TULIPs: tunable, light-controlled interacting protein tags for cell biology.

PubMed

Strickland, Devin; Lin, Yuan; Wagner, Elizabeth; Hope, C Matthew; Zayner, Josiah; Antoniou, Chloe; Sosnick, Tobin R; Weiss, Eric L; Glotzer, Michael

2012-03-04

Naturally photoswitchable proteins offer a means of directly manipulating the formation of protein complexes that drive a diversity of cellular processes. We developed tunable light-inducible dimerization tags (TULIPs) based on a synthetic interaction between the LOV2 domain of Avena sativa phototropin 1 (AsLOV2) and an engineered PDZ domain (ePDZ). TULIPs can recruit proteins to diverse structures in living yeast and mammalian cells, either globally or with precise spatial control using a steerable laser. The equilibrium binding and kinetic parameters of the interaction are tunable by mutation, making TULIPs readily adaptable to signaling pathways with varying sensitivities and response times. We demonstrate the utility of TULIPs by conferring light sensitivity to functionally distinct components of the yeast mating pathway and by directing the site of cell polarization.

RAID: a comprehensive resource for human RNA-associated (RNA-RNA/RNA-protein) interaction.

PubMed

Zhang, Xiaomeng; Wu, Deng; Chen, Liqun; Li, Xiang; Yang, Jinxurong; Fan, Dandan; Dong, Tingting; Liu, Mingyue; Tan, Puwen; Xu, Jintian; Yi, Ying; Wang, Yuting; Zou, Hua; Hu, Yongfei; Fan, Kaili; Kang, Juanjuan; Huang, Yan; Miao, Zhengqiang; Bi, Miaoman; Jin, Nana; Li, Kongning; Li, Xia; Xu, Jianzhen; Wang, Dong

2014-07-01

Transcriptomic analyses have revealed an unexpected complexity in the eukaryote transcriptome, which includes not only protein-coding transcripts but also an expanding catalog of noncoding RNAs (ncRNAs). Diverse coding and noncoding RNAs (ncRNAs) perform functions through interaction with each other in various cellular processes. In this project, we have developed RAID (http://www.rna-society.org/raid), an RNA-associated (RNA-RNA/RNA-protein) interaction database. RAID intends to provide the scientific community with all-in-one resources for efficient browsing and extraction of the RNA-associated interactions in human. This version of RAID contains more than 6100 RNA-associated interactions obtained by manually reviewing more than 2100 published papers, including 4493 RNA-RNA interactions and 1619 RNA-protein interactions. Each entry contains detailed information on an RNA-associated interaction, including RAID ID, RNA/protein symbol, RNA/protein categories, validated method, expressing tissue, literature references (Pubmed IDs), and detailed functional description. Users can query, browse, analyze, and manipulate RNA-associated (RNA-RNA/RNA-protein) interaction. RAID provides a comprehensive resource of human RNA-associated (RNA-RNA/RNA-protein) interaction network. Furthermore, this resource will help in uncovering the generic organizing principles of cellular function network. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

PubMed Central

Engin, H. Billur; Guney, Emre; Keskin, Ozlem; Oliva, Baldo; Gursoy, Attila

2013-01-01

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the “guilt-by-association” principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis. PMID:24278371

Exploring protein-DNA interactions in 3D using in situ construction, manipulation, and visualization of individual DNA-dumbbells with optical traps, microfluidics, and fluorescence microscopy

PubMed Central

Forget, Anthony L.; Dombrowski, Christopher C.; Amitani, Ichiro; Kowalczykowski, Stephen C.

2015-01-01

In this Protocol, we describe a procedure to generate ‘DNA-dumbbells’ — single molecules of DNA with a microscopic bead attached at each end — and techniques for manipulating individual DNA-dumbbells. We also detail the design and fabrication of a microfluidic device (flow cell) used in conjunction with dual optical trapping to manipulate DNA-dumbbells and to visualize individual protein–DNA complexes by single-molecule epifluorescence microscopy. Our design of the flow cell enables the rapid movement of trapped molecules between laminar flow channels and a flow-free ‘reservoir’. The reservoir provides the means to examine formation of DNA–protein complexes in solution in the absence of external flow forces, while still maintaining a predetermined end-to-end extension of the DNA. These features facilitate examination of the role of three-dimensional DNA conformation and dynamics in protein–DNA interactions. Preparation of flow cells and reagents requires two days each; in situ DNA-dumbbell assembly and imaging of single protein–DNA complexes requires another day. PMID:23411634

Non-interacting surface solvation and dynamics in protein-protein interactions.

PubMed

Visscher, Koen M; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

2015-03-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein-protein binding, even for simple lock-and-key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein-protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein-protein surfaces. We compare properties of the interface, rim, and non-interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non-interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non-interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein-protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein-protein complexes from unintended protein-protein interactions. © 2014 Wiley Periodicals, Inc.

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.

Experimental evolution of protein–protein interaction networks

PubMed Central

Kaçar, Betül; Gaucher, Eric A.

2013-01-01

The modern synthesis of evolutionary theory and genetics has enabled us to discover underlying molecular mechanisms of organismal evolution. We know that in order to maximize an organism's fitness in a particular environment, individual interactions among components of protein and nucleic acid networks need to be optimized by natural selection, or sometimes through random processes, as the organism responds to changes and/or challenges in the environment. Despite the significant role of molecular networks in determining an organism's adaptation to its environment, we still do not know how such inter- and intra-molecular interactions within networks change over time and contribute to an organism's evolvability while maintaining overall network functions. One way to address this challenge is to identify connections between molecular networks and their host organisms, to manipulate these connections, and then attempt to understand how such perturbations influence molecular dynamics of the network and thus influence evolutionary paths and organismal fitness. In the present review, we discuss how integrating evolutionary history with experimental systems that combine tools drawn from molecular evolution, synthetic biology and biochemistry allow us to identify the underlying mechanisms of organismal evolution, particularly from the perspective of protein interaction networks. PMID:23849056

Interaction entropy for protein-protein binding

NASA Astrophysics Data System (ADS)

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

2017-03-01

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 interaction entropy 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 interaction entropy 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.

Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta

PubMed Central

Kleffner, Robert; Flatten, Jeff; Leaver-Fay, Andrew; Baker, David; Siegel, Justin B.; Khatib, Firas; Cooper, Seth

2017-01-01

Abstract Summary: Foldit Standalone is an interactive graphical interface to the Rosetta molecular modeling package. In contrast to most command-line or batch interactions with Rosetta, Foldit Standalone is designed to allow easy, real-time, direct manipulation of protein structures, while also giving access to the extensive power of Rosetta computations. Derived from the user interface of the scientific discovery game Foldit (itself based on Rosetta), Foldit Standalone has added more advanced features and removed the competitive game elements. Foldit Standalone was built from the ground up with a custom rendering and event engine, configurable visualizations and interactions driven by Rosetta. Foldit Standalone contains, among other features: electron density and contact map visualizations, multiple sequence alignment tools for template-based modeling, rigid body transformation controls, RosettaScripts support and an embedded Lua interpreter. Availability and Implementation: Foldit Standalone is available for download at https://fold.it/standalone, under the Rosetta license, which is free for academic and non-profit users. It is implemented in cross-platform C ++ and binary executables are available for Windows, macOS and Linux. Contact: scooper@ccs.neu.edu PMID:28481970

Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta.

PubMed

Kleffner, Robert; Flatten, Jeff; Leaver-Fay, Andrew; Baker, David; Siegel, Justin B; Khatib, Firas; Cooper, Seth

2017-09-01

Foldit Standalone is an interactive graphical interface to the Rosetta molecular modeling package. In contrast to most command-line or batch interactions with Rosetta, Foldit Standalone is designed to allow easy, real-time, direct manipulation of protein structures, while also giving access to the extensive power of Rosetta computations. Derived from the user interface of the scientific discovery game Foldit (itself based on Rosetta), Foldit Standalone has added more advanced features and removed the competitive game elements. Foldit Standalone was built from the ground up with a custom rendering and event engine, configurable visualizations and interactions driven by Rosetta. Foldit Standalone contains, among other features: electron density and contact map visualizations, multiple sequence alignment tools for template-based modeling, rigid body transformation controls, RosettaScripts support and an embedded Lua interpreter. Foldit Standalone is available for download at https://fold.it/standalone , under the Rosetta license, which is free for academic and non-profit users. It is implemented in cross-platform C ++ and binary executables are available for Windows, macOS and Linux. scooper@ccs.neu.edu. © The Author(s) 2017. Published by Oxford University Press.

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

Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

PubMed Central

Khor, Susan

2014-01-01

Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

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

Revealing Abrupt and Spontaneous Ruptures of Protein Native Structure under picoNewton Compressive Force Manipulation.

PubMed

Chowdhury, S Roy; Cao, Jin; He, Yufan; Lu, H Peter

2018-03-27

Manipulating protein conformations for exploring protein structure-function relationship has shown great promise. Although protein conformational changes under pulling force manipulation have been extensively studied, protein conformation changes under a compressive force have not been explored quantitatively. The latter is even more biologically significant and relevant in revealing protein functions in living cells associated with protein crowdedness, distribution fluctuations, and cell osmotic stress. Here we report our experimental observations on abrupt ruptures of protein native structures under compressive force, demonstrated and studied by single-molecule AFM-FRET spectroscopic nanoscopy. Our results show that the protein ruptures are abrupt and spontaneous events occurred when the compressive force reaches a threshold of 12-75 pN, a force amplitude accessible from thermal fluctuations in a living cell. The abrupt ruptures are sensitive to local environment, likely a general and important pathway of protein unfolding in living cells.

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.

Nanoparticle-mediated local and remote manipulation of protein aggregation.

PubMed

Kogan, Marcelo J; Bastus, Neus G; Amigo, Roger; Grillo-Bosch, Dolors; Araya, Eyleen; Turiel, Antonio; Labarta, Amilcar; Giralt, Ernest; Puntes, Victor F

2006-01-01

The local heat delivered by metallic nanoparticles selectively attached to their target can be used as a molecular surgery to safely remove toxic and clogging aggregates. We apply this principle to protein aggregates, in particular to the amyloid beta protein (Abeta) involved in Alzheimer's disease (AD), a neurodegenerative disease where unnaturally folded Abeta proteins self-assemble and deposit forming amyloid fibrils and plaques. We show the possibility to remotely redissolve these deposits and to interfere with their growth, using the local heat dissipated by gold nanoparticles (AuNP) selectively attached to the aggregates and irradiated with low gigahertz electromagnetic fields. Simultaneous tagging and manipulation by AuNP of Abeta at different stages of aggregation allow both, noninvasive exploration and dissolution of molecular aggregates.

Identifying Protein-protein Interaction in Drosophila Adult Heads by Tandem Affinity Purification (TAP)

PubMed Central

Tian, Xiaolin; Zhu, Mingwei; Li, Long; Wu, Chunlai

2013-01-01

Genetic screens conducted using Drosophila melanogaster (fruit fly) have made numerous milestone discoveries in the advance of biological sciences. However, the use of biochemical screens aimed at extending the knowledge gained from genetic analysis was explored only recently. Here we describe a method to purify the protein complex that associates with any protein of interest from adult fly heads. This method takes advantage of the Drosophila GAL4/UAS system to express a bait protein fused with a Tandem Affinity Purification (TAP) tag in fly neurons in vivo, and then implements two rounds of purification using a TAP procedure similar to the one originally established in yeast1 to purify the interacting protein complex. At the end of this procedure, a mixture of multiple protein complexes is obtained whose molecular identities can be determined by mass spectrometry. Validation of the candidate proteins will benefit from the resource and ease of performing loss-of-function studies in flies. Similar approaches can be applied to other fly tissues. We believe that the combination of genetic manipulations and this proteomic approach in the fly model system holds tremendous potential for tackling fundamental problems in the field of neurobiology and beyond. PMID:24335807

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

Electrical manipulation of glycan-phosphatidyl inositol-tethered proteins in planar supported bilayers.

PubMed Central

Groves, J T; Wülfing, C; Boxer, S G

1996-01-01

Electric fields have been used to manipulate and concentrate glycan-phosphatidyl inositol (GPI)-tethered proteins in planar supported bilayers. Naturally GPI-linked CD48, along with engineered forms of I-Ek and B7-2, in which their transmembrane domains have been genetically replaced with the GPI linkage, were studied. The proteins were labeled with fluorescently tagged antibodies, allowing the electric field-induced behavior to be followed by epifluorescence microscopy. All three protein complexes were observed to migrate toward the cathode with the B7-2 and CD48, each tethered to the membrane by a single GPI linker, moving significantly faster than the I-Ek, which has two GPI linkers. Patterns scratched into the membrane function as barriers to lateral diffusion and were used to isolate the proteins into highly concentrated corrals. All field-induced concentration profiles were completely reversible, indicating that the supported bilayer provides a stable, fluid environment in which GPI-tethered proteins can be manipulated. The ability to electrically control the spatial distribution of membrane-tethered proteins provides new opportunities for the study of biological membranes and the development of membrane-based devices. Images FIGURE 2 FIGURE 3 FIGURE 4 FIGURE 5 FIGURE 6 PMID:8913608

R Script Approach to Infer Toxoplasma Infection Mechanisms From Microarrays and Domain-Domain Protein Interactions

PubMed Central

Arenas, Ailan F; Salcedo, Gladys E; Gomez-Marin, Jorge E

2017-01-01

Pathogen-host protein-protein interaction systems examine the interactions between the protein repertoires of 2 distinct organisms. Some of these pathogen proteins interact with the host protein system and may manipulate it for their own advantages. In this work, we designed an R script by concatenating 2 functions called rowDM and rowCVmed to infer pathogen-host interaction using previously reported microarray data, including host gene enrichment analysis and the crossing of interspecific domain-domain interactions. We applied this script to the Toxoplasma-host system to describe pathogen survival mechanisms from human, mouse, and Toxoplasma Gene Expression Omnibus series. Our outcomes exhibited similar results with previously reported microarray analyses, but we found other important proteins that could contribute to toxoplasma pathogenesis. We observed that Toxoplasma ROP38 is the most differentially expressed protein among toxoplasma strains. Enrichment analysis and KEGG mapping indicated that the human retinal genes most affected by Toxoplasma infections are those related to antiapoptotic mechanisms. We suggest that proteins PIK3R1, PRKCA, PRKCG, PRKCB, HRAS, and c-JUN could be the possible substrates for differentially expressed Toxoplasma kinase ROP38. Likewise, we propose that Toxoplasma causes overexpression of apoptotic suppression human genes. PMID:29317802

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.

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.

Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H

2016-12-01

Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

Insights into the immune manipulation mechanisms of pollen allergens by protein domain profiling.

PubMed

Patel, Seema; Rani, Aruna; Goyal, Arun

2017-10-01

Plant pollens are airborne allergens, as their inhalation causes immune activation, leading to rhinitis, conjunctivitis, sinusitis and oral allergy syndrome. A myriad of pollen proteins belonging to profilin, expansin, polygalacturonase, glucan endoglucosidase, pectin esterase, and lipid transfer protein class have been identified. In the present in silico study, the protein domains of fifteen pollen sequences were extracted from the UniProt database and submitted to the interactive web tool SMART (Simple Modular Architecture Research Tool), for finding the protein domain profiles. Analysis of the data based on custom-made scripts revealed the conservation of pathogenic domains such as OmpH, PROF, PreSET, Bet_v_1, Cpl-7 and GAS2. Further, the retention of critical domains like CHASE2, Galanin, Dak2, DALR_1, HAMP, PWI, EFh, Excalibur, CT, PbH1, HELICc, and Kelch in pollen proteins, much like cockroach allergens and lethal viruses (such as HIV, HCV, Ebola, Dengue and Zika) was observed. Based on the shared motifs in proteins of taxonomicall-ydispersed organisms, it can be hypothesized that allergens and pathogens manipulate the human immune system in a similar manner. Allergens, being inanimate, cannot replicate in human body, and are neutralized by immune system. But, when the allergens are unremitting, the immune system becomes persistently hyper-sensitized, creating an inflammatory milieu. This study is expected to contribute to the understanding of pollen allergenicity and pathogenicity. Copyright © 2017 Elsevier Ltd. All rights reserved.

MOLECULAR DESIGNER: an interactive program for the display of protein structure on the IBM-PC.

PubMed

Hannon, G J; Jentoft, J E

1985-09-01

A BASIC interactive graphics program has been developed for the IBM-PC which utilizes the graphics capabilities of that computer to display and manipulate protein structure from coordinates. Structures may be generated from typed files, or from Brookhaven National Laboratories' Protein Data Bank data tapes. Once displayed, images may be rotated, translated and expanded to any desired size. Figures may be viewed as ball-and-stick or space-filling models. Calculated multiple-point perspective may also be added to the display. Docking manipulations are possible since more than a single figure may be displayed and manipulated simultaneously. Further, stereo images and red/blue three-dimensional images may be generated using the accompanying DESIPLOT program and an HP-7475A plotter. A version of the program is also currently available for the Apple Macintosh. Full implementation on the Macintosh requires 512 K and at least one disk drive. Otherwise this version is essentially identical to the IBM-PC version described herein.

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

PubMed Central

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

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/.

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

PubMed

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web

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.

Combining NMR and Molecular Dynamics Studies for Insights into the Allostery of Small GTPase–Protein Interactions

PubMed Central

Zhang, Liqun; Bouguet-Bonnet, Sabine; Buck, Matthias

2014-01-01

Combinations of experimentally derived data from nuclear magnetic resonance spectroscopy and analyses of molecular dynamics trajectories increasingly allow us to obtain a detailed description of the molecular mechanisms by which proteins function in signal transduction. This chapter provides an introduction into these two methodologies, illustrated by example of a small GTPase–effector interaction. It is increasingly becoming clear that new insights are provided by the combination of experimental and computational methods. Understanding the structural and protein dynamical contributions to allostery will be useful for the engineering of new binding interfaces and protein functions, as well as for the design/in silico screening of chemical agents that can manipulate the function of small GTPase–protein interactions in diseases such as cancer. PMID:22052494

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.

Rigid-Docking Approaches to Explore Protein-Protein Interaction Space.

PubMed

Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ohue, Masahito; Akiyama, Yutaka

Protein-protein interactions play core roles in living cells, especially in the regulatory systems. As information on proteins has rapidly accumulated on publicly available databases, much effort has been made to obtain a better picture of protein-protein interaction networks using protein tertiary structure data. Predicting relevant interacting partners from their tertiary structure is a challenging task and computer science methods have the potential to assist with this. Protein-protein rigid docking has been utilized by several projects, docking-based approaches having the advantages that they can suggest binding poses of predicted binding partners which would help in understanding the interaction mechanisms and that comparing docking results of both non-binders and binders can lead to understanding the specificity of protein-protein interactions from structural viewpoints. In this review we focus on explaining current computational prediction methods to predict pairwise direct protein-protein interactions that form protein complexes.

Manipulating heat shock protein expression in laboratory animals.

PubMed

Tolson, J Keith; Roberts, Stephen M

2005-02-01

Upregulation of heat shock proteins (Hsps) has been observed to impart resistance to a wide variety of physical and chemical insults. Elucidation of the role of Hsps in cellular defense processes depends, in part, on the ability to manipulate Hsp expression in laboratory animals. Simple methods of inducing whole body hyperthermia, such as warm water immersion or heating pad application, are effective in producing generalized expression of Hsps. Hsps can be upregulated locally with focused direct or indirect heating, such as with ultrasound or with laser or microwave radiation. Increased Hsp expression in response to toxic doses of xenobiotics has been commonly observed. Some pharmacologic agents are capable of altering Hsps more specifically by affecting processes involved in Hsp regulation. Gene manipulation offers the ability to selectively increase or decrease individual Hsps. Knockout mouse strains and Hsp-overexpressing transgenics have been used successfully to examine the role of specific Hsps in protection against hyperthermia, chemical insults, and ischemia-reperfusion injury. Gene therapy approaches also offer the possibility of selective alteration of Hsp expression. Some methods of increasing Hsp expression have application in specialized areas of research, such cold response, myocardial protection from exercise, and responses to stressful or traumatic stimuli. Each method of manipulating Hsp expression in laboratory animals has advantages and disadvantages, and selection of the best method depends upon the experimental objectives (e.g., the alteration in Hsp expression needed, its timing, and its location) and resources available.

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

Kindergarten Children's Interactions with Touchscreen Mathematics Virtual Manipulatives: An Innovative Mixed Methods Analysis

ERIC Educational Resources Information Center

Tucker, Stephen I.; Lommatsch, Christina W.; Moyer-Packenham, Patricia S.; Anderson-Pence, Katie L.; Symanzik, Jürgen

2017-01-01

The purpose of this study was to examine patterns of mathematical practices evident during children's interactions with touchscreen mathematics virtual manipulatives. Researchers analyzed 33 Kindergarten children's interactions during activities involving apps featuring mathematical content of early number sense or quantity in base ten, recorded…

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.

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.

Protein- protein interaction detection system using fluorescent protein microdomains

DOEpatents

Waldo, Geoffrey S.; Cabantous, Stephanie

2010-02-23

The invention provides a protein labeling and interaction detection system based on engineered fragments of fluorescent and chromophoric proteins that require fused interacting polypeptides to drive the association of the fragments, and further are soluble and stable, and do not change the solubility of polypeptides to which they are fused. In one embodiment, a test protein X is fused to a sixteen amino acid fragment of GFP (.beta.-strand 10, amino acids 198-214), engineered to not perturb fusion protein solubility. A second test protein Y is fused to a sixteen amino acid fragment of GFP (.beta.-strand 11, amino acids 215-230), engineered to not perturb fusion protein solubility. When X and Y interact, they bring the GFP strands into proximity, and are detected by complementation with a third GFP fragment consisting of GFP amino acids 1-198 (strands 1-9). When GFP strands 10 and 11 are held together by interaction of protein X and Y, they spontaneous association with GFP strands 1-9, resulting in structural complementation, folding, and concomitant GFP fluorescence.

Manipulator interactive design with interconnected flexible elements

NASA Technical Reports Server (NTRS)

Singh, R. P.; Likins, P. W.

1983-01-01

This paper describes the development of an analysis tool for the interactive design of control systems for manipulators and similar electro-mechanical systems amenable to representation as structures in a topological chain. The chain consists of a series of elastic bodies subject to small deformations and arbitrary displacements. The bodies are connected by hinges which permit kinematic constraints, control, or relative motion with six degrees of freedom. The equations of motion for the chain configuration are derived via Kane's method, extended for application to interconnected flexible bodies with time-varying boundary conditions. A corresponding set of modal coordinates has been selected. The motion equations are imbedded within a simulation that transforms the vector-dyadic equations into scalar form for numerical integration. The simulation also includes a linear, time-invariant controler specified in transfer function format and a set of sensors and actuators that interface between the structure and controller. The simulation is driven by an interactive set-up program resulting in an easy-to-use analysis tool.

The critical protein interactions and structures that elicit growth deregulation in cancer and viral replication

PubMed Central

Ou, Horng D.; May, Andrew P.

2010-01-01

One of the greatest challenges in biomedicine is to define the critical targets and network interactions that are subverted to elicit growth deregulation in human cells. Understanding and developing rational treatments for cancer requires a definition of the key molecular targets and how they interact to elicit the complex growth deregulation phenotype. Viral proteins provide discerning and powerful probes to understand both how cells work and how they can be manipulated using a minimal number of components. The small DNA viruses have evolved to target inherent weaknesses in cellular protein interaction networks to hijack the cellular DNA and protein replication machinery. In the battle to escape the inevitability of senescence and programmed cell death, cancers have converged on similar mechanisms, through the acquisition and selection of somatic mutations that drive unchecked cellular replication in tumors. Understanding the dynamic mechanisms through which a minimal number of viral proteins promote host cells to undergo unscheduled and pathological replication is a powerful strategy to identify critical targets that are also disrupted in cancer. Viruses can therefore be used as tools to probe the system-wide protein-protein interactions and structures that drive growth deregulation in human cells. Ultimately this can provide a path for developing system context-dependent therapeutics. This review will describe ongoing experimental approaches using viruses to study pathways deregulated in cancer, with a particular focus on viral cellular protein-protein interactions and structures. PMID:21061422

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

Optical manipulation of the alpha subunits of heterotrimeric G proteins using photoswitchable dimerization systems

PubMed Central

Yu, Gaigai; Onodera, Hiroyuki; Aono, Yuki; Kawano, Fuun; Ueda, Yoshibumi; Furuya, Akihiro; Suzuki, Hideyuki; Sato, Moritoshi

2016-01-01

Alpha subunits of heterotrimeric G proteins (Gα) are involved in a variety of cellular functions. Here we report an optogenetic strategy to spatially and temporally manipulate Gα in living cells. More specifically, we applied the blue light-induced dimerization system, known as the Magnet system, and an alternative red light-induced dimerization system consisting of Arabidopsis thaliana phytochrome B (PhyB) and phytochrome-interacting factor 6 (PIF6) to optically control the activation of two different classes of Gα (Gαq and Gαs). By utilizing this strategy, we demonstrate successful regulation of Ca2+ and cAMP using light in mammalian cells. The present strategy is generally applicable to different kinds of Gα and could contribute to expanding possibilities of spatiotemporal regulation of Gα in mammalian cells. PMID:27767077

Quantifying protein-protein interactions in high throughput using protein domain microarrays.

PubMed

Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

2010-04-01

Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

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.

Noninvasive imaging of protein-protein interactions in living animals

NASA Astrophysics Data System (ADS)

Luker, Gary D.; Sharma, Vijay; Pica, Christina M.; Dahlheimer, Julie L.; Li, Wei; Ochesky, Joseph; Ryan, Christine E.; Piwnica-Worms, Helen; Piwnica-Worms, David

2002-05-01

Protein-protein interactions control transcription, cell division, and cell proliferation as well as mediate signal transduction, oncogenic transformation, and regulation of cell death. Although a variety of methods have been used to investigate protein interactions in vitro and in cultured cells, none can analyze these interactions in intact, living animals. To enable noninvasive molecular imaging of protein-protein interactions in vivo by positron-emission tomography and fluorescence imaging, we engineered a fusion reporter gene comprising a mutant herpes simplex virus 1 thymidine kinase and green fluorescent protein for readout of a tetracycline-inducible, two-hybrid system in vivo. By using micro-positron-emission tomography, interactions between p53 tumor suppressor and the large T antigen of simian virus 40 were visualized in tumor xenografts of HeLa cells stably transfected with the imaging constructs. Imaging protein-binding partners in vivo will enable functional proteomics in whole animals and provide a tool for screening compounds targeted to specific protein-protein interactions in living animals.

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.

Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

PubMed

Wuchty, Stefan

2006-05-23

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

Exploring novel structures for manipulating relativistic laser-plasma interaction

NASA Astrophysics Data System (ADS)

Ji, Liangliang

2016-10-01

The prospect of realizing compact particle accelerators and x-ray sources based on high power lasers has gained numerous attention. Utilization of all the proposed schemes in the field requires the laser-matter-interaction process to be repeatable or moreover, controllable. This has been very challenging at ultra-high light intensities due to the pre-pulse issue and the limitation on target manufacturing. With recent development on pulse cleaning technique, such as XPW and the use of plasma mirror, we now propose a novel approach that leverages recent advancements in 3D nano-printing of materials and high contrast lasers to manipulate the laser-matter interactions on the micro-scales. The current 3D direct laser-writing (DLW) technique can produce repeatable structures with at a resolution as high as 100 nm. Based on 3D PIC simulations, we explored two typical structures, the micro-cylinder and micro-tube targets. The former serves to enhance and control laser-electron acceleration and the latter is dedicated to manipulate relativistic light intensity. First principle-of-proof experiments were carried out in the SCARLET laser facility and confirmed some of our predictions on enhancing direct laser acceleration of electrons and ion acceleration. We believe that the use of the micro-structured elements provides another degree of freedom in LPI and these new results will open new paths towards micro-engineering interaction process that will benefit high field science, laser-based proton therapy, near-QED physics, and relativistic nonlinear optics. This work is supported by the AFOSR Basic Research Initiative (FA9550-14-1-0085).

An ontology-based search engine for protein-protein interactions.

PubMed

Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

Building protein-protein interaction networks for Leishmania species through protein structural information.

PubMed

Dos Santos Vasconcelos, Crhisllane Rafaele; de Lima Campos, Túlio; Rezende, Antonio Mauro

2018-03-06

Systematic analysis of a parasite interactome is a key approach to understand different biological processes. It makes possible to elucidate disease mechanisms, to predict protein functions and to select promising targets for drug development. Currently, several approaches for protein interaction prediction for non-model species incorporate only small fractions of the entire proteomes and their interactions. Based on this perspective, this study presents an integration of computational methodologies, protein network predictions and comparative analysis of the protozoan species Leishmania braziliensis and Leishmania infantum. These parasites cause Leishmaniasis, a worldwide distributed and neglected disease, with limited treatment options using currently available drugs. The predicted interactions were obtained from a meta-approach, applying rigid body docking tests and template-based docking on protein structures predicted by different comparative modeling techniques. In addition, we trained a machine-learning algorithm (Gradient Boosting) using docking information performed on a curated set of positive and negative protein interaction data. Our final model obtained an AUC = 0.88, with recall = 0.69, specificity = 0.88 and precision = 0.83. Using this approach, it was possible to confidently predict 681 protein structures and 6198 protein interactions for L. braziliensis, and 708 protein structures and 7391 protein interactions for L. infantum. The predicted networks were integrated to protein interaction data already available, analyzed using several topological features and used to classify proteins as essential for network stability. The present study allowed to demonstrate the importance of integrating different methodologies of interaction prediction to increase the coverage of the protein interaction of the studied protocols, besides it made available protein structures and interactions not previously reported.

Computational prediction of host-pathogen protein-protein interactions.

PubMed

Dyer, Matthew D; Murali, T M; Sobral, Bruno W

2007-07-01

Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein-protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens-Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions. Supplementary data are available at http://staff.vbi.vt.edu/dyermd/publications/dyer2007a.html. Supplementary data are available at Bioinformatics online.

Advances in colloidal manipulation and transport via hydrodynamic interactions.

PubMed

Martínez-Pedrero, F; Tierno, P

2018-06-01

In this review article, we highlight many recent advances in the field of micromanipulation of colloidal particles using hydrodynamic interactions (HIs), namely solvent mediated long-range interactions. At the micrsocale, the hydrodynamic laws are time reversible and the flow becomes laminar, features that allow precise manipulation and control of colloidal matter. We focus on different strategies where externally operated microstructures generate local flow fields that induce the advection and motion of the surrounding components. In addition, we review cases where the induced flow gives rise to hydrodynamic bound states that may synchronize during the process, a phenomenon essential in different systems such as those that exhibit self-assembly and swarming. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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

GelScape: a web-based server for interactively annotating, manipulating, comparing and archiving 1D and 2D gel images.

PubMed

Young, Nelson; Chang, Zhan; Wishart, David S

2004-04-12

GelScape is a web-based tool that permits facile, interactive annotation, comparison, manipulation and storage of protein gel images. It uses Java applet-servlet technology to allow rapid, remote image handling and image processing in a platform-independent manner. It supports many of the features found in commercial, stand-alone gel analysis software including spot annotation, spot integration, gel warping, image resizing, HTML image mapping, image overlaying as well as the storage of gel image and gel annotation data in compliance with Federated Gel Database requirements.

An ontology-based search engine for protein-protein interactions

PubMed Central

2010-01-01

Background Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. Results We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Conclusion Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology. PMID:20122195

Signatures of Pleiotropy, Economy and Convergent Evolution in a Domain-Resolved Map of Human–Virus Protein–Protein Interaction Networks

PubMed Central

Garamszegi, Sara; Franzosa, Eric A.; Xia, Yu

2013-01-01

A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Biospecific protein immobilization for rapid analysis of weak protein interactions using self-interaction nanoparticle spectroscopy.

PubMed

Bengali, Aditya N; Tessier, Peter M

2009-10-01

"Reversible" protein interactions govern diverse biological behavior ranging from intracellular transport and toxic protein aggregation to protein crystallization and inactivation of protein therapeutics. Much less is known about weak protein interactions than their stronger counterparts since they are difficult to characterize, especially in a parallel format (in contrast to a sequential format) necessary for high-throughput screening. We have recently introduced a highly efficient approach of characterizing protein self-association, namely self-interaction nanoparticle spectroscopy (SINS; Tessier et al., 2008; J Am Chem Soc 130:3106-3112). This approach exploits the separation-dependent optical properties of gold nanoparticles to detect weak self-interactions between proteins immobilized on nanoparticles. A limitation of our previous work is that differences in the sequence and structure of proteins can lead to significant differences in their affinity to adsorb to nanoparticle surfaces, which complicates analysis of the corresponding protein self-association behavior. In this work we demonstrate a highly specific approach for coating nanoparticles with proteins using biotin-avidin interactions to generate protein-nanoparticle conjugates that report protein self-interactions through changes in their optical properties. Using lysozyme as a model protein that is refractory to characterization by conventional SINS, we demonstrate that surface Plasmon wavelengths for gold-avidin-lysozyme conjugates over a range of solution conditions (i.e., pH and ionic strength) are well correlated with lysozyme osmotic second virial coefficient measurements. Since SINS requires orders of magnitude less protein and time than conventional methods (e.g., static light scattering), we envision this approach will find application in large screens of protein self-association aimed at either preventing (e.g., protein aggregation) or promoting (e.g., protein crystallization) these

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

ability to influence interactions among host proteins are important components for F. tularensis to avoid host-cell defense mechanisms and successfully establish an infection. Although direct host-pathogen protein-protein binding is only one aspect of Francisella virulence, it is a critical component in directly manipulating and interfering with cellular processes in the host cell.

Selection of peptides interfering with protein-protein interaction.

PubMed

Gaida, Annette; Hagemann, Urs B; Mattay, Dinah; Räuber, Christina; Müller, Kristian M; Arndt, Katja M

2009-01-01

Cell physiology depends on a fine-tuned network of protein-protein interactions, and misguided interactions are often associated with various diseases. Consequently, peptides, which are able to specifically interfere with such adventitious interactions, are of high interest for analytical as well as medical purposes. One of the most abundant protein interaction domains is the coiled-coil motif, and thus provides a premier target. Coiled coils, which consist of two or more alpha-helices wrapped around each other, have one of the simplest interaction interfaces, yet they are able to confer highly specific homo- and heterotypic interactions involved in virtually any cellular process. While there are several ways to generate interfering peptides, the combination of library design with a powerful selection system seems to be one of the most effective and promising approaches. This chapter guides through all steps of such a process, starting with library options and cloning, detailing suitable selection techniques and ending with purification for further down-stream characterization. Such generated peptides will function as versatile tools to interfere with the natural function of their targets thereby illuminating their down-stream signaling and, in general, promoting understanding of factors leading to specificity and stability in protein-protein interactions. Furthermore, peptides interfering with medically relevant proteins might become important diagnostics and therapeutics.

The Potato leafroll virus structural proteins manipulate overlapping, yet distinct protein interaction networks during infection

USDA-ARS?s Scientific Manuscript database

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a non-incorporated protein in concert with numerous insect and plant proteins to regulate virus movem...

A Discontinuous Potential Model for Protein-Protein Interactions.

PubMed

Shao, Qing; Hall, Carol K

2016-01-01

Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.

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

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

PubMed

Yang, Ming; Ge, Yan; Wu, Jiayan; Xiao, Jingfa; Yu, Jun

2011-05-20

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.

Protein-protein interactions and cancer: targeting the central dogma.

PubMed

Garner, Amanda L; Janda, Kim D

2011-01-01

Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

Does flavor impact function? Potential consequences of polyphenol-protein interactions in delivery and bioactivity of flavan-3-ols from foods.

PubMed

Ferruzzi, Mario G; Bordenave, Nicolas; Hamaker, Bruce R

2012-11-05

Astringency is a component of the overall flavor experienced when consuming polyphenol rich foods and beverages such as tea, wine, cocoa and select fruits. Following consumption, the astringent sensation results from the well documented ability of polyphenols to bind to salivary proline rich proteins (PRP) and facilitate their precipitation in the oral cavity. In a similar fashion, polyphenols are also known to non-specifically bind food and other biological proteins. While much is known regarding the polyphenol-protein interactions leading to astringency, significantly less information is available regarding the impact of these polyphenol-protein interactions with food or other biological proteins on relevant physiological outcomes. This paper focuses on the interactions between flavan-3-ols, one of the most abundant dietary polyphenol forms, with proteins in food, salivary PRP and other physiological proteins. The physiological implications of these interactions in food and through the gut will be discussed in relation to manipulation of flavan-3-ol bioavailability, metabolism and biological activities including inhibition of digestive enzymes in the gut. Copyright © 2012 Elsevier Inc. All rights reserved.

Dynamic Fluctuations of Protein-Carbohydrate Interactions Promote Protein Aggregation

PubMed Central

Voynov, Vladimir; Chennamsetty, Naresh; Kayser, Veysel; Helk, Bernhard; Forrer, Kurt; Zhang, Heidi; Fritsch, Cornelius; Heine, Holger; Trout, Bernhardt L.

2009-01-01

Protein-carbohydrate interactions are important for glycoprotein structure and function. Antibodies of the IgG class, with increasing significance as therapeutics, are glycosylated at a conserved site in the constant Fc region. We hypothesized that disruption of protein-carbohydrate interactions in the glycosylated domain of antibodies leads to the exposure of aggregation-prone motifs. Aggregation is one of the main problems in protein-based therapeutics because of immunogenicity concerns and decreased efficacy. To explore the significance of intramolecular interactions between aromatic amino acids and carbohydrates in the IgG glycosylated domain, we utilized computer simulations, fluorescence analysis, and site-directed mutagenesis. We find that the surface exposure of one aromatic amino acid increases due to dynamic fluctuations. Moreover, protein-carbohydrate interactions decrease upon stress, while protein-protein and carbohydrate-carbohydrate interactions increase. Substitution of the carbohydrate-interacting aromatic amino acids with non-aromatic residues leads to a significantly lower stability than wild type, and to compromised binding to Fc receptors. Our results support a mechanism for antibody aggregation via decreased protein-carbohydrate interactions, leading to the exposure of aggregation-prone regions, and to aggregation. PMID:20037630

Quality control methodology for high-throughput protein-protein interaction screening.

PubMed

Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

PubMed

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Phytophthora infestans RXLR Effector AVR1 Interacts with Exocyst Component Sec5 to Manipulate Plant Immunity.

PubMed

Du, Yu; Mpina, Mohamed H; Birch, Paul R J; Bouwmeester, Klaas; Govers, Francine

2015-11-01

Phytophthora infestans secretes numerous RXLR effectors that modulate host defense and thereby pave the way for successful invasion. Here, we show that the RXLR effector AVR1 is a virulence factor that promotes colonization and suppresses callose deposition, a hallmark of basal defense. To identify host targets of AVR1, we performed yeast two-hybrid screens and selected Sec5 as a candidate. Sec5 is a subunit of the exocyst, a protein complex that is involved in vesicle trafficking. AVR1-like (A-L), a close homolog of AVR1, also acts as a virulence factor, but unlike AVR1, A-L does not suppress CRINKLER2 (CRN2)-induced cell death or interact with Sec5. Compared with AVR1, A-L is shorter and lacks the carboxyl-terminal tail, the T-region that is crucial for CRN2-induced cell death suppression and Sec5 interaction. In planta analyses revealed that AVR1 and Sec5 are in close proximity, and coimmunoprecipitation confirmed the interaction. Sec5 is required for secretion of the pathogenesis-related protein PR-1 and callose deposition and also plays a role in CRN2-induced cell death. Our findings show that P. infestans manipulates an exocyst subunit and thereby potentially disturbs vesicle trafficking, a cellular process that is important for basal defense. This is a novel strategy that oomycete pathogens exploit to modulate host defense. © 2015 American Society of Plant Biologists. All Rights Reserved.

Protein-protein interaction predictions using text mining methods.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Iliopoulos, Ioannis

2015-03-01

It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools. Copyright © 2014 Elsevier Inc. 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.

A credit-card library approach for disrupting protein-protein interactions.

PubMed

Xu, Yang; Shi, Jin; Yamamoto, Noboru; Moss, Jason A; Vogt, Peter K; Janda, Kim D

2006-04-15

Protein-protein interfaces are prominent in many therapeutically important targets. Using small organic molecules to disrupt protein-protein interactions is a current challenge in chemical biology. An important example of protein-protein interactions is provided by the Myc protein, which is frequently deregulated in human cancers. Myc belongs to the family of basic helix-loop-helix leucine zipper (bHLH-ZIP) transcription factors. It is biologically active only as heterodimer with the bHLH-ZIP protein Max. Herein, we report a new strategy for the disruption of protein-protein interactions that has been corroborated through the design and synthesis of a small parallel library composed of 'credit-card' compounds. These compounds are derived from a planar, aromatic scaffold and functionalized with four points of diversity. From a 285 membered library, several hits were obtained that disrupted the c-Myc-Max interaction and cellular functions of c-Myc. The IC50 values determined for this small focused library for the disruption of Myc-Max dimerization are quite potent, especially since small molecule antagonists of protein-protein interactions are notoriously difficult to find. Furthermore, several of the compounds were active at the cellular level as shown by their biological effects on Myc action in chicken embryo fibroblast assays. In light of our findings, this approach is considered a valuable addition to the armamentarium of new molecules being developed to interact with protein-protein interfaces. Finally, this strategy for disrupting protein-protein interactions should prove applicable to other families of proteins.

Molecular tweezers modulate 14-3-3 protein-protein interactions

NASA Astrophysics Data System (ADS)

Bier, David; Rose, Rolf; Bravo-Rodriguez, Kenny; Bartel, Maria; Ramirez-Anguita, Juan Manuel; Dutt, Som; Wilch, Constanze; Klärner, Frank-Gerrit; Sanchez-Garcia, Elsa; Schrader, Thomas; Ottmann, Christian

2013-03-01

Supramolecular chemistry has recently emerged as a promising way to modulate protein functions, but devising molecules that will interact with a protein in the desired manner is difficult as many competing interactions exist in a biological environment (with solvents, salts or different sites for the target biomolecule). We now show that lysine-specific molecular tweezers bind to a 14-3-3 adapter protein and modulate its interaction with partner proteins. The tweezers inhibit binding between the 14-3-3 protein and two partner proteins—a phosphorylated (C-Raf) protein and an unphosphorylated one (ExoS)—in a concentration-dependent manner. Protein crystallography shows that this effect arises from the binding of the tweezers to a single surface-exposed lysine (Lys214) of the 14-3-3 protein in the proximity of its central channel, which normally binds the partner proteins. A combination of structural analysis and computer simulations provides rules for the tweezers' binding preferences, thus allowing us to predict their influence on this type of protein-protein interactions.

Predicting Physical Interactions between Protein Complexes*

PubMed Central

Clancy, Trevor; Rødland, Einar Andreas; Nygard, Ståle; Hovig, Eivind

2013-01-01

Protein complexes enact most biochemical functions in the cell. Dynamic interactions between protein complexes are frequent in many cellular processes. As they are often of a transient nature, they may be difficult to detect using current genome-wide screens. Here, we describe a method to computationally predict physical interactions between protein complexes, applied to both humans and yeast. We integrated manually curated protein complexes and physical protein interaction networks, and we designed a statistical method to identify pairs of protein complexes where the number of protein interactions between a complex pair is due to an actual physical interaction between the complexes. An evaluation against manually curated physical complex-complex interactions in yeast revealed that 50% of these interactions could be predicted in this manner. A community network analysis of the highest scoring pairs revealed a biologically sensible organization of physical complex-complex interactions in the cell. Such analyses of proteomes may serve as a guide to the discovery of novel functional cellular relationships. PMID:23438732

Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection

DTIC Science & Technology

2009-06-05

the interaction data sets we determined, via comparisons with strict randomized simulations , the propensity for essential proteins to selectively...and analysis of high- quality PPI data sets. Materials and Methods We analyzed protein interaction networks for yeast and E. coli determined from Y2H...we reinvestigated the centrality-lethality rule, which implies that proteins having more interactions are more likely to be essential. From analysis

[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.

The Victor C++ library for protein representation and advanced manipulation.

PubMed

Hirsh, Layla; Piovesan, Damiano; Giollo, Manuel; Ferrari, Carlo; Tosatto, Silvio C E

2015-04-01

Protein sequence and structure representation and manipulation require dedicated software libraries to support methods of increasing complexity. Here, we describe the VIrtual Constrution TOol for pRoteins (Victor) C++ library, an open source platform dedicated to enabling inexperienced users to develop advanced tools and gathering contributions from the community. The provided application examples cover statistical energy potentials, profile-profile sequence alignments and ab initio loop modeling. Victor was used over the last 15 years in several publications and optimized for efficiency. It is provided as a GitHub repository with source files and unit tests, plus extensive online documentation, including a Wiki with help files and tutorials, examples and Doxygen documentation. The C++ library and online documentation, distributed under a GPL license are available from URL: http://protein.bio.unipd.it/victor/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Protein function prediction using neighbor relativity in protein-protein interaction network.

PubMed

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Quantification of the Influence of Protein-Protein Interactions on Adsorbed Protein Structure and Bioactivity

PubMed Central

Wei, Yang; Thyparambil, Aby A.; Latour, Robert A.

2013-01-01

While protein-surface interactions have been widely studied, relatively little is understood at this time regarding how protein-surface interaction effects are influenced by protein-protein interactions and how these effects combine with the internal stability of a protein to influence its adsorbed-state structure and bioactivity. The objectives of this study were to develop a method to study these combined effects under widely varying protein-protein interaction conditions using hen egg-white lysozyme (HEWL) adsorbed on silica glass, poly(methyl methacrylate), and polyethylene as our model systems. In order to vary protein-protein interaction effects over a wide range, HEWL was first adsorbed to each surface type under widely varying protein solution concentrations for 2 h to saturate the surface, followed by immersion in pure buffer solution for 15 h to equilibrate the adsorbed protein layers in the absence of additionally adsorbing protein. Periodic measurements were made at selected time points of the areal density of the adsorbed protein layer as an indicator of the level of protein-protein interaction effects within the layer, and these values were then correlated with measurements of the adsorbed protein’s secondary structure and bioactivity. The results from these studies indicate that protein-protein interaction effects help stabilize the structure of HEWL adsorbed on silica glass, have little influence on the structural behavior of HEWL on HDPE, and actually serve to destabilize HEWL’s structure on PMMA. The bioactivity of HEWL on silica glass and HDPE was found to decrease in direct proportion to the degree of adsorption-induce protein unfolding. A direct correlation between bioactivity and the conformational state of adsorbed HEWL was less apparent on PMMA, thus suggesting that other factors influenced HEWL’s bioactivity on this surface, such as the accessibility of HEWL’s bioactive site being blocked by neighboring proteins or the surface

Dynamic imaging of protein-protein interactions by MP-FLIM

NASA Astrophysics Data System (ADS)

Ameer-Beg, Simon M.; Peter, Marion; Keppler, Melanie D.; Prag, Soren; Barber, Paul R.; Ng, Tony C.; Vojnovic, Borivoj

2005-03-01

The spatio-temporal localization of molecular interactions within cells in situ is of great importance in elucidating the key mechanisms in regulation of fundamental process within the cell. Measurements of such near-field localization of protein complexes may be achieved by the detection of fluorescence (or Forster) resonance energy transfer (FRET) between protein-conjugated fluorophores. We demonstrate the applicability of time-correlated single photon counting multiphoton microscopy to the spatio-temporal localization of protein-protein interactions in live and fixed cell populations. Intramolecular interactions between protein hetero-dimers are investigated using green fluorescent protein variants. We present an improved monomeric form of the red fluorescent protein, mRFP1, as the acceptor in biological fluorescence resonance energy transfer (FRET) experiments using the enhanced green fluorescent protein as donor. We find particular advantage in using this fluorophore pair for quantitative measurements of FRET. The technique was exploited to demonstrate a novel receptor-kinase interaction between the chemokine receptor (CXCR4) and protein kinase C (PKC) α in carcinoma cells for both live and fixed cell experiments.

Captive gorillas' manual laterality: The impact of gestures, manipulators and interaction specificity.

PubMed

Prieur, Jacques; Barbu, Stéphanie; Blois-Heulin, Catherine; Pika, Simone

2017-12-01

Relationships between humans' manual laterality in non-communicative and communicative functions are still poorly understood. Recently, studies showed that chimpanzees' manual laterality is influenced by functional, interactional and individual factors and their mutual intertwinement. However, what about manual laterality in species living in stable social groups? We tackled this question by studying three groups of captive gorillas (N=35) and analysed their most frequent manual signals: three manipulators and 16 gesture types. Our multifactorial investigation showed that conspecific-directed gestures were overall more right-lateralized than conspecific-directed manipulators. Furthermore, it revealed a difference between conspecific- and human-directed gestural laterality for signallers living in one of the study groups. Our results support the hypothesis that gestural laterality is a relevant marker of language left-brain specialisation. We suggest that components of communication and of manipulation (not only of an object but also of a conspecific) do not share the same lateralised cerebral system in some primate species. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

PubMed

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Evolutionary diversification of protein-protein interactions by interface add-ons.

PubMed

Plach, Maximilian G; Semmelmann, Florian; Busch, Florian; Busch, Markus; Heizinger, Leonhard; Wysocki, Vicki H; Merkl, Rainer; Sterner, Reinhard

2017-10-03

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.

Web3DMol: interactive protein structure visualization based on WebGL.

PubMed

Shi, Maoxiang; Gao, Juntao; Zhang, Michael Q

2017-07-03

A growing number of web-based databases and tools for protein research are being developed. There is now a widespread need for visualization tools to present the three-dimensional (3D) structure of proteins in web browsers. Here, we introduce our 3D modeling program-Web3DMol-a web application focusing on protein structure visualization in modern web browsers. Users submit a PDB identification code or select a PDB archive from their local disk, and Web3DMol will display and allow interactive manipulation of the 3D structure. Featured functions, such as sequence plot, fragment segmentation, measure tool and meta-information display, are offered for users to gain a better understanding of protein structure. Easy-to-use APIs are available for developers to reuse and extend Web3DMol. Web3DMol can be freely accessed at http://web3dmol.duapp.com/, and the source code is distributed under the MIT license. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Druggable orthosteric and allosteric hot spots to target protein-protein interactions.

PubMed

Ma, Buyong; Nussinov, Ruth

2014-01-01

Drug designing targeting protein-protein interactions is challenging. Because structural elucidation and computational analysis have revealed the importance of hot spot residues in stabilizing these interactions, there have been on-going efforts to develop drugs which bind the hot spots and out-compete the native protein partners. The question arises as to what are the key 'druggable' properties of hot spots in protein-protein interactions and whether these mimic the general hot spot definition. Identification of orthosteric (at the protein- protein interaction site) and allosteric (elsewhere) druggable hot spots is expected to help in discovering compounds that can more effectively modulate protein-protein interactions. For example, are there any other significant features beyond their location in pockets in the interface? The interactions of protein-protein hot spots are coupled with conformational dynamics of protein complexes. Currently increasing efforts focus on the allosteric drug discovery. Allosteric drugs bind away from the native binding site and can modulate the native interactions. We propose that identification of allosteric hot spots could similarly help in more effective allosteric drug discovery. While detection of allosteric hot spots is challenging, targeting drugs to these residues has the potential of greatly increasing the hot spot and protein druggability.

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

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

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

Revealing protein functions based on relationships of interacting proteins and GO terms.

PubMed

Teng, Zhixia; Guo, Maozu; Liu, Xiaoyan; Tian, Zhen; Che, Kai

2017-09-20

In recent years, numerous computational methods predicted protein function based on the protein-protein interaction (PPI) network. These methods supposed that two proteins share the same function if they interact with each other. However, it is reported by recent studies that the functions of two interacting proteins may be just related. It will mislead the prediction of protein function. Therefore, there is a need for investigating the functional relationship between interacting proteins. In this paper, the functional relationship between interacting proteins is studied and a novel method, called as GoDIN, is advanced to annotate functions of interacting proteins in Gene Ontology (GO) context. It is assumed that the functional difference between interacting proteins can be expressed by semantic difference between GO term and its relatives. Thus, the method uses GO term and its relatives to annotate the interacting proteins separately according to their functional roles in the PPI network. The method is validated by a series of experiments and compared with the concerned method. The experimental results confirm the assumption and suggest that GoDIN is effective on predicting functions of protein. This study demonstrates that: (1) interacting proteins are not equal in the PPI network, and their function may be same or similar, or just related; (2) functional difference between interacting proteins can be measured by their degrees in the PPI network; (3) functional relationship between interacting proteins can be expressed by relationship between GO term and its relatives.

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

Towards Inferring Protein Interactions: Challenges and Solutions

NASA Astrophysics Data System (ADS)

Zhang, Ya; Zha, Hongyuan; Chu, Chao-Hsien; Ji, Xiang

2006-12-01

Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.

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

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-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.

The Role of Shape Complementarity in the Protein-Protein Interactions

NASA Astrophysics Data System (ADS)

Li, Ye; Zhang, Xianren; Cao, Dapeng

2013-11-01

We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody-antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity.

The binary protein-protein interaction landscape of Escherichia coli

PubMed Central

Rajagopala, Seesandra V.; Vlasblom, James; Arnold, Roland; Franca-Koh, Jonathan; Pakala, Suman B.; Phanse, Sadhna; Ceol, Arnaud; Häuser, Roman; Siszler, Gabriella; Wuchty, Stefan; Emili, Andrew; Babu, Mohan; Aloy, Patrick; Pieper, Rembert; Uetz, Peter

2014-01-01

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (~70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, approximately doubling the number of known binary PPIs in E. coli. Integration of binary PPIs and genetic interactions revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that could be mapped within multi-protein complexes were informative regarding internal topology and indicated that interactions within complexes are significantly more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily significant model microbe. PMID:24561554

Monitoring protein-protein interactions using split synthetic renilla luciferase protein-fragment-assisted complementation.

PubMed

Paulmurugan, R; Gambhir, S S

2003-04-01

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 alpha through NFkappaB-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.

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Potential Interference of Protein-Protein Interactions by Graphyne.

PubMed

Luan, Binquan; Huynh, Tien; Zhou, Ruhong

2016-03-10

Graphyne has attracted tremendous attention recently due to its many potentially superior properties relative to those of graphene. Although extensive efforts have been devoted to explore the applicability of graphyne as an alternative nanomaterial for state-of-the-art nanotechnology (including biomedical applications), knowledge regarding its possible adverse effects to biological cells is still lacking. Here, using large-scale all-atom molecular dynamics simulations, we investigate the potential toxicity of graphyne by interfering a protein-protein interaction (ppI). We found that graphyne could indeed disrupt the ppIs by cutting through the protein-protein interface and separating the protein complex into noncontacting ones, due to graphyne's dispersive and hydrophobic interaction with the hydrophobic residues residing at the dimer interface. Our results help to elucidate the mechanism of interaction between graphyne and ppI networks within a biological cell and provide insights for its hazard reduction.

Cell-permeable nanobodies for targeted immunolabelling and antigen manipulation in living cells

NASA Astrophysics Data System (ADS)

Herce, Henry D.; Schumacher, Dominik; Schneider, Anselm F. L.; Ludwig, Anne K.; Mann, Florian A.; Fillies, Marion; Kasper, Marc-André; Reinke, Stefan; Krause, Eberhard; Leonhardt, Heinrich; Cardoso, M. Cristina; Hackenberger, Christian P. R.

2017-08-01

Functional antibody delivery in living cells would enable the labelling and manipulation of intracellular antigens, which constitutes a long-thought goal in cell biology and medicine. Here we present a modular strategy to create functional cell-permeable nanobodies capable of targeted labelling and manipulation of intracellular antigens in living cells. The cell-permeable nanobodies are formed by the site-specific attachment of intracellularly stable (or cleavable) cyclic arginine-rich cell-penetrating peptides to camelid-derived single-chain VHH antibody fragments. We used this strategy for the non-endocytic delivery of two recombinant nanobodies into living cells, which enabled the relocalization of the polymerase clamp PCNA (proliferating cell nuclear antigen) and tumour suppressor p53 to the nucleolus, and thereby allowed the detection of protein-protein interactions that involve these two proteins in living cells. Furthermore, cell-permeable nanobodies permitted the co-transport of therapeutically relevant proteins, such as Mecp2, into the cells. This technology constitutes a major step in the labelling, delivery and targeted manipulation of intracellular antigens. Ultimately, this approach opens the door towards immunostaining in living cells and the expansion of immunotherapies to intracellular antigen targets.

Manipulating Cognitive Complexity across Task Types and Its Impact on Learners' Interaction during Oral Performance

ERIC Educational Resources Information Center

Gilabert, Roger; Baron, Julia; Llanes, Angels

2009-01-01

The goal of this study is to investigate the impact of manipulating the cognitive complexity of three different types of oral tasks on interaction. The study first considers the concepts of task complexity and interaction and then examines the specific studies that have looked at the effects of increasing task complexity on conversational…

The Role of Shape Complementarity in the Protein-Protein Interactions

PubMed Central

Li, Ye; Zhang, Xianren; Cao, Dapeng

2013-01-01

We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody–antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity. PMID:24253561

Spin manipulation and spin-lattice interaction in magnetic colloidal quantum dots

NASA Astrophysics Data System (ADS)

Moro, Fabrizio; Turyanska, Lyudmila; Granwehr, Josef; Patanè, Amalia

2014-11-01

We report on the spin-lattice interaction and coherent manipulation of electron spins in Mn-doped colloidal PbS quantum dots (QDs) by electron spin resonance. We show that the phase memory time,TM , is limited by Mn-Mn dipolar interactions, hyperfine interactions of the protons (1H) on the QD capping ligands with Mn ions in their proximity (<1 nm), and surface phonons originating from thermal fluctuations of the capping ligands. In the low Mn concentration limit and at low temperature, we achieve a long phase memory time constant TM˜0.9 μ s , thus enabling the observation of Rabi oscillations. Our findings suggest routes to the rational design of magnetic colloidal QDs with phase memory times exceeding the current limits of relevance for the implementation of QDs as qubits in quantum information processing.

Probe manipulators for Wendelstein 7-X and their interaction with the magnetic topology

NASA Astrophysics Data System (ADS)

M, RACK; D, HÖSCHEN; D, REITER; B, UNTERBERG; J, W. COENEN; S, BREZINSEK; O, NEUBAUER; S, BOZHENKOV; G, CZYMEK; Y, LIANG; M, HUBENY; Ch, LINSMEIER; the Wendelstein 7-X Team

2018-05-01

Probe manipulators are a versatile addition to typical plasma edge diagnostics. Equipped with material samples they allow for detailed investigation of plasma–wall interaction processes, such as material erosion, deposition or impurity transport pathways. When combined with electrical probes, a study of scrape-off layer and plasma edge density, temperature and flow profiles as well as magnetic topologies is possible. A mid-plane manipulator is already in operation on Wendelstein 7-X. A system in the divertor region is currently under development. In the present paper we discuss the critical issue of heat and power loads, power redistribution and experimental access to the complex magnetic topology of Wendelstein 7-X. All the aforementioned aspects are of relevance for the design and operation of a probe manipulator in a device like Wendelstein 7-X. A focus is put on the topological region that is accessible for the different coil current configurations at Wendelstein 7-X and the power load on the manipulator with respect to the resulting different magnetic configurations. Qualitative analysis of power loads on plasma-facing components is performed using a numerical tracer particle diffusion tool provided via the Wendelstein 7-X Webservices.

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.

Protein interaction networks from literature mining

NASA Astrophysics Data System (ADS)

Ihara, Sigeo

2005-03-01

The ability to accurately predict and understand physiological changes in the biological network system in response to disease or drug therapeutics is of crucial importance in life science. The extensive amount of gene expression data generated from even a single microarray experiment often proves difficult to fully interpret and comprehend the biological significance. An increasing knowledge of protein interactions stored in the PubMed database, as well as the advancement of natural language processing, however, makes it possible to construct protein interaction networks from the gene expression information that are essential for understanding the biological meaning. From the in house literature mining system we have developed, the protein interaction network for humans was constructed. By analysis based on the graph-theoretical characterization of the total interaction network in literature, we found that the network is scale-free and semantic long-ranged interactions (i.e. inhibit, induce) between proteins dominate in the total interaction network, reducing the degree exponent. Interaction networks generated based on scientific text in which the interaction event is ambiguously described result in disconnected networks. In contrast interaction networks based on text in which the interaction events are clearly stated result in strongly connected networks. The results of protein-protein interaction networks obtained in real applications from microarray experiments are discussed: For example, comparisons of the gene expression data indicative of either a good or a poor prognosis for acute lymphoblastic leukemia with MLL rearrangements, using our system, showed newly discovered signaling cross-talk.

Visualizing an ultra-weak protein-protein interaction in phosphorylation signaling.

PubMed

Xing, Qiong; Huang, Peng; Yang, Ju; Sun, Jian-Qiang; Gong, Zhou; Dong, Xu; Guo, Da-Chuan; Chen, Shao-Min; Yang, Yu-Hong; Wang, Yan; Yang, Ming-Hui; Yi, Ming; Ding, Yi-Ming; Liu, Mai-Li; Zhang, Wei-Ping; Tang, Chun

2014-10-20

Proteins interact with each other to fulfill their functions. The importance of weak protein-protein interactions has been increasingly recognized. However, owing to technical difficulties, ultra-weak interactions remain to be characterized. Phosphorylation can take place via a K(D)≈25 mM interaction between two bacterial enzymes. Using paramagnetic NMR spectroscopy and with the introduction of a novel Gd(III)-based probe, we determined the structure of the resulting complex to atomic resolution. The structure accounts for the mechanism of phosphoryl transfer between the two enzymes and demonstrates the physical basis for their ultra-weak interaction. Further, molecular dynamics (MD) simulations suggest that the complex has a lifetime in the micro- to millisecond regimen. Hence such interaction is termed a fleeting interaction. From mathematical modeling, we propose that an ultra-weak fleeting interaction enables rapid flux of phosphoryl signal, providing a high effective protein concentration. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Manipulability, force, and compliance analysis for planar continuum manipulators

NASA Technical Reports Server (NTRS)

Gravagne, Ian A.; Walker, Ian D.

2002-01-01

Continuum manipulators, inspired by the natural capabilities of elephant trunks and octopus tentacles, may find niche applications in areas like human-robot interaction, multiarm manipulation, and unknown environment exploration. However, their true capabilities will remain largely inaccessible without proper analytical tools to evaluate their unique properties. Ellipsoids have long served as one of the foremost analytical tools available to the robotics researcher, and the purpose of this paper is to first formulate, and then to examine, three types of ellipsoids for continuum robots: manipulability, force, and compliance.

Manipulability, force, and compliance analysis for planar continuum manipulators.

PubMed

Gravagne, Ian A; Walker, Ian D

2002-06-01

Continuum manipulators, inspired by the natural capabilities of elephant trunks and octopus tentacles, may find niche applications in areas like human-robot interaction, multiarm manipulation, and unknown environment exploration. However, their true capabilities will remain largely inaccessible without proper analytical tools to evaluate their unique properties. Ellipsoids have long served as one of the foremost analytical tools available to the robotics researcher, and the purpose of this paper is to first formulate, and then to examine, three types of ellipsoids for continuum robots: manipulability, force, and compliance.

TSEMA: interactive prediction of protein pairings between interacting families

PubMed Central

Izarzugaza, José M. G.; Juan, David; Pons, Carles; Ranea, Juan A. G.; Valencia, Alfonso; Pazos, Florencio

2006-01-01

An entire family of methodologies for predicting protein interactions is based on the observed fact that families of interacting proteins tend to have similar phylogenetic trees due to co-evolution. One application of this concept is the prediction of the mapping between the members of two interacting protein families (which protein within one family interacts with which protein within the other). The idea is that the real mapping would be the one maximizing the similarity between the trees. Since the exhaustive exploration of all possible mappings is not feasible for large families, current approaches use heuristic techniques which do not ensure the best solution to be found. This is why it is important to check the results proposed by heuristic techniques and to manually explore other solutions. Here we present TSEMA, the server for efficient mapping assessment. This system calculates an initial mapping between two families of proteins based on a Monte Carlo approach and allows the user to interactively modify it based on performance figures and/or specific biological knowledge. All the explored mappings are graphically shown over a representation of the phylogenetic trees. The system is freely available at . Standalone versions of the software behind the interface are available upon request from the authors. PMID:16845017

Manipulating perfume delivery to the interface using polymer-surfactant interactions.

PubMed

Bradbury, Robert; Penfold, Jeffrey; Thomas, Robert K; Tucker, Ian M; Petkov, Jordan T; Jones, Craig

2016-03-15

Enhanced delivery of perfumes to interfaces is an important element of their effectiveness in a range of home and personal care products. The role of polyelectrolyte-surfactant mixtures to promote perfume adsorption at interfaces is explored here. Neutron reflectivity, NR, was used to quantify the adsorption of the model perfumes phenylethanol, PE, and linalool, LL, at the air-water interface in the presence of the anionic surfactant sodium dodecylsulfate, SDS, and the cationic polyelectrolytes, poly(dimethyldiallyl ammonium chloride), polydmdaac, and poly(ethyleneimine), PEI. The strong SDS-polydmdaac interaction dominates the surface adsorption in SDS-polymer-perfume (PE, LL) mixtures, such that the PE and LL adsorption is greatly suppressed. For PEI-SDS-perfume mixtures the PEI-LL interaction competes with the SDS-PEI interaction at all pH at the surface and significant LL adsorption occurs, whereas for PE the PEI-SDS interaction dominates and the PE adsorption is greatly reduced. The use of the strong surface polyelectrolyte-ionic surfactant interaction to manipulate perfume adsorption at the air-water interface has been demonstrated. In particular the results show how the competition between polyelectrolyte, surfactant and perfume interactions at the surface and in solution affect the partitioning of perfumes to the surface. Copyright © 2015 Elsevier Inc. All rights reserved.

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Scoring functions for protein-protein interactions.

PubMed

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Protein-protein recognition control by modulating electrostatic interactions.

PubMed

Han, Song; Yin, Shijin; Yi, Hong; Mouhat, Stéphanie; Qiu, Su; Cao, Zhijian; Sabatier, Jean-Marc; Wu, Yingliang; Li, Wenxin

2010-06-04

Protein-protein control recognition remains a huge challenge, and its development depends on understanding the chemical and biological mechanisms by which these interactions occur. Here we describe a protein-protein control recognition technique based on the dominant electrostatic interactions occurring between the proteins. We designed a potassium channel inhibitor, BmP05-T, that was 90.32% identical to wild-type BmP05. Negatively charged residues were translocated from the nonbinding interface to the binding interface of BmP05 inhibitor, such that BmP05-T now used BmP05 nonbinding interface as the binding interface. This switch demonstrated that nonbinding interfaces were able to control the orientation of protein binding interfaces in the process of protein-protein recognition. The novel function findings of BmP05-T peptide suggested that the control recognition technique described here had the potential for use in designing and utilizing functional proteins in many biological scenarios.

Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data.

PubMed

Greenwald, William W; Li, He; Smith, Erin N; Benaglio, Paola; Nariai, Naoki; Frazer, Kelly A

2017-04-07

Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and analysis tools exist for storing and manipulating single locus NGS data, there is currently no file standard or analysis tool suite for manipulating and storing paired-genomic-loci: the data type resulting from "genomic interaction" studies. As genomic interaction sequencing data are becoming prevalent, a standard file format and tools for working with these data conveniently and efficiently are needed. This article details a file standard and novel software tool suite for working with paired-genomic-loci data. We present the paired-genomic-loci (PGL) file standard for genomic-interactions data, and the accompanying analysis tool suite "pgltools": a cross platform, pypy compatible python package available both as an easy-to-use UNIX package, and as a python module, for integration into pipelines of paired-genomic-loci analyses. Pgltools is a freely available, open source tool suite for manipulating paired-genomic-loci data. Source code, an in-depth manual, and a tutorial are available publicly at www.github.com/billgreenwald/pgltools , and a python module of the operations can be installed from PyPI via the PyGLtools module.

The role of electrostatics in protein-protein interactions of a monoclonal antibody.

PubMed

Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R

2014-07-07

Understanding how protein-protein interactions depend on the choice of buffer, salt, ionic strength, and pH is needed to have better control over protein solution behavior. Here, we have characterized the pH and ionic strength dependence of protein-protein interactions in terms of an interaction parameter kD obtained from dynamic light scattering and the osmotic second virial coefficient B22 measured by static light scattering. A simplified protein-protein interaction model based on a Baxter adhesive potential and an electric double layer force is used to separate out the contributions of longer-ranged electrostatic interactions from short-ranged attractive forces. The ionic strength dependence of protein-protein interactions for solutions at pH 6.5 and below can be accurately captured using a Deryaguin-Landau-Verwey-Overbeek (DLVO) potential to describe the double layer forces. In solutions at pH 9, attractive electrostatics occur over the ionic strength range of 5-275 mM. At intermediate pH values (7.25 to 8.5), there is a crossover effect characterized by a nonmonotonic ionic strength dependence of protein-protein interactions, which can be rationalized by the competing effects of long-ranged repulsive double layer forces at low ionic strength and a shorter ranged electrostatic attraction, which dominates above a critical ionic strength. The change of interactions from repulsive to attractive indicates a concomitant change in the angular dependence of protein-protein interaction from isotropic to anisotropic. In the second part of the paper, we show how the Baxter adhesive potential can be used to predict values of kD from fitting to B22 measurements, thus providing a molecular basis for the linear correlation between the two protein-protein interaction parameters.

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.

Phytophthora infestans RXLR Effector AVR1 Interacts with Exocyst Component Sec5 to Manipulate Plant Immunity1[OPEN

PubMed Central

Du, Yu; Mpina, Mohamed H.; Birch, Paul R.J.; Bouwmeester, Klaas; Govers, Francine

2015-01-01

Phytophthora infestans secretes numerous RXLR effectors that modulate host defense and thereby pave the way for successful invasion. Here, we show that the RXLR effector AVR1 is a virulence factor that promotes colonization and suppresses callose deposition, a hallmark of basal defense. To identify host targets of AVR1, we performed yeast two-hybrid screens and selected Sec5 as a candidate. Sec5 is a subunit of the exocyst, a protein complex that is involved in vesicle trafficking. AVR1-like (A-L), a close homolog of AVR1, also acts as a virulence factor, but unlike AVR1, A-L does not suppress CRINKLER2 (CRN2)-induced cell death or interact with Sec5. Compared with AVR1, A-L is shorter and lacks the carboxyl-terminal tail, the T-region that is crucial for CRN2-induced cell death suppression and Sec5 interaction. In planta analyses revealed that AVR1 and Sec5 are in close proximity, and coimmunoprecipitation confirmed the interaction. Sec5 is required for secretion of the pathogenesis-related protein PR-1 and callose deposition and also plays a role in CRN2-induced cell death. Our findings show that P. infestans manipulates an exocyst subunit and thereby potentially disturbs vesicle trafficking, a cellular process that is important for basal defense. This is a novel strategy that oomycete pathogens exploit to modulate host defense. PMID:26336092

Mapping protein-protein interactions using yeast two-hybrid assays.

PubMed

Mehla, Jitender; Caufield, J Harry; Uetz, Peter

2015-05-01

Yeast two-hybrid (Y2H) screens are an efficient system for mapping protein-protein interactions and whole interactomes. The screens can be performed using random libraries or collections of defined open reading frames (ORFs) called ORFeomes. This protocol describes both library and array-based Y2H screening, with an emphasis on array-based assays. Array-based Y2H is commonly used to test a number of "prey" proteins for interactions with a single "bait" (target) protein or pool of proteins. The advantage of this approach is the direct identification of interacting protein pairs without further downstream experiments: The identity of the preys is known and does not require further confirmation. In contrast, constructing and screening a random prey library requires identification of individual prey clones and systematic retesting. Retesting is typically performed in an array format. © 2015 Cold Spring Harbor Laboratory Press.

[Chemical libraries dedicated to protein-protein interactions].

PubMed

Sperandio, Olivier; Villoutreix, Bruno O; Morelli, Xavier; Roche, Philippe

2015-03-01

The identification of complete networks of protein-protein interactions (PPI) within a cell has contributed to major breakthroughs in understanding biological pathways, host-pathogen interactions and cancer development. As a consequence, PPI have emerged as a new class of promising therapeutic targets. However, they are still considered as a challenging class of targets for drug discovery programs. Recent successes have allowed the characterization of structural and physicochemical properties of protein-protein interfaces leading to a better understanding of how they can be disrupted with small molecule compounds. In addition, characterization of the profiles of PPI inhibitors has allowed the development of PPI-focused libraries. In this review, we present the current efforts at developing chemical libraries dedicated to these innovative targets. © 2015 médecine/sciences – Inserm.

Dendrimer-protein interactions versus dendrimer-based nanomedicine.

PubMed

Shcharbin, Dzmitry; Shcharbina, Natallia; Dzmitruk, Volha; Pedziwiatr-Werbicka, Elzbieta; Ionov, Maksim; Mignani, Serge; de la Mata, F Javier; Gómez, Rafael; Muñoz-Fernández, Maria Angeles; Majoral, Jean-Pierre; Bryszewska, Maria

2017-04-01

Dendrimers are hyperbranched polymers belonging to the huge class of nanomedical devices. Their wide application in biology and medicine requires understanding of the fundamental mechanisms of their interactions with biological systems. Summarizing, electrostatic force plays the predominant role in dendrimer-protein interactions, especially with charged dendrimers. Other kinds of interactions have been proven, such as H-bonding, van der Waals forces, and even hydrophobic interactions. These interactions depend on the characteristics of both participants: flexibility and surface charge of a dendrimer, rigidity of protein structure and the localization of charged amino acids at its surface. pH and ionic strength of solutions can significantly modulate interactions. Ligands and cofactors attached to a protein can also change dendrimer-protein interactions. Binding of dendrimers to a protein can change its secondary structure, conformation, intramolecular mobility and functional activity. However, this strongly depends on rigidity versus flexibility of a protein's structure. In addition, the potential applications of dendrimers to nanomedicine are reviwed related to dendrimer-protein interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Examination and Manipulation of Protein Surface Charge in Solution with Electrospray Ionization Mass Spectrometry

ERIC Educational Resources Information Center

Gross, Deborah S.; Van Ryswyk, Hal

2014-01-01

Electrospray ionization mass spectrometry (ESI-MS) is a powerful tool for examining the charge of proteins in solution. The charge can be manipulated through choice of solvent and pH. Furthermore, solution-accessible, protonated lysine side chains can be specifically tagged with 18-crown-6 ether to form noncovalent adducts. Chemical derivatization…

Understanding and Manipulating Electrostatic Fields at the Protein-Protein Interface Using Vibrational Spectroscopy and Continuum Electrostatics Calculations.

PubMed

Ritchie, Andrew W; Webb, Lauren J

2015-11-05

Biological function emerges in large part from the interactions of biomacromolecules in the complex and dynamic environment of the living cell. For this reason, macromolecular interactions in biological systems are now a major focus of interest throughout the biochemical and biophysical communities. The affinity and specificity of macromolecular interactions are the result of both structural and electrostatic factors. Significant advances have been made in characterizing structural features of stable protein-protein interfaces through the techniques of modern structural biology, but much less is understood about how electrostatic factors promote and stabilize specific functional macromolecular interactions over all possible choices presented to a given molecule in a crowded environment. In this Feature Article, we describe how vibrational Stark effect (VSE) spectroscopy is being applied to measure electrostatic fields at protein-protein interfaces, focusing on measurements of guanosine triphosphate (GTP)-binding proteins of the Ras superfamily binding with structurally related but functionally distinct downstream effector proteins. In VSE spectroscopy, spectral shifts of a probe oscillator's energy are related directly to that probe's local electrostatic environment. By performing this experiment repeatedly throughout a protein-protein interface, an experimental map of measured electrostatic fields generated at that interface is determined. These data can be used to rationalize selective binding of similarly structured proteins in both in vitro and in vivo environments. Furthermore, these data can be used to compare to computational predictions of electrostatic fields to explore the level of simulation detail that is necessary to accurately predict our experimental findings.

RNA-protein interactions in an unstructured context.

PubMed

Zagrovic, Bojan; Bartonek, Lukas; Polyansky, Anton A

2018-05-31

Despite their importance, our understanding of noncovalent RNA-protein interactions is incomplete. This especially concerns the binding between RNA and unstructured protein regions, a widespread class of such interactions. Here, we review the recent experimental and computational work on RNA-protein interactions in an unstructured context with a particular focus on how such interactions may be shaped by the intrinsic interaction affinities between individual nucleobases and protein side chains. Specifically, we articulate the claim that the universal genetic code reflects the binding specificity between nucleobases and protein side chains and that, in turn, the code may be seen as the Rosetta stone for understanding RNA-protein interactions in general. © 2018 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

PubMed

Yang, Lei; Zhao, Xudong; Tang, Xianglong

2014-01-01

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

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.

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.

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.

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

PodNet, a protein-protein interaction network of the podocyte.

PubMed

Warsow, Gregor; Endlich, Nicole; Schordan, Eric; Schordan, Sandra; Chilukoti, Ravi K; Homuth, Georg; Moeller, Marcus J; Fuellen, Georg; Endlich, Karlhans

2013-07-01

Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

Interplay between negative and positive design elements in Gα helical domains of G proteins determines interaction specificity towards RGS2.

PubMed

Kasom, Mohammad; Gharra, Samia; Sadiya, Isra; Avital-Shacham, Meirav; Kosloff, Mickey

2018-06-20

Regulators of G protein Signaling (RGS) proteins inactivate Gα subunits, thereby controling G protein-coupled signaling networks. Among all RGS proteins, RGS2 is unique in interacting only with the Gα q and not with the Gα i sub-family. Previous studies suggested that this specificity is determined by the RGS domain, and in particular by three RGS2-specific residues that lead to a unique mode of interaction with Gα q This interaction was further proposed to act through contacts with the Gα GTPase domain. Here, we combined energy calculations and GTPase activity measurements to determine which Gα residues dictate specificity toward RGS2. We identified putative specificity-determining residues in the Gα helical domain, which among G proteins is found only in Gα subunits. Replacing these helical domain residues in Gα i with their Gα q counterparts resulted in a dramatic specificity-switch towards RGS2. We further show that Gα-RGS2 specificity is set by Gα i residues that perturb interactions with RGS2, and by Gα q residues that enhance these interactions. These results show, for the first time, that the Gα helical domain is central to dictating specificity towards RGS2, suggesting this domain plays a general role in governing Gα-RGS specificity. Our insights provide new options for manipulating RGS-G protein interactions in vivo , for better understanding of their "wiring" into signaling networks, and for devising novel drugs targeting such interactions. ©2018 The Author(s).

Protein-Protein Interaction Assays with Effector-GFP Fusions in Nicotiana benthamiana.

PubMed

Petre, Benjamin; Win, Joe; Menke, Frank L H; Kamoun, Sophien

2017-01-01

Plant parasites secrete proteins known as effectors into host tissues to manipulate host cell structures and functions. One of the major goals in effector biology is to determine the host cell compartments and the protein complexes in which effectors accumulate. Here, we describe a five-step pipeline that we routinely use in our lab to achieve this goal, which consists of (1) Golden Gate assembly of pathogen effector-green fluorescent protein (GFP) fusions into binary vectors, (2) Agrobacterium-mediated heterologous protein expression in Nicotiana benthamiana leaf cells, (3) laser-scanning confocal microscopy assay, (4) anti-GFP coimmunoprecipitation-liquid chromatography-tandem mass spectrometry (coIP/MS) assay, and (5) anti-GFP western blotting. This pipeline is suitable for rapid, cost-effective, and medium-throughput screening of pathogen effectors in planta.

Building blocks for protein interaction devices

PubMed Central

Grünberg, Raik; Ferrar, Tony S.; van der Sloot, Almer M.; Constante, Marco; Serrano, Luis

2010-01-01

Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them. PMID:20215443

The Complexity of the Affordance-Ability Relationship When Second-Grade Children Interact with Mathematics Virtual Manipulative Apps

ERIC Educational Resources Information Center

Tucker, Stephen I.; Moyer-Packenham, Patricia S.; Westenskow, Arla; Jordan, Kerry E.

2016-01-01

The purpose of this study was to explore relationships between app affordances and user abilities in second graders' interactions with mathematics virtual manipulative touchscreen tablet apps. The research questions focused on varying manifestations of affordance-ability relationships during children's interactions with mathematics virtual…

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.

Cross-regulatory protein-protein interactions between Hox and Pax transcription factors.

PubMed

Plaza, Serge; Prince, Frederic; Adachi, Yoshitsugu; Punzo, Claudio; Cribbs, David L; Gehring, Walter J

2008-09-09

Homeotic Hox selector genes encode highly conserved transcriptional regulators involved in the differentiation of multicellular organisms. Ectopic expression of the Antennapedia (ANTP) homeodomain protein in Drosophila imaginal discs induces distinct phenotypes, including an antenna-to-leg transformation and eye reduction. We have proposed that the eye loss phenotype is a consequence of a negative posttranslational control mechanism because of direct protein-protein interactions between ANTP and Eyeless (EY). In the present work, we analyzed the effect of various ANTP homeodomain mutations for their interaction with EY and for head development. Contrasting with the eye loss phenotype, we provide evidence that the antenna-to-leg transformation involves ANTP DNA-binding activity. In a complementary genetic screen performed in yeast, we isolated mutations located in the N terminus of the ANTP homeodomain that inhibit direct interactions with EY without abolishing DNA binding in vitro and in vivo. In a bimolecular fluorescence complementation assay, we detected the ANTP-EY interaction in vivo, these interactions occurring through the paired domain and/or the homeodomain of EY. These results demonstrate that the homeodomain supports multiple molecular regulatory functions in addition to protein-DNA and protein-RNA interactions; it is also involved in protein-protein interactions.

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.

Role of water mediated interactions in protein-protein recognition landscapes.

PubMed

Papoian, Garegin A; Ulander, Johan; Wolynes, Peter G

2003-07-30

The energy landscape picture of protein folding and binding is employed to optimize a number of pair potentials for direct and water-mediated interactions in protein complex interfaces. We find that water-mediated interactions greatly complement direct interactions in discriminating against various types of trap interactions that model those present in the cell. We highlight the context dependent nature of knowledge-based binding potentials, as contrasted with the situation for autonomous folding. By performing a Principal Component Analysis (PCA) of the corresponding interaction matrixes, we rationalize the strength of the recognition signal for each combination of the contact type and reference trap states using the differential in the idealized "canonical" amino acid compositions of native and trap layers. The comparison of direct and water-mediated contact potential matrixes emphasizes the importance of partial solvation in stabilizing charged groups in the protein interfaces. Specific water-mediated interresidue interactions are expected to influence significantly the kinetics as well as thermodynamics of protein association.

The Xanthomonas euvesicatoria type III effector XopAU is an active protein kinase that manipulates plant MAP kinase signaling.

PubMed

Teper, Doron; Girija, Anil Madhusoodana; Bosis, Eran; Popov, Georgy; Savidor, Alon; Sessa, Guido

2018-01-01

The Gram-negative bacterium Xanthomonas euvesicatoria (Xe) is the causal agent of bacterial spot disease of pepper and tomato. Xe delivers effector proteins into host cells through the type III secretion system to promote disease. Here, we show that the Xe effector XopAU, which is conserved in numerous Xanthomonas species, is a catalytically active protein kinase and contributes to the development of disease symptoms in pepper plants. Agrobacterium-mediated expression of XopAU in host and non-host plants activated typical defense responses, including MAP kinase phosphorylation, accumulation of pathogenesis-related (PR) proteins and elicitation of cell death, that were dependent on the kinase activity of the effector. XopAU-mediated cell death was not dependent on early signaling components of effector-triggered immunity and was also observed when the effector was delivered into pepper leaves by Xanthomonas campestris pv. campestris, but not by Xe. Protein-protein interaction studies in yeast and in planta revealed that XopAU physically interacts with components of plant immunity-associated MAP kinase cascades. Remarkably, XopAU directly phosphorylated MKK2 in vitro and enhanced its phosphorylation at multiple sites in planta. Consistent with the notion that MKK2 is a target of XopAU, silencing of the MKK2 homolog or overexpression of the catalytically inactive mutant MKK2K99R in N. benthamiana plants reduced XopAU-mediated cell death and MAPK phosphorylation. Furthermore, yeast co-expressing XopAU and MKK2 displayed reduced growth and this phenotype was dependent on the kinase activity of both proteins. Together, our results support the conclusion that XopAU contributes to Xe disease symptoms in pepper plants and manipulates host MAPK signaling through phosphorylation and activation of MKK2.

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.

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

The geometric framework for nutrition reveals interactions between protein and carbohydrate during larval growth in honey bees

PubMed Central

Slater, Garett P.; Rajamohan, Arun; Yocum, George D.; Greenlee, Kendra J.; Bowsher, Julia H.

2017-01-01

ABSTRACT In holometabolous insects, larval nutrition affects adult body size, a life history trait with a profound influence on performance and fitness. Individual nutritional components of larval diets are often complex and may interact with one another, necessitating the use of a geometric framework for elucidating nutritional effects. In the honey bee, Apis mellifera, nurse bees provision food to developing larvae, directly moderating growth rates and caste development. However, the eusocial nature of honey bees makes nutritional studies challenging, because diet components cannot be systematically manipulated in the hive. Using in vitro rearing, we investigated the roles and interactions between carbohydrate and protein content on larval survival, growth, and development in A. mellifera. We applied a geometric framework to determine how these two nutritional components interact across nine artificial diets. Honey bees successfully completed larval development under a wide range of protein and carbohydrate contents, with the medium protein (∼5%) diet having the highest survival. Protein and carbohydrate both had significant and non-linear effects on growth rate, with the highest growth rates observed on a medium-protein, low-carbohydrate diet. Diet composition did not have a statistically significant effect on development time. These results confirm previous findings that protein and carbohydrate content affect the growth of A. mellifera larvae. However, this study identified an interaction between carbohydrate and protein content that indicates a low-protein, high-carb diet has a negative effect on larval growth and survival. These results imply that worker recruitment in the hive would decline under low protein conditions, even when nectar abundance or honey stores are sufficient. PMID:28396492

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.

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

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

Van der Waals Interactions Involving Proteins

NASA Technical Reports Server (NTRS)

Roth, Charles M.; Neal, Brian L.; Lenhoff, Abraham M.

1996-01-01

Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. Whereas the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models. with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation, and crystal growth.

Prediction of virus-host protein-protein interactions mediated by short linear motifs.

PubMed

Becerra, Andrés; Bucheli, Victor A; Moreno, Pedro A

2017-03-09

Short linear motifs in host organisms proteins can be mimicked by viruses to create protein-protein interactions that disable or control metabolic pathways. Given that viral linear motif instances of host motif regular expressions can be found by chance, it is necessary to develop filtering methods of functional linear motifs. We conduct a systematic comparison of linear motifs filtering methods to develop a computational approach for predicting motif-mediated protein-protein interactions between human and the human immunodeficiency virus 1 (HIV-1). We implemented three filtering methods to obtain linear motif sets: 1) conserved in viral proteins (C), 2) located in disordered regions (D) and 3) rare or scarce in a set of randomized viral sequences (R). The sets C,D,R are united and intersected. The resulting sets are compared by the number of protein-protein interactions correctly inferred with them - with experimental validation. The comparison is done with HIV-1 sequences and interactions from the National Institute of Allergy and Infectious Diseases (NIAID). The number of correctly inferred interactions allows to rank the interactions by the sets used to deduce them: D∪R and C. The ordering of the sets is descending on the probability of capturing functional interactions. With respect to HIV-1, the sets C∪R, D∪R, C∪D∪R infer all known interactions between HIV1 and human proteins mediated by linear motifs. We found that the majority of conserved linear motifs in the virus are located in disordered regions. We have developed a method for predicting protein-protein interactions mediated by linear motifs between HIV-1 and human proteins. The method only use protein sequences as inputs. We can extend the software developed to any other eukaryotic virus and host in order to find and rank candidate interactions. In future works we will use it to explore possible viral attack mechanisms based on linear motif mimicry.

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.

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

Interplay between binding affinity and kinetics in protein-protein interactions.

PubMed

Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

2016-07-01

To clarify the interplay between the binding affinity and kinetics of protein-protein interactions, and the possible role of intrinsically disordered proteins in such interactions, molecular simulations were carried out on 20 protein complexes. With bias potential and reweighting techniques, the free energy profiles were obtained under physiological affinities, which showed that the bound-state valley is deep with a barrier height of 12 - 33 RT. From the dependence of the affinity on interface interactions, the entropic contribution to the binding affinity is approximated to be proportional to the interface area. The extracted dissociation rates based on the Arrhenius law correlate reasonably well with the experimental values (Pearson correlation coefficient R = 0.79). For each protein complex, a linear free energy relationship between binding affinity and the dissociation rate was confirmed, but the distribution of the slopes for intrinsically disordered proteins showed no essential difference with that observed for ordered proteins. A comparison with protein folding was also performed. Proteins 2016; 84:920-933. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

Wine and grape tannin interactions with salivary proteins and their impact on astringency: a review of current research.

PubMed

McRae, Jacqui M; Kennedy, James A

2011-03-11

Astringency is an important characteristic of red wine quality. The sensation is generally thought to be produced by the interaction of wine tannins with salivary proteins and the subsequent aggregation and precipitation of protein-tannin complexes. The importance of wine astringency for marketability has led to a wealth of research on the causes of astringency and how tannins impact the quality of the sensation, particularly with respect to tannin structure. Ultimately, the understanding of how tannin structure impacts astringency will allow the controlled manipulation of tannins via such methods as micro-oxygenation or fining to improve the quality of wines.

Relevance of protein-protein interactions on the biological identity of nanoparticles.

PubMed

Vasti, Cecilia; Bonnet, Laura V; Galiano, Mauricio R; Rojas, Ricardo; Giacomelli, Carla E

2018-06-01

Considering that the use of nanoparticles (NPs) as carriers of therapeutic or theranostic agents has increased in the last years, it is mandatory to understand the interaction between NPs and living systems. In contact with biological fluids, the NPs (synthetic identity) are covered with biomolecules that form a protein corona, which defines the biological identity. It is well known that the protein corona formation is mediated by non-specific physical interactions, but protein-protein interactions (PPI), involving specific recognition sites of the polypeptides, are also involved. This work explores the relationship between the synthetic and biological identities of layered double hydroxides nanoparticles (LDH-NPs) and the effect of the protein corona on the cellular response. With such a purpose, the synthetic identity was modified by coating LDH-NPs with either a single protein or a complex mixture of them, followed by the characterization of the protein corona formed in a commonly used cell culture medium. A proteomic approach was used to identify the protein corona molecules and the PPI network was constructed with a novel bioinformatic tool. The coating on LDH-NPs defines the biological identity in such a way that the composition of the protein corona as well as PPI are changed. Electrostatic interactions appear not to be the only driving force regulating the interactions between NPs, proteins and cells since the specific recognition also play a fundamental role. However, the biological identity of LDH-NPs does not affect the interactions with cells that shows negligible cytotoxicity and high internalization levels. Copyright © 2018 Elsevier B.V. All rights reserved.

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

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.

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

Computational Prediction of Protein-Protein Interactions

PubMed Central

Ehrenberger, Tobias; Cantley, Lewis C.; Yaffe, Michael B.

2015-01-01

The prediction of protein-protein interactions and kinase-specific phosphorylation sites on individual proteins is critical for correctly placing proteins within signaling pathways and networks. The importance of this type of annotation continues to increase with the continued explosion of genomic and proteomic data, particularly with emerging data categorizing posttranslational modifications on a large scale. A variety of computational tools are available for this purpose. In this chapter, we review the general methodologies for these types of computational predictions and present a detailed user-focused tutorial of one such method and computational tool, Scansite, which is freely available to the entire scientific community over the Internet. PMID:25859943

Bioluminescence Resonance Energy Transfer System for Measuring Dynamic Protein-Protein Interactions in Bacteria

PubMed Central

Cui, Boyu; Wang, Yao; Song, Yunhong; Wang, Tietao; Li, Changfu; Wei, Yahong

2014-01-01

ABSTRACT 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. PMID:24846380

Modeling and simulating networks of interdependent protein interactions.

PubMed

Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

2018-05-21

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package

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.

3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

PubMed

Li, Hui; Liu, Chunmei

2014-06-14

3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

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.

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

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

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

Green fluorescent protein nanopolygons as monodisperse supramolecular assemblies of functional proteins with defined valency

PubMed Central

Kim, Young Eun; Kim, Yu-na; Kim, Jung A.; Kim, Ho Min; Jung, Yongwon

2015-01-01

Supramolecular protein assemblies offer novel nanoscale architectures with molecular precision and unparalleled functional diversity. A key challenge, however, is to create precise nano-assemblies of functional proteins with both defined structures and a controlled number of protein-building blocks. Here we report a series of supramolecular green fluorescent protein oligomers that are assembled in precise polygonal geometries and prepared in a monodisperse population. Green fluorescent protein is engineered to be self-assembled in cells into oligomeric assemblies that are natively separated in a single-protein resolution by surface charge manipulation, affording monodisperse protein (nano)polygons from dimer to decamer. Several functional proteins are multivalently displayed on the oligomers with controlled orientations. Spatial arrangements of protein oligomers and displayed functional proteins are directly visualized by a transmission electron microscope. By employing our functional protein assemblies, we provide experimental insight into multivalent protein–protein interactions and tools to manipulate receptor clustering on live cell surfaces. PMID:25972078

Multi-level machine learning prediction of protein-protein interactions in Saccharomyces cerevisiae.

PubMed

Zubek, Julian; Tatjewski, Marcin; Boniecki, Adam; Mnich, Maciej; Basu, Subhadip; Plewczynski, Dariusz

2015-01-01

Accurate identification of protein-protein interactions (PPI) is the key step in understanding proteins' biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein-protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB) database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein-protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC). Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent).

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

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

New paradigm in ankyrin repeats: Beyond protein-protein interaction module.

PubMed

Islam, Zeyaul; Nagampalli, Raghavendra Sashi Krishna; Fatima, Munazza Tamkeen; Ashraf, Ghulam Md

2018-04-01

Classically, ankyrin repeat (ANK) proteins are built from tandems of two or more repeats and form curved solenoid structures that are associated with protein-protein interactions. These are short, widespread structural motif of around 33 amino acids repeats in tandem, having a canonical helix-loop-helix fold, found individually or in combination with other domains. The multiplicity of structural pattern enables it to form assemblies of diverse sizes, required for their abilities to confer multiple binding and structural roles of proteins. Three-dimensional structures of these repeats determined to date reveal a degree of structural variability that translates into the considerable functional versatility of this protein superfamily. Recent work on the ANK has proposed novel structural information, especially protein-lipid, protein-sugar and protein-protein interaction. Self-assembly of these repeats was also shown to prevent the associated protein in forming filaments. In this review, we summarize the latest findings and how the new structural information has increased our understanding of the structural determinants of ANK proteins. We discussed latest findings on how these proteins participate in various interactions to diversify the ANK roles in numerous biological processes, and explored the emerging and evolving field of designer ankyrins and its framework for protein engineering emphasizing on biotechnological applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Optoelectronic tweezers integrated with lensfree holographic microscopy for wide-field interactive cell and particle manipulation on a chip.

PubMed

Huang, Kuo-Wei; Su, Ting-Wei; Ozcan, Aydogan; Chiou, Pei-Yu

2013-06-21

We demonstrate an optoelectronic tweezer (OET) coupled to a lensfree holographic microscope for real-time interactive manipulation of cells and micro-particles over a large field-of-view (FOV). This integrated platform can record the holographic images of cells and particles over the entire active area of a CCD sensor array, perform digital image reconstruction to identify target cells, dynamically track the positions of cells and particles, and project light beams to trigger light-induced dielectrophoretic forces to pattern and sort cells on a chip. OET technology has been previously shown to be capable of performing parallel single cell manipulation over a large area. However, its throughput has been bottlenecked by the number of cells that can be imaged within the limited FOV of a conventional microscope objective lens. Integrating lensfree holographic imaging with OET solves this fundamental FOV barrier, while also creating a compact on-chip cell/particle manipulation platform. Using this unique platform, we have successfully demonstrated real-time interactive manipulation of thousands of single cells and micro-particles over an ultra-large area of e.g., 240 mm(2) (i.e. 17.96 mm × 13.52 mm).

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.

NPIDB: Nucleic acid-Protein Interaction DataBase.

PubMed

Kirsanov, Dmitry D; Zanegina, Olga N; Aksianov, Evgeniy A; Spirin, Sergei A; Karyagina, Anna S; Alexeevski, Andrei V

2013-01-01

The Nucleic acid-Protein Interaction DataBase (http://npidb.belozersky.msu.ru/) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from the Protein Data Bank (3846 complexes in October 2012). It provides a web interface and a set of tools for extracting biologically meaningful characteristics of nucleoprotein complexes. The content of the database is updated weekly. The current version of the Nucleic acid-Protein Interaction DataBase is an upgrade of the version published in 2007. The improvements include a new web interface, new tools for calculation of intermolecular interactions, a classification of SCOP families that contains DNA-binding protein domains and data on conserved water molecules on the DNA-protein interface.

Inhibition of Protein-Protein Interactions and Signaling by Small Molecules

NASA Astrophysics Data System (ADS)

Freire, Ernesto

2010-03-01

Protein-protein interactions are at the core of cell signaling pathways as well as many bacterial and viral infection processes. As such, they define critical targets for drug development against diseases such as cancer, arthritis, obesity, AIDS and many others. Until now, the clinical inhibition of protein-protein interactions and signaling has been accomplished with the use of antibodies or soluble versions of receptor molecules. Small molecule replacements of these therapeutic agents have been extremely difficult to develop; either the necessary potency has been hard to achieve or the expected biological effect has not been obtained. In this presentation, we show that a rigorous thermodynamic approach that combines differential scanning calorimetry (DSC) and isothermal titration calorimetry (ITC) provides a unique platform for the identification and optimization of small molecular weight inhibitors of protein-protein interactions. Recent advances in the development of cell entry inhibitors of HIV-1 using this approach will be discussed.

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

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

Course 1: Physics of Protein-DNA Interaction

NASA Astrophysics Data System (ADS)

Bruinsma, R. F.

1 Introduction 1.1 The central dogma and bacterial gene expression 1.2 Molecular structure 2 Thermodynamics and kinetics of repressor-DNA interaction 2.1 Thermodynamics and the lac repressor 2.2 Kinetics of repressor-DNA interaction 3 DNA deformability and protein-DNA interaction 3.1 Introduction 3.2 The worm-like chain 3.3 The RST model 4 Electrostatics in water and protein-DNA interaction 4.1 Macro-ions and aqueous electrostatics 4.2 The primitive model 4.3 Manning condensation 4.4 Counter-ion release and non-specific protein-DNA interaction

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

Kinetic Measurements Reveal Enhanced Protein-Protein Interactions at Intercellular Junctions

PubMed Central

Shashikanth, Nitesh; Kisting, Meridith A.; Leckband, Deborah E.

2016-01-01

The binding properties of adhesion proteins are typically quantified from measurements with soluble fragments, under conditions that differ radically from the confined microenvironment of membrane bound proteins in adhesion zones. Using classical cadherin as a model adhesion protein, we tested the postulate that confinement within quasi two-dimensional intercellular gaps exposes weak protein interactions that are not detected in solution binding assays. Micropipette-based measurements of cadherin-mediated, cell-cell binding kinetics identified a unique kinetic signature that reflects both adhesive (trans) bonds between cadherins on opposing cells and lateral (cis) interactions between cadherins on the same cell. In solution, proposed lateral interactions were not detected, even at high cadherin concentrations. Mutations postulated to disrupt lateral cadherin association altered the kinetic signatures, but did not affect the adhesive (trans) binding affinity. Perturbed kinetics further coincided with altered cadherin distributions at junctions, wound healing dynamics, and paracellular permeability. Intercellular binding kinetics thus revealed cadherin interactions that occur within confined, intermembrane gaps but not in solution. Findings further demonstrate the impact of these revealed interactions on the organization and function of intercellular junctions. PMID:27009566

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/ .

Incoherent manipulation of the photoactive yellow protein photocycle with dispersed pump-dump-probe spectroscopy.

PubMed

Larsen, Delmar S; van Stokkum, Ivo H M; Vengris, Mikas; van Der Horst, Michael A; de Weerd, Frank L; Hellingwerf, Klaas J; van Grondelle, Rienk

2004-09-01

Photoactive yellow protein is the protein responsible for initiating the "blue-light vision" of Halorhodospira halophila. The dynamical processes responsible for triggering the photoactive yellow protein photocycle have been disentangled with the use of a novel application of dispersed ultrafast pump-dump-probe spectroscopy, where the photocycle can be started and interrupted with appropriately tuned and timed laser pulses. This "incoherent" manipulation of the photocycle allows for the detailed spectroscopic investigation of the underlying photocycle dynamics and the construction of a fully self-consistent dynamical model. This model requires three kinetically distinct excited-state intermediates, two (ground-state) photocycle intermediates, I(0) and pR, and a ground-state intermediate through which the protein, after unsuccessful attempts at initiating the photocycle, returns to the equilibrium ground state. Also observed is a previously unknown two-photon ionization channel that generates a radical and an ejected electron into the protein environment. This second excitation pathway evolves simultaneously with the pathway containing the one-photon photocycle intermediates.

Ion-dipole interactions and their functions in proteins.

PubMed

Sippel, Katherine H; Quiocho, Florante A

2015-07-01

Ion-dipole interactions in biological macromolecules are formed between atomic or molecular ions and neutral protein dipolar groups through either hydrogen bond or coordination. Since their discovery 30 years ago, these interactions have proven to be a frequent occurrence in protein structures, appearing in everything from transporters and ion channels to enzyme active sites to protein-protein interfaces. However, their significance and roles in protein functions are largely underappreciated. We performed PDB data mining to identify a sampling of proteins that possess these interactions. In this review, we will define the ion-dipole interaction and discuss several prominent examples of their functional roles in nature. © 2015 The Protein Society.

Energetics of protein-DNA interactions.

PubMed

Donald, Jason E; Chen, William W; Shakhnovich, Eugene I

2007-01-01

Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.

Single Molecule Approaches in RNA-Protein Interactions.

PubMed

Serebrov, Victor; Moore, Melissa J

RNA-protein interactions govern every aspect of RNA metabolism, and aberrant RNA-binding proteins are the cause of hundreds of genetic diseases. Quantitative measurements of these interactions are necessary in order to understand mechanisms leading to diseases and to develop efficient therapies. Existing methods of RNA-protein interactome capture can afford a comprehensive snapshot of RNA-protein interaction networks but lack the ability to characterize the dynamics of these interactions. As all ensemble methods, their resolution is also limited by statistical averaging. Here we discuss recent advances in single molecule techniques that have the potential to tackle these challenges. We also provide a thorough overview of single molecule colocalization microscopy and the essential protein and RNA tagging and detection techniques.

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.

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.

Monitoring Ligand-Activated Protein-Protein Interactions Using Bioluminescent Resonance Energy Transfer (BRET) Assay.

PubMed

Coriano, Carlos; Powell, Emily; Xu, Wei

2016-01-01

The bioluminescent resonance energy transfer (BRET) assay has been extensively used in cell-based and in vivo imaging systems for detecting protein-protein interactions in the native environment of living cells. These protein-protein interactions are essential for the functional response of many signaling pathways to environmental chemicals. BRET has been used as a toxicological tool for identifying chemicals that either induce or inhibit these protein-protein interactions. This chapter focuses on describing the toxicological applications of BRET and its optimization as a high-throughput detection system in live cells. Here we review the construction of BRET fusion proteins, describe the BRET methodology, and outline strategies to overcome obstacles that may arise. Furthermore, we describe the advantage of BRET over other resonance energy transfer methods for monitoring protein-protein interactions.

RNA polymerase II conserved protein domains as platforms for protein-protein interactions

PubMed Central

García-López, M Carmen

2011-01-01

RNA polymerase II establishes many protein-protein interactions with transcriptional regulators to coordinate gene expression, but little is known about protein domains involved in the contact with them. We use a new approach to look for conserved regions of the RNA pol II of S. cerevisiae located at the surface of the structure of the complex, hypothesizing that they might be involved in the interaction with transcriptional regulators. We defined five different conserved domains and demonstrate that all of them make contact with transcriptional regulators. PMID:21922063

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.

Free energy decomposition of protein-protein interactions.

PubMed

Noskov, S Y; Lim, C

2001-08-01

A free energy decomposition scheme has been developed and tested on antibody-antigen and protease-inhibitor binding for which accurate experimental structures were available for both free and bound proteins. Using the x-ray coordinates of the free and bound proteins, the absolute binding free energy was computed assuming additivity of three well-defined, physical processes: desolvation of the x-ray structures, isomerization of the x-ray conformation to a nearby local minimum in the gas-phase, and subsequent noncovalent complex formation in the gas phase. This free energy scheme, together with the Generalized Born model for computing the electrostatic solvation free energy, yielded binding free energies in remarkable agreement with experimental data. Two assumptions commonly used in theoretical treatments; viz., the rigid-binding approximation (which assumes no conformational change upon complexation) and the neglect of vdW interactions, were found to yield large errors in the binding free energy. Protein-protein vdW and electrostatic interactions between complementary surfaces over a relatively large area (1400--1700 A(2)) were found to drive antibody-antigen and protease-inhibitor binding.

Protein interactions in concentrated ribonuclease solutions

NASA Astrophysics Data System (ADS)

Boyer, Mireille; Roy, Marie-Odile; Jullien, Magali; Bonneté, Françoise; Tardieu, Annette

1999-01-01

To investigate the protein interactions involved in the crystallization process of ribonuclease A, dynamic light scattering (DLS) and small angle X-ray scattering experiments (SAXS) were performed on concentrated solutions. Whereas the translational diffusion coefficient obtained from DLS is sensitive to thermodynamic and hydrodynamic interactions and permits to calculate an interaction parameter, the shape of the SAXS curves is related to the type of interaction (attractive or repulsive). We compared the effect of pH on protein interactions in the case of two types of crystallizing agents: a mixture of salts (3 M sodium chloride plus 0.2 M ammonium sulfate) and an organic solvent (ethanol). The results show that in the presence of ethanol, as in low salt, protein interactions become more attractive as the pH increases from 4 to 8 and approaches the isoelectric point. In contrast, a reverse effect is observed in high salt conditions: the strength of attractive interactions decreases as the pH increases. The range of the pH effect can be related to ionization of histidine residues, particularly those located in the active site of the protein. The present observations point out the important role played by localized charges in crystallization conditions, whatever the precipitating agent.

Predicting protein functions from redundancies in large-scale protein interaction networks

NASA Technical Reports Server (NTRS)

Samanta, Manoj Pratim; Liang, Shoudan

2003-01-01

Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Revisiting Mathematics Manipulative Materials

ERIC Educational Resources Information Center

Swan, Paul; Marshall, Linda

2010-01-01

It is over 12 years since "APMC" published Bob Perry and Peter Howard's research on the use of mathematics manipulative materials in primary mathematics classrooms. Since then the availability of virtual manipulatives and associated access to computers and interactive whiteboards have caused educators to rethink the use of mathematics…

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

On the role of electrostatics in protein-protein interactions

NASA Astrophysics Data System (ADS)

Zhang, Zhe; Witham, Shawn; Alexov, Emil

2011-06-01

The role of electrostatics in protein-protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity.

RAIN: RNA–protein Association and Interaction Networks

PubMed Central

Junge, Alexander; Refsgaard, Jan C.; Garde, Christian; Pan, Xiaoyong; Santos, Alberto; Alkan, Ferhat; Anthon, Christian; von Mering, Christian; Workman, Christopher T.; Jensen, Lars Juhl; Gorodkin, Jan

2017-01-01

Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA–RNA and ncRNA–protein interactions and its integration with the STRING database of protein–protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literature mining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessible web interface and all interaction data can be downloaded. Database URL: http://rth.dk/resources/rain PMID:28077569

PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

NASA Astrophysics Data System (ADS)

Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

2011-06-01

Physics approaches focus on uncovering, modeling and quantitating the general principles governing the micro and macro universe. This has always been an important component of biological research, however recent advances in experimental techniques and the accumulation of unprecedented genome-scale experimental data produced by these novel technologies now allow for addressing fundamental questions on a large scale. These relate to molecular interactions, principles of bimolecular recognition, and mechanisms of signal propagation. The functioning of a cell requires a variety of intermolecular interactions including protein-protein, protein-DNA, protein-RNA, hormones, peptides, small molecules, lipids and more. Biomolecules work together to provide specific functions and perturbations in intermolecular communication channels often lead to cellular malfunction and disease. A full understanding of the interactome requires an in-depth grasp of the biophysical principles underlying individual interactions as well as their organization in cellular networks. Phenomena can be described at different levels of abstraction. Computational and systems biology strive to model cellular processes by integrating and analyzing complex data from multiple experimental sources using interdisciplinary tools. As a result, both the causal relationships between the variables and the general features of the system can be discovered, which even without knowing the details of the underlying mechanisms allow for putting forth hypotheses and predicting the behavior of the systems in response to perturbation. And here lies the strength of in silico models which provide control and predictive power. At the same time, the complexity of individual elements and molecules can be addressed by the fields of molecular biophysics, physical biology and structural biology, which focus on the underlying physico-chemical principles and may explain the molecular mechanisms of cellular function. In this issue

Protein-protein interactions within late pre-40S ribosomes.

PubMed

Campbell, Melody G; Karbstein, Katrin

2011-01-20

Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps.

Real-time interactive 3D manipulation of particles viewed in two orthogonal observation planes.

PubMed

Perch-Nielsen, Ivan; Rodrigo, Peter; Glückstad, Jesper

2005-04-18

The generalized phase contrast (GPC) method has been applied to transform a single TEM00 beam into a manifold of counterpropagating-beam traps capable of real-time interactive manipulation of multiple microparticles in three dimensions (3D). This paper reports on the use of low numerical aperture (NA), non-immersion, objective lenses in an implementation of the GPC-based 3D trapping system. Contrary to high-NA based optical tweezers, the GPC trapping system demonstrated here operates with long working distance (>10 mm), and offers a wider manipulation region and a larger field of view for imaging through each of the two opposing objective lenses. As a consequence of the large working distance, simultaneous monitoring of the trapped particles in a second orthogonal observation plane is demonstrated.

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.

Mapping protein-DNA and protein-protein interactions of ATP-dependent chromatin remodelers.

PubMed

Hota, Swetansu K; Dechassa, Mekonnen Lemma; Prasad, Punit; Bartholomew, Blaine

2012-01-01

Chromatin plays a key regulatory role in several DNA-dependent processes as it regulates DNA access to different protein factors. Several multisubunit protein complexes interact, modify, or mobilize nucleosomes: the basic unit of chromatin, from its original location in an ATP-dependent manner to facilitate processes, such as transcription, replication, repair, and recombination. Knowledge of the interactions of chromatin remodelers with nucleosomes is a crucial requirement to understand the mechanism of chromatin remodeling. Here, we describe several methods to analyze the interactions of multisubunit chromatin-remodeling enzymes with nucleosomes.

Moonlighting Proteins and Protein–Protein Interactions as Neurotherapeutic Targets in the G Protein-Coupled Receptor Field

PubMed Central

Fuxe, Kjell; Borroto-Escuela, Dasiel O; Romero-Fernandez, Wilber; Palkovits, Miklós; Tarakanov, Alexander O; Ciruela, Francisco; Agnati, Luigi F

2014-01-01

There is serious interest in understanding the dynamics of the receptor–receptor and receptor–protein interactions in space and time and their integration in GPCR heteroreceptor complexes of the CNS. Moonlighting proteins are special multifunctional proteins because they perform multiple autonomous, often unrelated, functions without partitioning into different protein domains. Moonlighting through receptor oligomerization can be operationally defined as an allosteric receptor–receptor interaction, which leads to novel functions of at least one receptor protomer. GPCR-mediated signaling is a more complicated process than previously described as every GPCR and GPCR heteroreceptor complex requires a set of G protein interacting proteins, which interacts with the receptor in an orchestrated spatio-temporal fashion. GPCR heteroreceptor complexes with allosteric receptor–receptor interactions operating through the receptor interface have become major integrative centers at the molecular level and their receptor protomers act as moonlighting proteins. The GPCR heteroreceptor complexes in the CNS have become exciting new targets for neurotherapeutics in Parkinson's disease, schizophrenia, drug addiction, and anxiety and depression opening a new field in neuropsychopharmacology. PMID:24105074

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.

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.

PLIP: fully automated protein-ligand interaction profiler.

PubMed

Salentin, Sebastian; Schreiber, Sven; Haupt, V Joachim; Adasme, Melissa F; Schroeder, Michael

2015-07-01

The characterization of interactions in protein-ligand complexes is essential for research in structural bioinformatics, drug discovery and biology. However, comprehensive tools are not freely available to the research community. Here, we present the protein-ligand interaction profiler (PLIP), a novel web service for fully automated detection and visualization of relevant non-covalent protein-ligand contacts in 3D structures, freely available at projects.biotec.tu-dresden.de/plip-web. The input is either a Protein Data Bank structure, a protein or ligand name, or a custom protein-ligand complex (e.g. from docking). In contrast to other tools, the rule-based PLIP algorithm does not require any structure preparation. It returns a list of detected interactions on single atom level, covering seven interaction types (hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges and halogen bonds). PLIP stands out by offering publication-ready images, PyMOL session files to generate custom images and parsable result files to facilitate successive data processing. The full python source code is available for download on the website. PLIP's command-line mode allows for high-throughput interaction profiling. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Regulation of PXR and CAR by protein-protein interaction and signaling crosstalk

PubMed Central

Oladimeji, Peter; Cui, Hongmei; Zhang, Chen; Chen, Taosheng

2016-01-01

Introduction Protein-protein interaction and signaling crosstalk contribute to the regulation of pregnane X receptor (PXR) and constitutive androstane receptor (CAR) and broaden their cellular function. Area covered This review covers key historic discoveries and recent advances in our understanding of the broad function of PXR and CAR and their regulation by protein-protein interaction and signaling crosstalk. Expert opinion PXR and CAR were first discovered as xenobiotic receptors. However, it is clear that PXR and CAR perform a much broader range of cellular functions through protein-protein interaction and signaling crosstalk, which typically mutually affect the function of all the partners involved. Future research on PXR and CAR should, therefore, look beyond their xenobiotic function. PMID:27295009

On the role of electrostatics on protein-protein interactions

PubMed Central

Zhang, Zhe; Witham, Shawn; Alexov, Emil

2011-01-01

The role of electrostatics on protein-protein interactions and binding is reviewed in this article. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and basic electrostatic effects occurring upon the formation of the complex are discussed. The role of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated and indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartment. At the end, the similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity. PMID:21572182

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803.

PubMed

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactions as well as their protein-level interactions using the model cyanobacterium, Synechocystis sp. PCC 6803. It predicts the protein-protein interactions using public interaction databases that contain mutually complementary and redundant data. Furthermore, SynechoNET provides information on transmembrane topology, signal peptide, and domain structure in order to support the analysis of regulatory membrane proteins. Such biological information can be queried and visualized in user-friendly web interfaces that include the interactive network viewer and search pages by keyword and functional category. SynechoNET is an integrated protein-protein interaction database designed to analyze regulatory membrane proteins in cyanobacteria. It provides a platform for biologists to extend the genomic data of cyanobacteria by predicting interaction partners, membrane association, and membrane topology of Synechocystis proteins. SynechoNET is freely available at http://synechocystis.org/ or directly at http://bioportal.kobic.kr/SynechoNET/.

A Laboratory-Intensive Course on the Experimental Study of Protein-Protein Interactions

ERIC Educational Resources Information Center

Witherow, D. Scott; Carson, Sue

2011-01-01

The study of protein-protein interactions is important to scientists in a wide range of disciplines. We present here the assessment of a lab-intensive course that teaches students techniques used to identify and further study protein-protein interactions. One of the unique elements of the course is that students perform a yeast two-hybrid screen…

Measuring protein-protein and protein-nucleic Acid interactions by biolayer interferometry.

PubMed

Sultana, Azmiri; Lee, Jeffrey E

2015-02-02

Biolayer interferometry (BLI) is a simple, optical dip-and-read system useful for measuring interactions between proteins, peptides, nucleic acids, small molecules, and/or lipids in real time. In BLI, a biomolecular bait is immobilized on a matrix at the tip of a fiber-optic sensor. The binding between the immobilized ligand and another molecule in an analyte solution produces a change in optical thickness at the tip and results in a wavelength shift proportional to binding. BLI provides direct binding affinities and rates of association and dissociation. This unit describes an efficient approach using streptavidin-based BLI to analyze DNA-protein and protein-protein interactions. A quantitative set of equilibrium binding affinities (K(d)) and rates of association and dissociation (k(a)/k(d)) can be measured in minutes using nanomole quantities of sample. Copyright © 2015 John Wiley & Sons, Inc.

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.

Prediction of Heterodimeric Protein Complexes from Weighted Protein-Protein Interaction Networks Using Novel Features and Kernel Functions

PubMed Central

Ruan, Peiying; Hayashida, Morihiro; Maruyama, Osamu; Akutsu, Tatsuya

2013-01-01

Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes. PMID:23776458

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

PubMed

Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Parallel force assay for protein-protein interactions.

PubMed

Aschenbrenner, Daniela; Pippig, Diana A; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E

2014-01-01

Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay.

Surface energetics and protein-protein interactions: analysis and mechanistic implications

PubMed Central

Peri, Claudio; Morra, Giulia; Colombo, Giorgio

2016-01-01

Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions. PMID:27050828

Toward a molecular understanding of nanoparticle-protein interactions.

PubMed

Treuel, Lennart; Nienhaus, Gerd Ulrich

2012-06-01

Wherever nanoparticles (NPs) come in contact with a living organism, physical and chemical interactions take place between the surfaces of the NPs and biomatter, in particular proteins. When NP are exposed to biological fluids, an adsorption layer of proteins, a "protein corona" forms around the NPs. Consequently, living systems interact with the protein-coated NP rather than with a bare NP. To anticipate biological responses to NPs, we thus require comprehensive knowledge of the interactions at the bio-nano interface. In recent years, a wide variety of biophysical techniques have been employed to elucidate mechanistic aspects of NP-protein interactions. In this brief review, we present the latest findings regarding the composition of the protein corona as it forms on NPs in the blood stream. We also discuss molecular aspects of this adsorption layer and its time evolution. The current state of knowledge is summarized, and issues that still need to be addressed to further advance our understanding of NP-protein interactions are identified.

Protein-Protein Interactions within Late Pre-40S Ribosomes

PubMed Central

Campbell, Melody G.; Karbstein, Katrin

2011-01-01

Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps. PMID:21283762

SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome.

PubMed

Li, Yiwei; Ilie, Lucian

2017-11-15

Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Many computational methods have been proposed among which sequence-based ones are very promising. However, so far no such method is able to predict effectively the entire human interactome: they require too much time or memory. We present SPRINT (Scoring PRotein INTeractions), a new sequence-based algorithm and tool for predicting protein-protein interactions. We comprehensively compare SPRINT with state-of-the-art programs on seven most reliable human PPI datasets and show that it is more accurate while running orders of magnitude faster and using very little memory. SPRINT is the only sequence-based program that can effectively predict the entire human interactome: it requires between 15 and 100 min, depending on the dataset. Our goal is to transform the very challenging problem of predicting the entire human interactome into a routine task. The source code of SPRINT is freely available from https://github.com/lucian-ilie/SPRINT/ and the datasets and predicted PPIs from www.csd.uwo.ca/faculty/ilie/SPRINT/ .

Analysis of hand contact areas and interaction capabilities during manipulation and exploration.

PubMed

Gonzalez, Franck; Gosselin, Florian; Bachta, Wael

2014-01-01

Manual human-computer interfaces for virtual reality are designed to allow an operator interacting with a computer simulation as naturally as possible. Dexterous haptic interfaces are the best suited for this goal. They give intuitive and efficient control on the environment with haptic and tactile feedback. This paper is aimed at helping in the choice of the interaction areas to be taken into account in the design of such interfaces. The literature dealing with hand interactions is first reviewed in order to point out the contact areas involved in exploration and manipulation tasks. Their frequencies of use are then extracted from existing recordings. The results are gathered in an original graphical interaction map allowing for a simple visualization of the way the hand is used, and compared with a map of mechanoreceptors densities. Then an interaction tree, mapping the relative amount of actions made available through the use of a given contact area, is built and correlated with the losses of hand function induced by amputations. A rating of some existing haptic interfaces and guidelines for their design are finally achieved to illustrate a possible use of the developed graphical tools.

Kinome signaling through regulated protein-protein interactions in normal and cancer cells.

PubMed

Pawson, Tony; Kofler, Michael

2009-04-01

The flow of molecular information through normal and oncogenic signaling pathways frequently depends on protein phosphorylation, mediated by specific kinases, and the selective binding of the resulting phosphorylation sites to interaction domains present on downstream targets. This physical and functional interplay of catalytic and interaction domains can be clearly seen in cytoplasmic tyrosine kinases such as Src, Abl, Fes, and ZAP-70. Although the kinase and SH2 domains of these proteins possess similar intrinsic properties of phosphorylating tyrosine residues or binding phosphotyrosine sites, they also undergo intramolecular interactions when linked together, in a fashion that varies from protein to protein. These cooperative interactions can have diverse effects on substrate recognition and kinase activity, and provide a variety of mechanisms to link the stimulation of catalytic activity to substrate recognition. Taken together, these data have suggested how protein kinases, and the signaling pathways in which they are embedded, can evolve complex properties through the stepwise linkage of domains within single polypeptides or multi-protein assemblies.

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

Prediction of protein-protein interaction sites using electrostatic desolvation profiles.

PubMed

Fiorucci, Sébastien; Zacharias, Martin

2010-05-19

Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

PubMed Central

Fiorucci, Sébastien; Zacharias, Martin

2010-01-01

Abstract Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. PMID:20441756

Incoherent Manipulation of the Photoactive Yellow Protein Photocycle with Dispersed Pump-Dump-Probe Spectroscopy

PubMed Central

Larsen, Delmar S.; van Stokkum, Ivo H. M.; Vengris, Mikas; van der Horst, Michael A.; de Weerd, Frank L.; Hellingwerf, Klaas J.; van Grondelle, Rienk

2004-01-01

Photoactive yellow protein is the protein responsible for initiating the “blue-light vision” of Halorhodospira halophila. The dynamical processes responsible for triggering the photoactive yellow protein photocycle have been disentangled with the use of a novel application of dispersed ultrafast pump-dump-probe spectroscopy, where the photocycle can be started and interrupted with appropriately tuned and timed laser pulses. This “incoherent” manipulation of the photocycle allows for the detailed spectroscopic investigation of the underlying photocycle dynamics and the construction of a fully self-consistent dynamical model. This model requires three kinetically distinct excited-state intermediates, two (ground-state) photocycle intermediates, I0 and pR, and a ground-state intermediate through which the protein, after unsuccessful attempts at initiating the photocycle, returns to the equilibrium ground state. Also observed is a previously unknown two-photon ionization channel that generates a radical and an ejected electron into the protein environment. This second excitation pathway evolves simultaneously with the pathway containing the one-photon photocycle intermediates. PMID:15345564

Reconstituting protein interaction networks using parameter-dependent domain-domain interactions

PubMed Central

2013-01-01

Background We can describe protein-protein interactions (PPIs) as sets of distinct domain-domain interactions (DDIs) that mediate the physical interactions between proteins. Experimental data confirm that DDIs are more consistent than their corresponding PPIs, lending support to the notion that analyses of DDIs may improve our understanding of PPIs and lead to further insights into cellular function, disease, and evolution. However, currently available experimental DDI data cover only a small fraction of all existing PPIs and, in the absence of structural data, determining which particular DDI mediates any given PPI is a challenge. Results We present two contributions to the field of domain interaction analysis. First, we introduce a novel computational strategy to merge domain annotation data from multiple databases. We show that when we merged yeast domain annotations from six annotation databases we increased the average number of domains per protein from 1.05 to 2.44, bringing it closer to the estimated average value of 3. Second, we introduce a novel computational method, parameter-dependent DDI selection (PADDS), which, given a set of PPIs, extracts a small set of domain pairs that can reconstruct the original set of protein interactions, while attempting to minimize false positives. Based on a set of PPIs from multiple organisms, our method extracted 27% more experimentally detected DDIs than existing computational approaches. Conclusions We have provided a method to merge domain annotation data from multiple sources, ensuring large and consistent domain annotation for any given organism. Moreover, we provided a method to extract a small set of DDIs from the underlying set of PPIs and we showed that, in contrast to existing approaches, our method was not biased towards DDIs with low or high occurrence counts. Finally, we used these two methods to highlight the influence of the underlying annotation density on the characteristics of extracted DDIs. Although

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.

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.

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

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

PubMed

Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be

A Brief Review of RNA–Protein Interaction Database Resources

PubMed Central

Yi, Ying; Zhao, Yue; Huang, Yan; Wang, Dong

2017-01-01

RNA–Protein interactions play critical roles in various biological processes. By collecting and analyzing the RNA–Protein interactions and binding sites from experiments and predictions, RNA–Protein interaction databases have become an essential resource for the exploration of the transcriptional and post-transcriptional regulatory network. Here, we briefly review several widely used RNA–Protein interaction database resources developed in recent years to provide a guide of these databases. The content and major functions in databases are presented. The brief description of database helps users to quickly choose the database containing information they interested. In short, these RNA–Protein interaction database resources are continually updated, but the current state shows the efforts to identify and analyze the large amount of RNA–Protein interactions. PMID:29657278

Folding superfunnel to describe cooperative folding of interacting proteins.

PubMed

Smeller, László

2016-07-01

This paper proposes a generalization of the well-known folding funnel concept of proteins. In the funnel model the polypeptide chain is treated as an individual object not interacting with other proteins. Since biological systems are considerably crowded, protein-protein interaction is a fundamental feature during the life cycle of proteins. The folding superfunnel proposed here describes the folding process of interacting proteins in various situations. The first example discussed is the folding of the freshly synthesized protein with the aid of chaperones. Another important aspect of protein-protein interactions is the folding of the recently characterized intrinsically disordered proteins, where binding to target proteins plays a crucial role in the completion of the folding process. The third scenario where the folding superfunnel is used is the formation of aggregates from destabilized proteins, which is an important factor in case of several conformational diseases. The folding superfunnel constructed here with the minimal assumption about the interaction potential explains all three cases mentioned above. Proteins 2016; 84:1009-1016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell.

PubMed

De Las Rivas, Javier; Fontanillo, Celia

2012-11-01

Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics.

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

A convenient method for synthesis of glyconanoparticles for colorimetric measuring carbohydrate-protein interactions

PubMed Central

Chuang, Yen-Jun; Zhou, Xichun; Pan, Zhengwei; Turchi, Craig

2009-01-01

Carbohydrate functionalized nanoparticles, i.e., the glyconanoparticles, have wide application ranging from studies of carbohydrate-protein interactions, in vivo cell imaging, biolabeling, etc. Currently reported methods for preparation of glyconanoaprticles require multi-step modifications of carbohydrates moieties to conjugate to nanoparticle surface. However, the required synthetic manipulations are difficult and time consuming. We report herewith a simple and versatile method for preparing glyconanoparticles. This method is based on the utilization of clean and convenient microwave irradiation energy for one-step, site-specific conjugation of unmodified carbohydrates onto hydrazide-functionalized Au nanoparticles. A colorimetric assay that utilizes the ensemble of gold glyconanoparticles and Concanavalin A (ConA) was also presented. This feasible assay system was developed to analyze multivalent interactions and to determine the dissociation constant (Kd) for five kind of Au glyconanoparticles with lectin. Surface plasmon changes of the Au glyconanparticles as a function of lectin-carbohydrate interactions were measured and the dissociation constants were determined based on non-linear curve fitting. The strength of the interaction of carbohydrates with ConA was found to be as follows: Maltose > Mannose > Glucose > Lactose > MAN5. PMID:19698698

Multiple protein-protein interactions converging on the Prp38 protein during activation of the human spliceosome.

PubMed

Schütze, Tonio; Ulrich, Alexander K C; Apelt, Luise; Will, Cindy L; Bartlick, Natascha; Seeger, Martin; Weber, Gert; Lührmann, Reinhard; Stelzl, Ulrich; Wahl, Markus C

2016-02-01

Spliceosomal Prp38 proteins contain a conserved amino-terminal domain, but only higher eukaryotic orthologs also harbor a carboxy-terminal RS domain, a hallmark of splicing regulatory SR proteins. We show by crystal structure analysis that the amino-terminal domain of human Prp38 is organized around three pairs of antiparallel α-helices and lacks similarities to RNA-binding domains found in canonical SR proteins. Instead, yeast two-hybrid analyses suggest that the amino-terminal domain is a versatile protein-protein interaction hub that possibly binds 12 other spliceosomal proteins, most of which are recruited at the same stage as Prp38. By quantitative, alanine surface-scanning two-hybrid screens and biochemical analyses we delineated four distinct interfaces on the Prp38 amino-terminal domain. In vitro interaction assays using recombinant proteins showed that Prp38 can bind at least two proteins simultaneously via two different interfaces. Addition of excess Prp38 amino-terminal domain to in vitro splicing assays, but not of an interaction-deficient mutant, stalled splicing at a precatalytic stage. Our results show that human Prp38 is an unusual SR protein, whose amino-terminal domain is a multi-interface protein-protein interaction platform that might organize the relative positioning of other proteins during splicing. © 2016 Schütze et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Comprehensive peptidomimetic libraries targeting protein-protein interactions.

PubMed

Whitby, Landon R; Boger, Dale L

2012-10-16

Transient protein-protein interactions (PPIs) are essential components in cellular signaling pathways as well as in important processes such as viral infection, replication, and immune suppression. The unknown or uncharacterized PPIs involved in such interaction networks often represent compelling therapeutic targets for drug discovery. To date, however, the main strategies for discovery of small molecule modulators of PPIs are typically limited to structurally characterized targets. Recent developments in molecular scaffolds that mimic the side chain display of peptide secondary structures have yielded effective designs, but few screening libraries of such mimetics are available to interrogate PPI targets. We initiated a program to prepare a comprehensive small molecule library designed to mimic the three major recognition motifs that mediate PPIs (α-helix, β-turn, and β-strand). Three libraries would be built around templates designed to mimic each such secondary structure and substituted with all triplet combinations of groups representing the 20 natural amino acid side chains. When combined, the three libraries would contain a member capable of mimicking the key interaction and recognition residues of most targetable PPIs. In this Account, we summarize the results of the design, synthesis, and validation of an 8000 member α-helix mimetic library and a 4200 member β-turn mimetic library. We expect that the screening of these libraries will not only provide lead structures against α-helix- or β-turn-mediated protein-protein or peptide-receptor interactions, even if the nature of the interaction is unknown, but also yield key insights into the recognition motif (α-helix or β-turn) and identify the key residues mediating the interaction. Consistent with this expectation, the screening of the libraries against p53/MDM2 and HIV-1 gp41 (α-helix mimetic library) or the opioid receptors (β-turn mimetic library) led to the discovery of library members expected

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%).

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.

Protein-Protein Interactions of Azurin Complex by Coarse-Grained Simulations with a Gō-Like Model

NASA Astrophysics Data System (ADS)

Rusmerryani, Micke; Takasu, Masako; Kawaguchi, Kazutomo; Saito, Hiroaki; Nagao, Hidemi

Proteins usually perform their biological functions by forming a complex with other proteins. It is very important to study the protein-protein interactions since these interactions are crucial in many processes of a living organism. In this study, we develop a coarse grained model to simulate protein complex in liquid system. We carry out molecular dynamics simulations with topology-based potential interactions to simulate dynamical properties of Pseudomonas Aeruginosa azurin complex systems. Azurin is known to play an essential role as an anticancer agent and bind many important intracellular molecules. Some physical properties are monitored during simulation time to get a better understanding of the influence of protein-protein interactions to the azurin complex dynamics. These studies will provide valuable insights for further investigation on protein-protein interactions in more realistic system.

Precise Manipulation and Patterning of Protein Crystals for Macromolecular Crystallography Using Surface Acoustic Waves.

PubMed

Guo, Feng; Zhou, Weijie; Li, Peng; Mao, Zhangming; Yennawar, Neela H; French, Jarrod B; Huang, Tony Jun

2015-06-01

Advances in modern X-ray sources and detector technology have made it possible for crystallographers to collect usable data on crystals of only a few micrometers or less in size. Despite these developments, sample handling techniques have significantly lagged behind and often prevent the full realization of current beamline capabilities. In order to address this shortcoming, a surface acoustic wave-based method for manipulating and patterning crystals is developed. This method, which does not damage the fragile protein crystals, can precisely manipulate and pattern micrometer and submicrometer-sized crystals for data collection and screening. The technique is robust, inexpensive, and easy to implement. This method not only promises to significantly increase efficiency and throughput of both conventional and serial crystallography experiments, but will also make it possible to collect data on samples that were previously intractable. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using simple manipulatives to improve student comprehension of a complex biological process: protein synthesis.

PubMed

Guzman, Karen; Bartlett, John

2012-01-01

Biological systems and living processes involve a complex interplay of biochemicals and macromolecular structures that can be challenging for undergraduate students to comprehend and, thus, misconceptions abound. Protein synthesis, or translation, is an example of a biological process for which students often hold many misconceptions. This article describes an exercise that was developed to illustrate the process of translation using simple objects to represent complex molecules. Animations, 3D physical models, computer simulations, laboratory experiments and classroom lectures are also used to reinforce the students' understanding of translation, but by focusing on the simple manipulatives in this exercise, students are better able to visualize concepts that can elude them when using the other methods. The translation exercise is described along with suggestions for background material, questions used to evaluate student comprehension and tips for using the manipulatives to identify common misconceptions. Copyright © 2012 Wiley Periodicals, Inc.

Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

PubMed

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

Targeting protein-protein interaction between MLL1 and reciprocal proteins for leukemia therapy.

PubMed

Wang, Zhi-Hui; Li, Dong-Dong; Chen, Wei-Lin; You, Qi-Dong; Guo, Xiao-Ke

2018-01-15

The mixed lineage leukemia protein-1 (MLL1), as a lysine methyltransferase, predominantly regulates the methylation of histone H3 lysine 4 (H3K4) and functions in hematopoietic stem cell (HSC) self-renewal. MLL1 gene fuses with partner genes that results in the generation of MLL1 fusion proteins (MLL1-FPs), which are frequently detected in acute leukemia. In the progress of leukemogenesis, a great deal of proteins cooperate with MLL1 to form multiprotein complexes serving for the dysregulation of H3K4 methylation, the overexpression of homeobox (HOX) cluster genes, and the consequent generation of leukemia. Hence, disrupting the interactions between MLL1 and the reciprocal proteins has been considered to be a new treatment strategy for leukemia. Here, we reviewed potential protein-protein interactions (PPIs) between MLL1 and its reciprocal proteins, and summarized the inhibitors to target MLL1 PPIs. The druggability of MLL1 PPIs for leukemia were also discussed. Copyright © 2017. Published by Elsevier Ltd.

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

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.

Cotton and Protein Interactions

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

Goheen, Steven C.; Edwards, J. V.; Rayburn, Alfred R.

The adsorbent properties of important wound fluid proteins and cotton cellulose are reviewed. This review focuses on the adsorption of albumin to cotton-based wound dressings and some chemically modified derivatives targeted for chronic wounds. Adsorption of elastase in the presence of albumin was examined as a model to understand the interactive properties of these wound fluid components with cotton fibers. In the chronic non-healing wound, elastase appears to be over-expressed, and it digests tissue and growth factors, interfering with the normal healing process. Albumin is the most prevalent protein in wound fluid, and in highly to moderately exudative wounds, itmore » may bind significantly to the fibers of wound dressings. Thus, the relative binding properties of both elastase and albumin to wound dressing fibers are of interest in the design of more effective wound dressings. The present work examines the binding of albumin to two different derivatives of cotton, and quantifies the elastase binding to the same derivatives following exposure of albumin to the fiber surface. An HPLC adsorption technique was employed coupled with a colorimetric enzyme assay to quantify the relative binding properties of albumin and elastase to cotton. The results of wound protein binding are discussed in relation to the porosity and surface chemistry interactions of cotton and wound proteins. Studies are directed to understanding the implications of protein adsorption phenomena in terms of fiber-protein models that have implications for rationally designing dressings for chronic wounds.« less

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

Facile manipulation of protein localization in fission yeast through binding of GFP-binding protein to GFP.

PubMed

Chen, Ying-Hui; Wang, Gao-Yuan; Hao, Hao-Chao; Chao, Chun-Jiang; Wang, Yamei; Jin, Quan-Wen

2017-03-01

GFP-binding protein (or GBP) has been recently developed in various systems and organisms as an efficient tool to purify GFP-fusion proteins. Due to the high affinity between GBP and GFP or GFP variants, this GBP-based approach is also ideally suited to alter the localization of functional proteins in live cells. In order to facilitate the wide use of the GBP-targeting approach in the fission yeast Schizosaccharomyces pombe , we developed a set of pFA6a-, pJK148- and pUC119-based vectors containing GBP- or GBP-mCherry-coding sequences and variants of inducible nmt1 or constitutive adh1 promoters that result in different levels of expression. The GBP or GBP-mCherry fragments can serve as cassettes for N- or C-terminal genomic tagging of genes of interest. We illustrated the application of these vectors in the construction of yeast strains with Dma1 or Cdc7 tagged with GBP-mCherry and efficient targeting of Dma1- or Cdc7-GBP-mCherry to the spindle pole body by Sid4-GFP. This series of vectors should help to facilitate the application of the GBP-targeting approach in manipulating protein localization and the analysis of gene function in fission yeast, at the level of single genes, as well as at a systematic scale. © 2017. Published by The Company of Biologists Ltd.

Combining multiple positive training sets to generate confidence scores for protein-protein interactions.

PubMed

Yu, Jingkai; Finley, Russell L

2009-01-01

High-throughput experimental and computational methods are generating a wealth of protein-protein interaction data for a variety of organisms. However, data produced by current state-of-the-art methods include many false positives, which can hinder the analyses needed to derive biological insights. One way to address this problem is to assign confidence scores that reflect the reliability and biological significance of each interaction. Most previously described scoring methods use a set of likely true positives to train a model to score all interactions in a dataset. A single positive training set, however, may be biased and not representative of true interaction space. We demonstrate a method to score protein interactions by utilizing multiple independent sets of training positives to reduce the potential bias inherent in using a single training set. We used a set of benchmark yeast protein interactions to show that our approach outperforms other scoring methods. Our approach can also score interactions across data types, which makes it more widely applicable than many previously proposed methods. We applied the method to protein interaction data from both Drosophila melanogaster and Homo sapiens. Independent evaluations show that the resulting confidence scores accurately reflect the biological significance of the interactions.

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.

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.

Parallel Force Assay for Protein-Protein Interactions

PubMed Central

Aschenbrenner, Daniela; Pippig, Diana A.; Klamecka, Kamila; Limmer, Katja; Leonhardt, Heinrich; Gaub, Hermann E.

2014-01-01

Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay. PMID:25546146

Protein Surface Mimetics: Understanding How Ruthenium Tris(Bipyridines) Interact with Proteins.

PubMed

Hewitt, Sarah H; Filby, Maria H; Hayes, Ed; Kuhn, Lars T; Kalverda, Arnout P; Webb, Michael E; Wilson, Andrew J

2017-01-17

Protein surface mimetics achieve high-affinity binding by exploiting a scaffold to project binding groups over a large area of solvent-exposed protein surface to make multiple cooperative noncovalent interactions. Such recognition is a prerequisite for competitive/orthosteric inhibition of protein-protein interactions (PPIs). This paper describes biophysical and structural studies on ruthenium(II) tris(bipyridine) surface mimetics that recognize cytochrome (cyt) c and inhibit the cyt c/cyt c peroxidase (CCP) PPI. Binding is electrostatically driven, with enhanced affinity achieved through enthalpic contributions thought to arise from the ability of the surface mimetics to make a greater number of noncovalent interactions than CCP with surface-exposed basic residues on cyt c. High-field natural abundance 1 H, 15 N HSQC NMR experiments are consistent with surface mimetics binding to cyt c in similar manner to CCP. This provides a framework for understanding recognition of proteins by supramolecular receptors and informing the design of ligands superior to the protein partners upon which they are inspired. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein-Protein Interactions of Viroporins in Coronaviruses and Paramyxoviruses: New Targets for Antivirals?

PubMed Central

Torres, Jaume; Surya, Wahyu; Li, Yan; Liu, Ding Xiang

2015-01-01

Viroporins are members of a rapidly growing family of channel-forming small polypeptides found in viruses. The present review will be focused on recent structural and protein-protein interaction information involving two viroporins found in enveloped viruses that target the respiratory tract; (i) the envelope protein in coronaviruses and (ii) the small hydrophobic protein in paramyxoviruses. Deletion of these two viroporins leads to viral attenuation in vivo, whereas data from cell culture shows involvement in the regulation of stress and inflammation. The channel activity and structure of some representative members of these viroporins have been recently characterized in some detail. In addition, searches for protein-protein interactions using yeast-two hybrid techniques have shed light on possible functional roles for their exposed cytoplasmic domains. A deeper analysis of these interactions should not only provide a more complete overview of the multiple functions of these viroporins, but also suggest novel strategies that target protein-protein interactions as much needed antivirals. These should complement current efforts to block viroporin channel activity. PMID:26053927

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-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.

Protein Interaction Profile Sequencing (PIP-seq).

PubMed

Foley, Shawn W; Gregory, Brian D

2016-10-10

Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

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.

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

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

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.

High-Sensitivity Real-Time Imaging of Dual Protein-Protein Interactions in Living Subjects Using Multicolor Luciferases

PubMed Central

Hida, Naoki; Awais, Muhammad; Takeuchi, Masaki; Ueno, Naoto; Tashiro, Mayuri; Takagi, Chiyo; Singh, Tanuja; Hayashi, Makoto; Ohmiya, Yoshihiro; Ozawa, Takeaki

2009-01-01

Networks of protein-protein interactions play key roles in numerous important biological processes in living subjects. An effective methodology to assess protein-protein interactions in living cells of interest is protein-fragment complement assay (PCA). Particularly the assays using fluorescent proteins are powerful techniques, but they do not directly track interactions because of its irreversibility or the time for chromophore formation. By contrast, PCAs using bioluminescent proteins can overcome these drawbacks. We herein describe an imaging method for real-time analysis of protein-protein interactions using multicolor luciferases with different spectral characteristics. The sensitivity and signal-to-background ratio were improved considerably by developing a carboxy-terminal fragment engineered from a click beetle luciferase. We demonstrate its utility in spatiotemporal characterization of Smad1–Smad4 and Smad2–Smad4 interactions in early developing stages of a single living Xenopus laevis embryo. We also describe the value of this method by application of specific protein-protein interactions in cell cultures and living mice. This technique supports quantitative analyses and imaging of versatile protein-protein interactions with a selective luminescence wavelength in opaque or strongly auto-fluorescent living subjects. PMID:19536355

Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

PubMed

Meckes, David G

2014-01-01

The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

New partner proteins containing novel internal recognition motif for human Glutaminase Interacting Protein (hGIP)

PubMed Central

Zencir, Sevil; Banerjee, Monimoy; Dobson, Melanie J.; Ayaydin, Ferhan; Fodor, Elfrieda Ayaydin; Topcu, Zeki; Mohanty, Smita

2013-01-01

Regulation of gene expression in cells is mediated by protein-protein, DNA-protein and receptor-ligand interactions. PDZ (PSD-95/Discs-large/ZO-1) domains are protein–protein interaction modules. PDZ-containing proteins function in the organization of multi-protein complexes controlling spatial and temporal fidelity of intracellular signaling pathways. In general, PDZ proteins possess multiple domains facilitating distinct interactions. The human Glutaminase Interacting Protein (hGIP) is an unusual PDZ protein comprising entirely of a single PDZ domain and plays pivotal roles in many cellular processes through its interaction with the C-terminus of partner proteins. Here, we report the identification by yeast two-hybrid screening of two new hGIP-interacting partners, DTX1 and STAU1. Both proteins lack the typical C-terminal PDZ recognition motif but contain a novel internal hGIP recognition motif recently identified in a phage display library screen. Fluorescence resonance energy transfer and confocal microscopy analysis confirmed the in vivo association of hGIP with DTX1 and STAU1 in mammalian cells validating the previous discovery of S/T-X-V/L-D as a consensus internal motif for hGIP recognition. Similar to hGIP, DTX1 and STAU1 have been implicated in neuronal function. Identification of these new interacting partners furthers our understanding of GIP-regulated signaling cascades and these interactions may represent potential new drug targets in humans. PMID:23395680

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.

Beyond Control Panels: Direct Manipulation for Visual Analytics

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

Endert, Alexander; Bradel, Lauren; North, Chris

2013-07-19

Information Visualization strives to provide visual representations through which users can think about and gain insight into information. By leveraging the visual and cognitive systems of humans, complex relationships and phenomena occurring within datasets can be uncovered by exploring information visually. Interaction metaphors for such visualizations are designed to enable users direct control over the filters, queries, and other parameters controlling how the data is visually represented. Through the evolution of information visualization, more complex mathematical and data analytic models are being used to visualize relationships and patterns in data – creating the field of Visual Analytics. However, the expectationsmore » for how users interact with these visualizations has remained largely unchanged – focused primarily on the direct manipulation of parameters of the underlying mathematical models. In this article we present an opportunity to evolve the methodology for user interaction from the direct manipulation of parameters through visual control panels, to interactions designed specifically for visual analytic systems. Instead of focusing on traditional direct manipulation of mathematical parameters, the evolution of the field can be realized through direct manipulation within the visual representation – where users can not only gain insight, but also interact. This article describes future directions and research challenges that fundamentally change the meaning of direct manipulation with regards to visual analytics, advancing the Science of Interaction.« less

In silico modeling of the yeast protein and protein family interaction network

NASA Astrophysics Data System (ADS)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

Dynamic interactions of proteins in complex networks

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

Appella, E.; Anderson, C.

2009-10-01

Recent advances in techniques such as NMR and EPR spectroscopy have enabled the elucidation of how proteins undergo structural changes to act in concert in complex networks. The three minireviews in this series highlight current findings and the capabilities of new methodologies for unraveling the dynamic changes controlling diverse cellular functions. They represent a sampling of the cutting-edge research presented at the 17th Meeting of Methods in Protein Structure Analysis, MPSA2008, in Sapporo, Japan, 26-29 August, 2008 (http://www.iapsap.bnl.gov). The first minireview, by Christensen and Klevit, reports on a structure-based yeast two-hybrid method for identifying E2 ubiquitin-conjugating enzymes that interact withmore » the E3 BRCA1/BARD1 heterodimer ligase to generate either mono- or polyubiquitinated products. This method demonstrated for the first time that the BRCA1/BARD1 E3 can interact with 10 different E2 enzymes. Interestingly, the interaction with multiple E2 enzymes displayed unique ubiquitin-transfer properties, a feature expected to be common among other RING and U-box E3s. Further characterization of new E3 ligases and the E2 enzymes that interact with them will greatly enhance our understanding of ubiquitin transfer and facilitate studies of roles of ubiquitin and ubiquitin-like proteins in protein processing and trafficking. Stein et al., in the second minireview, describe recent progress in defining the binding specificity of different peptide-binding domains. The authors clearly point out that transient peptide interactions mediated by both post-translational modifications and disordered regions ensure a high level of specificity. They postulate that a regulatory code may dictate the number of combinations of domains and post-translational modifications needed to achieve the required level of interaction specificity. Moreover, recognition alone is not enough to obtain a stable complex, especially in a complex cellular environment. Increasing

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.

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

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

PubMed Central

Wang, Li; Carnegie, Graeme K.

2013-01-01

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction. PMID:23979513

Flow cytometric analysis of bimolecular fluorescence complementation: a high throughput quantitative method to study protein-protein interaction.

PubMed

Wang, Li; Carnegie, Graeme K

2013-08-15

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.

The HUPO PSI's molecular interaction format--a community standard for the representation of protein interaction data.

PubMed

Hermjakob, Henning; Montecchi-Palazzi, Luisa; Bader, Gary; Wojcik, Jérôme; Salwinski, Lukasz; Ceol, Arnaud; Moore, Susan; Orchard, Sandra; Sarkans, Ugis; von Mering, Christian; Roechert, Bernd; Poux, Sylvain; Jung, Eva; Mersch, Henning; Kersey, Paul; Lappe, Michael; Li, Yixue; Zeng, Rong; Rana, Debashis; Nikolski, Macha; Husi, Holger; Brun, Christine; Shanker, K; Grant, Seth G N; Sander, Chris; Bork, Peer; Zhu, Weimin; Pandey, Akhilesh; Brazma, Alvis; Jacq, Bernard; Vidal, Marc; Sherman, David; Legrain, Pierre; Cesareni, Gianni; Xenarios, Ioannis; Eisenberg, David; Steipe, Boris; Hogue, Chris; Apweiler, Rolf

2004-02-01

A major goal of proteomics is the complete description of the protein interaction network underlying cell physiology. A large number of small scale and, more recently, large-scale experiments have contributed to expanding our understanding of the nature of the interaction network. However, the necessary data integration across experiments is currently hampered by the fragmentation of publicly available protein interaction data, which exists in different formats in databases, on authors' websites or sometimes only in print publications. Here, we propose a community standard data model for the representation and exchange of protein interaction data. This data model has been jointly developed by members of the Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organization (HUPO), and is supported by major protein interaction data providers, in particular the Biomolecular Interaction Network Database (BIND), Cellzome (Heidelberg, Germany), the Database of Interacting Proteins (DIP), Dana Farber Cancer Institute (Boston, MA, USA), the Human Protein Reference Database (HPRD), Hybrigenics (Paris, France), the European Bioinformatics Institute's (EMBL-EBI, Hinxton, UK) IntAct, the Molecular Interactions (MINT, Rome, Italy) database, the Protein-Protein Interaction Database (PPID, Edinburgh, UK) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING, EMBL, Heidelberg, Germany).

Single-well monitoring of protein-protein interaction and phosphorylation-dephosphorylation events.

PubMed

Arcand, Mathieu; Roby, Philippe; Bossé, Roger; Lipari, Francesco; Padrós, Jaime; Beaudet, Lucille; Marcil, Alexandre; Dahan, Sophie

2010-04-20

We combined oxygen channeling assays with two distinct chemiluminescent beads to detect simultaneously protein phosphorylation and interaction events that are usually monitored separately. This novel method was tested in the ERK1/2 MAP kinase pathway. It was first used to directly monitor dissociation of MAP kinase ERK2 from MEK1 upon phosphorylation and to evaluate MAP kinase phosphatase (MKP) selectivity and mechanism of action. In addition, MEK1 and ERK2 were probed with an ATP competitor and an allosteric MEK1 inhibitor, which generated distinct phosphorylation-interaction patterns. Simultaneous monitoring of protein-protein interactions and substrate phosphorylation can provide significant mechanistic insight into enzyme activity and small molecule action.

Differential Occurrence of Interactions and Interaction Domains in Proteins Containing Homopolymeric Amino Acid Repeats

PubMed Central

Pelassa, Ilaria; Fiumara, Ferdinando

2015-01-01

Homopolymeric amino acids repeats (AARs), which are widespread in proteomes, have often been viewed simply as spacers between protein domains, or even as “junk” sequences with no obvious function but with a potential to cause harm upon expansion as in genetic diseases associated with polyglutamine or polyalanine expansions, including Huntington disease and cleidocranial dysplasia. A growing body of evidence indicates however that at least some AARs can form organized, functional protein structures, and can regulate protein function. In particular, certain AARs can mediate protein-protein interactions, either through homotypic AAR-AAR contacts or through heterotypic contacts with other protein domains. It is still unclear however, whether AARs may have a generalized, proteome-wide role in shaping protein-protein interaction networks. Therefore, we have undertaken here a bioinformatics screening of the human proteome and interactome in search of quantitative evidence of such a role. We first identified the sets of proteins that contain repeats of any one of the 20 amino acids, as well as control sets of proteins chosen at random in the proteome. We then analyzed the connectivity between the proteins of the AAR-containing protein sets and we compared it with that observed in the corresponding control networks. We find evidence for different degrees of connectivity in the different AAR-containing protein networks. Indeed, networks of proteins containing polyglutamine, polyglutamate, polyproline, and other AARs show significantly increased levels of connectivity, whereas networks containing polyleucine and other hydrophobic repeats show lower degrees of connectivity. Furthermore, we observed that numerous protein-protein, -nucleic acid, and -lipid interaction domains are significantly enriched in specific AAR protein groups. These findings support the notion of a generalized, combinatorial role of AARs, together with conventional protein interaction domains, in

How Structure Defines Affinity in Protein-Protein Interactions

PubMed Central

Erijman, Ariel; Rosenthal, Eran; Shifman, Julia M.

2014-01-01

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins. PMID:25329579

Trimeric Transmembrane Domain Interactions in Paramyxovirus Fusion Proteins

PubMed Central

Smith, Everett Clinton; Smith, Stacy E.; Carter, James R.; Webb, Stacy R.; Gibson, Kathleen M.; Hellman, Lance M.; Fried, Michael G.; Dutch, Rebecca Ellis

2013-01-01

Paramyxovirus fusion (F) proteins promote membrane fusion between the viral envelope and host cell membranes, a critical early step in viral infection. Although mutational analyses have indicated that transmembrane (TM) domain residues can affect folding or function of viral fusion proteins, direct analysis of TM-TM interactions has proved challenging. To directly assess TM interactions, the oligomeric state of purified chimeric proteins containing the Staphylococcal nuclease (SN) protein linked to the TM segments from three paramyxovirus F proteins was analyzed by sedimentation equilibrium analysis in detergent and buffer conditions that allowed density matching. A monomer-trimer equilibrium best fit was found for all three SN-TM constructs tested, and similar fits were obtained with peptides corresponding to just the TM region of two different paramyxovirus F proteins. These findings demonstrate for the first time that class I viral fusion protein TM domains can self-associate as trimeric complexes in the absence of the rest of the protein. Glycine residues have been implicated in TM helix interactions, so the effect of mutations at Hendra F Gly-508 was assessed in the context of the whole F protein. Mutations G508I or G508L resulted in decreased cell surface expression of the fusogenic form, consistent with decreased stability of the prefusion form of the protein. Sedimentation equilibrium analysis of TM domains containing these mutations gave higher relative association constants, suggesting altered TM-TM interactions. Overall, these results suggest that trimeric TM interactions are important driving forces for protein folding, stability and membrane fusion promotion. PMID:24178297

Interaction of AIP with protein kinase A (cAMP-dependent protein kinase).

PubMed

Schernthaner-Reiter, Marie Helene; Trivellin, Giampaolo; Stratakis, Constantine A

2018-05-02

Germline mutations in the aryl hydrocarbon receptor-interacting protein (AIP) gene cause mostly somatotropinomas and/or prolactinomas in a subset of familial isolated pituitary adenomas (FIPA). AIP has been shown to interact with phosphodiesterases (PDEs) and G proteins, suggesting a link to the cyclic AMP (cAMP)-dependent protein kinase (PKA) pathway. Upregulation of PKA is seen in sporadic somatotropinomas that carry GNAS1 mutations, and those in Carney complex that are due to PRKAR1A mutations. To elucidate the mechanism of AIP-dependent pituitary tumorigenesis, we studied potential functional and physical interactions of AIP with PKA's main subunits PRKAR1A (R1α) and PRKACA (Cα). We found that AIP physically interacts with both R1α and Cα; this interaction is enhanced when all three components are present, but maintained during Cα-R1α dissociation by PKA pathway activation, indicating that AIP binds Cα/R1α both in complex and separately. The interaction between AIP and R1α/Cα is reduced when the frequent AIP pathogenic mutation p.R304* is present. AIP protein levels are regulated both by translation and the ubiquitin/proteasome pathway and Cα stabilizes both AIP and R1α protein levels. AIP reduction by siRNA leads to an increase of PKA pathway activity, which is disproportionately enhanced during PDE4-inhibition. We show that AIP interacts with the PKA pathway on multiple levels, including a physical interaction with both the main regulatory (R1α) and catalytic (Cα) PKA subunits and a functional interaction with PDE4-dependent PKA activation. These findings provide novel insights on the mechanisms of AIP-dependent pituitary tumorigenesis.

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

Role of electrostatic interaction on surfactant induced protein unfolding

NASA Astrophysics Data System (ADS)

Sumit, Kumar, Sugam; Aswal, V. K.

2013-02-01

Small Angle Neutron Scattering has been used to examine the effect of electrostatic interaction on surfactant induced protein unfolding. Measurements are carried out from 1 wt% Bovine Serum Albumin (BSA) protein with 1 wt% Sodium Dodecyl Sulphate (SDS) surfactant at pH 7 in presence of varying concentration of NaCl. It is found that both the components (protein and surfactant micelle which are likely charged) exist individually without any interaction in absence of salt, whereas their interaction and protein unfolding is enhanced with the increase in salt concentration. The structure of protein-surfactant interaction is characterized by fractal bead-necklace model.

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.

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.

Gene essentiality and the topology of protein interaction networks

PubMed Central

Coulomb, Stéphane; Bauer, Michel; Bernard, Denis; Marsolier-Kergoat, Marie-Claude

2005-01-01

The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology. PMID:16087428

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.

Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

PubMed

Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

2017-11-21

Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative analysis of protein-ligand interactions by NMR.

PubMed

Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

2016-08-01

Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used