape and hydrodynamic interactions, the rotational diffusion coefficient is affected by macromolecular shape, direct intermolecular interactions, and both translational and rotational hydrodynamic interactions.

Towards a map of the Populus biomass protein-protein interaction network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beers, Eric; Brunner, Amy; Helm, Richard

Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of themore » fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in-depth characterizations. Characterizations involved both in vivo and in vitro independent methods to confirm protein-protein interactions and the evaluation of novel phenotypes resulting from creation of transgenic poplar and Arabidopsis plants engineered for increased or decreased expression of the selected genes. Transgenic poplar trees were studied in growth chamber, greenhouse, and two separate replicated field trials involving over 25 distinct wood-associated proteins. In-depth characterizations yielding positive results include the following. First, a NAC domain transcription factor (NAC154) that is a promoter of stress response and dormancy in trees was discovered. Increasing expression of NAC154 caused stunted growth and premature senescence, while decreasing expression led to both delayed bud and leaf expansion in spring and delayed leaf drop (i.e., prolonged leaf retention) in fall. Second, we discovered and characterized a new connection between a negative regulator of wood formation, the NAC domain transcription factor XND1, and an important regulator of cell division and cell differentiation, RBR. Third, we identified a new network of interacting wood-associated transcription factors belonging to the MYB and HD families. One of the HD family proteins, WOX13, was used to prepare transgenic poplar for high-level expression, resulting in significantly increased lateral branch growth. Finally, we modeled and performed in vitro analyses of the insect protein rubber resilin and we prepared transgenic Arabidopsis plants for expression of resilin to test the feasibility of using resilin to modify lignin cross-linking in wood and reduce recalcitrance and improve yield of fermentable sugars for biofuels production. Analysis of these and additional transgenics created with this support is continuing.« less

High-throughput profiling of nanoparticle-protein interactions by fluorescamine labeling.

PubMed

Ashby, Jonathan; Duan, Yaokai; Ligans, Erik; Tamsi, Michael; Zhong, Wenwan

2015-02-17

A rapid, high throughput fluorescence assay was designed to screen interactions between proteins and nanoparticles. The assay employs fluorescamine, a primary-amine specific fluorogenic dye, to label proteins. Because fluorescamine could specifically target the surface amines on proteins, a conformational change of the protein upon interaction with nanoparticles will result in a change in fluorescence. In the present study, the assay was applied to test the interactions between a selection of proteins and nanoparticles made of polystyrene, silica, or iron oxide. The particles were also different in their hydrodynamic diameter, synthesis procedure, or surface modification. Significant labeling differences were detected when the same protein incubated with different particles. Principal component analysis (PCA) on the collected fluorescence profiles revealed clear grouping effects of the particles based on their properties. The results prove that fluorescamine labeling is capable of detecting protein-nanoparticle interactions, and the resulting fluorescence profile is sensitive to differences in nanoparticle's physical properties. The assay can be carried out in a high-throughput manner, and is rapid with low operation cost. Thus, it is well suited for evaluating interactions between a larger number of proteins and nanoparticles. Such assessment can help to improve our understanding on the molecular basis that governs the biological behaviors of nanomaterials. It will also be useful for initial examination of the bioactivity and reproducibility of nanomaterials employed in biomedical fields.

Structure, dynamics and biophysics of the cytoplasmic protein–protein complexes of the bacterial phosphoenolpyruvate: Sugar phosphotransferase system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clore, G. Marius; Venditti, Vincenzo

2013-10-01

The bacterial phosphotransferase system (PTS) couples phosphoryl transfer, via a series of bimolecular protein–protein interactions, to sugar transport across the membrane. The multitude of complexes in the PTS provides a paradigm for studying protein interactions, and for understanding how the same binding surface can specifically recognize a diverse array of targets. Fifteen years of work aimed at solving the solution structures of all soluble protein–protein complexes of the PTS has served as a test bed for developing NMR and integrated hybrid approaches to study larger complexes in solution and to probe transient, spectroscopically invisible states, including encounter complexes. We reviewmore » these approaches, highlighting the problems that can be tackled with these methods, and summarize the current findings on protein interactions.« less

Linker histone H1.0 interacts with an extensive network of proteins found in the nucleolus

PubMed Central

Kalashnikova, Anna A.; Winkler, Duane D.; McBryant, Steven J.; Henderson, Ryan K.; Herman, Jacob A.; DeLuca, Jennifer G.; Luger, Karolin; Prenni, Jessica E.; Hansen, Jeffrey C.

2013-01-01

The H1 linker histones are abundant chromatin-associated DNA-binding proteins. Recent evidence suggests that linker histones also may function through protein–protein interactions. To gain a better understanding of the scope of linker histone involvement in protein–protein interactions, we used a proteomics approach to identify H1-binding proteins in human nuclear extracts. Full-length H1.0 and H1.0 lacking its C-terminal domain (CTD) were used for protein pull-downs. A total of 107 candidate H1.0 binding proteins were identified by LC-MS/MS. About one-third of the H1.0-dependent interactions were mediated by the CTD, and two-thirds by the N-terminal domain-globular domain fragment. Many of the proteins pulled down by H1.0 were core splicing factors. Another group of H1-binding proteins functions in rRNA biogenesis. H1.0 also pulled down numerous ribosomal proteins and proteins involved in cellular transport. Strikingly, nearly all of the H1.0-binding proteins are found in the nucleolus. Quantitative biophysical studies with recombinant proteins confirmed that H1.0 directly binds to FACT and the splicing factors SF2/ASF and U2AF65. Our results demonstrate that H1.0 interacts with an extensive network of proteins that function in RNA metabolism in the nucleolus, and suggest that a new paradigm for linker histone action is in order. PMID:23435226

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

PubMed Central

Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not necessarily imply that one detection methodology was better or worse, but rather that, to a large extent, the insights reflected the methodological biases themselves. Consequently, interpreting the protein interaction data within their experimental or cellular context provided the best avenue for overcoming biases and inferring biological knowledge. PMID:21876202

Visualizing Active Enzyme Complexes Using a Photoreactive Inhibitor for Proximity Ligation – Application on γ-Secretase

PubMed Central

Schedin-Weiss, Sophia; Inoue, Mitsuhiro; Teranishi, Yasuhiro; Yamamoto, Natsuko Goto; Karlström, Helena; Winblad, Bengt; Tjernberg, Lars O.

2013-01-01

Here, we present a highly sensitive method to study protein-protein interactions and subcellular location selectively for active multicomponent enzymes. We apply the method on γ-secretase, the enzyme complex that catalyzes the cleavage of the amyloid precursor protein (APP) to generate amyloid β-peptide (Aβ), the major causative agent in Alzheimer disease (AD). The novel assay is based on proximity ligation, which can be used to study protein interactions in situ with very high sensitivity. In traditional proximity ligation assay (PLA), primary antibody recognition is typically accompanied by oligonucleotide-conjugated secondary antibodies as detection probes. Here, we first performed PLA experiments using antibodies against the γ-secretase components presenilin 1 (PS1), containing the catalytic site residues, and nicastrin, suggested to be involved in substrate recognition. To selectively study the interactions of active γ-secretase, we replaced one of the primary antibodies with a photoreactive γ-secretase inhibitor containing a PEG linker and a biotin group (GTB), and used oligonucleotide-conjugated streptavidin as a probe. Interestingly, significantly fewer interactions were detected with the latter, novel, assay, which is a reasonable finding considering that a substantial portion of PS1 is inactive. In addition, the PLA signals were located more peripherally when GTB was used instead of a PS1 antibody, suggesting that γ-secretase matures distal from the perinuclear ER region. This novel technique thus enables highly sensitive protein interaction studies, determines the subcellular location of the interactions, and differentiates between active and inactive γ-secretase in intact cells. We suggest that similar PLA assays using enzyme inhibitors could be useful also for other enzyme interaction studies. PMID:23717518

SCOWLP classification: Structural comparison and analysis of protein binding regions

PubMed Central

Teyra, Joan; Paszkowski-Rogacz, Maciej; Anders, Gerd; Pisabarro, M Teresa

2008-01-01

Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs) might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions. The hierarchical classification of PBRs is implemented into the SCOWLP database and extends the SCOP classification with three additional family sub-levels: Binding Region, Interface and Contacting Domains. SCOWLP contains 9,334 binding regions distributed within 2,561 families. In 65% of the cases we observe families containing more than one binding region. Besides, 22% of the regions are forming complex with more than one different protein family. Conclusion The current SCOWLP classification and its web application represent a framework for the study of protein interfaces and comparative analysis of protein family binding regions. This comparison can be performed at atomic level and allows the user to study interactome conservation and variability. The new SCOWLP classification may be of great utility for reconstruction of protein complexes, understanding protein networks and ligand design. SCOWLP will be updated with every SCOP release. The web application is available at . PMID:18182098

Exploring Biomolecular Recognition by Modeling and Simulation

NASA Astrophysics Data System (ADS)

Wade, Rebecca

2007-12-01

Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Purnima; Gunalan, Vithiagaran; Liu Boping

Severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) caused a severe outbreak in several regions of the world in 2003. The SARS-CoV genome is predicted to contain 14 functional open reading frames (ORFs). The first ORF (1a and 1b) encodes a large polyprotein that is cleaved into nonstructural proteins (nsp). The other ORFs encode for four structural proteins (spike, membrane, nucleocapsid and envelope) as well as eight SARS-CoV-specific accessory proteins (3a, 3b, 6, 7a, 7b, 8a, 8b and 9b). In this report we have cloned the predicted nsp8 gene and the ORF6 gene of the SARS-CoV and studied their abilities tomore » interact with each other. We expressed the two proteins as fusion proteins in the yeast two-hybrid system to demonstrate protein-protein interactions and tested the same using a yeast genetic cross. Further the strength of the interaction was measured by challenging growth of the positive interaction clones on increasing gradients of 2-amino trizole. The interaction was then verified by expressing both proteins separately in-vitro in a coupled-transcription translation system and by coimmunoprecipitation in mammalian cells. Finally, colocalization experiments were performed in SARS-CoV infected Vero E6 mammalian cells to confirm the nsp8-ORF6 interaction. To the best of our knowledge, this is the first report of the interaction between a SARS-CoV accessory protein and nsp8 and our findings suggest that ORF6 protein may play a role in virus replication.« less

Chromophore maturation and fluorescence fluctuation spectroscopy of fluorescent proteins in a cell-free expression system

PubMed Central

Macdonald, Patrick J.; Chen, Yan; Mueller, Joachim D.

2012-01-01

Cell-free synthesis, a method for the rapid expression of proteins, is increasingly used to study interactions of complex biological systems. GFP and its variants have become indispensable for fluorescence studies in live cells and are equally attractive as reporters for cell-free systems. This work investigates the use of fluorescence fluctuation spectroscopy (FFS) as a tool for quantitative analysis of protein interactions in cell-free expression systems. We also explore chromophore maturation of fluorescent proteins, which is of crucial importance for fluorescence studies. A droplet sample protocol was developed that ensured sufficient oxygenation for chromophore maturation and ease of manipulation for titration studies. The kinetics of chromophore maturation of EGFP, EYFP, and mCherry were analyzed as a function of temperature. A strong increase in the rate from room temperature to 37 °C was observed. We further demonstrate that all EGFP proteins fully mature in the cell-free solution and that brightness is a robust parameter specifying stoichiometry. Finally, FFS is applied to study the stoichiometry of the nuclear transport factor 2 in a cell-free system over a broad concentration range. We conclude that combining cell-free expression and FFS provides a powerful technique for quick, quantitative study of chromophore maturation and protein-protein interaction. PMID:22093611

The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

PubMed

Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

2017-08-01

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Plasma membrane lipid–protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana

PubMed Central

Zauber, Henrik; Burgos, Asdrubal; Garapati, Prashanth; Schulze, Waltraud X.

2014-01-01

The plasma membrane is an important organelle providing structure, signaling and transport as major biological functions. Being composed of lipids and proteins with different physicochemical properties, the biological functions of membranes depend on specific protein–protein and protein–lipid interactions. Interactions of proteins with their specific sterol and lipid environment were shown to be important factors for protein recruitment into sub-compartmental structures of the plasma membrane. System-wide implications of altered endogenous sterol levels for membrane functions in living cells were not studied in higher plant cells. In particular, little is known how alterations in membrane sterol composition affect protein and lipid organization and interaction within membranes. Here, we conducted a comparative analysis of the plasma membrane protein and lipid composition in Arabidopsis sterol-biosynthesis mutants smt1 and ugt80A2;B1. smt1 shows general alterations in sterol composition while ugt80A2;B1 is significantly impaired in sterol glycosylation. By systematically analyzing different cellular fractions and combining proteomic with lipidomic data we were able to reveal contrasting alterations in lipid–protein interactions in both mutants, with resulting differential changes in plasma membrane signaling status. PMID:24672530

Multifarious Roles of Intrinsic Disorder in Proteins Illustrate Its Broad Impact on Plant Biology

PubMed Central

Sun, Xiaolin; Rikkerink, Erik H.A.; Jones, William T.; Uversky, Vladimir N.

2013-01-01

Intrinsically disordered proteins (IDPs) are highly abundant in eukaryotic proteomes. Plant IDPs play critical roles in plant biology and often act as integrators of signals from multiple plant regulatory and environmental inputs. Binding promiscuity and plasticity allow IDPs to interact with multiple partners in protein interaction networks and provide important functional advantages in molecular recognition through transient protein–protein interactions. Short interaction-prone segments within IDPs, termed molecular recognition features, represent potential binding sites that can undergo disorder-to-order transition upon binding to their partners. In this review, we summarize the evidence for the importance of IDPs in plant biology and evaluate the functions associated with intrinsic disorder in five different types of plant protein families experimentally confirmed as IDPs. Functional studies of these proteins illustrate the broad impact of disorder on many areas of plant biology, including abiotic stress, transcriptional regulation, light perception, and development. Based on the roles of disorder in the protein–protein interactions, we propose various modes of action for plant IDPs that may provide insight for future experimental approaches aimed at understanding the molecular basis of protein function within important plant pathways. PMID:23362206

BindML/BindML+: Detecting Protein-Protein Interaction Interface Propensity from Amino Acid Substitution Patterns.

PubMed

Wei, Qing; La, David; Kihara, Daisuke

2017-01-01

Prediction of protein-protein interaction sites in a protein structure provides important information for elucidating the mechanism of protein function and can also be useful in guiding a modeling or design procedures of protein complex structures. Since prediction methods essentially assess the propensity of amino acids that are likely to be part of a protein docking interface, they can help in designing protein-protein interactions. Here, we introduce BindML and BindML+ protein-protein interaction sites prediction methods. BindML predicts protein-protein interaction sites by identifying mutation patterns found in known protein-protein complexes using phylogenetic substitution models. BindML+ is an extension of BindML for distinguishing permanent and transient types of protein-protein interaction sites. We developed an interactive web-server that provides a convenient interface to assist in structural visualization of protein-protein interactions site predictions. The input data for the web-server are a tertiary structure of interest. BindML and BindML+ are available at http://kiharalab.org/bindml/ and http://kiharalab.org/bindml/plus/ .

Protein-Nanoparticle Interactions: Improving Immobilized Lytic Enzyme Activity and Surface Energy Effects

NASA Astrophysics Data System (ADS)

Downs, Emily Elizabeth

Protein-nanostructure conjugates, particularly particles, are a subject of significant interest due to changes in their fundamental behavior compared to bulk surfaces. As the size scale of nano-structured materials and proteins are on the same order of magnitude, nanomaterial properties can heavily influence how proteins adsorb and conform to the surface. Previous work has demonstrated the ability of nanoscale surfaces to modulate protein activity, conformation, and retention by modifying the particle surface curvature, morphology, and surface charge. This work has improved our understanding of the protein material interactions, but a complete understanding is still lacking. The goal of this thesis is to investigate two missing areas of understanding using two distinct systems. The first system utilizes a particle with controlled surface energy to observe the impact of surface energy on protein-particle interactions, while the second system uses a modified Listeria-specific protein to determine how protein structure and flexibility affects protein adsorption and activity on particles. Spherical, amorphous, and uniformly doped Zn-silica particles with tailored surface energies were synthesized to understand the impact of surface energy on protein adsorption behavior. Particle surface energy increased with a decrease in particle size and greater dopant concentrations. Protein adsorption and structural loss increased with both particle size and particle surface energy. Higher surface energies promoted protein-particle association and increased protein unfolding. Particle curvature and protein steric hindrance effects limited adsorption and structural loss on smaller particles. Protein surface charge heterogeneity was also found to be linked to both protein adsorption and unfolding behavior on larger particles. Greater surface charge heterogeneity led to higher adsorption concentrations and multilayer formation. These multilayers transitioned from protein-particle interactions to protein-protein interactions and were thicker with greater surface energy, which resulted in the recovery of secondary structure in the outermost layer. To help understand the impact of protein structure on nano-bio conjugate interactions, a listeria specific protein was used. This system was chosen as it has applications in the food industry in preventing bacterial contamination. The insertion of an amino acid linker between the enzymatic and binding domain of the protein improved the flexibility between domains, leading to increased adsorption, and improved activity in both cell-wall and plating assays. Additionally, linker modified protein incorporated into the silica-polymer nanocomposite showed significant activity in a real-world example of contaminated lettuce. This thesis study has isolated the impact of surface energy and protein flexibility on protein adsorption and structure. Particle surface energy affects adsorbed protein concentration and conformation. Coupled with protein surface charge, surface energy was also found to dictate multilayer thickness. The conformational flexibility of the protein was shown to help in controlling not only protein adsorption concentration but also in retaining protein activity after immobilization. Also, a controllable synthesis method for particles with adjustable surface energy, an ideal platform for studying protein-particle interactions, has been established.

Protein-ligand docking using FFT based sampling: D3R case study.

PubMed

Padhorny, Dzmitry; Hall, David R; Mirzaei, Hanieh; Mamonov, Artem B; Moghadasi, Mohammad; Alekseenko, Andrey; Beglov, Dmitri; Kozakov, Dima

2018-01-01

Fast Fourier transform (FFT) based approaches have been successful in application to modeling of relatively rigid protein-protein complexes. Recently, we have been able to adapt the FFT methodology to treatment of flexible protein-peptide interactions. Here, we report our latest attempt to expand the capabilities of the FFT approach to treatment of flexible protein-ligand interactions in application to the D3R PL-2016-1 challenge. Based on the D3R assessment, our FFT approach in conjunction with Monte Carlo minimization off-grid refinement was among the top performing methods in the challenge. The potential advantage of our method is its ability to globally sample the protein-ligand interaction landscape, which will be explored in further applications.

C-Terminal DxD-Containing Sequences within Paramyxovirus Nucleocapsid Proteins Determine Matrix Protein Compatibility and Can Direct Foreign Proteins into Budding Particles

PubMed Central

Ray, Greeshma; Schmitt, Phuong Tieu

2016-01-01

ABSTRACT Paramyxovirus particles are formed by a budding process coordinated by viral matrix (M) proteins. M proteins coalesce at sites underlying infected cell membranes and induce other viral components, including viral glycoproteins and viral ribonucleoprotein complexes (vRNPs), to assemble at these locations from which particles bud. M proteins interact with the nucleocapsid (NP or N) components of vRNPs, and these interactions enable production of infectious, genome-containing virions. For the paramyxoviruses parainfluenza virus 5 (PIV5) and mumps virus, M-NP interaction also contributes to efficient production of virus-like particles (VLPs) in transfected cells. A DLD sequence near the C-terminal end of PIV5 NP protein was previously found to be necessary for M-NP interaction and efficient VLP production. Here, we demonstrate that 15-residue-long, DLD-containing sequences derived from either the PIV5 or Nipah virus nucleocapsid protein C-terminal ends are sufficient to direct packaging of a foreign protein, Renilla luciferase, into budding VLPs. Mumps virus NP protein harbors DWD in place of the DLD sequence found in PIV5 NP protein, and consequently, PIV5 NP protein is incompatible with mumps virus M protein. A single amino acid change converting DLD to DWD within PIV5 NP protein induced compatibility between these proteins and allowed efficient production of mumps VLPs. Our data suggest a model in which paramyxoviruses share an overall common strategy for directing M-NP interactions but with important variations contained within DLD-like sequences that play key roles in defining M/NP protein compatibilities. IMPORTANCE Paramyxoviruses are responsible for a wide range of diseases that affect both humans and animals. Paramyxovirus pathogens include measles virus, mumps virus, human respiratory syncytial virus, and the zoonotic paramyxoviruses Nipah virus and Hendra virus. Infectivity of paramyxovirus particles depends on matrix-nucleocapsid protein interactions which enable efficient packaging of encapsidated viral RNA genomes into budding virions. In this study, we have defined regions near the C-terminal ends of paramyxovirus nucleocapsid proteins that are important for matrix protein interaction and that are sufficient to direct a foreign protein into budding particles. These results advance our basic understanding of paramyxovirus genome packaging interactions and also have implications for the potential use of virus-like particles as protein delivery tools. PMID:26792745

C-Terminal DxD-Containing Sequences within Paramyxovirus Nucleocapsid Proteins Determine Matrix Protein Compatibility and Can Direct Foreign Proteins into Budding Particles.

PubMed

Ray, Greeshma; Schmitt, Phuong Tieu; Schmitt, Anthony P

2016-01-20

Paramyxovirus particles are formed by a budding process coordinated by viral matrix (M) proteins. M proteins coalesce at sites underlying infected cell membranes and induce other viral components, including viral glycoproteins and viral ribonucleoprotein complexes (vRNPs), to assemble at these locations from which particles bud. M proteins interact with the nucleocapsid (NP or N) components of vRNPs, and these interactions enable production of infectious, genome-containing virions. For the paramyxoviruses parainfluenza virus 5 (PIV5) and mumps virus, M-NP interaction also contributes to efficient production of virus-like particles (VLPs) in transfected cells. A DLD sequence near the C-terminal end of PIV5 NP protein was previously found to be necessary for M-NP interaction and efficient VLP production. Here, we demonstrate that 15-residue-long, DLD-containing sequences derived from either the PIV5 or Nipah virus nucleocapsid protein C-terminal ends are sufficient to direct packaging of a foreign protein, Renilla luciferase, into budding VLPs. Mumps virus NP protein harbors DWD in place of the DLD sequence found in PIV5 NP protein, and consequently, PIV5 NP protein is incompatible with mumps virus M protein. A single amino acid change converting DLD to DWD within PIV5 NP protein induced compatibility between these proteins and allowed efficient production of mumps VLPs. Our data suggest a model in which paramyxoviruses share an overall common strategy for directing M-NP interactions but with important variations contained within DLD-like sequences that play key roles in defining M/NP protein compatibilities. Paramyxoviruses are responsible for a wide range of diseases that affect both humans and animals. Paramyxovirus pathogens include measles virus, mumps virus, human respiratory syncytial virus, and the zoonotic paramyxoviruses Nipah virus and Hendra virus. Infectivity of paramyxovirus particles depends on matrix-nucleocapsid protein interactions which enable efficient packaging of encapsidated viral RNA genomes into budding virions. In this study, we have defined regions near the C-terminal ends of paramyxovirus nucleocapsid proteins that are important for matrix protein interaction and that are sufficient to direct a foreign protein into budding particles. These results advance our basic understanding of paramyxovirus genome packaging interactions and also have implications for the potential use of virus-like particles as protein delivery tools. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Interaction of Erp Protein of Mycobacterium tuberculosis with Rv2212 Enhances Intracellular Survival of Mycobacterium smegmatis.

PubMed

Ganaie, Arsheed Ahmad; Trivedi, Garima; Kaur, Amanpreet; Jha, Sidharth Shankar; Anand, Shashi; Rana, Vibhuti; Singh, Amit; Kumar, Shekhar; Sharma, Charu

2016-10-15

The Mycobacterium tuberculosis exported repetitive protein (RvErp) is a crucial virulence-associated factor as determined by its role in the survival and multiplication of mycobacteria in cultured macrophages and in vivo Although attempts have been made to understand the function of Erp protein, its exact role in Mycobacterium pathogenesis is still elusive. One way to determine this is by searching for novel interactions of RvErp. Using a yeast two-hybrid assay, an adenylyl cyclase (AC), Rv2212, was found to interact with RvErp. The interaction between RvErp and Rv2212 is direct and occurs at the endogenous level. The Erp protein of Mycobacterium smegmatis (MSMEG_6405, or MsErp) interacts neither with Rv2212 nor with Ms_4279, the M. smegmatis homologue of Rv2212. Deletion mutants of Rv2212 revealed its adenylyl cyclase domain to be responsible for the interaction. RvErp enhances Rv2212-mediated cyclic AMP (cAMP) production. Also, the biological significance of the interaction between RvErp and Rv2212 was demonstrated by the enhanced survival of M. smegmatis within THP-1 macrophages. Taken together, these studies address a novel mechanism by which Erp executes its function. RvErp is one of the important virulence factors of M. tuberculosis This study describes a novel function of RvErp protein of M. tuberculosis by identifying Rv2212 as its interacting protein. Rv2212 is an adenylyl cyclase (AC) and produces cAMP, one of the prime second messengers that regulate the intracellular survival of mycobacteria. Therefore, the significance of investigating novel interactions of RvErp is paramount in unraveling the mechanisms governing the intracellular survival of mycobacteria. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Amyloid precursor protein and Presenilin 1 interaction studied by FRET in human H4 cells.

PubMed

Nizzari, Mario; Venezia, Valentina; Bianchini, Paolo; Caorsi, Valentina; Diaspro, Alberto; Repetto, Emanuela; Thellung, Stefano; Corsaro, Alessandro; Carlo, Pia; Schettini, Gennaro; Florio, Tullio; Russo, Claudio

2007-01-01

The mayor pathologic hallmarks of Alzheimer's disease (AD) are senile plaque and neurofibrillary tangles. Senile plaque are primarily made up of deposits of amyloid-beta protein, a proteolytic product derived from the amyloid precursor protein (APP). APP is a transmembrane protein detected into the endoplasmic reticulum, in the Golgi apparatus, at the cell surface, recycled by endocytosis to endosomes, whose physiological function is unclear. Presenilins (PS), are a component of gamma-secretase complex that cleave alpha-CTFs (carboxy-terminal fragment), or beta-CTFs, leaving 40 or 42 amino acids amyloid-beta peptides and 58 or 56 amino acids intracellular domains (AICD). Where the amyloid-beta peptides is generated is not clear. The study of APP-PS interaction in specific cell compartments provides a good opportunity to light upon the molecular mechanisms regulating the activity of the "gamma-secretase complex," and where beta-amyloid is generated. In our study we used a biophysical assay of protein proximity: fluorescence resonance energy transfer (FRET), that can provide information about molecular interactions when two proteins are in the close proximity (<10 nm), to examine the subcellular localization and interaction between APP and PS1 in human neuroglioma cells (H4). Confocal microscopic analysis reveals extensive colocalization in different cells' compartment, and centrosomal or microtubule organizing center (MTOC) localization of APP and PS1, but not necessarily a close molecular interaction. We used FRET to determine if APP and PS1 interact at the cell centrosome. FRET data suggest a close interaction between APP and PS1 in subcellular compartments and at the centrosome of H4 cells. Using this approach we show that APP and PS1 are closely associated in the centrosomes of the H4 cell.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

PubMed

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-06-27

A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information

PubMed Central

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-01-01

Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN. PMID:19558694

Interactions of cullin3/KCTD5 complexes with both cytoplasmic and nuclear proteins: Evidence for a role in protein stabilization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rutz, Natalja; Heilbronn, Regine; Weger, Stefan, E-mail: stefan.weger@charite.de

2015-08-28

Based on its specific interaction with cullin3 mediated by an N-terminal BTB/POZ homologous domain, KCTD5 has been proposed to function as substrate adapter for cullin3 based ubiquitin E3 ligases. In the present study we tried to validate this hypothesis through identification and characterization of additional KCTD5 interaction partners. For the replication protein MCM7, the zinc finger protein ZNF711 and FAM193B, a yet poorly characterized cytoplasmic protein, we could demonstrate specific interaction with KCTD5 both in yeast two-hybrid and co-precipitation studies in mammalian cells. Whereas trimeric complexes of cullin3 and KCTD5 with the respective KCTD5 binding partner were formed, KCTD5/cullin3 inducedmore » polyubiquitylation and/or proteasome-dependent degradation of these binding partners could not be demonstrated. On the contrary, KCTD5 or Cullin3 overexpression increased ZNF711 protein stability. - Highlights: • KCTD5 nuclear translocation depends upon M phase and protein oligomerization. • Identification of MCM7, ZNF711 and FAM193 as KCTD5 interaction partners. • Formation of trimeric complexes of KCTD5/cullin3 with MCM7, ZNF711 and FAM193B. • KCTD5 is not involved in polyubiquitylation of MCM7 replication factor. • The KCTD5/cullin3 complex stabilizes ZNF711 transcription factor.« less

Super-resolution imaging and tracking of protein–protein interactions in sub-diffraction cellular space

PubMed Central

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-01-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein–protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB–EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB–EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB–EF-Tu interactions. PMID:25030837

Analysis of Protein-DNA Interaction by Chromatin Immunoprecipitation and DNA Tiling Microarray (ChIP-on-chip).

PubMed

Gao, Hui; Zhao, Chunyan

2018-01-01

Chromatin immunoprecipitation (ChIP) has become the most effective and widely used tool to study the interactions between specific proteins or modified forms of proteins and a genomic DNA region. Combined with genome-wide profiling technologies, such as microarray hybridization (ChIP-on-chip) or massively parallel sequencing (ChIP-seq), ChIP could provide a genome-wide mapping of in vivo protein-DNA interactions in various organisms. Here, we describe a protocol of ChIP-on-chip that uses tiling microarray to obtain a genome-wide profiling of ChIPed DNA.

In silico study of protein to protein interaction analysis of AMP-activated protein kinase and mitochondrial activity in three different farm animal species

NASA Astrophysics Data System (ADS)

Prastowo, S.; Widyas, N.

2018-03-01

AMP-activated protein kinase (AMPK) is cellular energy censor which works based on ATP and AMP concentration. This protein interacts with mitochondria in determine its activity to generate energy for cell metabolism purposes. For that, this paper aims to compare the protein to protein interaction of AMPK and mitochondrial activity genes in the metabolism of known animal farm (domesticated) that are cattle (Bos taurus), pig (Sus scrofa) and chicken (Gallus gallus). In silico study was done using STRING V.10 as prominent protein interaction database, followed with biological function comparison in KEGG PATHWAY database. Set of genes (12 in total) were used as input analysis that are PRKAA1, PRKAA2, PRKAB1, PRKAB2, PRKAG1, PRKAG2, PRKAG3, PPARGC1, ACC, CPT1B, NRF2 and SOD. The first 7 genes belong to gene in AMPK family, while the last 5 belong to mitochondrial activity genes. The protein interaction result shows 11, 8 and 5 metabolism pathways in Bos taurus, Sus scrofa and Gallus gallus, respectively. The top pathway in Bos taurus is AMPK signaling pathway (10 genes), Sus scrofa is Adipocytokine signaling pathway (8 genes) and Gallus gallus is FoxO signaling pathway (5 genes). Moreover, the common pathways found in those 3 species are Adipocytokine signaling pathway, Insulin signaling pathway and FoxO signaling pathway. Genes clustered in Adipocytokine and Insulin signaling pathway are PRKAA2, PPARGC1A, PRKAB1 and PRKAG2. While, in FoxO signaling pathway are PRKAA2, PRKAB1, PRKAG2. According to that, we found PRKAA2, PRKAB1 and PRKAG2 are the common genes. Based on the bioinformatics analysis, we can demonstrate that protein to protein interaction shows distinct different of metabolism in different species. However, further validation is needed to give a clear explanation.

Carbon Nanotubes Facilitate Oxidation of Cysteine Residues of Proteins.

PubMed

Hirano, Atsushi; Kameda, Tomoshi; Wada, Momoyo; Tanaka, Takeshi; Kataura, Hiromichi

2017-10-19

The adsorption of proteins onto nanoparticles such as carbon nanotubes (CNTs) governs the early stages of nanoparticle uptake into biological systems. Previous studies regarding these adsorption processes have primarily focused on the physical interactions between proteins and nanoparticles. In this study, using reduced lysozyme and intact human serum albumin in aqueous solutions, we demonstrated that CNTs interact chemically with proteins. The CNTs induce the oxidation of cysteine residues of the proteins, which is accounted for by charge transfer from the sulfhydryl groups of the cysteine residues to the CNTs. The redox reaction simultaneously suppresses the intermolecular association of proteins via disulfide bonds. These results suggest that CNTs can affect the folding and oxidation degree of proteins in biological systems such as blood and cytosol.

Dynamics, Conformational Entropy, and Frustration in Protein-Protein Interactions Involving an Intrinsically Disordered Protein Domain.

PubMed

Lindström, Ida; Dogan, Jakob

2018-05-18

Intrinsically disordered proteins (IDPs) are abundant in the eukaryotic proteome. However, little is known about the role of subnanosecond dynamics and the conformational entropy that it represents in protein-protein interactions involving IDPs. Using nuclear magnetic resonance side chain and backbone relaxation, stopped-flow kinetics, isothermal titration calorimetry, and computational studies, we have characterized the interaction between the globular TAZ1 domain of the CREB binding protein and the intrinsically disordered transactivation domain of STAT2 (TAD-STAT2). We show that the TAZ1/TAD-STAT2 complex retains considerable subnanosecond motions, with TAD-STAT2 undergoing only a partial disorder-to-order transition. We report here the first experimental determination of the conformational entropy change for both binding partners in an IDP binding interaction and find that the total change even exceeds in magnitude the binding enthalpy and is comparable to the contribution from the hydrophobic effect, demonstrating its importance in the binding energetics. Furthermore, we show that the conformational entropy change for TAZ1 is also instrumental in maintaining a biologically meaningful binding affinity. Strikingly, a spatial clustering of very high amplitude motions and a cluster of more rigid sites in the complex exist, which through computational studies we found to overlap with regions that experience energetic frustration and are less frustrated, respectively. Thus, the residual dynamics in the bound state could be necessary for faster dissociation, which is important for proteins that interact with multiple binding partners.

Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics.

PubMed

Sun, Kaiwen; Zheng, Yuyu; Zhu, Ziqiang

2017-11-20

Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel protein-protein interaction pairs and monitoring protein interaction dynamics are of particular interest for revealing how plants respond to environmental factors and/or developmental signals. A plethora of approaches have been developed to examine protein-protein interactions, either in vitro or in vivo. Among them, the recently established luciferase complementation imaging (LCI) assay is the simplest and fastest method for demonstrating in vivo protein-protein interactions. In this assay, protein A or protein B is fused with the amino-terminal or carboxyl-terminal half of luciferase, respectively. When protein A interacts with protein B, the two halves of luciferase will be reconstituted to form a functional and active luciferase enzyme. Luciferase activity can be recorded with a luminometer or CCD-camera. Compared with other approaches, the LCI assay shows protein-protein interactions both qualitatively and quantitatively. Agrobacterium infiltration in Nicotiana benthamiana leaves is a widely used system for transient protein expression. With the combination of LCI and transient expression, these approaches show that the physical interaction between COP1 and SPA1 was gradually reduced after jasmonate treatment.

Interaction between dimer interface residues of native and mutated SOD1 protein: a theoretical study.

PubMed

Keerthana, S P; Kolandaivel, P

2015-04-01

Cu-Zn superoxide dismutase 1 (SOD1) is a highly conserved bimetallic protein enzyme, used for the scavenging the superoxide radicals (O2 (-)) produced due to aerobic metabolism in the mitochondrial respiratory chain. Over 100 mutations have been identified and found to be in the homodimeric structure of SOD1. The enzyme has to be maintained in its dimeric state for the structural stability and enzymatic activity. From our investigation, we found that the mutations apart from the dimer interface residues are found to affect the dimer stability of protein and hence enhancing the aggregation and misfolding tendency of mutated protein. The homodimeric state of SOD1 is found to be held together by the non-covalent interactions. The molecular dynamics simulation has been used to study the hydrogen bond interactions between the dimer interface residues of the monomers in native and mutated forms of SOD1 in apo- and holo-states. The results obtained by this analysis reveal the fact that the loss of hydrogen bond interactions between the monomers of the dimer is responsible for the reduced stability of the apo- and holo-mutant forms of SOD1. The conformers with dimer interface residues in native and mutated protein obtained by the molecular dynamics simulation is subjected to quantum mechanical study using M052X/6-31G(d) level of theory. The charge transfer between N-H···O interactions in the dimer interface residues were studied. The weak interaction between the monomers of the dimer accounts for the reduced dimerization and enhanced deformation energy in the mutated SOD1 protein.

Interaction between two adapter proteins, PAG and EBP50: a possible link between membrane rafts and actin cytoskeleton.

PubMed

Brdicková, N; Brdicka, T; Andera, L; Spicka, J; Angelisová, P; Milgram, S L; Horejsí, V

2001-10-26

Phosphoprotein associated with GEMs (PAG), also known as Csk-binding protein (Cbp), is a broadly expressed palmitoylated transmembrane adapter protein found in membrane rafts, also called GEMs (glycosphingolipid-enriched membrane microdomains). PAG is known to bind and activate the essential regulator of Src-family kinases, cytoplasmic protein tyrosine kinase Csk. In the present study we used the yeast 2-hybrid system to search for additional proteins which might bind to PAG. We have identified the abundant cytoplasmic adapter protein EBP50 (ezrin/radixin/moesin (ERM)-binding phosphoprotein of 50 kDa), also known as NHERF (Na(+)/H(+) exchanger regulatory factor), as a specific PAG-binding partner. The interaction involves the C-terminal sequence (TRL) of PAG and N-terminal PDZ domain(s) of EBP50. As EBP50 is known to interact via its C-terminal domain with the ERM-family proteins, which in turn bind to actin cytoskeleton, the PAG-EBP50 interaction may be important for connecting membrane rafts to the actin cytoskeleton.

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904