Hou, Rong; Sibinga, Nicholas E. S.
Fat1, an atypical cadherin induced robustly after arterial injury, has significant effects on mammalian vascular smooth muscle cell (VSMC) growth and migration. The related Drosophila protein Fat interacts genetically and physically with Atrophin, a protein essential for development and control of cell polarity. We hypothesized that interactions between Fat1 and mammalian Atrophin (Atr) proteins might contribute to Fat1 effects on VSMCs. Like Fat1, mammalian Atr expres...
Davis, Shaun M.; Thomas, Amanda L.; Nomie, Krystle J.; Huang, Longwen; Dierick, Herman A.
Aggressive behaviour is widespread throughout the animal kingdom. However, its mechanisms are poorly understood, and the degree of molecular conservation between distantly related species is unknown. Here we show that knockdown of tailless (tll) increases aggression in Drosophila, similar to the effect of its mouse orthologue Nr2e1. Tll localizes to the adult pars intercerebralis (PI), which shows similarity to the mammalian hypothalamus. Knockdown of tll in the PI is sufficient to increase aggression and is rescued by co-expressing human NR2E1. Knockdown of Atrophin, a Tll co-repressor, also increases aggression, and both proteins physically interact in the PI. tll knockdown-induced aggression is fully suppressed by blocking neuropeptide processing or release from the PI. In addition, genetically activating PI neurons increases aggression, mimicking the aggression-inducing effect of hypothalamic stimulation. Together, our results suggest that a transcriptional control module regulates neuropeptide signalling from the neurosecretory cells of the brain to control aggressive behaviour.
Byron, Olwyn; Vestergaard, Bente
Responsive formation of protein:protein interaction (PPI) upon diverse stimuli is a fundament of cellular function. As a consequence, PPIs are complex, adaptive entities, and exist in structurally heterogeneous interplays defined by the energetic states of the free and complexed protomers. The...
Tina, KG; Bhadra, R.; Srinivasan, N.
Interactions within a protein structure and interactions between proteins in an assembly are essential considerations in understanding molecular basis of stability and functions of proteins and their complexes. There are several weak and strong interactions that render stability to a protein structure or an assembly. Protein Interactions Calculator (PIC) is a server which, given the coordinate set of 3D structure of a protein or an assembly, computes various interactions such as disulphide bo...
Szklarczyk, Damian; Jensen, Lars Juhl
of research are explored. Here we present an overview of the most widely used protein-protein interaction databases and the methods they employ to gather, combine, and predict interactions. We also point out the trade-off between comprehensiveness and accuracy and the main pitfall scientists have to be aware...
Yin, Hang; Flynn, Aaron D
The majority of therapeutics target membrane proteins, accessible on the surface of cells, to alter cellular signaling. Cells use membrane proteins to transduce signals into cells, transport ions and molecules, bind cells to a surface or substrate, and catalyze reactions. Newly devised technologies allow us to drug conventionally "undruggable" regions of membrane proteins, enabling modulation of protein-protein, protein-lipid, and protein-nucleic acid interactions. In this review, we survey the state of the art of high-throughput screening and rational design in drug discovery, and we evaluate the advances in biological understanding and technological capacity that will drive pharmacotherapy forward against unorthodox membrane protein targets. PMID:26863923
Protein-surfactant interactions in aqueous media have been investigated. The globular proteins lysozyme and bovine serum albumin (BSA) served as model proteins. Several ionic and non-ionic surfactants were used. Fluorescence probe measurements showed that at low sodium dodecyl sulfate (SDS) concentration (< 0.1 M) one micelle-like SDS cluster is bound to lysozyme. From dynamic light scattering (DLS) results it was observed that lysozyme in the complex does not correspond to the fully unfol...
Jones, S; Thornton, J. M.
This review examines protein complexes in the Brookhaven Protein Databank to gain a better understanding of the principles governing the interactions involved in protein-protein recognition. The factors that influence the formation of protein-protein complexes are explored in four different types of protein-protein complexes--homodimeric proteins, heterodimeric proteins, enzyme-inhibitor complexes, and antibody-protein complexes. The comparison between the complexes highlights differences tha...
We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures.
We describe an interactive visualization and modeling program for the creation of protein structures ''from scratch''. The input to our program is an amino acid sequence -decoded from a gene- and a sequence of predicted secondary structure types for each amino acid-provided by external structure prediction programs. Our program can be used in the set-up phase of a protein structure prediction process; the structures created with it serve as input for a subsequent global internal energy minimization, or another method of protein structure prediction. Our program supports basic visualization methods for protein structures, interactive manipulation based on inverse kinematics, and visualization guides to aid a user in creating ''good'' initial structures
Peng Liu; Lei Yang; Daming Shi; Xianglong Tang
A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction net...
Janin, J.; Bonvin, A.M.J.J.
We are proud to present the first edition of the Protein–protein interactions Section of Current Opinion in Structural Biology. The Section is new, but the topic has been present in the journal from the very start. Volume 1, Issue 1, dated February 1991, had a review by Janin entitled Protein–protei
Full Text Available Abstract Background Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO, we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS between two GO terms. Description Based on the RSS method, here, we introduce a predicted Saccharomyces protein-protein interaction database called SPIDer. It houses a gold standard positive dataset (GSP with high confidence level that covered 79.2% of the high-quality interaction dataset. Our predicted protein-protein interaction network reconstructed from the GSPs consists of 92 257 interactions among 3600 proteins, and forms 23 connected components. It also provides general links to connect predicted protein-protein interactions with three other databases, DIP, BIND and MIPS. An Internet-based interface provides users with fast and convenient access to protein-protein interactions based on various search features (searching by protein information, GO term information or sequence similarity. In addition, the RSS value of two GO terms in the same ontology, and the inter-member interactions in a list of proteins of interest or in a protein complex could be retrieved. Furthermore, the database presents a user-friendly graphical interface which is created dynamically for visualizing an interaction sub-network. The database is accessible at http://cmb.bnu.edu.cn/SPIDer/index.html. Conclusion SPIDer is a public database server for protein-protein interactions based on the yeast genome. It provides a variety of search options and graphical visualization of an interaction network. In particular, it will be very useful for the study of inter-member interactions
Quang, Leigh J; Sandler, Stanley I; Lenhoff, Abraham M
The anisotropy of shape and functionality of proteins complicates the prediction of protein-protein interactions. We examine the distribution of electrostatic and nonelectrostatic contributions to these interactions for two globular proteins, lysozyme and chymosin B, which differ in molecular weight by about a factor of 2. The interaction trends for these proteins are computed in terms of contributions to the osmotic second virial coefficient that are evaluated using atomistic models of the proteins. Our emphasis is on identifying the orientational configurations that contribute most strongly to the overall interactions due to high-complementarity interactions, and on calculating the effect of ionic strength on such interactions. The results emphasize the quantitative importance of several features of protein interactions, notably that despite differences in their frequency of occurrence, configurations differing appreciably in interaction energy can contribute meaningfully to overall interactions. However, relatively small effects due to charge anisotropy or specific hydration can affect the overall interaction significantly only if they contribute to strongly attractive configurations. The results emphasize the necessity of accounting for detailed anisotropy to capture actual experimental trends, and the sensitivity of even very detailed atomistic models to subtle solution contributions. PMID:26580057
Nussinov, Ruth; Tsai, Chung-Jung
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
The biological processes that are the basis of all life forms are mediated largely by protein-protein interactions. The protein complexes involved in these interactions can be categorised by their affinity, which results in a range from static to transient complexes. Electron transfer complexes, whi
Stephan Ederer; Florian Fink; Wolfram Gronwald
Based on a protein-protein docking approach we have developed a procedure to verify or falsify protein-protein interactions that were proposed by other methods such as yeast-2-hybrid assays. Our method currently utilizes intermolecular energies but can be expanded to incorporate additional terms such as amino acid based pair-potentials. We show some early results that demonstrate the general applicability of our approach.
Sánchez Claros, Carmen
Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.
U.S. Department of Health & Human Services — The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent...
Rinaldi, F; Schneider, G; Kaljurand, K.; Clematide, S
The detection of mentions of protein-protein interactions in the scientific literature has recently emerged as a core task in biomedical text mining. We present effective techniques for this task, which have been developed using the IntAct database as a gold standard, and have been evaluated in two text mining competitions.
Nepusz, Tamás; Yu, Haiyuan; Paccanaro, Alberto
We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a...
Full Text Available d in closely related Saccharomyces species; protein detected in large-scale protein-protein interaction studies...cies; protein detected in large-scale protein-protein interaction studies Rows with this prey as prey (4) Ro...n; not conserved in closely related Saccharomyces species; protein detected in large-scale protein-protein interaction studies... species; protein detected in large-scale protein-protein interaction studies Rows with this prey as prey Ro
Lehne Benjamin; Schlitt Thomas
Abstract Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction ...
Mahmood; A.; Mahdavi; Yen-Han; Lin
Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain inter- actions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis ele- gans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area un- der the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs in- creased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on aver- age 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.
Cieplak, Marek; Niewieczerzał, Szymon
We incorporate hydrodynamic interactions (HI) in a coarse-grained and structure-based model of proteins by employing the Rotne-Prager hydrodynamic tensor. We study several small proteins and demonstrate that HI facilitate folding. We also study HIV-1 protease and show that HI make the flap closing dynamics faster. The HI are found to affect time correlation functions in the vicinity of the native state even though they have no impact on same time characteristics of the structure fluctuations ...
Liu, Peilei; Wang, Ting
Protein-protein interaction extraction is the key precondition of the construction of protein knowledge network, and it is very important for the research in the biomedicine. This paper extracted directional protein-protein interaction from the biological text, using the SVM-based method. Experiments were evaluated on the LLL05 corpus with good results. The results show that dependency features are import for the protein-protein interaction extraction and features related to the interaction w...
Xenarios, Ioannis; Rice, Danny W.; Salwinski, Lukasz; Baron, Marisa K.; Edward M. Marcotte; Eisenberg, David
The Database of Interacting Proteins (DIP; http://dip.doe-mbi.ucla.edu ) is a database that documents experimentally determined protein–protein interactions. This database is intended to provide the scientific community with a comprehensive and integrated tool for browsing and efficiently extracting information about protein interactions and interaction networks in biological processes. Beyond cataloging details of protein–protein interactions, the DIP is useful for understanding protein func...
Waldo, Geoffrey S.; Cabantous, Stephanie
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.
This project aimed to establish feasibility of using experimental techniques based on direct measurements of interaction forces on the single molecule scale to characterize equilibrium interaction potentials between individual biological molecules. Such capability will impact several research areas, ranging from rapid interaction screening capabilities to providing verifiable inputs for computational models. It should be one of the enabling technologies for modern proteomics research. This study used a combination of Monte-Carlo simulations, theoretical considerations, and direct experimental measurements to investigate two model systems that represented typical experimental situations: force-induced melting of DNA rigidly attached to the tip, and force-induced unbinding of a protein-antibody pair connected to flexible tethers. Our results establish that for both systems researchers can use force spectroscopy measurements to extract reliable information about equilibrium interaction potentials. However, the approaches necessary to extract these potentials in each case--Jarzynski reconstruction and Dynamic Force Spectroscopy--are very different. We also show how the thermodynamics and kinetics of unbinding process dictates the choice between in each case
Noy, A; Sulchek, T A; Friddle, R W
This project aimed to establish feasibility of using experimental techniques based on direct measurements of interaction forces on the single molecule scale to characterize equilibrium interaction potentials between individual biological molecules. Such capability will impact several research areas, ranging from rapid interaction screening capabilities to providing verifiable inputs for computational models. It should be one of the enabling technologies for modern proteomics research. This study used a combination of Monte-Carlo simulations, theoretical considerations, and direct experimental measurements to investigate two model systems that represented typical experimental situations: force-induced melting of DNA rigidly attached to the tip, and force-induced unbinding of a protein-antibody pair connected to flexible tethers. Our results establish that for both systems researchers can use force spectroscopy measurements to extract reliable information about equilibrium interaction potentials. However, the approaches necessary to extract these potentials in each case--Jarzynski reconstruction and Dynamic Force Spectroscopy--are very different. We also show how the thermodynamics and kinetics of unbinding process dictates the choice between in each case.
Haasl Ryan J
Full Text Available Abstract Background The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-protein interaction (PPI datasets. Mining these datasets for underlying biological knowledge has, however, remained a challenge. Results A total of 3108 sequence signatures were found, each of which was shared by a set of guest proteins interacting with one of 944 host proteins in Saccharomyces cerevisiae genome. Approximately 94% of these sequence signatures matched entries in InterPro member databases. We identified 84 distinct sequence signatures from the remaining 172 unknown signatures. The signature sharing information was then applied in predicting sub-cellular localization of yeast proteins and the novel signatures were used in identifying possible interacting sites. Conclusion We reported a method of PPI data mining that facilitated the discovery of novel sequence signatures using a large PPI dataset from S. cerevisiae genome as input. The fact that 94% of discovered signatures were known validated the ability of the approach to identify large numbers of signatures from PPI data. The significance of these discovered signatures was demonstrated by their application in predicting sub-cellular localizations and identifying potential interaction binding sites of yeast proteins.
Cieplak, Marek; Niewieczerzał, Szymon
We incorporate hydrodynamic interactions (HIs) in a coarse-grained and structure-based model of proteins by employing the Rotne-Prager hydrodynamic tensor. We study several small proteins and demonstrate that HIs facilitate folding. We also study HIV-1 protease and show that HIs make the flap closing dynamics faster. The HIs are found to affect time correlation functions in the vicinity of the native state even though they have no impact on same time characteristics of the structure fluctuations around the native state.
Fraser, Hunter B.; Hirsh, Aaron E.; Wall, Dennis P.; Eisen, Michael B.
Physically interacting proteins or parts of proteins are expected to evolve in a coordinated manner that preserves proper interactions. Such coevolution at the amino acid-sequence level is well documented and has been used to predict interacting proteins, domains, and amino acids. Interacting proteins are also often precisely coexpressed with one another, presumably to maintain proper stoichiometry among interacting components. Here, we show that the expression levels of physically inter...
Garma, Leonardo; Mukherjee, Srayanta; Mitra, Pralay; Zhang, Yang
“Protein quaternary structure universe” refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the pro...
Leonardo Garma; Srayanta Mukherjee; Pralay Mitra; Yang Zhang
"Protein quaternary structure universe" refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the pro...
Full Text Available Abstract Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction database [MINT], the Biomolecular Interaction Network Database [BIND], the Database of Interacting Proteins [DIP], the IntAct molecular interaction database [IntAct] and the Human Protein Reference Database [HPRD] differ in scope and content; integration of all datasets is non-trivial owing to differences in data annotation. With respect to human protein-protein interaction data, HPRD seems to be the most comprehensive. To obtain a complete dataset, however, interactions from all six databases have to be combined. To overcome this limitation, meta-databases such as the Agile Protein Interaction Database (APID offer access to integrated protein-protein interaction datasets, although these also currently have certain restrictions.
Yang Zhihao; Lin Hongfei; Xu Bo
Abstract Background Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of protein complexes detection algorithms. Methods We have developed novel semantic similarity metho...
@@ Protein-protein interactions (PPIs) are of vital importance for virtually all processes of a living cell. The study of these associations of protein molecules could improve people's understanding of diseases and provide basis for therapeutic approaches.
Full Text Available on quantitative analysis of protein-protein interaction maps; may interact with ribosomes, based on co-purification studies...ing based on quantitative analysis of protein-protein interaction maps; may interact with ribosomes, based on co-purification studies
Haruki Nakamura; Kengo Kinoshita; Ashwini Patil
Hubs are proteins with a large number of interactions in a protein-protein interaction network. They are the principal agents in the interaction network and affect its function and stability. Their specific recognition of many different protein partners is of great interest from the structural viewpoint. Over the last few years, the structural properties of hubs have been extensively studied. We review the currently known features that are particular to hubs, possibly affecting their binding ...
Kemmer, Gerdi Christine
are implemented by soluble proteins reversibly binding to, as well as by integral membrane proteins embedded in, cellular membranes. The activity and interaction of these proteins is furthermore modulated by the lipids of the membrane. Here, liposomes were used as model membrane systems to investigate...... interactions between proteins and lipids. First, interactions of soluble proteins with membranes and specific lipids were studied, using two proteins: Annexin V and Tma1. The protein was first subjected to a lipid/protein overlay assay to identify candidate interaction partners in a fast and efficient way....... Discovered interactions were then probed on the level of the membrane using liposome-based assays. In the second part, a transmembrane protein was investigated. Assays to probe activity of the plasma membrane ATPase (Arabidopsis thaliana H+ -ATPase isoform 2 (AHA2)) in single liposomes using both giant...
Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.
V. Srinivasa Rao; Srinivas, K.; Sujini, G. N.; G. N. Sunand Kumar
Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate t...
Full Text Available tein; not conserved in closely related Saccharomyces species; protein detected in large-scale protein-protein interaction studies...myces species; protein detected in large-scale protein-protein interaction studies Rows with this prey as pr
Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.
Fraser, Hunter B.; Hirsh, Aaron E.; Wall, Dennis P.; Eisen,Michael B.
Physically interacting proteins or parts of proteins are expected to evolve in a coordinated manner that preserves proper interactions. Such coevolution at the amino acid-sequence level is well documented and has been used to predict interacting proteins, domains, and amino acids. Interacting proteins are also often precisely coexpressed with one another, presumably to maintain proper stoichiometry among interacting components. Here, we show that the expression levels of physically interacting proteins coevolve. We estimate average expression levels of genes from four closely related fungi of the genus Saccharomyces using the codon adaptation index and show that expression levels of interacting proteins exhibit coordinated changes in these different species. We find that this coevolution of expression is a more powerful predictor of physical interaction than is coevolution of amino acid sequence. These results demonstrate previously uncharacterized coevolution of gene expression, adding a different dimension to the study of the coevolution of interacting proteins and underscoring the importance of maintaining coexpression of interacting proteins over evolutionary time. Our results also suggest that expression coevolution can be used for computational prediction of protein protein interactions.
Friedhoff, Peter; Li, Pingping; Gotthardt, Julia
The principal DNA mismatch repair proteins MutS and MutL are versatile enzymes that couple DNA mismatch or damage recognition to other cellular processes. Besides interaction with their DNA substrates this involves transient interactions with other proteins which is triggered by the DNA mismatch or damage and controlled by conformational changes. Both MutS and MutL proteins have ATPase activity, which adds another level to control their activity and interactions with DNA substrates and other proteins. Here we focus on the protein-protein interactions, protein interaction sites and the different levels of structural knowledge about the protein complexes formed with MutS and MutL during the mismatch repair reaction. PMID:26725162
Bitbol, Anne-Florence; Colwell, Lucy J; Wingreen, Ned S
Specific protein-protein interactions are crucial in the cell, both to ensure the formation and stability of multi-protein complexes, and to enable signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interaction partners. Hence, the sequences of interacting partners are correlated. Here we exploit these correlations to accurately identify which proteins are specific interaction partners from sequence data alone. Our general approach, which employs a pairwise maximum entropy model to infer direct couplings between residues, has been successfully used to predict the three-dimensional structures of proteins from sequences. Building on this approach, we introduce an iterative algorithm to predict specific interaction partners from among the members of two protein families. We assess the algorithm's performance on histidine kinases and response regulators from bacterial two-component signaling systems. The algorithm proves successful without any a pri...
Full Text Available Abstract 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.
Liu, Zhu; Gong, Zhou; Dong, Xu; Tang, Chun
Proteins interact with each other to establish their identities in cell. The affinities for the interactions span more than ten orders of magnitude, and KD values in μM-mM regimen are considered transient and are important in cell signaling. Solution NMR including diamagnetic and paramagnetic techniques has enabled atomic-resolution depictions of transient protein-protein interactions. Diamagnetic NMR allows characterization of protein complexes with KD values up to several mM, whereas ultraweak and fleeting complexes can be modeled with the use of paramagnetic NMR especially paramagnetic relaxation enhancement (PRE). When tackling ever-larger protein complexes, PRE can be particularly useful in providing long-range intermolecular distance restraints. As NMR measurements are averaged over the ensemble of complex structures, structural information for dynamic protein-protein interactions besides the stereospecific one can often be extracted. Herein the protein interaction dynamics are exemplified by encounter complexes, alternative binding modes, and coupled binding/folding of intrinsically disordered proteins. Further integration of NMR with other biophysical techniques should allow better visualization of transient protein-protein interactions. In particular, single-molecule data may facilitate the interpretation of ensemble-averaged NMR data. Though same structures of proteins and protein complexes were found in cell as in diluted solution, we anticipate that the dynamics of transient protein protein-protein interactions be different, which awaits awaits exploration by NMR. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. PMID:25896389
Bowler, Emily H; Wang, Zhenghe; Ewing, Rob M
The acquisition of mutations that activate oncogenes or inactivate tumor suppressors is a primary feature of most cancers. Mutations that directly alter protein sequence and structure drive the development of tumors through aberrant expression and modification of proteins, in many cases directly impacting components of signal transduction pathways and cellular architecture. Cancer-associated mutations may have direct or indirect effects on proteins and their interactions and while the effects of mutations on signaling pathways have been widely studied, how mutations alter underlying protein-protein interaction networks is much less well understood. Systematic mapping of oncoprotein protein interactions using proteomics techniques as well as computational network analyses is revealing how oncoprotein mutations perturb protein-protein interaction networks and drive the cancer phenotype. PMID:26325016
Kuchaiev, Oleksii; Rasajski, Marija; Higham, Desmond J.; Przul, Natasa; Przytycka, Teresa Maria
Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, i...
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Wei, Yang; Thyparambil, Aby A.; Latour, Robert A.
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-whit...
Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier;
Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation of this...... classification suggests that the balance between favoring and disfavoring structural features determines if a pair of proteins interacts or not. Our results are in agreement with previous works and support the funnel-like intermolecular energy landscape theory that explains PPIs. We have used these features to...
Borch, Jonas; Jørgensen, Thomas J. D.; Roepstorff, Peter
Mass spectrometry is a powerful tool for identification of interaction partners and structural characterization of protein interactions because of its high sensitivity, mass accuracy and tolerance towards sample heterogeneity. Several tools that allow studies of protein interaction are now...... available and recent developments that increase the confidence of studies of protein interaction by mass spectrometry include quantification of affinity-purified proteins by stable isotope labeling and reagents for surface topology studies that can be identified by mass-contributing reporters (e.g. isotope...... labels, cleavable cross-linkers or fragment ions. The use of mass spectrometers to study protein interactions using deuterium exchange and for analysis of intact protein complexes recently has progressed considerably....
Fang, Yi; Sun, Mengtian; Dai, Guoxian; Ramain, Karthik
Recent developments in high-throughput technologies for measuring protein-protein interaction (PPI) have profoundly advanced our ability to systematically infer protein function and regulation. However, inherently high false positive and false negative rates in measurement have posed great challenges in computational approaches for the prediction of PPI. A good PPI predictor should be 1) resistant to high rate of missing and spurious PPIs, and 2) robust against incompleteness of observed PPI networks. To predict PPI in a network, we developed an intrinsic geometry structure (IGS) for network, which exploits the intrinsic and hidden relationship among proteins in network through a heat diffusion process. In this process, all explicit PPIs participate simultaneously to glue local infinitesimal and noisy experimental interaction data to generate a global macroscopic descriptions about relationships among proteins. The revealed implicit relationship can be interpreted as the probability of two proteins interacting with each other. The revealed relationship is intrinsic and robust against individual, local and explicit protein interactions in the original network. We apply our approach to publicly available PPI network data for the evaluation of the performance of PPI prediction. Experimental results indicate that, under different levels of the missing and spurious PPIs, IGS is able to robustly exploit the intrinsic and hidden relationship for PPI prediction with a higher sensitivity and specificity compared to that of recently proposed methods. PMID:26886733
Grünberg, Raik; Ferrar, Tony S.; van der Sloot, Almer M.; Constante, Marco; Serrano, Luis
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 contro...
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.
Hartmann-Petersen, Rasmus; Gordon, Colin
The family of ubiquitin-like (UBL) domain proteins (UDPs) comprises a conserved group of proteins involved in a multitude of different cellular activities. However, recent studies on UBL-domain proteins indicate that these proteins appear to share a common property in their ability to interact with......-domain proteins catalyse the formation of ubiquitin-protein conjugates, whereas others appear to target ubiquitinated proteins for degradation and interact with chaperones. Hence, by binding to the 26S proteasome the UBL-domain proteins seem to tailor and direct the basic proteolytic functions of the particle to...... 26S proteasomes. The 26S proteasome is a multisubunit protease which is responsible for the majority of intracellular proteolysis in eukaryotic cells. Before degradation commences most proteins are first marked for destruction by being coupled to a chain of ubiquitin molecules. Some UBL...
Ivanov, Andrei A.; Khuri, Fadlo R.; Fu, Haian
The emergence and convergence of cancer genomics, targeted therapies, and network oncology have significantly expanded the landscape of protein-protein interaction (PPI) networks in cancer for therapeutic discovery. Extensive biological and clinical investigations have led to the identification of protein interaction hubs and nodes that are critical for the acquisition and maintaining characteristics of cancer essential for cell transformation. Such cancer enabling PPIs have become promising ...
Lee, W. Theodore
To improve student understanding of protein structure and the significance of noncovalent interactions in protein structure and function, students are assigned a project to write a paper complemented with computer-generated images. The assignment provides an opportunity for students to select a protein structure that is of interest and detail…
Full Text Available Abstract Background Protein-protein interaction (PPI is essential to most biological processes. Abnormal interactions may have implications in a number of neurological syndromes. Given that the association and dissociation of protein molecules is crucial, computational tools capable of effectively identifying PPI are desirable. In this paper, we propose a simple yet effective method to detect PPI based on pairwise similarity and using only the primary structure of the protein. The PPI based on Pairwise Similarity (PPI-PS method consists of a representation of each protein sequence by a vector of pairwise similarities against large subsequences of amino acids created by a shifting window which passes over concatenated protein training sequences. Each coordinate of this vector is typically the E-value of the Smith-Waterman score. These vectors are then used to compute the kernel matrix which will be exploited in conjunction with support vector machines. Results To assess the ability of the proposed method to recognize the difference between "interacted" and "non-interacted" proteins pairs, we applied it on different datasets from the available yeast saccharomyces cerevisiae protein interaction. The proposed method achieved reasonable improvement over the existing state-of-the-art methods for PPI prediction. Conclusion Pairwise similarity score provides a relevant measure of similarity between protein sequences. This similarity incorporates biological knowledge about proteins and it is extremely powerful when combined with support vector machine to predict PPI.
Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the
Full Text Available Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV and Kaposi's sarcoma-associated herpesvirus (KSHV. In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1, murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H, and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.
Tarcea, V. Glenn; Weymouth, Terry; Ade, Alex; Bookvich, Aaron; Gao, Jing; Mahavisno, Vasudeva; Wright, Zach; Chapman, Adriane; Jayapandian, Magesh; Özgür, Arzucan; Tian, Yuanyuan; Cavalcoli, Jim; Mirel, Barbara; Patel, Jignesh; Radev, Dragomir
Molecular interaction data exists in a number of repositories, each with its own data format, molecule identifier and information coverage. Michigan molecular interactions (MiMI) assists scientists searching through this profusion of molecular interaction data. The original release of MiMI gathered data from well-known protein interaction databases, and deep merged this information while keeping track of provenance. Based on the feedback received from users, MiMI has been completely redesigne...
Davis Melissa J
Full Text Available Abstract Background Many biological processes are mediated by dynamic interactions between and among proteins. In order to interact, two proteins must co-occur spatially and temporally. As protein-protein interactions (PPIs and subcellular location (SCL are discovered via separate empirical approaches, PPI and SCL annotations are independent and might complement each other in helping us to understand the role of individual proteins in cellular networks. We expect reliable PPI annotations to show that proteins interacting in vivo are co-located in the same cellular compartment. Our goal here is to evaluate the potential of using PPI annotation in determining SCL of proteins in human, mouse, fly and yeast, and to identify and quantify the factors that contribute to this complementarity. Results Using publicly available data, we evaluate the hypothesis that interacting proteins must be co-located within the same subcellular compartment. Based on a large, manually curated PPI dataset, we demonstrate that a substantial proportion of interacting proteins are in fact co-located. We develop an approach to predict the SCL of a protein based on the SCL of its interaction partners, given sufficient confidence in the interaction itself. The frequency of false positive PPIs can be reduced by use of six lines of supporting evidence, three based on type of recorded evidence (empirical approach, multiplicity of databases, and multiplicity of literature citations and three based on type of biological evidence (inferred biological process, domain-domain interactions, and orthology relationships, with biological evidence more-effective than recorded evidence. Our approach performs better than four existing prediction methods in identifying the SCL of membrane proteins, and as well as or better for soluble proteins. Conclusion Understanding cellular systems requires knowledge of the SCL of interacting proteins. We show how PPI data can be used more effectively to
Gordon J King
Full Text Available BACKGROUND: Protein crystallisation screening involves the parallel testing of large numbers of candidate conditions with the aim of identifying conditions suitable as a starting point for the production of diffraction quality crystals. Generally, condition screening is performed in 96-well plates. While previous studies have examined the effects of protein construct, protein purity, or crystallisation condition ingredients on protein crystallisation, few have examined the effect of the crystallisation plate. METHODOLOGY/PRINCIPAL FINDINGS: We performed a statistically rigorous examination of protein crystallisation, and evaluated interactions between crystallisation success and plate row/column, different plates of same make, different plate makes and different proteins. From our analysis of protein crystallisation, we found a significant interaction between plate make and the specific protein being crystallised. CONCLUSIONS/SIGNIFICANCE: Protein crystal structure determination is the principal method for determining protein structure but is limited by the need to produce crystals of the protein under study. Many important proteins are difficult to crystallize, so that identification of factors that assist crystallisation could open up the structure determination of these more challenging targets. Our findings suggest that protein crystallisation success may be improved by matching a protein with its optimal plate make.
Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy
Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...... spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used to...... characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions....
Hosp, Fabian; Vossfeldt, Hannes; Heinig, Matthias; Vasiljevic, Djordje; Arumughan, Anup; Wyler, Emanuel; Landthaler, Markus; Hubner, Norbert; Wanker, Erich E; Lannfelt, Lars; Ingelsson, Martin; Lalowski, Maciej; Voigt, Aaron; Selbach, Matthias
Several proteins have been linked to neurodegenerative disorders (NDDs), but their molecular function is not completely understood. Here, we used quantitative interaction proteomics to identify binding partners of Amyloid beta precursor protein (APP) and Presenilin-1 (PSEN1) for Alzheimer's disease (AD), Huntingtin (HTT) for Huntington's disease, Parkin (PARK2) for Parkinson's disease, and Ataxin-1 (ATXN1) for spinocerebellar ataxia type 1. Our network reveals common signatures of protein degradation and misfolding and recapitulates known biology. Toxicity modifier screens and comparison to genome-wide association studies show that interaction partners are significantly linked to disease phenotypes in vivo. Direct comparison of wild-type proteins and disease-associated variants identified binders involved in pathogenesis, highlighting the value of differential interactome mapping. Finally, we show that the mitochondrial protein LRPPRC interacts preferentially with an early-onset AD variant of APP. This interaction appears to induce mitochondrial dysfunction, which is an early phenotype of AD. PMID:25959826
CAI Lun; XUE Hong; LU Hongchao; ZHAO Yi; ZHU Xiaopeng; BU Dongbo; LING Lunjiang; CHEN Runsheng
Protein-protein interaction is a physical interaction of two proteins in living cells. In budding yeast Saccharomyces cerevisiae, large-scale protein-protein interaction data have been obtained through high-throughput yeast two-hybrid systems (Y2H) and protein complex purification techniques based on mass-spectrometry. Here, we collect 11855 interactions between total 2617 proteins. Through seriate genome-wide mRNA expression data, similarity between two genes could be measured. Protein complex data can also be obtained publicly and can be translated to pair relationship that any two proteins can only exist in the same complex or not. Analysis of protein complex data, protein-protein interaction data and mRNA expression data can elucidate correlations between them. The results show that proteins that have interactions or similar expression patterns have a higher possibility to be in the same protein complex than randomized selected proteins, and proteins which have interactions and similar expression patterns are even more possible to exist in the same protein complex. The work indicates that comprehensive integration and analysis of public large-scale bioinformatical data, such as protein complex data, protein-protein interaction data and mRNA expression data, may help to uncover their relationships and common biological information underlying these data. The strategies described here may help to integrate and analyze other functional genomic and proteomic data, such as gene expression profiling, protein-localization mapping and large-scale phenotypic data, both in yeast and in other organisms.
Full Text Available Abstract Background The study of gene mutants and their interactions is fundamental to understanding gene function and backup mechanisms within the cell. The recent availability of large scale genetic interaction networks in yeast and worm allows the investigation of the biological mechanisms underlying these interactions at a global scale. To date, less than 2% of the known genetic interactions in yeast or worm can be accounted for by sequence similarity. Results Here, we perform a genome-scale structural comparison among protein pairs in the two species. We show that significant fractions of genetic interactions involve structurally similar proteins, spanning 7–10% and 14% of all known interactions in yeast and worm, respectively. We identify several structural features that are predictive of genetic interactions and show their superiority over sequence-based features. Conclusion Structural similarity is an important property that can explain and predict genetic interactions. According to the available data, the most abundant mechanism for genetic interactions among structurally similar proteins is a common interacting partner shared by two genetically interacting proteins.
Re, Angela; Joshi, Tejal; Kulberkyte, Eleonora;
RNAs bound by individual RBPs, or vice versa, for both in vitro and in vivo methodologies. To help highlight the biological significance of RBP mediated regulation, online resources on experimentally verified protein-RNA interactions are briefly presented. Finally, we present the major tools to...... sequence and structural features uniquely characterizing protein-RNA interactions.......RNA binding proteins (RBPs) are key players in the regulation of gene expression. In this chapter we discuss the main protein-RNA recognition modes used by RBPs in order to regulate multiple steps of RNA processing. We discuss traditional and state-of-the-art technologies that can be used to study...
Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate
The structure of DNA Binding Proteins enables a strong interaction with their specific target site on DNA. However, recent single molecule experiment reported that proteins can diffuse on DNA. This suggests that the interactions between proteins and DNA play a role during the target search even far from the specific site. It is unclear how these non-specific interactions optimize the search process, and how the protein structure comes into play. Each nucleotide being negatively charged, one may think that the positive surface of DNA-BPs should electrostatically collapse onto DNA. Here we show by means of Monte Carlo simulations and analytical calculations that a counter-intuitive repulsion between the two oppositely charged macromolecules exists at a nanometer range. We also show that this repulsion is due to a local increase of the osmotic pressure exerted by the ions which are trapped at the interface. For the concave shape of DNA-BPs, and for realistic protein charge densities, we find that the repulsion pushes the protein in a free energy minimum at a distance from DNA. As a consequence, a favourable path exists along which proteins can slide without interacting with the DNA bases. When a protein encounters its target, the osmotic barrier is completely counter-balanced by the H-bond interaction, thus enabling the sequence recognition. (authors)
Bacci, Giorgio; Miculan, Marino; 10.4204/EPTCS.11.1
We present a bigraphical framework suited for modeling biological systems both at protein level and at membrane level. We characterize formally bigraphs corresponding to biologically meaningful systems, and bigraphic rewriting rules representing biologically admissible interactions. At the protein level, these bigraphic reactive systems correspond exactly to systems of kappa-calculus. Membrane-level interactions are represented by just two general rules, whose application can be triggered by protein-level interactions in a well-de\\"ined and precise way. This framework can be used to compare and merge models at different abstraction levels; in particular, higher-level (e.g. mobility) activities can be given a formal biological justification in terms of low-level (i.e., protein) interactions. As examples, we formalize in our framework the vesiculation and the phagocytosis processes.
In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine) motif proteins (LYRMs) of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6) or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1) of the oxidative phosphorylation (OXPHOS) core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM) independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria. PMID:25686363
Full Text Available In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine motif proteins (LYRMs of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6 or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1 of the oxidative phosphorylation (OXPHOS core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have been provided by analyses of EM and X-ray structures of complex I from bovine and the yeast Yarrowia lipolytica, respectively. Combined structural and biochemical studies revealed that LYRM6 resides at the matrix arm close to the ubiquinone reduction site. For LYRM3, a position at the distal proton-pumping membrane arm facing the matrix space is suggested. Both LYRMs are supposed to anchor an acyl-carrier protein (ACPM independently to complex I. The function of this duplicated protein interaction of ACPM with respiratory complex I is still unknown. Analysis of protein-protein interaction screens, genetic analyses and predicted multi-domain LYRMs offer further clues on an interaction network and adaptor-like function of LYR proteins in mitochondria.
Gottschalk, Marie; Bach, Anders; Hansen, Jakob Lerche;
to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C...
Samanta, Manoj; Liang, Shoudan; Biegel, Bryan (Technical Monitor)
In today's world, three seemingly diverse fields - computer information technology, nanotechnology and biotechnology are joining forces to enlarge our scientific knowledge and solve complex technological problems. Our group is dedicated to conduct theoretical research exploring the challenges in this area. The major areas of research include: 1) Yeast Protein Interactions; 2) Protein Structures; and 3) Current Transport through Small Molecules.
Becker, Emmanuelle; Robisson, Benoît; Chapple, Charles E.; Guénoche, Alain; Brun, Christine
Motivation: Multifunctional proteins perform several functions. They are expected to interact specifically with distinct sets of partners, simultaneously or not, depending on the function performed. Current graph clustering methods usually allow a protein to belong to only one cluster, therefore impeding a realistic assignment of multifunctional proteins to clusters. Results: Here, we present Overlapping Cluster Generator (OCG), a novel clustering method which decomposes a network into overla...
In eukaryotic cells, mitochondria host ancient essential bioenergetic and biosynthetic pathways. LYR (leucine/tyrosine/arginine) motif proteins (LYRMs) of the Complex1_LYR-like superfamily interact with protein complexes of bacterial origin. Many LYR proteins function as extra subunits (LYRM3 and LYRM6) or novel assembly factors (LYRM7, LYRM8, ACN9 and FMC1) of the oxidative phosphorylation (OXPHOS) core complexes. Structural insights into complex I accessory subunits LYRM6 and LYRM3 have bee...
To understand the role of water in life at molecular and atomic levels, structures and interactions at the protein-water interface have been investigated by cryogenic X-ray crystallography. The method enabled a much clearer visualization of definite hydration sites on the protein surface than at ambient temperature. Using the structural models of proteins, including several hydration water molecules, the characteristics in hydration structures were systematically analysed for the amount, the ...
The nature of the interactions between whey proteins and kaolinite surfaces was investigated by adsorption-desorption experiments at room temperature, performed at the isoelectric point (IEP) of the proteins and at pH 7. It was found that kaolinite is a strong adsorbent for proteins, reaching the maximum adsorption capacity at the IEP of each protein. At pH 7.0, the retention capacity decreased considerably. The adsorption isotherms showed typical Langmuir characteristics. X-ray diffraction data for the protein-kaolinite complexes showed that protein molecules were not intercalated in the mineral structure, but immobilized at the external surfaces and the edges of the kaolinite. Fourier transform IR results indicate the absence of hydrogen bonding between kaolinite surfaces and the polypeptide chain. The adsorption patterns appear to be related to electrostatic interactions, although steric effects should be also considered
Kwofie, Samuel K.
It is essential to catalog characterized hepatitis C virus (HCV) protein-protein interaction (PPI) data and the associated plethora of vital functional information to augment the search for therapies, vaccines and diagnostic biomarkers. In furtherance of these goals, we have developed the hepatitis C virus protein interaction database (HCVpro) by integrating manually verified hepatitis C virus-virus and virus-human protein interactions curated from literature and databases. HCVpro is a comprehensive and integrated HCV-specific knowledgebase housing consolidated information on PPIs, functional genomics and molecular data obtained from a variety of virus databases (VirHostNet, VirusMint, HCVdb and euHCVdb), and from BIND and other relevant biology repositories. HCVpro is further populated with information on hepatocellular carcinoma (HCC) related genes that are mapped onto their encoded cellular proteins. Incorporated proteins have been mapped onto Gene Ontologies, canonical pathways, Online Mendelian Inheritance in Man (OMIM) and extensively cross-referenced to other essential annotations. The database is enriched with exhaustive reviews on structure and functions of HCV proteins, current state of drug and vaccine development and links to recommended journal articles. Users can query the database using specific protein identifiers (IDs), chromosomal locations of a gene, interaction detection methods, indexed PubMed sources as well as HCVpro, BIND and VirusMint IDs. The use of HCVpro is free and the resource can be accessed via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/. © 2011 Elsevier B.V.
Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use
Lees, J G; Heriche, J K; Morilla, I; Ranea, J A; Orengo, C A
Determining the network of physical protein associations is an important first step in developing mechanistic evidence for elucidating biological pathways. Despite rapid advances in the field of high throughput experiments to determine protein interactions, the majority of associations remain unknown. Here we describe computational methods for significantly expanding protein association networks. We describe methods for integrating multiple independent sources of evidence to obtain higher quality predictions and we compare the major publicly available resources available for experimentalists to use. PMID:21572181
Fornasari, Maria Silvina; Parisi, Gustavo; Echave, Julian
Noncovalent interactions and physicochemical properties of amino acids are important topics in biochemistry courses. Here, we present a computational laboratory where the capacity of each of the 20 amino acids to maintain different noncovalent interactions are used to investigate the stabilizing forces in a set of proteins coming from organisms…
Jiang Jonathan Q; Wu Maoying
Abstract Background Proteins that interact in vivo tend to reside within the same or "adjacent" subcellular compartments. This observation provides opportunities to reveal protein subcellular localization in the context of the protein-protein interaction (PPI) network. However, so far, only a few efforts based on heuristic rules have been made in this regard. Results We systematically and quantitatively validate the hypothesis that proteins physically interacting with each other probably shar...
Aakre, Christopher D; Herrou, Julien; Phung, Tuyen N; Perchuk, Barrett S; Crosson, Sean; Laub, Michael T
Interacting proteins typically coevolve, and the identification of coevolving amino acids can pinpoint residues required for interaction specificity. This approach often assumes that an interface-disrupting mutation in one protein drives selection of a compensatory mutation in its partner during evolution. However, this model requires a non-functional intermediate state prior to the compensatory change. Alternatively, a mutation in one protein could first broaden its specificity, allowing changes in its partner, followed by a specificity-restricting mutation. Using bacterial toxin-antitoxin systems, we demonstrate the plausibility of this second, promiscuity-based model. By screening large libraries of interface mutants, we show that toxins and antitoxins with high specificity are frequently connected in sequence space to more promiscuous variants that can serve as intermediates during a reprogramming of interaction specificity. We propose that the abundance of promiscuous variants promotes the expansion and diversification of toxin-antitoxin systems and other paralogous protein families during evolution. PMID:26478181
Protein-domains play an important role in mediating protein-protein interactions. Furthermore, the same domain-pairs mediate different interactions in different contexts and in various organisms, and therefore domain-pairs are considered as the building blocks of interactome networks. Here we extend these principles to the host-virus interface and find the domain-pairs that potentially mediate human-herpesvirus interactions. Notably, we find that the same domain-pairs used by other organisms ...
Ming Yang; Yan Ge; Jiayan Wu; Jingfa Xiao; Jun Yu
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 x 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.
Full Text Available Understanding complex networks of protein-protein interactions (PPIs is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H, tandem affinity purification (TAP and other high-throughput methods for protein-protein interaction (PPI detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, it is thought that the false positive rate could be as high as 64%, and the false negative rate may range from 43% to 71%. TAP experiments are believed to have comparable levels of noise.We present a novel technique to assess the confidence levels of interactions in PPI networks obtained from experimental studies. We use it for predicting new interactions and thus for guiding future biological experiments. This technique is the first to utilize currently the best fitting network model for PPI networks, geometric graphs. Our approach achieves specificity of 85% and sensitivity of 90%. We use it to assign confidence scores to physical protein-protein interactions in the human PPI network downloaded from BioGRID. Using our approach, we predict 251 interactions in the human PPI network, a statistically significant fraction of which correspond to protein pairs sharing common GO terms. Moreover, we validate a statistically significant portion of our predicted interactions in the HPRD database and the newer release of BioGRID. The data and Matlab code implementing the methods are freely available from the web site: http://www.kuchaev.com/Denoising.
Nazar Zaki; Elfadil A. Mohamed; Antonio Mora
The identification and characterization of protein complexes implicated in protein-protein interaction data are crucial to the understanding of the molecular events under normal and abnormal physiological conditions. This paper provides a novel characterization of subcomplexes in protein interaction databases, stressing definition and representation issues, quantification, biological validation, network metrics, motifs, modularity, and gene ontology (GO) terms. The paper introduces the concep...
Giot, L.; Bader, J. S.; Brouwer, C.; Chaudhuri, A.; Kuang, B.; Li, Y.; Hao, Y. L.; Ooi, C. E.; Godwin, B.; Vitols, E.; Vijayadamodar, G.; Pochart, P.; Machineni, H.; Welsh, M.; Kong, Y.; Zerhusen, B.; Malcolm, R.; Varrone, Z.; Collis, A.; Minto, M.; Burgess, S.; McDaniel, L.; Stimpson, E.; Spriggs, F.; Williams, J.; Neurath, K.; Ioime, N.; Agee, M.; Voss, E.; Furtak, K.; Renzulli, R.; Aanensen, N.; Carrolla, S.; Bickelhaupt, E.; Lazovatsky, Y.; DaSilva, A.; Zhong, J.; Stanyon, C. A.; Finley, R. L.; White, K. P.; Braverman, M.; Jarvie, T.; Gold, S.; Leach, M.; Knight, J.; Shimkets, R. A.; McKenna, M. P.; Chant, J.; Rothberg, J. M.
Drosophila melanogaster is a proven model system for many aspects of human biology. Here we present a two-hybrid-based protein-interaction map of the fly proteome. A total of 10,623 predicted transcripts were isolated and screened against standard and normalized complementary DNA libraries to produce a draft map of 7048 proteins and 20,405 interactions. A computational method of rating two-hybrid interaction confidence was developed to refine this draft map to a higher confidence map of 4679 proteins and 4780 interactions. Statistical modeling of the network showed two levels of organization: a short-range organization, presumably corresponding to multiprotein complexes, and a more global organization, presumably corresponding to intercomplex connections. The network recapitulated known pathways, extended pathways, and uncovered previously unknown pathway components. This map serves as a starting point for a systems biology modeling of multicellular organisms, including humans.
Full Text Available YDR026C - Protein of unknown function that may interact with ribosomes, based on co-purification...ein of unknown function that may interact with ribosomes, based on co-purification
Sun Zhirong; Liu Ke; Chen Hu; Zhang Song
Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI) networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to pre...
To understand the role of water in life at molecular and atomic levels, structures and interactions at the protein-water interface have been investigated by cryogenic X-ray crystallography. The method enabled a much clearer visualization of definite hydration sites on the protein surface than at ambient temperature. Using the structural models of proteins, including several hydration water molecules, the characteristics in hydration structures were systematically analysed for the amount, the interaction geometries between water molecules and proteins, and the local and global distribution of water molecules on the surface of proteins. The tetrahedral hydrogen-bond geometry of water molecules in bulk solvent was retained at the interface and enabled the extension of a three-dimensional chain connection of a hydrogen-bond network among hydration water molecules and polar protein atoms over the entire surface of proteins. Networks of hydrogen bonds were quite flexible to accommodate and/or to regulate the conformational changes of proteins such as domain motions. The present experimental results may have profound implications in the understanding of the physico-chemical principles governing the dynamics of proteins in an aqueous environment and a discussion of why water is essential to life at a molecular level. PMID:15306376
Yan, Chengfei; Xu, Xianjin; Zou, Xiaoqin; Zou lab Team
Protein-peptide interactions play an important role in many cellular processes. The ability to predict protein-peptide complex structures is valuable for mechanistic investigation and therapeutic development. Due to the high flexibility of peptides and lack of templates for homologous modeling, predicting protein-peptide complex structures is extremely challenging. Recently, we have developed a novel docking framework for protein-peptide structure prediction. Specifically, given the sequence of a peptide and a 3D structure of the protein, initial conformations of the peptide are built through protein threading. Then, the peptide is globally and flexibly docked onto the protein using a novel iterative approach. Finally, the sampled modes are scored and ranked by a statistical potential-based energy scoring function that was derived for protein-peptide interactions from statistical mechanics principles. Our docking methodology has been tested on the Peptidb database and compared with other protein-peptide docking methods. Systematic analysis shows significantly improved results compared to the performances of the existing methods. Our method is computationally efficient and suitable for large-scale applications. Nsf CAREER Award 0953839 (XZ) NIH R01GM109980 (XZ).
Melody G Campbell
Full Text Available 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.
Huisman, I.H.; Prádanos, P.; Hernández, A.
It was studied how protein-protein and protein-membrane interactions influence the filtration performance during the ultrafiltration of protein solutions over polymeric membranes. This was done by measuring flux, streaming potential, and protein transmission during filtration of bovine serum albumin
Darnell, Steven J; LeGault, Laura; Mitchell, Julie C
The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model-a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein-protein or protein-DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org. PMID:18539611
Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong
Studies of protein phenotypes represent a central challenge of modern genetics in the post-genome era because effective and accurate investigation of protein phenotypes is one of the most critical procedures to identify functional biological processes in microscale, which involves the analysis of multifactorial traits and has greatly contributed to the development of modern biology in the post genome era. Therefore, we have developed a novel computational method that identifies novel proteins associated with certain phenotypes in yeast based on the protein-protein interaction network. Unlike some existing network-based computational methods that identify the phenotype of a query protein based on its direct neighbors in the local network, the proposed method identifies novel candidate proteins for a certain phenotype by considering all annotated proteins with this phenotype on the global network using a shortest path (SP) algorithm. The identified proteins are further filtered using both a permutation test and their interactions and sequence similarities to annotated proteins. We compared our method with another widely used method called random walk with restart (RWR). The biological functions of proteins for each phenotype identified by our SP method and the RWR method were analyzed and compared. The results confirmed a large proportion of our novel protein phenotype annotation, and the RWR method showed a higher false positive rate than the SP method. Our method is equally effective for the prediction of proteins involving in all the eleven clustered yeast phenotypes with a quite low false positive rate. Considering the universality and generalizability of our supporting materials and computing strategies, our method can further be applied to study other organisms and the new functions we predicted can provide pertinent instructions for the further experimental verifications. PMID:26728152
Jonnalagadda, Siddhartha; Gonzalez, Graciela
Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of s...
Full Text Available YOR097C - Putative protein of unknown function; identified as interacting with Hsp82p in a high-throughput... description Putative protein of unknown function; identified as interacting with Hsp82p in a high-through...put two-hybrid screen; YOR097C is not an essential gene Rows with this bait as bait
Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong
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.
Hayes, Sheri; Malacrida, Beatrice; Kiely, Maeve; Kiely, Patrick A
Signalling proteins are intrinsic to all biological processes and interact with each other in tightly regulated and orchestrated signalling complexes and pathways. Characterization of protein binding can help to elucidate protein function within signalling pathways. This information is vital for researchers to gain a more comprehensive knowledge of cellular networks which can then be used to develop new therapeutic strategies for disease. However, studying protein-protein interactions (PPIs) can be challenging as the interactions can be extremely transient downstream of specific environmental cues. There are many powerful techniques currently available to identify and confirm PPIs. Choosing the most appropriate range of techniques merits serious consideration. The aim of this review is to provide a starting point for researchers embarking on a PPI study. We provide an overview and point of reference for some of the many methods available to identify interactions from in silico analysis and large scale screening tools through to the methods used to validate potential PPIs. We discuss the advantages and disadvantages of each method and we also provide a workflow chart to highlight the main experimental questions to consider when planning cell lysis to maximize experimental success. PMID:27528744
Guangyu Cui; Yu Chen; De-Shuang Huang; Kyungsook Han
Biological processes are often performed by a group of proteins rather than by individual proteins, and proteins in a same biological group form a densely connected subgraph in a protein-protein interaction network. Therefore, finding a densely connected subgraph provides useful information to predict the function or protein complex of uncharacterized proteins in the highly connected subgraph. We have developed an efficient algorithm and program for finding cliques and near-cliques in a prote...
Farhat N. Jaffery; Viswanathan, P N
In order to understand the molecular mechanism of the toxicity of Si containing particulate air pollutants, the interaction between silicate anion and proteins was studied. On the basis of molecular sieving profile, the presence of a protein fraction capable of binding silicic acid was detected in rat lung and serum. The binding is firm being able to withstand dialysis, Si-binding by Bovine Serum Albumin (BSA) follows stoichiometric principles indicating true chemical reaction in terms of eff...
Christina M Taylor
Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly
Full Text Available Several proteins have been linked to neurodegenerative disorders (NDDs, but their molecular function is not completely understood. Here, we used quantitative interaction proteomics to identify binding partners of Amyloid beta precursor protein (APP and Presenilin-1 (PSEN1 for Alzheimer’s disease (AD, Huntingtin (HTT for Huntington’s disease, Parkin (PARK2 for Parkinson’s disease, and Ataxin-1 (ATXN1 for spinocerebellar ataxia type 1. Our network reveals common signatures of protein degradation and misfolding and recapitulates known biology. Toxicity modifier screens and comparison to genome-wide association studies show that interaction partners are significantly linked to disease phenotypes in vivo. Direct comparison of wild-type proteins and disease-associated variants identified binders involved in pathogenesis, highlighting the value of differential interactome mapping. Finally, we show that the mitochondrial protein LRPPRC interacts preferentially with an early-onset AD variant of APP. This interaction appears to induce mitochondrial dysfunction, which is an early phenotype of AD.
Uetz Peter; Casjens Sherwood; Rajagopala Seesandra V
Abstract 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 ou...
Full Text Available YGR048W UFD1 Protein that interacts with Cdc48p and Npl4p, involved in recognition of polyubiqui ... tinated proteins and their presentation ... to the 26S proteasome for degradation; involved in ... ecognition of polyubiquitinated proteins and their presentation ... to the 26S proteasome for degradation; involved in ...
Full Text Available cally and genetically with Tap42p, which regulates protein phosphatase 2A; compo...phatase 2A; component of the TOR (target of rapamycin) signaling pathway Rows with this bait as bait...rnative path with 2 intervening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ... ...YPR040W TIP41 Protein that interacts physically and genetically with Tap42p, which regulates protein phos...gen accumulation; interacts with Tap42p, which binds to and regulates other protein phosphatases Rows wit
Lua, Rhonald C; Marciano, David C; Katsonis, Panagiotis; Adikesavan, Anbu K; Wilkins, Angela D; Lichtarge, Olivier
Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI. PMID:24878423
One of the important means to control eukaryotic gene expression involves the binding of proteins to specific sites in the promoter and other regulatory regions of the gene. This chapter is devoted to methodology for identifying DNA sequences that are bound in vitro by proteins in crude nuclear extracts. The authors present four methods of detection: nitrocellulose filter binding, mobility shift, exonuclease III protection, and DNAse I protection. In addition to providing assay conditions, they discuss some applications of the different methods. Very often data from protein-DNA interaction studies permit ambiguous interpretations. They there discuss control experiments designed to help the researcher to evaluate data
Corbi-Verge, Carles; Kim, Philip M
Protein-protein interactions (PPI) are involved in virtually every cellular process and thus represent an attractive target for therapeutic interventions. A significant number of protein interactions are frequently formed between globular domains and short linear peptide motifs (DMI). Targeting these DMIs has proven challenging and classical approaches to inhibiting such interactions with small molecules have had limited success. However, recent new approaches have led to the discovery of potent inhibitors, some of them, such as Obatoclax, ABT-199, AEG-40826 and SAH-p53-8 are likely to become approved drugs. These novel inhibitors belong to a wide range of different molecule classes, ranging from small molecules to peptidomimetics and biologicals. This article reviews the main reasons for limited success in targeting PPIs, discusses how successful approaches overcome these obstacles to discovery promising inhibitors for human protein double minute 2 (HDM2), B-cell lymphoma 2 (Bcl-2), X-linked inhibitor of apoptosis protein (XIAP), and provides a summary of the promising approaches currently in development that indicate the future potential of PPI inhibitors in drug discovery. PMID:26936767
Alfaras-Melainis, Konstantinos; Gomes, Ivone; Rozenfeld, Raphael; Zachariou, Venetia; Devi, Lakshmi
Opioid receptors, MORP, DORP and KORP, belong to the family A of G protein coupled receptors (GPCR), and have been found to modulate a large number of physiological functions, including mood, stress, appetite, nociception and immune responses. Exogenously applied opioid alkaloids produce analgesia, hedonia and addiction. Addiction is linked to alterations in function and responsiveness of all three opioid receptors in the brain. Over the last few years, a large number of studies identified protein-protein interactions that play an essential role in opioid receptor function and responsiveness. Here, we summarize interactions shown to affect receptor biogenesis and trafficking, as well as those affecting signal transduction events following receptor activation. This article also examines protein interactions modulating the rate of receptor endocytosis and degradation, events that play a major role in opiate analgesia. Like several other GPCRs, opioid receptors may form homo or heterodimers. The last part of this review summarizes recent knowledge on proteins known to affect opioid receptor dimerization. PMID:19273296
Bacci, Giorgio; Miculan, Marino; 10.4204/EPTCS.11.2
We introduce the BioBeta Framework, a meta-model for both protein-level and membrane-level interactions of living cells. This formalism aims to provide a formal setting where to encode, compare and merge models at different abstraction levels; in particular, higher-level (e.g. membrane) activities can be given a formal biological justification in terms of low-level (i.e., protein) interactions. A BioBeta specification provides a protein signature together a set of protein reactions, in the spirit of the kappa-calculus. Moreover, the specification describes when a protein configuration triggers one of the only two membrane interaction allowed, that is "pinch" and "fuse". In this paper we define the syntax and semantics of BioBeta, analyse its properties, give it an interpretation as biobigraphical reactive systems, and discuss its expressivity by comparing with kappa-calculus and modelling significant examples. Notably, BioBeta has been designed after a bigraphical metamodel for the same purposes. Hence, each ...
Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.
Giorgini, Flaviano; Muchowski, Paul J.
Analysis of protein-protein interaction networks is becoming important for inferring the function of uncharacterized proteins. A recent study using this approach has identified new proteins and interactions that might be involved in the pathogenesis of the neurodegenerative disorder Huntington's disease, including a GTPase-activating protein that co-localizes with protein aggregates in Huntington's disease patients.
Xiong, Wei; Xie, Luyu; Zhou, Shuigeng; Liu, Hui; Guan, Jihong
Topological analysis of protein-protein interaction (PPI) networks has been widely applied to the investigation on cancer mechanisms. However, there is still a debate on whether cancer proteins exhibit more topological centrality compared to the other proteins in the human PPI network. To resolve this debate, we first identified four sets of human proteins, and then mapped these proteins into the yeast PPI network by homologous genes. Finally, we compared these proteins' properties in human and yeast PPI networks. Experiments over two real datasets demonstrated that cancer proteins tend to have higher degree and smaller clustering coefficient than non-cancer proteins. Experimental results also validated that cancer proteins have larger betweenness centrality compared to the other proteins on the STRING dataset. However, on the BioGRID dataset, the average betweenness centrality of cancer proteins is larger than that of disease and control proteins, but smaller than that of essential proteins. PMID:24878726
Full Text Available interactions with ESCRT-I and ubiquitin-dependent sorting of proteins into the endoso...ing in EAP45) domain which is involved in interactions with ESCRT-I and ubiquitin-dependent sortin...YPL002C SNF8 Component of the ESCRT-II complex, which is involved in ubiquitin-dependent sorting of protein...s into the endosome; appears to be functionally related to SNF7; involved in glucose der...ESCRT-II complex, which is involved in ubiquitin-dependent sorting of proteins into the endosome; appears to be functi
Full Text Available YNL044W YIP3 Protein localized to COPII vesicles, proposed to be involved in ER to Golgi transpo ... rt; interacts with members of the Rab GTPase family ... and Yip1p; also interacts with Rtn1p Rows with thi ... ransport; interacts with members of the Rab GTPase family ... and Yip1p; also interacts with Rtn1p Rows with thi ...
Tan Kai; Kim Jongkwang
Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity), to infer protein complexes in a protein-pr...
Best, Christoph; Zimmer, Ralf; Apostolakis, Joannis
We discuss probabilistic methods for predicting protein functions from protein-protein interaction networks. Previous work based on Markov Randon Fields is extended and compared to a general machine-learning theoretic approach. Using actual protein interaction networks for yeast from the MIPS database and GO-SLIM function assignments, we compare the predictions of the different probabilistic methods and of a standard support vector machine. It turns out that, with the currently available netw...
Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of sentences has on the performance of a state-of-art PPI extraction system, showing a substantial improvement in recall (8%) when the sentence simplification method is applied, without significant impact to precision.
Farhat N. Jaffery
Full Text Available In order to understand the molecular mechanism of the toxicity of Si containing particulate air pollutants, the interaction between silicate anion and proteins was studied. On the basis of molecular sieving profile, the presence of a protein fraction capable of binding silicic acid was detected in rat lung and serum. The binding is firm being able to withstand dialysis, Si-binding by Bovine Serum Albumin (BSA follows stoichiometric principles indicating true chemical reaction in terms of effects of pH, temperature and period of incubation. Fluorescence spectrum of the BSA-Si complex decreased with an increase in Si concentration. Effect of Si-binding on trypsin activity against albumin showed that proteins other than albumin could also interact with Si-trypsin containing silica showed distinctly low, catalytic activity against native BSA. When both the substrate and enzyme contained bound Si, the activity further reduced by 36 per cent as compared to both pure trypsin and pure BSA, clearly indicating that binding of Si with substrate or enzyme proteins can adversely effect the biological activity. Complexing with proteins is likely to play a role in pathogenesis of pneumoconiosis, elimination of dusts, formation of silicate stones in plants and animals, and possibly in the reported role of Si in nutrition, cardiovascular diseases and ageing.
Yeh, Hsin-Sung; Chang, Jae-Woong; Yong, Jeongsik
Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses. PMID:26965265
Tarcea, V Glenn; Weymouth, Terry; Ade, Alex; Bookvich, Aaron; Gao, Jing; Mahavisno, Vasudeva; Wright, Zach; Chapman, Adriane; Jayapandian, Magesh; Ozgür, Arzucan; Tian, Yuanyuan; Cavalcoli, Jim; Mirel, Barbara; Patel, Jignesh; Radev, Dragomir; Athey, Brian; States, David; Jagadish, H V
Molecular interaction data exists in a number of repositories, each with its own data format, molecule identifier and information coverage. Michigan molecular interactions (MiMI) assists scientists searching through this profusion of molecular interaction data. The original release of MiMI gathered data from well-known protein interaction databases, and deep merged this information while keeping track of provenance. Based on the feedback received from users, MiMI has been completely redesigned. This article describes the resulting MiMI Release 2 (MiMIr2). New functionality includes extension from proteins to genes and to pathways; identification of highlighted sentences in source publications; seamless two-way linkage with Cytoscape; query facilities based on MeSH/GO terms and other concepts; approximate graph matching to find relevant pathways; support for querying in bulk; and a user focus-group driven interface design. MiMI is part of the NIH's; National Center for Integrative Biomedical Informatics (NCIBI) and is publicly available at: http://mimi.ncibi.org. PMID:18978014
Iyer, Lavanya K.; Moorthy, Balakrishnan S.; Topp, Elizabeth M.
Protein structure and local environment in lyophilized formulations were probed using high-resolution solid-state photolytic crosslinking with mass spectrometric analysis (ssPC-MS). In order to characterize structure and microenvironment, protein-protein, protein-excipient and protein-water interactions in lyophilized powders were identified. Myoglobin (Mb) was derivatized in solution with the heterobifunctional probe succinimidyl 4,4’-azipentanoate (SDA) and the structural integrity of the l...
Protein-protein interactions are essential biological reactions occurring at inter- and intra-cellular levels. The analysis of their mechanism is generally required in order link to understand their various cellular functions. Bioluminescence resonance energy transfer (BRET), which is based on an enzymatic activity of luciferase, is a useful tool for investigating protein-protein interactions in live cells. The combination of the BRET system and biomolecular fluorescence complementation (BiFC) would provide us a better understanding of the hetero-oligomeric structural states of protein complexes. In this review, we discuss the application of BRET to the protein-protein interactions of mitochondrial-associated proteins and discuss its physiological relevance. PMID:27493852
代启国; 郭茂祖; 刘晓燕; 滕志霞; 王春宇
Proteins usually bind together to form complexes, which play an important role in cellular activities. Many graph clustering methods have been proposed to identify protein complexes by finding dense regions in protein-protein interaction networks. We present a novel framework (CPL) that detects protein complexes by propagating labels through interactions in a network, in which labels denote complex identifiers. With proper propagation in CPL, proteins in the same complex will be assigned with the same labels. CPL does not make any strong assumptions about the topological structures of the complexes, as in previous methods. The CPL algorithm is tested on several publicly available yeast protein-protein interaction networks and compared with several state-of-the-art methods. The results suggest that CPL performs better than the existing methods. An analysis of the functional homogeneity based on a gene ontology analysis shows that the detected complexes of CPL are highly biologically relevant.
Kaake, Robyn M; Wang, Xiaorong; Huang, Lan
Protein-protein interactions are important for nearly all biological processes, and it is known that aberrant protein-protein interactions can lead to human disease and cancer. Recent evidence has suggested that protein interaction interfaces describe a new class of attractive targets for drug development. Full characterization of protein interaction networks of protein complexes and their dynamics in response to various cellular cues will provide essential information for us to understand ho...
Roč. 2, č. 23 (2006), s. 613-618. ISSN 0044-2968. [European Powder Diffraction Conference /9./. Prague, 02.09.2004-05.09.2004] R&D Projects: GA ČR(CZ) GA204/02/0843 Institutional research plan: CEZ:AV0Z40500505 Keywords : poly(ethylene glycol) * PEO * protein-polymer interaction Subject RIV: CD - Macromolecular Chemistry Impact factor: 1.897, year: 2006
Full Text Available YJR091C JSN1 Member of the Puf family of RNA-binding proteins, interacts with mRNAs encoding mem ... th this bait as prey (0) YKL076C PSY1 Dubious open reading ... frame, unlikely to encode a protein; not conserved ... Prey gene name PSY1 Prey description Dubious open reading ... frame, unlikely to encode a protein; not conserved ...
Full Text Available This mini review highlights several interesting aspects of glycan-mediated interactions that are common between cells, bacteria, and viruses. Glycans are ubiquitously found on all living cells, and in the extracellular milieu of multicellular organisms. They are known to mediate initial binding and recognition events of both immune cells and pathogens with their target cells or tissues. The host target tissues are hidden under a layer of secreted glycosylated decoy targets. In addition, pathogens can utilize and display host glycans to prevent identification as foreign by the host’s immune system (molecular mimicry. Both the host and pathogens continually evolve. The host evolves to prevent infection and the pathogens evolve to evade host defenses. Many pathogens express both glycan-binding proteins and glycosidases. Interestingly, these proteins are often located at the tip of elongated protrusions in bacteria, or in the leading edge of the cell. Glycan-protein interactions have low affinity and, as a result, multivalent interactions are often required to achieve biologically relevant binding. These enable dynamic forms of adhesion mechanisms, reviewed here, and include rolling (cells, stick and roll (bacteria or surfacing (viruses.
Full Text Available YMR032W HOF1 Bud neck-localized, SH3 domain-containing protein required for cytokinesis; regulat ... es actomyosin ring dynamics ... and septin localization; interacts with the formin ... equired for cytokinesis; regulates actomyosin ring dynamics ... and septin localization; interacts with the formin ...
Full Text Available YBR260C RGD1 GTPase-activating protein (RhoGAP) for Rho3p and Rho4p, possibly involved in contro ... equired for cytokinesis; regulates actomyosin ring dynamics ... and septin localization; interacts with the formin ... equired for cytokinesis; regulates actomyosin ring dynamics ... and septin localization; interacts with the formin ...
Full Text Available phery, cytoplasm, bud, and bud neck; interacts with Crm1p in two-hybrid assay; YMR124W is not an essential g...fusion protein localizes to the cell periphery, cytoplasm, bud, and bud neck; interacts with Crm1p in two-hybrid assay
Full Text Available ein import machinery; interacts with both PTS1 (Pex5p) and PTS2 (Pex7p), peroxisomal matrix protein signal r... gene name PEX14 Prey description Peroxisomal membrane peroxin that is a central component of the peroxisoma...l protein import machinery; interacts with both PTS1 (Pex5p) and PTS2 (Pex7p), peroxisomal matrix protein si...ure on prey （YPD） 12 Literature shared by bait and prey 2 Literature sharing score 2 Cura...t as prey (0) YGL153W PEX14 Peroxisomal membrane peroxin that is a central component of the peroxisomal prot
Full Text Available nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates PC biosynthesi...h nucleoporins to mediate nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates...in (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 6 IST hit in the opposite bait/prey orientation - ... ...YLR347C KAP95 Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts with nucleoporins to mediate...cription Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts wit
Full Text Available nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates PC biosynthesi...h nucleoporins to mediate nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates...in (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ... ...YLR347C KAP95 Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts with nucleoporins to mediate... ORF YLR347C Bait gene name KAP95 Bait description Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts wit
Full Text Available nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates PC biosynthesi...rins to mediate nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates PC biosynthes... gene name KAP95 Bait description Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts with nucleopo...h 2 intervening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ... ...YLR347C KAP95 Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts with nucleoporins to mediate
Bateman Alex; Schuster-Böckler Benjamin
Abstract Background Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases. Results We find that known structural domain interactions can only explain a subset of 4–19% of the available...
Full Text Available Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity, to infer protein complexes in a protein-protein interaction network. The algorithm uses a novel graph theoretic measure, parametric local modularity, to identify highly connected sub-networks as candidate protein complexes. Using gold standard sets of protein complexes and protein function and localization annotations, we show our algorithm achieved an overall improvement over previous algorithms in terms of precision, recall, and biological relevance of the predicted complexes. We applied our algorithm to predict and characterize a set of 138 novel protein complexes in S. cerevisiae. Conclusions miPALM is a novel algorithm for detecting protein complexes from large protein-protein interaction networks with improved accuracy than previous methods. The software is implemented in Matlab and is freely available at http://www.medicine.uiowa.edu/Labs/tan/software.html.
Full Text Available 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.
van Helden Jacques
Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This
Xiaomin Wang; Zhengzhi Wang; Jun Ye
With the availability of more and more genome-scale protein-protein interaction (PPI) networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly use...
PENG Xin-jun; WANG Yi-fei
Protein-protein interactions play a crucial role in the cellular process such as metabolic pathways and immunological recognition. This paper presents a new domain score-based support vector machine (SVM) to infer protein interactions, which can be used not only to explore all possible domain interactions by the kernel method, but also to reflect the evolutionary conservation of domains in proteins by using the domain scores of proteins. The experimental result on the Saccharomyces cerevisiae dataset demonstrates that this approach can predict protein-protein interactions with higher performances compared to the existing approaches.
Ogishima, Soichi; Tanaka, Hiroshi; Nakaya, Jun
Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction netw...
Eishingdrelo, Haifeng; Cai, Jidong; Weissensee, Paul; Sharma, Praveen; Tocci, Michael J; Wright, Paul S
We have developed a novel cell-based protein-protein interaction assay method. The method relies on conversion of an inactive permuted luciferase containing a Tobacco Etch Virus protease (TEV) cleavage sequence fused onto protein (A) to an active luciferase upon interaction and cleavage by another protein (B) fused with the TEV protease. We demonstrate assay applicability for ligand-induced protein-protein interactions including G-protein coupled receptors, receptor tyrosine kinases and nucle...
Maroun, M; Aronheim, A
The Ras Recruitment System (RRS) is a method for identification and isolation of protein-protein interaction. The method is based on translocation of cytoplasmic mammalian Ras protein to the inner leaflet of the plasma membrane through protein-protein interaction. The system is studied in a temperature-sensitive yeast strain where the yeast Ras guanyl nucleotide exchange factor is inactive at 36 degrees C. Protein-protein interaction results in cell growth at the restrictive temperature. We d...
Martin, Shawn Bryan; Sale, Kenneth L.; Faulon, Jean-Loup Michel; Roe, Diana C.
The goal of this project was to examine the protein-protein docking problem, especially as it relates to homology-based structures, identify the key bottlenecks in current software tools, and evaluate and prototype new algorithms that may be developed to improve these bottlenecks. This report describes the current challenges in the protein-protein docking problem: correctly predicting the binding site for the protein-protein interaction and correctly placing the sidechains. Two different and complementary approaches are taken that can help with the protein-protein docking problem. The first approach is to predict interaction sites prior to docking, and uses bioinformatics studies of protein-protein interactions to predict theses interaction site. The second approach is to improve validation of predicted complexes after docking, and uses an improved scoring function for evaluating proposed docked poses, incorporating a solvation term. This scoring function demonstrates significant improvement over current state-of-the art functions. Initial studies on both these approaches are promising, and argue for full development of these algorithms.
Ouimet, Claire M; Shao, Hao; Rauch, Jennifer N; Dawod, Mohamed; Nordhues, Bryce; Dickey, Chad A; Gestwicki, Jason E; Kennedy, Robert T
Capillary electrophoresis (CE) has been identified as a useful platform for detecting, quantifying, and screening for modulators of protein-protein interactions (PPIs). In this method, one protein binding partner is labeled with a fluorophore, the protein binding partners are mixed, and then, the complex is separated from free protein to allow direct determination of bound to free ratios. Although it possesses many advantages for PPI studies, the method is limited by the need to have separation conditions that both prevent protein adsorption to capillary and maintain protein interactions during the separation. In this work, we use protein cross-linking capillary electrophoresis (PXCE) to overcome this limitation. In PXCE, the proteins are cross-linked under binding conditions and then separated. This approach eliminates the need to maintain noncovalent interactions during electrophoresis and facilitates method development. We report PXCE methods for an antibody-antigen interaction and heterodimer and homodimer heat shock protein complexes. Complexes are cross-linked by short treatments with formaldehyde after reaching binding equilibrium. Cross-linked complexes are separated by electrophoretic mobility using free solution CE or by size using sieving electrophoresis of SDS complexes. The method gives good quantitative results; e.g., a lysozyme-antibody interaction was found to have Kd = 24 ± 3 nM by PXCE and Kd = 17 ± 2 nM using isothermal calorimetry (ITC). Heat shock protein 70 (Hsp70) in complex with bcl2 associated athanogene 3 (Bag3) was found to have Kd = 25 ± 5 nM by PXCE which agrees with Kd values reported without cross-linking. Hsp70-Bag3 binding site mutants and small molecule inhibitors of Hsp70-Bag3 were characterized by PXCE with good agreement to inhibitory constants and IC50 values obtained by a bead-based flow cytometry protein interaction assay (FCPIA). PXCE allows rapid method development for quantitative analysis of PPIs. PMID:27434096
Full Text Available YBR108W AIM3 Protein interacting with Rvs167p; null mutant is viable and displays e...0) YDR388W RVS167 Actin-associated protein, interacts with Rvs161p to regulate actin cytoskeleton, endocytosis, and via...8 - Show YBR108W Bait ORF YBR108W Bait gene name AIM3 Bait description Protein interacting with Rvs167p; null mutant is viable and...Rvs161p to regulate actin cytoskeleton, endocytosis, and viability following star... on prey （YPD） 34 Literature shared by bait and prey 4 Literature sharing score 11 CuraGen （0 or 1） 0 S. Fields （0 or 1） 0 Associa
SUN Jingchun; XU Jinlin; LI Yixue; SHI Tieliu
Protein-protein interactions play key roles in cells. Lots of experimental approaches and in silico methods have been developed to identify and predict large-scale protein-protein interactions. However, compared with the traditionally experimental results, the high-throughput protein-protein interaction data often contain the false positives in high probability. In order to fully utilize the large-scale data, it is necessary to develop bioinformatic methods for systematically evaluating those data in order to further improve the data reliability and mine biological information. This review summarizes the methodologies of analysis and application of high-throughput protein-protein interaction data, including the evaluation methods, the relationship between protein-protein interaction data and other protein biological information, and their applications in biological study. In addition, this paper also suggests some interesting topics on mining high-throughput protein-protein interaction data.
Pusey, Marc L.; Smith, Lori; Forsythe, Elizabeth
We are investigating protein-protein interactions in under- and over-saturated crystallization solution conditions using fluorescence methods. The use of fluorescence requires fluorescent derivatives where the probe does not markedly affect the crystal packing. A number of chicken egg white lysozyme (CEWL) derivatives have been prepared, with the probes covalently attached to one of two different sites on the protein molecule; the side chain carboxyl of ASP 101, within the active site cleft, and the N-terminal amine. The ASP 101 derivatives crystallize while the N-terminal amine derivatives do not. However, the N-terminal amine is part of the contact region between adjacent 43 helix chains, and blocking this site does would not interfere with formation of these structures in solution. Preliminary FRET data have been obtained at pH 4.6, 0.1M NaAc buffer, at 5 and 7% NaCl, 4 C, using the N-terminal bound pyrene acetic acid (PAA, Ex 340 nm, Em 376 nm) and ASP 101 bound Lucifer Yellow (LY, Ex 425 nm, Em 525 nm) probe combination. The corresponding Csat values are 0.471 and 0.362 mg/ml (approximately 3.3 and approximately 2.5 x 10 (exp 5) M respectively), and all experiments were carried out at approximately Csat or lower total protein concentration. The data at both salt concentrations show a consistent trend of decreasing fluorescence yield of the donor species (PAA) with increasing total protein concentration. This decrease is apparently more pronounced at 7% NaCl, consistent with the expected increased intermolecular interactions at higher salt concentrations (reflected in the lower solubility). The estimated average distance between protein molecules at 5 x 10 (exp 6) M is approximately 70 nm, well beyond the range where any FRET can be expected. The calculated RO, where 50% of the donor energy is transferred to the acceptor, for the PAA-CEWL * LY-CEWL system is 3.28 nm, based upon a PAA-CEWL quantum efficiency of 0.41.
Pereira Leal, J.B.; Levy, E.D.; van de Kamp, C.; Teichmann, S.A.
BACKGROUND: Cellular functions are accomplished by the concerted actions of functional modules. The mechanisms driving the emergence and evolution of these modules are still unclear. Here we investigate the evolutionary origins of protein complexes, modules in physical protein-protein interaction networks. RESULTS: We studied protein complexes in Saccharomyces cerevisiae, complexes of known three-dimensional structure in the Protein Data Bank and clusters of pairwise protein interactions in t...
Pereira-Leal, Jose B; Levy, Emmanuel D; Kamp, Christel; Teichmann, Sarah A.
Background Cellular functions are accomplished by the concerted actions of functional modules. The mechanisms driving the emergence and evolution of these modules are still unclear. Here we investigate the evolutionary origins of protein complexes, modules in physical protein-protein interaction networks. Results We studied protein complexes in Saccharomyces cerevisiae, complexes of known three-dimensional structure in the Protein Data Bank and clusters of pairwise protein interactions in the...
Full Text Available YDL044C MTF2 Mitochondrial matrix protein that interacts with an N-terminal region of mitochondri...L044C Bait ORF YDL044C Bait gene name MTF2 Bait description Mitochondrial matrix protein that...ure on prey （YPD） 5 Literature shared by bait and prey 0 Literature sharing score 0 CuraGen （0 or 1） 0 S...al RNA polymerase (Rpo41p) and couples RNA processing and translation to transcription Rows wi... interacts with an N-terminal region of mitochondrial RNA polymerase (Rpo41p) and couples RNA processing and translat
Full Text Available YDL139C SCM3 Nonhistone component of centromeric chromatin that binds stoichiometri... YDL139C Bait gene name SCM3 Bait description Nonhistone component of centromeric chromatin that binds stoichiometri...e peroxisomal protein import machinery; interacts with both PTS1 (Pex5p) and PTS2 (Pex7p), peroxisomal matri...153W Prey gene name PEX14 Prey description Peroxisomal membrane peroxin that is a central component of the p...eroxisomal protein import machinery; interacts with both PTS1 (Pex5p) and PTS2 (Pex7p), peroxisomal matrix p
Full Text Available Abstract Background Elucidating protein-protein interactions (PPIs is essential to constructing protein interaction networks and facilitating our understanding of the general principles of biological systems. Previous studies have revealed that interacting protein pairs can be predicted by their primary structure. Most of these approaches have achieved satisfactory performance on datasets comprising equal number of interacting and non-interacting protein pairs. However, this ratio is highly unbalanced in nature, and these techniques have not been comprehensively evaluated with respect to the effect of the large number of non-interacting pairs in realistic datasets. Moreover, since highly unbalanced distributions usually lead to large datasets, more efficient predictors are desired when handling such challenging tasks. Results This study presents a method for PPI prediction based only on sequence information, which contributes in three aspects. First, we propose a probability-based mechanism for transforming protein sequences into feature vectors. Second, the proposed predictor is designed with an efficient classification algorithm, where the efficiency is essential for handling highly unbalanced datasets. Third, the proposed PPI predictor is assessed with several unbalanced datasets with different positive-to-negative ratios (from 1:1 to 1:15. This analysis provides solid evidence that the degree of dataset imbalance is important to PPI predictors. Conclusions Dealing with data imbalance is a key issue in PPI prediction since there are far fewer interacting protein pairs than non-interacting ones. This article provides a comprehensive study on this issue and develops a practical tool that achieves both good prediction performance and efficiency using only protein sequence information.
Cedano Juan; Querol Enrique; Bonàs Sílvia; Gómez Antonio; Delicado Pedro; Amela Isaac
Abstract Background Is it possible to identify what the best solution of a docking program is? The usual answer to this question is the highest score solution, but interactions between proteins are dynamic processes, and many times the interaction regions are wide enough to permit protein-protein interactions with different orientations and/or interaction energies. In some cases, as in a multimeric protein complex, several interaction regions are possible among the monomers. These dynamic pro...
G Jack Peterson; Steve Pressé; Peterson, Kristin S.; Dill, Ken A.
We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the t...
Full Text Available Abstract Background Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases. Results We find that known structural domain interactions can only explain a subset of 4–19% of the available protein interactions, nevertheless this fraction is still significantly bigger than expected by chance. There is a correlation between the frequency of a domain interaction and the connectivity of the proteins it occurs in. Furthermore, a large proportion of protein interactions can be attributed to a small number of domain interactions. We conclude that many, but not all, domain interactions constitute reusable modules of molecular recognition. A substantial proportion of domain interactions are conserved between E. coli, S. cerevisiae and H. sapiens. These domains are related to essential cellular functions, suggesting that many domain interactions were already present in the last universal common ancestor. Conclusion Our results support the concept of domain interactions as reusable, conserved building blocks of protein interactions, but also highlight the limitations currently imposed by the small number of available protein structures.
Vincent Vagenende; Han, Alvin X.; Han B Pek; Bernard L W Loo
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 th...
Full Text Available YNL078W NIS1 Protein localized in the bud neck at G2/M phase; physically interacts with septins; ... possibly involved in a mitotic signaling network ... Rows with this bait as bait (2) Rows with this bai ... septins; possibly involved in a mitotic signaling network ... Rows with this bait as bait Rows with this bait as ...
Full Text Available YIL007C NAS2 Proteasome-interacting protein involved in the assembly of the base su... - - - - - 0 0 3 4 Show YIL007C Bait ORF YIL007C Bait gene name NAS2 Bait description Proteasome-interacti
Full Text Available YNL078W NIS1 Protein localized in the bud neck at G2/M phase; physically interacts with septins; ... Clb2p; required for the regulation of microtubule dynamics ... during mitosis; controls bud morphogenesis; involv ... Clb2p; required for the regulation of microtubule dynamics ... during mitosis; controls bud morphogenesis; involv ...
The second messenger cyclic adenosine monophosphate (cAMP) is ubiquitous and directs a plethora of functions in all cells. Although theoretically freely diffusible through the cell from the site of its synthesis it is not evenly distributed. It rather is shaped into gradients and these gradients are established by phospodiesterases (PDEs), the only enzymes that hydrolyse cAMP and thereby terminate cAMP signalling upstream of cAMP's effector systems. Miles D. Houslay has devoted most of his scientific life highly successfully to a particular family of PDEs, the PDE4 family. The family is encoded by four genes and gives rise to around 20 enzymes, all with different functions. M. Houslay has discovered many of these functions and realised early on that PDE4 family enzymes are attractive drug targets in a variety of human diseases, but not their catalytic activity as that is encoded in conserved domains in all family members. He postulated that targeting the intracellular location would provide the specificity that modern innovative drugs require to improve disease conditions with fewer side effects than conventional drugs. Due to the wealth of M. Houslay's work, this article can only summarize some of his discoveries and, therefore, focuses on protein-protein interactions of PDE4. The aim is to discuss functions of selected protein-protein interactions and peptide spot technology, which M. Houslay introduced into the PDE4 field for identifying interacting domains. The therapeutic potential of PDE4 interactions will also be discussed. PMID:26498857
Full Text Available YJR091C JSN1 Member of the Puf family of RNA-binding proteins, interacts with mRNAs encoding mem ... x to mitochondria; overexpression causes increased sensitivity ... to benomyl Rows with this bait as bait (22) Rows w ... x to mitochondria; overexpression causes increased sensitivity ... to benomyl Rows with this bait as bait Rows with t ...
Full Text Available YJR091C JSN1 Member of the Puf family of RNA-binding proteins, interacts with mRNAs encoding mem ... x to mitochondria; overexpression causes increased sensitivity ... to benomyl Rows with this bait as bait (22) Rows w ... x to mitochondria; overexpression causes increased sensitivity ... to benomyl Rows with this bait as bait Rows with t ...
Full Text Available YJR091C JSN1 Member of the Puf family of RNA-binding proteins, interacts with mRNAs encoding mem ... x to mitochondria; overexpression causes increased sensitivity ... to benomyl Rows with this bait as bait (22) Rows w ... x to mitochondria; overexpression causes increased sensitivity ... to benomyl Rows with this bait as bait Rows with t ...
Full Text Available YPR028W YOP1 Membrane protein that interacts with Yip1p to mediate membrane traffic; overexpress ... ion results in cell death ... and accumulation of internal cell membranes; regul ... e membrane traffic; overexpression results in cell death ... and accumulation of internal cell membranes; regul ...
Full Text Available YDL089W NUR1 Protein of unknown function; interacts with Csm1p, Lrs4p; required for rDNA repeat ... e membrane traffic; overexpression results in cell death ... and accumulation of internal cell membranes; regul ... e membrane traffic; overexpression results in cell death ... and accumulation of internal cell membranes; regul ...
Full Text Available Abstract Background Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, C.Elegans and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the
Dyson, H. Jane
Interactions between proteins and nucleic acids typify the role of disordered segments, linkers, tails and other entities in the function of complexes that must form with high affinity and specificity but which must be capable of dissociating when no longer needed. While much of the emphasis in the literature has been on the interactions of disordered proteins with other proteins, disorder is also frequently observed in nucleic acids (particularly RNA) and in the proteins that interact with t...
Full Text Available Abstract Background 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. Results 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. Conclusion 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
La, David; Kihara, Daisuke
Protein-protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein-protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein-protein interaction site predicti...
Li, Ye; Zhang, Xianren; Cao, Dapeng
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 mol...
Full Text Available 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.
We present an approximate method for calculating the electrostatic free energy of concentrated protein solutions. Our method uses a cell model and accounts for both the coulomb energy and the entropic cost of Donnan salt partitioning. The former term is calculated by linearizing the Poisson-Boltzmann equation around a nonzero average potential, while the second term is calculated using a jellium approximation that is empirically modified to reproduce the dilute solution limit. When combined with a short-ranged binding interaction, calculated using the mean spherical approximation, our model reproduces osmotic pressure measurements of bovine serum albumin solutions. We also use our free energy to calculate the salt-dependent shift in the critical temperature of lysozyme solutions and show why the predicted salt partitioning between the dilute and dense phases has proven experimentally elusive.
Li, Ye; Zhang, Xianren; Cao, Dapeng
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
Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.
GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interac-tion data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automati-cally selects the most appropriate functional classes as specific as possible during the learning proc-ess, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to “biology process” by three measures particularly designed for functional classes organ-ized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.
GAO Lei; LI Xia; GUO Zheng; ZHU MingZhu; LI YanHui; RAO ShaoQi
GESTs (gene expression similarity and taxonomy similarity), a gene functional prediction approach previously proposed by us, is based on gene expression similarity and concept similarity of functional classes defined in Gene Ontology (GO). In this paper, we extend this method to protein-protein interaction data by introducing several methods to filter the neighbors in protein interaction networks for a protein of unknown function(s). Unlike other conventional methods, the proposed approach automatically selects the most appropriate functional classes as specific as possible during the learning process, and calls on genes annotated to nearby classes to support the predictions to some small-sized specific classes in GO. Based on the yeast protein-protein interaction information from MIPS and a dataset of gene expression profiles, we assess the performances of our approach for predicting protein functions to "biology process" by three measures particularly designed for functional classes organized in GO. Results show that our method is powerful for widely predicting gene functions with very specific functional terms. Based on the GO database published in December 2004, we predict some proteins whose functions were unknown at that time, and some of the predictions have been confirmed by the new SGD annotation data published in April, 2006.
Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.
Farid Amir-Ghiasvand; Abbas Nowzari-Dalini; Vida Momenzadeh
To date, few tools for aligning protein-protein interaction networks have been suggested. These tools typically find conserved interaction patterns using various local or global alignment algorithms. However, the improvement of the speed, scalability, simplification, and accuracy of network alignment tools is still the target of new researches. In this paper, we introduce Pin-Align, a new tool for local alignment of protein-protein interaction networks. Pin-Align accuracy is tested on protein...
Full Text Available L064C Bait gene name TEM1 Bait description GTP-binding protein of the ras superfamily involved in termin...atase, key regulatory enzyme in the gluconeogenesis pathway, required for glucose metabolism; undergoes either...YML064C TEM1 GTP-binding protein of the ras superfamily involved in termination of ...sis pathway, required for glucose metabolism; undergoes either proteasome-mediate...d or autophagy-mediated degradation depending on growth conditions; interacts with Vid30p Rows with this pre
Full Text Available YDR256C CTA1 Catalase A, breaks down hydrogen peroxide in the peroxisomal matrix fo...mal protein import machinery; interacts with both PTS1 (Pex5p) and PTS2 (Pex7p), peroxisomal matri... Bait gene name CTA1 Bait description Catalase A, breaks down hydrogen peroxide in the peroxisomal matri...y ORF YGL153W Prey gene name PEX14 Prey description Peroxisomal membrane peroxin that is a centr...d PTS2 (Pex7p), peroxisomal matrix protein signal recognition factors and membrane receptor Pex13p Rows with
Saha, Indrajit; Zubek, Julian; Klingström, Tomas; Forsberg, Simon; Wikander, Johan; Kierczak, Marcin; Maulik, Ujjwal; Plewczynski, Dariusz
Protein-protein interactions are important for the majority of biological processes. A significant number of computational methods have been developed to predict protein-protein interactions using protein sequence, structural and genomic data. Vast experimental data is publicly available on the Internet, but it is scattered across numerous databases. This fact motivated us to create and evaluate new high-throughput datasets of interacting proteins. We extracted interaction data from DIP, MINT, BioGRID and IntAct databases. Then we constructed descriptive features for machine learning purposes based on data from Gene Ontology and DOMINE. Thereafter, four well-established machine learning methods: Support Vector Machine, Random Forest, Decision Tree and Naïve Bayes, were used on these datasets to build an Ensemble Learning method based on majority voting. In cross-validation experiment, sensitivity exceeded 80% and classification/prediction accuracy reached 90% for the Ensemble Learning method. We extended the experiment to a bigger and more realistic dataset maintaining sensitivity over 70%. These results confirmed that our datasets are suitable for performing PPI prediction and Ensemble Learning method is well suited for this task. Both the processed PPI datasets and the software are available at . PMID:24469380
Full Text Available ps in mRNA function and decay, interacts with both the decapping and deadenylase complexes, ma...rvening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ... ...ps in mRNA function and decay, interacts with both the decapping and deadenylase complexes, m...cription Component of glucose deprivation induced stress granules, involved in P-body-...y have a role in mRNA export and translation Rows with this bait as bait (2) Rows with this bait as prey (0) YGR178C PBP1 Compo
Qian, Wenfeng; He, Xionglei; Chan, Edwin; Xu, Huailiang; Zhang, Jianzhi
Despite our extensive knowledge about the rate of protein sequence evolution for thousands of genes in hundreds of species, the corresponding rate of protein function evolution is virtually unknown, especially at the genomic scale. This lack of knowledge is primarily because of the huge diversity in protein function and the consequent difficulty in gauging and comparing rates of protein function evolution. Nevertheless, most proteins function through interacting with other proteins, and prote...
Lin, Tien-ho; Bar-Joseph, Ziv; Murphy, Robert F.
Proper subcellular localization is critical for proteins to perform their roles in cellular functions. Proteins are transported by different cellular sorting pathways, some of which take a protein through several intermediate locations until reaching its final destination. The pathway a protein is transported through is determined by carrier proteins that bind to specific sequence motifs. In this article, we present a new method that integrates protein interaction and sequence motif data to m...
Witherow, D. Scott; Carson, Sue
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…
Somireddy Venkata, Bharat Kumar Reddy
Protein-protein interactions play an important role in all cellular processes such as signal transduction, electron transfer, gene regulation, transcription, and translation. Understanding these protein-protein interactions at the molecular level, is an important aim in structural biology. The prote
Full Text Available 0 or 1,YPD） 0 Co-induced by （YPD） - Co-repressed by （YPD） - Not affected by（YPD） - Interologs - Expression si...E (GRAM Like Ubiquitin binding in EAP45) domain which is involved in interactions with ESCRT-I and ubiquitin-dependent sorting of pr...n binding in EAP45) domain which is involved in interactions with ESCRT-I and ubiquitin-dependent sorting of pr...milarity (BRITE) - Alternative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 9 IST hit in the opposite bait/prey orientation - ... ... shared by bait and prey 2 Literature sharing score 5 CuraGen （0 or 1） 0 S. Fields （0 or 1） 0 Association
Simonson Thomas; Noirel Josselin
Abstract Background Protein-protein interactions are central to cellular organization, and must have appeared at an early stage of evolution. To understand better their role, we consider a simple model of protein evolution and determine the effect of an explicit selection for Protein-protein interactions. Results In the model, viable sequences all have the same fitness, following the neutral evolution theory. A very simple, two-dimensional lattice representation of the protein structures is u...
Mailand, Niels; Gibbs-Seymour, Ian; Bekker-Jensen, Simon
Proliferating cell nuclear antigen (PCNA) has a central role in promoting faithful DNA replication, providing a molecular platform that facilitates the myriad protein-protein and protein-DNA interactions that occur at the replication fork. Numerous PCNA-associated proteins compete for binding to ...
Silva-Filho Marcio C
Full Text Available Abstract Background Protein-protein interactions (PPIs constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C3 which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS (AT5G26710 we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630, a disease resistance protein (AT3G50950 and a zinc finger protein (AT5G24930, which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.
The investigation of promoter activity and DNA-protein interactions is very important for understanding many crucial cellular processes, including transcription, recombination and replication. Promoter activity and DNA-protein interactions can be studied in the lab (in vitro or in vivo) or using computational methods (in silico). Computational approaches for analysing promoters and DNA-protein interactions have become more powerful as more and more complete genome sequences, 3D...
Full Text Available x5p) and PTS2 (Pex7p), peroxisomal matrix protein signal recognition factors and membrane receptor Pex13p Ro...chinery; interacts with both PTS1 (Pex5p) and PTS2 (Pex7p), peroxisomal matrix protein signal recognition fa...ure on prey （YPD） 12 Literature shared by bait and prey 3 Literature sharing score 5 CuraGen （0 or 1） 0 S. ... as bait (1) Rows with this bait as prey (0) YGL153W PEX14 Peroxisomal membrane peroxin that is a central co...ption Peroxisomal membrane peroxin that is a central component of the peroxisomal protein import ma
Jie Song; Jiaxing Cheng; Xiuquan Du
Identification of protein-protein interface residues is crucial for structural biology. This paper proposes a covering algorithm for predicting protein-protein interface residues with features including protein sequence profile and residue accessible area. This method adequately utilizes the characters of a covering algorithm which have simple, lower complexity and high accuracy for high dimension data. The covering algorithm can achieve a comparable performance (69.62%, Complete dataset; 60....
Giepmans, Ben N G
Gap junctions form channels between adjacent cells. The core proteins of these channels are the connexins. Regulation of gap junction communication (GJC) can be modulated by connexin-associating proteins, such as regulatory protein phosphatases and protein kinases, of which c-Src is the best-studied
Roslan, Rosfuzah; Othman, Razib M; Shah, Zuraini A; Kasim, Shahreen; Asmuni, Hishammuddin; Taliba, Jumail; Hassan, Rohayanti; Zakaria, Zalmiyah
Protein-protein interactions (PPIs) play a significant role in many crucial cellular operations such as metabolism, signaling and regulations. The computational methods for predicting PPIs have shown tremendous growth in recent years, but problem such as huge false positive rates has contributed to the lack of solid PPI information. We aimed at enhancing the overlap between computational predictions and experimental results in an effort to partially remove PPIs falsely predicted. The use of protein function predictor named PFP() that are based on shared interacting domain patterns is introduced in this study with the purpose of aiding the Gene Ontology Annotations (GOA). We used GOA and PFP() as agents in a filtering process to reduce false positive pairs in the computationally predicted PPI datasets. The functions predicted by PFP() were extracted from cross-species PPI data in order to assign novel functional annotations for the uncharacterized proteins and also as additional functions for those that are already characterized by the GO (Gene Ontology). The implementation of PFP() managed to increase the chances of finding matching function annotation for the first rule in the filtration process as much as 20%. To assess the capability of the proposed framework in filtering false PPIs, we applied it on the available S. cerevisiae PPIs and measured the performance in two aspects, the improvement made indicated as Signal-to-Noise Ratio (SNR) and the strength of improvement, respectively. The proposed filtering framework significantly achieved better performance than without it in both metrics. PMID:20417930
Thattai, Mukund; Burak, Yoram; Shraiman , Boris I.
Polyketides, a diverse group of heteropolymers with antibiotic and antitumor properties, are assembled in bacteria by multiprotein chains of modular polyketide synthase (PKS) proteins. Specific protein–protein interactions determine the order of proteins within a multiprotein chain, and thereby the order in which chemically distinct monomers are added to the growing polyketide product. Here we investigate the evolutionary and molecular origins of protein interaction specificity. We focus on t...
Herce, Henry D.; Deng, Wen; Helma, Jonas; Leonhardt, Heinrich; Cardoso, M. Cristina
Protein–protein interactions are the basis of all processes in living cells, but most studies of these interactions rely on biochemical in vitro assays. Here we present a simple and versatile fluorescent-three-hybrid (F3H) strategy to visualize and target protein–protein interactions. A high-affinity nanobody anchors a GFP-fusion protein of interest at a defined cellular structure and the enrichment of red-labelled interacting proteins is measured at these sites. With this approach, we visual...
Full Text Available bly through regulating 1,6-beta-glucan levels in the wall; physically interacts with Cdc31p (centrin), which is a compo...bly through regulating 1,6-beta-glucan levels in the wall; physically interacts with Cdc31p (centrin), which is a comp...rvening proteins (YPD) 0 IST hit 12 IST hit in the opposite bait/prey orientation - ... ...gulation of Ace2p activity and cellular morphogenesis, interacts with Kic1p and Sog2p, localizes to sites of po...89W Prey gene name HYM1 Prey description Component of the RAM signaling network that is involved in regulation of Ace2p activit
Kyu Kwang Kim; Han Bok Kim
AIM: To understand the complex reaction of gastric inflammation induced by Helicobacter pylori (H pylori ) in a systematic manner using a protein interaction network. METHODS: The expression of genes significantly changed on microarray during H pylori infection was scanned from the web literary database and translated into proteins. A network of protein interactions was constructed by searching the primary interactions of selected proteins. The constructed network was mathematically analyzed and its biological function was examined. In addition, the nodes on the network were checked to determine if they had any further functional importance or relation to other proteins by extending them.RESULTS: The scale-free network showing the relationship between inflammation and carcinogenesis was constructed. Mathematical analysis showed hub and bottleneck proteins, and these proteins were mostly related to immune response. The network contained pathways and proteins related to H pylori infection, such as the JAK-STAT pathway triggered by interleukins. Activation of nuclear factor (NF)-kB, TLR4, and other proteins known to function as core proteins of immune response were also found.These immune-related proteins interacted on the network with pathways and proteins related to the cell cycle, cell maintenance and proliferation, and transcription regulators such as BRCA1, FOS, REL, and zinc finger proteins. The extension of nodes showed interactions of the immune proteins with cancerrelated proteins. One extended network, the core network, a summarized form of the extended network, and cell pathway model were constructed. CONCLUSION: Immune-related proteins activated by H pylori infection interact with proto-oncogene proteins. The hub and bottleneck proteins are potential drug targets for gastric inflammation and cancer.
Proteasome dysfunction has been repeatedly reported in alcoholic liver disease. Ethanol metabolism endproducts affect the structure of the proteasome, and, therefore, change the proteasome interaction with its regulatory complexes 19S and PA28, as well as its interacting proteins. Chronic ethanol feeding alters the ubiquitin-proteasome activity by altering the interaction between the 19S and the 20S proteasome interaction. The degradation of oxidized and damaged proteins is thus decreased and leads to accum...
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
The human cytomegalovirus (HCMV) IE86 Cdna was cloned into Pgex-2T and fusion protein GST-IE86 was expressed in E. Coli. SDS-PAGE and Western blot assay indicated that fusion protein GST-IE86 with molecular weight of 92 ku is soluble in the supernatant of cell lysate. Protein GST and fusion protein GST-IE86 were purified by affinity chromatography. The technology of co-separation and specific affinity chromatography was used to study the interactions of HCMV IE86 protein with some transcriptional regulatory proteins and transcriptional factors. The results indicated that IE86 interacts separately with transcriptional factor TFIIB and promoter DNA binding transcription trans-activating factors SP1, AP1 and AP2 to form a heterogenous protein complex. These transcriptional trans-activating factors, transcriptional factor and IE86 protein were adsorbed and retained in the affinity chromatography simultaneously. But IE86 protein could not interact with NF-Кb, suggesting that the function of IE86 protein that can interact with transcriptional factor and transcriptional trans-activating factors has no relevance to protein glycosylation. IE86 protein probably has two domains responsible for binding transcriptional trans-activating regulatory proteins and transcriptional factors respectively, thus activating the transcription of many genes. The interactions accelerated the assembly of the transcriptional initiation complexes.
Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a str...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....
Abstract Background Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based predi...
Holm, Louise Stenstrup; Thulstrup, Peter Waaben; Kasimova, Marina Robertovna;
BACKGROUND: PEGylation is a strategy used by the pharmaceutical industry to prolong systemic circulation of protein drugs, whereas formulation excipients are used for stabilization of proteins during storage. Here we investigate the role of PEGylation in protein stabilization by formulation...... excipients that preferentially interact with the protein. METHODOLOGY/PRINCIPAL FINDINGS: The model protein hen egg white lysozyme was doubly PEGylated on two lysines with 5 kDa linear PEGs (mPEG-succinimidyl valerate, MW 5000) and studied in the absence and presence of preferentially excluded sucrose and...... excipients. This suggests that formulation principles using preferentially interacting excipients are similar for PEGylated and non-PEGylated proteins....
Hartmann-Petersen, R; Gordon, C
The 26S proteasome is the multi-protein protease that recognizes and degrades ubiquitinylated substrates targeted for destruction by the ubiquitin pathway. In addition to the well-documented subunit organization of the 26S holoenzyme, it is clear that a number of other proteins transiently...... associate with the 26S complex. These transiently associated proteins confer a number of different roles such as substrate presentation, cleavage of the multi-ubiquitin chain from the protein substrate and turnover of misfolded proteins. Such activities are essential for the 26S proteasome to efficiently...... fulfill its intracellular function in protein degradation....
Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1). PMID:26217672
Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a...... strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....
Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.
Colantoni, Alessio; Bianchi, Valerio; Gherardini, Pier Federico; Scalia Tomba, Gianpaolo; Ausiello, Gabriele; Helmer-Citterich, Manuela; Ferrè, Fabrizio
Background Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites. In t...
Haijiang Geng; Tao Lu; Xiao Lin; Yu Liu; Fangrong Yan
Protein functions through interactions with other proteins and biomolecules and these interactions occur on the so-called interface residues of the protein sequences. Identifying interface residues makes us better understand the biological mechanism of protein interaction. Meanwhile, information about the interface residues contributes to the understanding of metabolic, signal transduction networks and indicates directions in drug designing. In recent years, researchers have focused on develo...
Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu
Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and "interologs" in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033
Full Text Available Abstract Background The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experimental and computational efforts on the creation and analysis of information derived from 3D structure. In particular, the high-throughput generation of protein-protein interaction data from a few organisms makes such an approach very important towards understanding the molecular recognition that make-up the entire protein-protein interaction network. Since the generation of sequences, and experimental protein-protein interactions increases faster than the 3D structure determination of protein complexes, there is tremendous interest in developing in silico methods that generate such structure for prediction and classification purposes. In this study we focused on classifying protein family members based on their protein-protein interaction distinctiveness. Structure-based classification of protein-protein interfaces has been described initially by Ponstingl et al. 1 and more recently by Valdar et al. 2 and Mintseris et al. 3, from complex structures that have been solved experimentally. However, little has been done on protein classification based on the prediction of protein-protein complexes obtained from homology modeling and docking simulation. Results We have developed an in silico classification system entitled HODOCO (Homology modeling, Docking and Classification Oracle, in which protein Residue Potential Interaction Profiles (RPIPS are used to summarize protein-protein interaction characteristics. This system applied to a dataset of 64 proteins of the death domain superfamily was used to classify each member into its proper subfamily. Two classification methods were attempted, heuristic and support vector machine learning. Both methods were tested with a 5-fold cross-validation. The heuristic approach yielded a 61% average accuracy, while the machine
Morrell-Falvey, J. L.; Qi, H.; Doktycz, M. J.; Venkatraman, S.
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 ...
Full Text Available Abstract Background As protein-protein interactions connect proteins that participate in either the same or different functions, networks of interacting and functionally annotated proteins can be converted into process graphs of inter-dependent function nodes (each node corresponding to interacting proteins with the same functional annotation. However, as proteins have multiple annotations, the process graph is non-redundant, if only proteins participating directly in a given function are included in the related function node. Results Reasoning that topological features (e.g., clusters of highly inter-connected proteins might help approaching structured and non-redundant understanding of molecular function, an algorithm was developed that prioritizes inclusion of proteins into the function nodes that best overlap protein clusters. Specifically, the algorithm identifies function nodes (and their mutual relations, based on the topological analysis of a protein interaction network, which can be related to various biological domains, such as cellular components (e.g., peroxisome and cellular bud or biological processes (e.g., cell budding of the model organism S. cerevisiae. Conclusions The method we have described allows converting a protein interaction network into a non-redundant process graph of inter-dependent function nodes. The examples we have described show that the resulting graph allows researchers to formulate testable hypotheses about dependencies among functions and the underlying mechanisms.
The vast majority of the chores in the living cell involve protein–protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein–protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations
Full Text Available YNL086W - Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein l ... 2) YKL061W - Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ... description Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ...
Full Text Available YLR108C - Protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ... as prey (1) YLR108C - Protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ... me - Bait description Protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ...
Full Text Available YJR056C - Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein l ... 2) YJR056C - Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ... description Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ...
Teilum, Kaare; Olsen, Johan G.; Kragelund, Birthe B.
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein...
Chiam Tak; Cho Young-Rae
Abstract Background Recent computational techniques have facilitated analyzing genome-wide protein-protein interaction data for several model organisms. Various graph-clustering algorithms have been applied to protein interaction networks on the genomic scale for predicting the entire set of potential protein complexes. In particular, the density-based clustering algorithms which are able to generate overlapping clusters, i.e. the clusters sharing a set of nodes, are well-suited to protein co...
Plante, Geneviève; Lusignan, Marie-France; Lafleur, Michel; Manjunath, Puttaswamy
Background Mammalian semen contains a family of closely related proteins known as Binder of SPerm (BSP proteins) that are added to sperm at ejaculation. BSP proteins extract lipids from the sperm membrane thereby extensively modifying its composition. These changes can ultimately be detrimental to sperm storage. We have demonstrated that bovine BSP proteins interact with major milk proteins and proposed that this interaction could be the basis of sperm protection by milk extenders. In the pre...
Herce, Henry D; Deng, Wen; Helma, Jonas; Leonhardt, Heinrich; Cardoso, M Cristina
Protein-protein interactions are the basis of all processes in living cells, but most studies of these interactions rely on biochemical in vitro assays. Here we present a simple and versatile fluorescent-three-hybrid (F3H) strategy to visualize and target protein-protein interactions. A high-affinity nanobody anchors a GFP-fusion protein of interest at a defined cellular structure and the enrichment of red-labelled interacting proteins is measured at these sites. With this approach, we visualize the p53-HDM2 interaction in living cells and directly monitor the disruption of this interaction by Nutlin 3, a drug developed to boost p53 activity in cancer therapy. We further use this approach to develop a cell-permeable vector that releases a highly specific peptide disrupting the p53 and HDM2 interaction. The availability of multiple anchor sites and the simple optical readout of this nanobody-based capture assay enable systematic and versatile analyses of protein-protein interactions in practically any cell type and species. PMID:24154492
Full Text Available The evaluation of the biological networks is considered the essential key to understanding the complex biological systems. Meanwhile, the graph clustering algorithms are mostly used in the protein-protein interaction (PPI network analysis. The complexes introduced by the clustering algorithms include noise proteins. The error rate of the noise proteins in the PPI network researches is about 40–90%. However, only 30–40% of the existing interactions in the PPI databases depend on the specific biological function. It is essential to eliminate the noise proteins and the interactions from the complexes created via clustering methods. We have introduced new methods of weighting interactions in protein clusters and the splicing of noise interactions and proteins-based interactions on their weights. The coexpression and the sequence similarity of each pair of proteins are considered the edge weight of the proteins in the network. The results showed that the edge filtering based on the amount of coexpression acts similar to the node filtering via graph-based characteristics. Regarding the removal of the noise edges, the edge filtering has a significant advantage over the graph-based method. The edge filtering based on the amount of sequence similarity has the ability to remove the noise proteins and the noise interactions.
Busse, Ricarda A; Scacioc, Andreea; Schalk, Amanda M; Krick, Roswitha; Thumm, Michael; Kühnel, Karin
Liposome flotation assays are a convenient tool to study protein-phosphoinositide interactions. Working with liposomes resembles physiological conditions more than protein-lipid overlay assays, which makes this method less prone to detect false positive interactions. However, liposome lipid composition must be well-considered in order to prevent nonspecific binding of the protein through electrostatic interactions with negatively charged lipids like phosphatidylserine. In this protocol we use the PROPPIN Hsv2 (homologous with swollen vacuole phenotype 2) as an example to demonstrate the influence of liposome lipid composition on binding and show how phosphoinositide binding specificities of a protein can be characterized with this method. PMID:26552682
Yang, Xinping; Coulombe-Huntington, Jasmin; Kang, Shuli; Sheynkman, Gloria M; Hao, Tong; Richardson, Aaron; Sun, Song; Yang, Fan; Shen, Yun A; Murray, Ryan R; Spirohn, Kerstin; Begg, Bridget E; Duran-Frigola, Miquel; MacWilliams, Andrew; Pevzner, Samuel J; Zhong, Quan; Trigg, Shelly A; Tam, Stanley; Ghamsari, Lila; Sahni, Nidhi; Yi, Song; Rodriguez, Maria D; Balcha, Dawit; Tan, Guihong; Costanzo, Michael; Andrews, Brenda; Boone, Charles; Zhou, Xianghong J; Salehi-Ashtiani, Kourosh; Charloteaux, Benoit; Chen, Alyce A; Calderwood, Michael A; Aloy, Patrick; Roth, Frederick P; Hill, David E; Iakoucheva, Lilia M; Xia, Yu; Vidal, Marc
While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms"). PMID:26871637
Full Text Available nuclear import of NLS-containing cargo proteins via the nuclear pore complex; regulates PC biosynthesi...ins via the nuclear pore complex; regulates PC biosynthesis; GDP-to-GTP exchange factor for Gsp1p Rows with this bait as bait...ins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ... ...YLR347C KAP95 Karyopherin beta, forms a complex with Srp1p/Kap60p; interacts with nucleoporins to mediate...nent Spc42p to the inner plaque component Spc110p; required for SPB duplication Rows wit
Cotecchia, Susanna; Stanasila, Laura; Diviani, Dario
The adrenergic receptors are among the best characterized G protein-coupled receptors (GPCRs) and knowledge on this receptor family has provided several important paradigms about GPCR function and regulation. One of the most recent paradigms initially supported by studies on adrenergic receptors is that both βarrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effect...
Szilagyi, Andras; Zhang, Yang
The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been wit...
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
Mehan, Sumit; Aswal, Vinod K., E-mail: firstname.lastname@example.org [Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400 085 (India); Kohlbrecher, Joachim [Laboratory for Neutron Scattering, Paul Scherrer Institut, CH-5232 PSI Villigen (Switzerland)
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.
Li, Xiao-Li; Tan, Soon-Heng; Foo, Chuan-Sheng; Ng, See-Kiong
While recent technological advances have made available large datasets of experimentally-detected pairwise protein-protein interactions, there is still a lack of experimentally-determined protein complex data. To make up for this lack of protein complex data, we explore the mining of existing protein interaction graphs for protein complexes. This paper proposes a novel graph mining algorithm to detect the dense neighborhoods (highly connected regions) in an interaction graph which may correspond to protein complexes. Our algorithm first locates local cliques for each graph vertex (protein) and then merge the detected local cliques according to their affinity to form maximal dense regions. We present experimental results with yeast protein interaction data to demonstrate the effectiveness of our proposed method. Compared with other existing techniques, our predicted complexes can match or overlap significantly better with the known protein complexes in the MIPS benchmark database. Novel protein complexes were also predicted to help biologists in their search for new protein complexes. PMID:16901108
Rodrigues, Francisco A; Costa, Luciano da Fontoura
The relationship between network structure/dynamics and biological function constitutes a fundamental issue in systems biology. However, despite many related investigations, the correspondence between structure and biological functions is not yet fully understood. A related subject that has deserved particular attention recently concerns how essentiality is related to the structure and dynamics of protein interactions. In the current work, protein essentiality is investigated in terms of long range influences in protein-protein interaction networks by considering simulated dynamical aspects. This analysis is performed with respect to outward activations, an approach which models the propagation of interactions between proteins by considering self-avoiding random walks. The obtained results are compared to protein local connectivity. Both the connectivity and the outward activations were found to be strongly related to protein essentiality. PMID:19396375
Tzanov, Tzanko; Andreaus, Juergen; Gübitz, Georg M.; Paulo, Artur Cavaco
Enzymes are the catalysts of all reactions in living systems. These reactions are catalysed in the active sites of globular proteins. The proteins are composed by amino acids with a variety of side chains ranging from non-polar aliphatic and aromatic to acidic, basic and neutral polar. This fact allows to a globular 3D protein to create in the active site all ranges of microenvironments for catalysis. Major advances in microbial technology and genetics allow recently the broad range of ...
Vasbinder, Astrid Jolanda
Heating of milk is an essential step in the processing of various dairy products, like for example yoghurt. A major consequence of the heat treatment is the denaturation of whey proteins, which either associate with the casein micelle or form soluble whey protein aggregates. By combination of enzymatic fractionation and capillary electrophoresis we were able to quantitatively determine the distribution of denatured whey proteins after heat treatment. This thesis describes the relation between...
Nissen, Klaus B; Kedström, Linda Maria Haugaard; Wilbek, Theis S;
related MAGUK proteins contain three consecutive PDZ domains, hence we envisioned that targeting all three PDZ domains simultaneously would lead to more potent and potentially more specific interactions with the MAGUK proteins. Here we describe the design, synthesis and characterization of a series of...... trimeric ligands targeting all three PDZ domains of PSD-95 and the related MAGUK proteins, PSD-93, SAP-97 and SAP-102. Using our dimeric ligands targeting the PDZ1-2 tandem as starting point, we designed novel trimeric ligands by introducing a PDZ3-binding peptide moiety via a cysteine-derivatized NPEG...... linker. The trimeric ligands generally displayed increased affinities compared to the dimeric ligands in fluorescence polarization binding experiments and optimized trimeric ligands showed low nanomolar inhibition towards the four MAGUK proteins, thus being the most potent inhibitors described. Kinetic...
Li, Yan; Liu, Zhihai; Han, Li; Li, Chengke; Wang, Renxiao
Protein-protein interactions are observed in various biological processes. They are important for understanding the underlying molecular mechanisms and can be potential targets for developing small-molecule regulators of such processes. Previous studies suggest that certain residues on protein-protein binding interfaces are "hot spots". As an extension to this concept, we have developed a residue-based method to identify the characteristic interaction patterns (CIPs) on protein-protein binding interfaces, in which each pattern is a cluster of four contacting residues. Systematic analysis was conducted on a nonredundant set of 1,222 protein-protein binding interfaces selected out of the entire Protein Data Bank. Favored interaction patterns across different protein-protein binding interfaces were retrieved by considering both geometrical and chemical conservations. As demonstrated on two test tests, our method was able to predict hot spot residues on protein-protein binding interfaces with good recall scores and acceptable precision scores. By analyzing the function annotations and the evolutionary tree of the protein-protein complexes in our data set, we also observed that protein-protein interfaces sharing common characteristic interaction patterns are normally associated with identical or similar biological functions. PMID:23930922
Alberto de Luis
Full Text Available In recent years, the biomolecular sciences have been driven forward by overwhelming advances in new biotechnological high-throughput experimental methods and bioinformatic genome-wide computational methods. Such breakthroughs are producing huge amounts of new data that need to be carefully analysed to obtain correct and useful scientific knowledge. One of the fields where this advance has become more intense is the study of the network of Ã¢Â€Â˜proteinÃ¢Â€Â“protein interactionsÃ¢Â€Â™, i.e. the Ã¢Â€Â˜interactomeÃ¢Â€Â™. In this short review we comment on the main data and databases produced in this field in last 5 years. We also present a rationalized scheme of biological definitions that will be useful for a better understanding and interpretation of Ã¢Â€Â˜what a proteinÃ¢Â€Â“protein interaction isÃ¢Â€Â™ and Ã¢Â€Â˜which types of proteinÃ¢Â€Â“protein interactions are found in a living cellÃ¢Â€Â™. Finally, we comment on some assignments of interactome data to defined types of protein interaction and we present a new bioinformatic tool called APIN (Agile Protein Interaction Network browser, which is in development and will be applied to browsing protein interaction databases.
Kenry, Affa Affb Affc; Loh, Kian Ping; Lim, Chwee Teck
We investigate the molecular interactions between graphene oxide (GO) and human blood plasma proteins. To gain an insight into the bio-physico-chemical activity of GO in biological and biomedical applications, we performed a series of biophysical assays to quantify the molecular interactions between GO with different lateral size distributions and the three essential human blood plasma proteins. We elucidate the various aspects of the GO-protein interactions, particularly, the adsorption, binding kinetics and equilibrium, and conformational stability, through determination of quantitative parameters, such as GO-protein association constants, binding cooperativity, and the binding-driven protein structural changes. We demonstrate that the molecular interactions between GO and plasma proteins are significantly dependent on the lateral size distribution and mean lateral sizes of the GO nanosheets and their subtle variations may markedly influence the GO-protein interactions. Consequently, we propose the existence of size-dependent molecular interactions between GO nanosheets and plasma proteins, and importantly, the presence of specific critical mean lateral sizes of GO nanosheets in achieving very high association and fluorescence quenching efficiency of the plasma proteins. We anticipate that this work will provide a basis for the design of graphene-based and other related nanomaterials for a plethora of biological and biomedical applications.
Historically, the central dogma of structural biology is the Anfinsen hypothesis: the linear primary sequence of amino acids of a protein codes for specific secondary structural elements which in turn lead to tertiary structural elements through protein folding and complex higher order systems throu...
Turner, Brian; Razick, Sabry; Turinsky, Andrei L.; Vlasblom, James; Crowdy, Edgard K.; Cho, Emerson; Morrison, Kyle; Donaldson, Ian M; Wodak, Shoshana J.
We present iRefWeb, a web interface to protein interaction data consolidated from 10 public databases: BIND, BioGRID, CORUM, DIP, IntAct, HPRD, MINT, MPact, MPPI and OPHID. iRefWeb enables users to examine aggregated interactions for a protein of interest, and presents various statistical summaries of the data across databases, such as the number of organism-specific interactions, proteins and cited publications. Through links to source databases and supporting evidence, researchers may gauge...
Estruch, Sara B.; Fisher, Simon E.
Assays based on Bioluminescence Resonance Energy Transfer (BRET) provide a sensitive and reliable means to monitor protein-protein interactions in live cells. BRET is the non-radiative transfer of energy from a 'donor' luciferase enzyme to an 'acceptor' fluorescent protein. In the most common configuration of this assay, the donor is Renilla reniformis luciferase and the acceptor is Yellow Fluorescent Protein (YFP). Because the efficiency of energy transfer is strongly distance-dependent, observation of the BRET phenomenon requires that the donor and acceptor be in close proximity. To test for an interaction between two proteins of interest in cultured mammalian cells, one protein is expressed as a fusion with luciferase and the second as a fusion with YFP. An interaction between the two proteins of interest may bring the donor and acceptor sufficiently close for energy transfer to occur. Compared to other techniques for investigating protein-protein interactions, the BRET assay is sensitive, requires little hands-on time and few reagents, and is able to detect interactions which are weak, transient, or dependent on the biochemical environment found within a live cell. It is therefore an ideal approach for confirming putative interactions suggested by yeast two-hybrid or mass spectrometry proteomics studies, and in addition it is well-suited for mapping interacting regions, assessing the effect of post-translational modifications on protein-protein interactions, and evaluating the impact of mutations identified in patient DNA. PMID:24893771
Vasbinder, Astrid Jolanda
Heating of milk is an essential step in the processing of various dairy products, like for example yoghurt. A major consequence of the heat treatment is the denaturation of whey proteins, which either associate with the casein micelle or form soluble whey protein aggregates. By combination of enzyma
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.
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
Kurt A. Jellinger
Full Text Available Protein aggregation is a common characteristic of many neurodegenerative disorders, and the interaction between pathological/toxic proteins to cause neurodegeneration is a hot topic of current neuroscience research. Despite clinical, genetic, and experimental differences, evidence increasingly indicates considerable overlap between synucleinopathies and tauopathies or other protein-misfolding diseases. Inclusions, characteristics of these disorders, also occurring in other neurodegenerative diseases, suggest interactions of pathological proteins engaging common downstream pathways. Novel findings that have shifted our understanding in the role of pathologic proteins in the pathogenesis of Parkinson and Alzheimer diseases have confirmed correlations/overlaps between these and other neurodegenerative disorders. The synergistic effects of α-synuclein, hyperphosphorylated tau, amyloid-β, and other pathologic proteins, and the underlying molecular pathogenic mechanisms, including induction and spread of protein aggregates, are critically reviewed, suggesting a dualism or triad of neurodegeneration in protein-misfolding disorders, although the etiology of most of these processes is still mysterious.
Cheryl D Wolting
Full Text Available PDZ (Post-synaptic density, 95 kDa, Discs large, Zona Occludens-1 domains are protein interaction domains that bind to the carboxy-terminal amino acids of binding partners, heterodimerize with other PDZ domains, and also bind phosphoinositides. PDZ domain containing proteins are frequently involved in the assembly of multi-protein complexes and clustering of transmembrane proteins. LNX1 (Ligand of Numb, protein X 1 is a RING (Really Interesting New Gene domain-containing E3 ubiquitin ligase that also includes four PDZ domains suggesting it functions as a scaffold for a multi-protein complex. Here we use a human protein array to identify direct LNX1 PDZ domain binding partners. Screening of 8,000 human proteins with isolated PDZ domains identified 53 potential LNX1 binding partners. We combined this set with LNX1 interacting proteins identified by other methods to assemble a list of 220 LNX1 interacting proteins. Bioinformatic analysis of this protein list was used to select interactions of interest for future studies. Using this approach we identify and confirm six novel LNX1 binding partners: KCNA4, PAK6, PLEKHG5, PKC-alpha1, TYK2 and PBK, and suggest that LNX1 functions as a signalling scaffold.
The article presents a survey on the significance of protein-material interactions, the mechanisms which control them and the techniques used for their study. Protein-surface interactions play a key role in regenerative medicine, drug delivery, biosensor technology and chromatography, while it is related to various undesired effects such as biofouling and bio-prosthetic malfunction. Although the effects of protein-surface interaction concern the micro-scale, being sometimes obvious even with bare eyes, they derive from biophysical events at the nano-scale. The sequential steps for protein adsorption involve events at the single biomolecule level and the forces driving or inhibiting protein adsorption act at the molecular level too. Following the scaling of protein-surface interactions, various techniques have been developed for their study both in the micro- and nano-scale. Protein labelling with radioisotopes or fluorescent probes, colorimetric assays and the quartz crystal microbalance were the first techniques used to monitor protein adsorption isotherms, while the surface force apparatus was used to measure the interaction forces between protein layers at the micro-scale. Recently, more elaborate techniques like total internal reflection fluorescence (TIRF), Fourier transform infrared spectroscopy (FTIR), surface plasmon resonance, Raman spectroscopy, ellipsometry and time of flight secondary ion mass spectrometry (ToF-SIMS) have been applied for the investigation of protein density, structure or orientation at the interfaces. However, a turning point in the study of protein interactions with the surfaces was the invention and the wide-spread use of atomic force microscopy (AFM) which can both image single protein molecules on surfaces and directly measure the interaction force
Tsapikouni, Theodora S. [Laboratory of Biomechanics and Biomedical Engineering, Mechanical Engineering and Aeronautics Department, University of Patras, Patras 26504 (Greece); Missirlis, Yannis F. [Laboratory of Biomechanics and Biomedical Engineering, Mechanical Engineering and Aeronautics Department, University of Patras, Patras 26504 (Greece)], E-mail: email@example.com
The article presents a survey on the significance of protein-material interactions, the mechanisms which control them and the techniques used for their study. Protein-surface interactions play a key role in regenerative medicine, drug delivery, biosensor technology and chromatography, while it is related to various undesired effects such as biofouling and bio-prosthetic malfunction. Although the effects of protein-surface interaction concern the micro-scale, being sometimes obvious even with bare eyes, they derive from biophysical events at the nano-scale. The sequential steps for protein adsorption involve events at the single biomolecule level and the forces driving or inhibiting protein adsorption act at the molecular level too. Following the scaling of protein-surface interactions, various techniques have been developed for their study both in the micro- and nano-scale. Protein labelling with radioisotopes or fluorescent probes, colorimetric assays and the quartz crystal microbalance were the first techniques used to monitor protein adsorption isotherms, while the surface force apparatus was used to measure the interaction forces between protein layers at the micro-scale. Recently, more elaborate techniques like total internal reflection fluorescence (TIRF), Fourier transform infrared spectroscopy (FTIR), surface plasmon resonance, Raman spectroscopy, ellipsometry and time of flight secondary ion mass spectrometry (ToF-SIMS) have been applied for the investigation of protein density, structure or orientation at the interfaces. However, a turning point in the study of protein interactions with the surfaces was the invention and the wide-spread use of atomic force microscopy (AFM) which can both image single protein molecules on surfaces and directly measure the interaction force.
Letteboer, S.J.F.; Roepman, R.
Identification of binary protein-protein interactions is a crucial step in determining the molecular context and functional pathways of proteins. State-of-the-art proteomics techniques provide high-throughput information on the content of proteomes and protein complexes, but give little information
Luise H Brand
Full Text Available DNA-binding proteins (DBPs, such as transcription factors, constitute about 10% of the protein-coding genes in eukaryotic genomes and play pivotal roles in the regulation of chromatin structure and gene expression by binding to short stretches of DNA. Despite their number and importance, only for a minor portion of DBPs the binding sequence had been disclosed. Methods that allow the de novo identification of DNA-binding motifs of known DBPs, such as protein binding microarray technology or SELEX, are not yet suited for high-throughput and automation. To close this gap, we report an automatable DNA-protein-interaction (DPI-ELISA screen of an optimized double-stranded DNA (dsDNA probe library that allows the high-throughput identification of hexanucleotide DNA-binding motifs. In contrast to other methods, this DPI-ELISA screen can be performed manually or with standard laboratory automation. Furthermore, output evaluation does not require extensive computational analysis to derive a binding consensus. We could show that the DPI-ELISA screen disclosed the full spectrum of binding preferences for a given DBP. As an example, AtWRKY11 was used to demonstrate that the automated DPI-ELISA screen revealed the entire range of in vitro binding preferences. In addition, protein extracts of AtbZIP63 and the DNA-binding domain of AtWRKY33 were analyzed, which led to a refinement of their known DNA-binding consensi. Finally, we performed a DPI-ELISA screen to disclose the DNA-binding consensus of a yet uncharacterized putative DBP, AtTIFY1. A palindromic TGATCA-consensus was uncovered and we could show that the GATC-core is compulsory for AtTIFY1 binding. This specific interaction between AtTIFY1 and its DNA-binding motif was confirmed by in vivo plant one-hybrid assays in protoplasts. Thus, the value and applicability of the DPI-ELISA screen for de novo binding site identification of DBPs, also under automatized conditions, is a promising approach for a
Santos, Maria João; Teixeira, J. A.; Rodrigues, L. R.
A method for the recovery and fractionation of whey proteins from a whey protein concentrate (80%, w/w) by hydrophobic interaction chromatography is proposed. Standard proteins and WPC 80 dissolved in phosphate buffer with ammonium sulfate 1M were loaded in a HiPrep Octyl Sepharose FF column coupled to a fast protein liquid chromatography (FPLC) system and eluted by decreasing the ionic strength of the buffer using a salt gradient. The results showed that the most hydrophobic prot...
Park, D; Lee, S; Bolser, D.; Schroeder, M.; Lappe, M.; Oh, D.; Bhak, J.
Motivation: Many genomes have been completely sequenced. However, detecting and analyzing their protein–protein interactions by experimental methods such as co-immunoprecipitation, tandem affinity purification and Y2H is not as fast as genome sequencing. Therefore, a computational prediction method based on the known protein structural interactions will be useful to analyze large-scale protein–protein interaction rules within and among complete genomes. Results: We confirmed that all the pred...
Panstruga Ralph; Lahaye Thomas; Bhat Riyaz A
Abstract Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this...
Carson M Andorf
Full Text Available BACKGROUND: Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners. METHODOLOGY: Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques. CONCLUSIONS: Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions. AVAILABILITY: We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.
Kaleeckal Mathew, Oommen; Sowdhamini, Ramanathan
Protein-protein interactions are essential for the basic biological machinery of the cell. This is important for processes like protein synthesis, enzyme kinetics, molecular assembly and signal transduction. A high number of macromolecular structural complexes are known due to recent advances in structure determination techniques. Therefore, it is of interest to develop an interactive tool to objectively analyze large protein complexes. Hence, we describe the development and utility of a web ...
Chen Yung-Chiang; Lo Yu-Shu; Yang Jinn-Moon
Abstract Background Comprehensive exploration of protein-protein interactions is a challenging route to understand biological processes. For efficiently enlarging protein interactions annotated with residue-based binding models, we proposed a new concept "3D-domain interolog mapping" with a scoring system to explore all possible protein pairs between the two homolog families, derived from a known 3D-structure dimmer (template), across multiple species. Each family consists of homologous prote...
Sitaraman Sujatha; Dipankar Chatterji
Protein–protein interactions influence many cellular processes and it is increasingly being felt that even a weak and remote interplay between two subunits of a protein or between two proteins in a complex may govern the fate of a particular biochemical pathway. In a bacterial system where the complete genome sequence is available, it is an arduous task to assign function to a large number of proteins. It is possible that many of them are peripherally associated with a cellular event and it is very difficult to probe such interaction. However, mutations in the genes that encode such proteins (primary mutations) are useful in these studies. Isolation of a suppressor or a second-site mutation that restores the phenotype abolished by the primary mutation could be an elegant yet simple way to follow a set of interacting proteins. Such a reversion site need not necessarily be geometrically close to the primary mutation site.
Darnell, Steven J.; LeGault, Laura; Mitchell, Julie C.
The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model—a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein–protein or protein–DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local str...
Nahálková, Jarmila; Tomkinson, Birgitta
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. PMID:25303791
Li, Xiyan; Wang, Xin; Snyder, Michael
Cell signaling is extensively wired between cellular components to sustain cell proliferation, differentiation, and adaptation. The interaction network is often manifested in how protein function is regulated through interacting with other cellular components including small molecule metabolites. While many biochemical interactions have been established as reactions between protein enzymes and their substrates and products, much less is known at the system level about how small metabolites regulate protein functions through allosteric binding. In the past decade, study of protein-small molecule interactions has been lagging behind other types of interactions. Recent technological advances have explored several high-throughput platforms to reveal many "unexpected" protein-small molecule interactions that could have profound impact on our understanding of cell signaling. These interactions will help bridge gaps in existing regulatory loops of cell signaling and serve as new targets for medical intervention. In this review, we summarize recent advances of systematic investigation of protein-metabolite/small molecule interactions, and discuss the impact of such studies and their potential impact on both biological researches and medicine. PMID:23225626
Full Text Available Polyketides, a diverse group of heteropolymers with antibiotic and antitumor properties, are assembled in bacteria by multiprotein chains of modular polyketide synthase (PKS proteins. Specific protein-protein interactions determine the order of proteins within a multiprotein chain, and thereby the order in which chemically distinct monomers are added to the growing polyketide product. Here we investigate the evolutionary and molecular origins of protein interaction specificity. We focus on the short, conserved N- and C-terminal docking domains that mediate interactions between modular PKS proteins. Our computational analysis, which combines protein sequence data with experimental protein interaction data, reveals a hierarchical interaction specificity code. PKS docking domains are descended from a single ancestral interacting pair, but have split into three phylogenetic classes that are mutually noninteracting. Specificity within one such compatibility class is determined by a few key residues, which can be used to define compatibility subclasses. We identify these residues using a novel, highly sensitive co-evolution detection algorithm called CRoSS (correlated residues of statistical significance. The residue pairs selected by CRoSS are involved in direct physical interactions in a docked-domain NMR structure. A single PKS system can use docking domain pairs from multiple classes, as well as domain pairs from multiple subclasses of any given class. The termini of individual proteins are frequently shuffled, but docking domain pairs straddling two interacting proteins are linked as an evolutionary module. The hierarchical and modular organization of the specificity code is intimately related to the processes by which bacteria generate new PKS pathways.
LIU Xiang; WANG Yifei
Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement.This paper briefly introduced the original Resonant Recognition Model (RRM),and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM).The key characteristic of the new model is that it can predict directly the proteinprotein interaction from the primary sequence,and the MRRM is more suitable than the RRM for this prediction.The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction.
Full Text Available BACKGROUND: The study and comparison of protein-protein interfaces is essential for the understanding of the mechanisms of interaction between proteins. While there are many methods for comparing protein structures and protein binding sites, so far no methods have been reported for comparing the geometry of non-covalent interactions occurring at protein-protein interfaces. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a method for aligning non-covalent interactions between different protein-protein interfaces. The method aligns the vector representations of van der Waals interactions and hydrogen bonds based on their geometry. The method has been applied to a dataset which comprises a variety of protein-protein interfaces. The alignments are consistent to a large extent with the results obtained using two other complementary approaches. In addition, we apply the method to three examples of protein mimicry. The method successfully aligns respective interfaces and allows for recognizing conserved interface regions. CONCLUSIONS/SIGNIFICANCE: The Galinter method has been validated in the comparison of interfaces in which homologous subunits are involved, including cases of mimicry. The method is also applicable to comparing interfaces involving non-peptidic compounds. Galinter assists users in identifying local interface regions with similar patterns of non-covalent interactions. This is particularly relevant to the investigation of the molecular basis of interaction mimicry.
Swapna Lakshmipuram S
Full Text Available Abstract Background The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods, many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.
Full Text Available Abstract Background Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species. Results We developed a new method for representing a protein sequence of variable length in a frequency vector of fixed length, which encodes the relative frequency of three consecutive amino acids of a sequence. We built a support vector machine (SVM model to predict human proteins that interact with virus proteins. In two types of viruses, human papillomaviruses (HPV and hepatitis C virus (HCV, our SVM model achieved an average accuracy above 80%, which is higher than that of another SVM model with a different representation scheme. Using the SVM model and Gene Ontology (GO annotations of proteins, we predicted new interactions between virus proteins and human proteins. Conclusions Encoding the relative frequency of amino acid triplets of a protein sequence is a simple yet powerful representation method for predicting protein-protein interactions across different species. The representation method has several advantages: (1 it enables a prediction model to achieve a better performance than other representations, (2 it generates feature vectors of fixed length regardless of the sequence length, and (3 the same representation is applicable to different types of proteins.
Samanta, M P; Samanta, Manoj Pratim; Liang, Shoudan
Understanding functional associations among genes discovered in sequencing projects is a key issue in post-genomic biology. However, reliable interpretation of the protein interaction data has been difficult. In this work, we show 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 more than 2800 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.
Spassov, V. Z.; Karshikoff, A. D.; Ladenstein, R
Protein-solvent interactions were analyzed using an optimization parameter based on the ratio of the solvent-accessible area in the native and the unfolded protein structure. The calculations were performed for a set of 183 nonhomologous proteins with known three-dimensional structure available in the Protein Data Bank. The dependence of the total solvent-accessible surface area on the protein molecular mass was analyzed. It was shown that there is no difference between the monomeric and olig...
Liao, Si-Ming; Du, Qi-Shi; Meng, Jian-Zong; Pang, Zong-Wen; Huang, Ri-Bo
Background Among the 20 natural amino acids histidine is the most active and versatile member that plays the multiple roles in protein interactions, often the key residue in enzyme catalytic reactions. A theoretical and comprehensive study on the structural features and interaction properties of histidine is certainly helpful. Results Four interaction types of histidine are quantitatively calculated, including: (1) Cation-π interactions, in which the histidine acts as the aromatic π-motif in ...
Full Text Available YEL005C VAB2 Protein with a potential role in vacuolar function, as suggested by its ability to ... bind Vac8p; green ... fluorescent protein (GFP)-fusion protein localizes ... 0) YNL086W - Putative protein of unknown function; green ... fluorescent protein (GFP)-fusion protein localizes ...
Jung Me Hwang
Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.
Kahraman, Osman; Koch, Peter D.; Klug, William S.; Haselwandter, Christoph A.
Hydrophobic thickness mismatch between integral membrane proteins and the surrounding lipid bilayer can produce lipid bilayer thickness deformations. Experiment and theory have shown that protein-induced lipid bilayer thickness deformations can yield energetically favorable bilayer-mediated interactions between integral membrane proteins, and large-scale organization of integral membrane proteins into protein clusters in cell membranes. Within the continuum elasticity theory of membranes, the energy cost of protein-induced bilayer thickness deformations can be captured by considering compression and expansion of the bilayer hydrophobic core, membrane tension, and bilayer bending, resulting in biharmonic equilibrium equations describing the shape of lipid bilayers for a given set of bilayer-protein boundary conditions. Here we develop a combined analytic and numerical methodology for the solution of the equilibrium elastic equations associated with protein-induced lipid bilayer deformations. Our methodology allows accurate prediction of thickness-mediated protein interactions for arbitrary protein symmetries at arbitrary protein separations and relative orientations. We provide exact analytic solutions for cylindrical integral membrane proteins with constant and varying hydrophobic thickness, and develop perturbative analytic solutions for noncylindrical protein shapes. We complement these analytic solutions, and assess their accuracy, by developing both finite element and finite difference numerical solution schemes. We provide error estimates of our numerical solution schemes and systematically assess their convergence properties. Taken together, the work presented here puts into place an analytic and numerical framework which allows calculation of bilayer-mediated elastic interactions between integral membrane proteins for the complicated protein shapes suggested by structural biology and at the small protein separations most relevant for the crowded membrane
Full Text Available We have conducted a protein interaction study of components within a specific sub-compartment of a eukaryotic flagellum. The trypanosome flagellum contains a para-crystalline extra-axonemal structure termed the paraflagellar rod (PFR with around forty identified components. We have used a Gateway cloning approach coupled with yeast two-hybrid, RNAi and 2D DiGE to define a protein-protein interaction network taking place in this structure. We define two clusters of interactions; the first being characterised by two proteins with a shared domain which is not sufficient for maintaining the interaction. The other cohort is populated by eight proteins, a number of which possess a PFR domain and sub-populations of this network exhibit dependency relationships. Finally, we provide clues as to the structural organisation of the PFR at the molecular level. This multi-strand approach shows that protein interactome data can be generated for insoluble protein complexes.
Møller, Thor C; Wirth, Volker F; Roberts, Nina Ingerslev; Bender, Julia; Bach, Anders; Jacky, Birgitte P S; Strømgaard, Kristian; Deussing, Jan M; Schwartz, Thue W; Martinez, Karen L
G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome. Their signaling is regulated by scaffold proteins containing PDZ domains, but although these interactions are important for GPCR function, they are still poorly understood. We here present a...... colocalization of the full-length proteins in cells and with previous studies, we suggest that the range of relevant interactions might extend to interactions with K i = 450 µM in the in vitro assays. Within this range, we identify novel PSD-95 interactions with the chemokine receptor CXCR2, the neuropeptide Y...... receptor Y2, and four of the somatostatin receptors (SSTRs). The interaction with SSTR1 was further investigated in mouse hippocampal neurons, where we found a clear colocalization between the endogenously expressed proteins, indicating a potential for further investigation of the role of this interaction...
Chowdhury, Saiful M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Liang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yoon, Hyunjin [Dartmouth College, Hanover, NH (United States); Ansong, Charles [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rommereim, Leah M. [Dartmouth College, Hanover, NH (United States); Norbeck, Angela D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Auberry, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moore, R. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Adkins, Joshua N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heffron, Fred [Oregon Health and Science Univ., Portland, OR (United States); Smith, Richard D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .
Full Text Available sed by （YPD） - Not affected by（YPD） - Interologs - Expression similarity (BRITE) - Alternative path with 1 intervening pr...gradation depending on growth conditions; interacts with Vid30p Rows with this prey as prey (4) Rows with this pre... may also play a role in regulation of protein degradation Rows with this bait as bait (55) Rows with this bait as pre...s pathway, required for glucose metabolism; undergoes either proteasome-mediated or autophagy-mediated de... (0 or 1,YPD) 0 Complex (0 or 1,YPD) 0 Synthetic lethality （0 or 1,YPD） 0 Co-induced by （YPD） - Co-repres
Highlights: → Brain-specific angiogenesis inhibitor 2 (BAI2) is a new partner protein for GIP. → BAI2 interaction with GIP was revealed by yeast two-hybrid assay. → Binding of BAI2 to GIP was characterized by NMR, CD and fluorescence. → BAI2 and GIP binding was mediated through the C-terminus of BAI2. -- Abstract: The vast majority of physiological processes in living cells are mediated by protein-protein interactions often specified by particular protein sequence motifs. PDZ domains, composed of 80-100 amino acid residues, are an important class of interaction motif. Among the PDZ-containing proteins, glutaminase interacting protein (GIP), also known as Tax Interacting Protein TIP-1, is unique in being composed almost exclusively of a single PDZ domain. GIP has important roles in cellular signaling, protein scaffolding and modulation of tumor growth and interacts with a number of physiological partner proteins, including Glutaminase L, β-Catenin, FAS, HTLV-1 Tax, HPV16 E6, Rhotekin and Kir 2.3. To identify the network of proteins that interact with GIP, a human fetal brain cDNA library was screened using a yeast two-hybrid assay with GIP as bait. We identified brain-specific angiogenesis inhibitor 2 (BAI2), a member of the adhesion-G protein-coupled receptors (GPCRs), as a new partner of GIP. BAI2 is expressed primarily in neurons, further expanding GIP cellular functions. The interaction between GIP and the carboxy-terminus of BAI2 was characterized using fluorescence, circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy assays. These biophysical analyses support the interaction identified in the yeast two-hybrid assay. This is the first study reporting BAI2 as an interaction partner of GIP.
Schulte, Roberta; Talamas, Jessica; Doucet, Christine; Hetzer, Martin W.
We present a miniaturized pull-down method for the detection of protein-protein interactions using standard affinity chromatography reagents. Binding events between different proteins, which are color-coded with quantum dots (QDs), are visualized on single affinity chromatography beads by fluorescence microscopy. The use of QDs for single molecule detection allows the simultaneous analysis of multiple protein-protein binding events and reduces the amount of time and material needed to perform...
Claudio Peri; Giulia Morra; Giorgio Colombo
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 identifi...
Becirovic, Elvir; Böhm, Sybille; Nguyen, Ong N. P.; Riedmayr, Lisa M.; Hammelmann, Verena; Schön, Christian; Butz, Elisabeth S.; Wahl-Schott, Christian; Biel, Martin; Michalakis, Stylianos
Fluorescence resonance energy transfer (FRET) is a powerful method for the detection and quantification of stationary and dynamic protein-protein interactions. Technical limitations have hampered systematic in vivo FRET experiments to study protein-protein interactions in their native environment. Here, we describe a rapid and robust protocol that combines adeno-associated virus (AAV) vector-mediated in vivo delivery of genetically encoded FRET partners with ex vivo FRET measurements. The method was established on acutely isolated outer segments of murine rod and cone photoreceptors and relies on the high co-transduction efficiency of retinal photoreceptors by co-delivered AAV vectors. The procedure can be used for the systematic analysis of protein-protein interactions of wild type or mutant outer segment proteins in their native environment. Conclusively, our protocol can help to characterize the physiological and pathophysiological relevance of photoreceptor specific proteins and, in principle, should also be transferable to other cell types. PMID:27516733
Bornert, Olivier; Møller, Thor Christian; Boeuf, Julien;
degradation pathway. This protein belongs to the recently identified GPCR-associated sorting proteins (GASPs) family that comprises ten members for which structural and functional details are poorly documented. We present here a detailed structure-function relationship analysis of the molecular interaction...... GPCRs and highlight the presence within GASPs of a novel protein-protein interaction motif that might represent a new target to investigate the involvement of GASPs in the modulation of the activity of GPCRs.......GPCR desensitization and down-regulation are considered key molecular events underlying the development of tolerance in vivo. Among the many regulatory proteins that are involved in these complex processes, GASP-1 have been shown to participate to the sorting of several receptors toward the...
Chen, Bolin; Shi, Jinhong; Zhang, Shenggui; Wu, Fang-Xiang
The identification of protein complexes plays a key role in understanding major cellular processes and biological functions. Various computational algorithms have been proposed to identify protein complexes from protein-protein interaction (PPI) networks. In this paper, we first introduce a new seed-selection strategy for seed-growth style algorithms. Cliques rather than individual vertices are employed as initial seeds. After that, a result-modification approach is proposed based on this seed-selection strategy. Predictions generated by higher order clique seeds are employed to modify results that are generated by lower order ones. The performance of this seed-selection strategy and the result-modification approach are tested by using the entropy-based algorithm, which is currently the best seed-growth style algorithm to detect protein complexes from PPI networks. In addition, we investigate four pairs of strategies for this algorithm in order to improve its accuracy. The numerical experiments are conducted on a Saccharomyces cerevisiae PPI network. The group of best predictions consists of 1711 clusters, with the average f-score at 0.68 after removing all similar and redundant clusters. We conclude that higher order clique seeds can generate predictions with higher accuracy and that our improved entropy-based algorithm outputs more reasonable predictions than the original one. PMID:23112006
R Sabarinathan; K Aishwarya; R Sarani; M Kirti Vaishnavi; K Sekar
It is well known that water molecules play an indispensable role in the structure and function of biological macromolecules. The water-mediated ionic interactions between the charged residues provide stability and plasticity and in turn address the function of the protein structures. Thus, this study specifically addresses the number of possible water-mediated ionic interactions, their occurrence, distribution and nature found in 90% non-redundant protein chains. Further, it provides a statistical report of different charged residue pairs that are mediated by surface or buried water molecules to form the interactions. Also, it discusses its contributions in stabilizing various secondary structural elements of the protein. Thus, the present study shows the ubiquitous nature of the interactions that imparts plasticity and flexibility to a protein molecule.
Cirillo, Davide; Agostini, Federico; Klus, Petr; Marchese, Domenica; Rodriguez, Silvia; Bolognesi, Benedetta; Tartaglia, Gian Gaetano
Increasing evidence indicates that RNA plays an active role in a number of neurodegenerative diseases. We recently introduced a theoretical framework, catRAPID, to predict the binding ability of protein and RNA molecules. Here, we use catRAPID to investigate ribonucleoprotein interactions linked to inherited intellectual disability, amyotrophic lateral sclerosis, Creutzfeuld-Jakob, Alzheimer's, and Parkinson's diseases. We specifically focus on (1) RNA interactions with fragile X mental retardation protein FMRP; (2) protein sequestration caused by CGG repeats; (3) noncoding transcripts regulated by TAR DNA-binding protein 43 TDP-43; (4) autogenous regulation of TDP-43 and FMRP; (5) iron-mediated expression of amyloid precursor protein APP and α-synuclein; (6) interactions between prions and RNA aptamers. Our results are in striking agreement with experimental evidence and provide new insights in processes associated with neuronal function and misfunction. PMID:23264567
Full Text Available In this paper, we present a novel rough-fuzzy clustering (RFC method to detect overlapping protein complexes in protein-protein interaction (PPI networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks.
Wu, Hao; Gao, Lin; Dong, Jihua; Yang, Xiaofei
In this paper, we present a novel rough-fuzzy clustering (RFC) method to detect overlapping protein complexes in protein-protein interaction (PPI) networks. RFC focuses on fuzzy relation model rather than graph model by integrating fuzzy sets and rough sets, employs the upper and lower approximations of rough sets to deal with overlapping complexes, and calculates the number of complexes automatically. Fuzzy relation between proteins is established and then transformed into fuzzy equivalence relation. Non-overlapping complexes correspond to equivalence classes satisfying certain equivalence relation. To obtain overlapping complexes, we calculate the similarity between one protein and each complex, and then determine whether the protein belongs to one or multiple complexes by computing the ratio of each similarity to maximum similarity. To validate RFC quantitatively, we test it in Gavin, Collins, Krogan and BioGRID datasets. Experiment results show that there is a good correspondence to reference complexes in MIPS and SGD databases. Then we compare RFC with several previous methods, including ClusterONE, CMC, MCL, GCE, OSLOM and CFinder. Results show the precision, sensitivity and separation are 32.4%, 42.9% and 81.9% higher than mean of the five methods in four weighted networks, and are 0.5%, 11.2% and 66.1% higher than mean of the six methods in five unweighted networks. Our method RFC works well for protein complexes detection and provides a new insight of network division, and it can also be applied to identify overlapping community structure in social networks and LFR benchmark networks. PMID:24642838
Full Text Available Abstract Background Structural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information. Results In this work, we present a novel method for predicting two kinds of protein motions in ordered structures. The prediction uses only information from the amino acid sequence. We prepared a dataset of the internal and external motions of segments in many proteins by application of NMA. Subsequently, we analyzed the relation between thermal motion assessed from X-ray crystallographic B-factor and internal/external motions calculated by NMA. Results show that attributes of amino acids related to the internal motion have different features from those related to the B-factors, although those related to the external motion are correlated strongly with the B-factors. Next, we developed a method to predict internal and external motions from amino acid sequences based on the Random Forest algorithm. The proposed method uses information associated with adjacent amino acid residues and secondary structures predicted from the amino acid sequence. The proposed method exhibited moderate correlation between predicted internal and external motions with those calculated by NMA. It has the highest prediction accuracy compared to a naïve model and three published predictors. Conclusions Finally, we applied the proposed method predicting the internal motion to a set of 20 proteins that undergo large conformational change upon protein-protein interaction. Results show significant overlaps between the
Robert Alfred Dick
Full Text Available Assembly of an infectious retroviral particle relies on multimerization of the Gag polyprotein at the inner leaflet of the plasma membrane. The three domains of Gag common to all retroviruses-- MA, CA, and NC-- provide the signals for membrane binding, assembly, and viral RNA packaging, respectively. These signals do not function independently of one another. For example, Gag multimerization enhances membrane binding and is more efficient when NC is interacting with RNA. MA binding to the plasma membrane is governed by several principles, including electrostatics, recognition of specific lipid head groups, hydrophobic interactions, and membrane order. HIV-1 uses many of these principles while Rous sarcoma virus (RSV appears to use fewer. This review describes the principles that govern Gag interactions with membranes, focusing on RSV and HIV-1 Gag. The review also defines lipid and membrane behavior, and discusses the complexities in determining how lipid and membrane behavior impact Gag membrane binding.
Talwar Priti; Rahnenführer Jörg; Hahn Andreas; Lengauer Thomas
Abstract Background With microarray technology the expression of thousands of genes can be measured simultaneously. It is well known that the expression levels of genes of interacting proteins are correlated significantly more strongly in Saccharomyces cerevisiae than those of proteins that are not interacting. The objective of this work is to investigate whether this observation extends to the human genome. Results We investigated the quantitative relationship between expression levels of ge...
Stefan Pinkert; Jörg Schultz; Jörg Reichardt
It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a ‘‘module’’ in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN) by searching for such cohesive groups of proteins. Here, we present an alternative approach independent o...
Marko, John F.
The function of DNA in cells depends on its interactions with protein molecules, which recognize and act on base sequence patterns along the double helix. These notes aim to introduce basic polymer physics of DNA molecules, biophysics of protein-DNA interactions and their study in single-DNA experiments, and some aspects of large-scale chromosome structure. Mechanisms for control of chromosome topology will also be discussed.
Full Text Available Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC, based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID, of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.Experimental results based on three different PPI(protein-protein interaction networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC.LIDC is more effective for the prediction of essential proteins than other recently developed methods.
Aalt D J van Dijk
Full Text Available Protein sequences encompass tertiary structures and contain information about specific molecular interactions, which in turn determine biological functions of proteins. Knowledge about how protein sequences define interaction specificity is largely missing, in particular for paralogous protein families with high sequence similarity, such as the plant MADS domain transcription factor family. In comparison to the situation in mammalian species, this important family of transcription regulators has expanded enormously in plant species and contains over 100 members in the model plant species Arabidopsis thaliana. Here, we provide insight into the mechanisms that determine protein-protein interaction specificity for the Arabidopsis MADS domain transcription factor family, using an integrated computational and experimental approach. Plant MADS proteins have highly similar amino acid sequences, but their dimerization patterns vary substantially. Our computational analysis uncovered small sequence regions that explain observed differences in dimerization patterns with reasonable accuracy. Furthermore, we show the usefulness of the method for prediction of MADS domain transcription factor interaction networks in other plant species. Introduction of mutations in the predicted interaction motifs demonstrated that single amino acid mutations can have a large effect and lead to loss or gain of specific interactions. In addition, various performed bioinformatics analyses shed light on the way evolution has shaped MADS domain transcription factor interaction specificity. Identified protein-protein interaction motifs appeared to be strongly conserved among orthologs, indicating their evolutionary importance. We also provide evidence that mutations in these motifs can be a source for sub- or neo-functionalization. The analyses presented here take us a step forward in understanding protein-protein interactions and the interplay between protein sequences and
Full Text Available Abstract Background Is it possible to identify what the best solution of a docking program is? The usual answer to this question is the highest score solution, but interactions between proteins are dynamic processes, and many times the interaction regions are wide enough to permit protein-protein interactions with different orientations and/or interaction energies. In some cases, as in a multimeric protein complex, several interaction regions are possible among the monomers. These dynamic processes involve interactions with surface displacements between the proteins to finally achieve the functional configuration of the protein complex. Consequently, there is not a static and single solution for the interaction between proteins, but there are several important configurations that also have to be analyzed. Results To extract those representative solutions from the docking output datafile, we have developed an unsupervised and automatic clustering application, named DockAnalyse. This application is based on the already existing DBscan clustering method, which searches for continuities among the clusters generated by the docking output data representation. The DBscan clustering method is very robust and, moreover, solves some of the inconsistency problems of the classical clustering methods like, for example, the treatment of outliers and the dependence of the previously defined number of clusters. Conclusions DockAnalyse makes the interpretation of the docking solutions through graphical and visual representations easier by guiding the user to find the representative solutions. We have applied our new approach to analyze several protein interactions and model the dynamic protein interaction behavior of a protein complex. DockAnalyse might also be used to describe interaction regions between proteins and, therefore, guide future flexible dockings. The application (implemented in the R package is accessible.
The interactions between proteins are of central importance for virtually every process in a living cell. It has long been a mystery how two proteins associate to form a complex in a complicated cellular context. Recently, it was found that an intermediate state called encounter state, of a protein
Blagoev, B.; Kratchmarova, I.; Ong, S.E.;
Mass spectrometry-based proteomics can reveal protein-protein interactions on a large scale, but it has been difficult to separate background binding from functionally important interactions and still preserve weak binders. To investigate the epidermal growth factor receptor (EGFR) pathway, we em...
Dukare, Sandeep; Klempnauer, Karl-Heinz
The transcription factor c-Myb plays a key role in the control of proliferation and differentiation in hematopoietic progenitor cells and has been implicated in the development of leukemia and certain non-hematopoietic tumors. c-Myb activity is highly dependent on the interaction with the coactivator p300 which is mediated by the transactivation domain of c-Myb and the KIX domain of p300. We have previously observed that conservative valine-to-isoleucine amino acid substitutions in a conserved stretch of hydrophobic amino acids have a profound effect on Myb activity. Here, we have explored the function of the hydrophobic region as a mediator of protein-protein interactions. We show that the hydrophobic region facilitates Myb self-interaction and binding of the histone acetyl transferase Tip60, a previously identified Myb interacting protein. We show that these interactions are affected by the valine-to-isoleucine amino acid substitutions and suppress Myb activity by interfering with the interaction of Myb and the KIX domain of p300. Taken together, our work identifies the hydrophobic region in the Myb transactivation domain as a binding site for homo- and heteromeric protein interactions and leads to a picture of the c-Myb transactivation domain as a composite protein binding region that facilitates interdependent protein-protein interactions of Myb with regulatory proteins. PMID:27080133
Alfaras-Melainis, Konstantinos; Gomes, Ivone; Rozenfeld, Raphael; Zachariou, Venetia; Devi, Lakshmi,
Opioid receptors, MORP, DORP and KORP, belong to the family A of G protein coupled receptors (GPCR), and have been found to modulate a large number of physiological functions, including mood, stress, appetite, nociception and immune responses. Exogenously applied opioid alkaloids produce analgesia, hedonia and addiction. Addiction is linked to alterations in function and responsiveness of all three opioid receptors in the brain. Over the last few years, a large number of studies identified pr...
Qing-Bo Yu; Yong-Lan Cui; Kang Chong; Yi-Xue Li; Yu-Hua Li; Zhongming Zhao; Tie-Liu Shi; Zhong-Nan Yang; Guang Li; Guan Wang; Jing-Chun Sun; Peng-Cheng Wang; Chen Wang; Hua-Ling Mi; Wei-Min Ma; Jian Cui
Chloroplast is a typical plant cell organeUe where photosynthesis takes place.In this study,a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions.We then constructed a chloroplast protein interaction network primarily based on these core protein interactions.The network had 22 925 protein interaction pairs which involved 2 214 proteins.A total of 160 previously uncharacterized proteins were annotated in this network.The subunits of the photosynthetic complexes were modularized,and the functional relationships among photosystem Ⅰ (PSI),photosystem Ⅱ (PSII),light harvesting complex of photosystem Ⅰ (LHC Ⅰ) and light harvesting complex of photosystem Ⅰ (LHC Ⅱ) could be deduced from the predicted protein interactions in this network.We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis.Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.
Yingjun Chi; Yan Yang; Yuan Zhou; Jie Zhou; Baofang Fan; Jing-Quan Yu; Zhixiang Chen
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 TrGACC/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.
Yin, L. L.; Wang, S. P.; Shan, X. N.; Zhang, S. T.; Tao, N. J.
Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.
Yin, L. L. [Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, Arizona 85287 (United States); College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044 (China); Wang, S. P., E-mail: firstname.lastname@example.org, E-mail: email@example.com; Shan, X. N.; Tao, N. J., E-mail: firstname.lastname@example.org, E-mail: email@example.com [Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, Arizona 85287 (United States); Zhang, S. T. [College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044 (China)
Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.
Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip
WANG Xiaojia; ZHANG Guozhong; ZHAO Jixun; WANG Ming
Binding sialates to hemagglutinin-neuramini- dase (HN) activates (triggers) the fusion protein (F) to start the membrane fusion process of paramyxovirus, but the mechanism by which the HN and F associate with each other to induce membrane fusion is still unclear. It is noteworthy to study the interaction domains of HN and F of paramyxovirus. To screen interacting domains of the HN and F proteins of Avian parainfluenza virus-2 (APIV-2) and identify the structure of binding proteins, the GST pull-down assay and mass spectroscopy (MS) and circular dichroism (CD) experiments were performed in this study. The study revealed that the globular head region of HN protein tends to form a complex with either the heptad repeat 1 (HR1) or the heptad repeat 2 (HR2) of F protein respectively. This paper discusses the novel fusion mechanism induced by paramyxovirus HN and F proteins.
Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.
Lichota, J.; Grasser, Klaus D.
maize HMGA and five different HMGB proteins with mononucleosomes (containing approx. 165 bp of DNA) purified from micrococcal nuclease-digested maize chromatin. The HMGB proteins interacted with the nucleosomes independent of the presence of the linker histone H1, while the binding of HMGA in the...
Full Text Available Abstract During apoptosis several mitochondrial proteins are released. Some of them participate in caspase-independent nuclear DNA degradation, especially apoptosis-inducing factor (AIF and endonuclease G (endoG. Another interesting protein, which was expected to act similarly as AIF due to the high sequence homology with AIF is AIF-homologous mitochondrion-associated inducer of death (AMID. We studied the structure, cellular localization, and interactions of several proteins in silico and also in cells using fluorescent microscopy. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the lipid membranes. Bioinformatic predictions were conducted to analyze the interactions of the studied proteins with each other and with other possible partners. We conducted molecular modeling of proteins with unknown 3D structures. These models were then refined by MolProbity server and employed in molecular docking simulations of interactions. Our results show data acquired using a combination of modern in silico methods and image analysis to understand the localization, interactions and functions of proteins AMID, AIF, endonuclease G, and other apoptosis-related proteins.
Yim, Nambin; Ryu, Seung-Wook; Choi, Kyungsun; Lee, Kwang Ryeol; Lee, Seunghee; Choi, Hojun; Kim, Jeongjin; Shaker, Mohammed R; Sun, Woong; Park, Ji-Ho; Kim, Daesoo; Heo, Won Do; Choi, Chulhee
Nanoparticle-mediated delivery of functional macromolecules is a promising method for treating a variety of human diseases. Among nanoparticles, cell-derived exosomes have recently been highlighted as a new therapeutic strategy for the in vivo delivery of nucleotides and chemical drugs. Here we describe a new tool for intracellular delivery of target proteins, named 'exosomes for protein loading via optically reversible protein-protein interactions' (EXPLORs). By integrating a reversible protein-protein interaction module controlled by blue light with the endogenous process of exosome biogenesis, we are able to successfully load cargo proteins into newly generated exosomes. Treatment with protein-loaded EXPLORs is shown to significantly increase intracellular levels of cargo proteins and their function in recipient cells in vitro and in vivo. These results clearly indicate the potential of EXPLORs as a mechanism for the efficient intracellular transfer of protein-based therapeutics into recipient cells and tissues. PMID:27447450
Wong, Jonathan; Nakajima, Yuko; Westermann, Stefan; Shang, Ching; Kang, Jung-seog; Goodner, Crystal; Houshmand, Pantea; Fields, Stanley; Chan, Clarence S.M.; Drubin, David; Barnes, Georjana; Hazbun, Tony
The mitotic spindle consists of a complex network of proteins that segregates chromosomes in eukaryotes. To strengthen our understanding of the molecular composition, organization, and regulation of the mitotic spindle, we performed a system-wide two-hybrid screen on 94 proteins implicated in spindle function in Saccharomyces cerevisiae. We report 604 predominantly novel interactions that were detected in multiple screens, involving 303 distinct prey proteins. We uncovered a pattern of extens...
Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.
Frank, Andreas O.; Feldkamp, Michael D.; Kennedy, J. Phillip; Waterson, Alex G.; Pelz, Nicholas F.; Patrone, James D.; Vangamudi, Bhavatarini; Camper, DeMarco V.; Rossanese, Olivia W.; Chazin, Walter J.; Fesik, Stephen W.
Replication protein A (RPA), the major eukaryotic single-stranded DNA (ssDNA) binding protein, is involved in nearly all cellular DNA transactions. The RPA N-terminal domain (RPA70N) is a recruitment site for proteins involved in DNA damage response and repair. Selective inhibition of these protein-protein interactions has the potential to inhibit the DNA damage response and sensitize cancer cells to DNA-damaging agents without affecting other functions of RPA. To discover a potent, selective...
Crivelli, Silvia; Kreylos, Oliver; Max, Nelson; Hamann, Bernd; Bethel, Wes
We describe ProteinShop, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds. ProteinShop may be used at different stages of a protein structure prediction process. First, it can create protein configurations containing secondary structures specified by the user. Second, it can interactively manipulate protein fragments to achieve desired folds by adjusting the dihedral angles of selected coil regions using an Inverse Kinematics method. Last, it serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine. ProteinShop was used to create initial configurations for a protein structure prediction method developed by a team that competed in CASP5. ProteinShop's use accelerated the process of generating initial configurations, reducing the time required from days to hours. This paper describes the structure of ProteinShop and discusses its main features.
Hui LI; Liu, Chunmei
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 interne...
Lei Yang; Xianglong Tang
Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based m...
Duncan, R R
Recent developments in cellular imaging spectroscopy now permit the minimally invasive study of protein dynamics inside living cells. These advances are of interest to cell biologists, as proteins rarely act in isolation, but rather in concert with others in forming cellular machinery. Until recently, all protein interactions had to be determined in vitro using biochemical approaches: this biochemical legacy has provided cell biologists with the basis to test defined protein-protein interactions not only inside cells, but now also with high spatial resolution. These techniques can detect and quantify protein behaviours down to the single-molecule level, all inside living cells. More recent developments in TCSPC (time-correlated single-photon counting) imaging are now also driving towards being able to determine protein interaction rates with similar spatial resolution, and together, these experimental advances allow investigators to perform biochemical experiments inside living cells. PMID:17052173
Szymczak, P [Institute of Theoretical Physics, Warsaw University, ulica Hoza 69, 00-681 Warsaw (Poland); Cieplak, Marek [Institute of Physics, Polish Academy of Sciences, Aleja Lotnikow 32/46, 02-668 Warsaw (Poland)
We incorporate hydrodynamic interactions in a structure-based model of ubiquitin and demonstrate that the hydrodynamic coupling may reduce the peak force when stretching the protein at constant speed, especially at larger speeds. Hydrodynamic interactions are also shown to facilitate unfolding at constant force and inhibit stretching by fluid flows.
Szymczak, P.; Cieplak, Marek
We incorporate hydrodynamic interactions in a structure-based model of ubiquitin and demonstrate that the hydrodynamic coupling may reduce the peak force when stretching the protein at constant speed, especially at larger speeds. Hydrodynamic interactions are also shown to facilitate unfolding at constant force and inhibit stretching by fluid flows.
Szymczak, P.; Cieplak, Marek
We incorporate hydrodynamic interactions in a structure-based model of ubiquitin and demonstrate that the hydrodynamic coupling may reduce the peak force when stretching the protein at constant speed, especially at larger speeds. Hydrodynamic interactions are also shown to facilitate unfolding at constant force and inhibit stretching by fluid flows.
Full Text Available 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.
In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases. (general)
A new foot-printing method for mapping protein interactions has been developed, using tritium as a radioactive label. As residues involved in an interaction are less labeled when the complex is formed, they can be identified via comparison of the tritium incorporation of each residue of the bound protein with that of the unbound one. Application of this foot-printing method to the complex formed by the histone H3 fragment H3122-135 and the protein hAsflA1-156 afforded data in good agreement with NMR results. (authors)
Interaction between proteins, cells and biomaterial surfaces is commonly observed and often used to measure biocompatibility of biomaterials.In this investigation, three kinds of biomaterials derived from chitosan were prepared.The surface wettability of these polymers, interaction of protein with material surface, and their effects on cell adhesion and growth were studied.The results show that the surface contact angle and surface charge of biomaterials have a close bearing on protein adsorption as well as cell adhesion and growth, indicating that through different chemical modifications, chitosan can be made into different kinds of biomedical materials to satisfy various needs.
The mechanism allowing a protein to search of a target sequence on DNA is currently described as an intermittent process composed of 3D diffusion in bulk and 1D diffusion along the DNA molecule. Due to the relevant charge of protein and DNA, electrostatic interaction should play a crucial role during this search. In this paper, we explicitly derive the mean field theory allowing for a description of the protein-DNA electrostatics in solution. This approach leads to a unified model of the search process, where 1D and 3D diffusion appear as a natural consequence of the diffusion on an extended interaction energy profile.
Dhole, Kaustubh; Singh, Gurdeep; Pai, Priyadarshini P; Mondal, Sukanta
Protein-protein interactions are of central importance for virtually every process in a living cell. Information about the interaction sites in proteins improves our understanding of disease mechanisms and can provide the basis for new therapeutic approaches. Since a multitude of unique residue-residue contacts facilitate the interactions, protein-protein interaction sites prediction has become one of the most important and challenging problems of computational biology. Although much progress in this field has been reported, this problem is yet to be satisfactorily solved. Here, a novel method (LORIS: L1-regularized LOgistic Regression based protein-protein Interaction Sites predictor) is proposed, that identifies interaction residues, using sequence features and is implemented via the L1-logreg classifier. Results show that LORIS is not only quite effective, but also, performs better than existing state-of-the art methods. LORIS, available as standalone package, can be useful for facilitating drug-design and targeted mutation related studies, which require a deeper knowledge of protein interactions sites. PMID:24486250
Zheng Huiru; Wang Haiying; Browne Fiona; Azuaje Francisco
Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases) and non-interacting proteins (negativ...
Yachie, Nozomu; Petsalaki, Evangelia; Mellor, Joseph C.; Weile, Jochen; Jacob, Yves; Verby, Marta; Ozturk, Sedide B.; Li, Siyang; Cote, Atina G; Mosca, Roberto; Knapp, Jennifer J; Ko, Minjeong; Yu, Analyn; Gebbia, Marinella; Sahni, Nidhi
Abstract High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Tw...
Zhang, Shu-Bo; Tang, Qiang-Rong
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. PMID:27117309
Haberkant, Per; van Meer, Gerrit
Photoactivatable groups meeting the criterion of minimal perturbance allow the investigation of interactions in biological samples. Here, we review the application of photoactivatable groups in lipids enabling the study of protein-lipid interactions in (biological) membranes. The chemistry of various photoactivatable groups is summarized and the specificity of the interactions detected is discussed. The recent introduction of 'click chemistry' in photocrosslinking of membrane proteins by photo-activatable lipids opens new possibilities for the analysis of crosslinked products and will help to close the gap between proteomics and lipidomics. PMID:19426134
Johansson, Kristoffer Enøe; Hamelryck, Thomas
predictions. Our coarse-grained model is compared to state-of-art methods that use full atomic detail. This article illustrates how the use of simple probabilistic models can lead to new opportunities in the treatment of nonlocal interactions in knowledge-based protein structure prediction and design.......Protein structure prediction methods typically use statistical potentials, which rely on statistics derived from a database of know protein structures. In the vast majority of cases, these potentials involve pairwise distances or contacts between amino acids or atoms. Although some potentials...... beyond pairwise interactions have been described, the formulation of a general multibody potential is seen as intractable due to the perceived limited amount of data. In this article, we show that it is possible to formulate a probabilistic model of higher order interactions in proteins, without...
The nucleotides guanosine tetraphosphate (ppGpp) and guanosine pentaphosphate (pppGpp) bind to target proteins to promote bacterial survival (Corrigan et al. 2016). Thus, the binding of the nucleotides to RsgA, a GTPase, inhibits the hydrolysis of GTP. The dose response, taken to be curvilinear with respect to the logarithm of the inhibitor concentration, is instead much better (P<0.001 when the 6 experiments are combined) represented as multiphasic, with high to exceedingly high absolute r values for the straight lines, and with transitions in the form of non-contiguities (jumps). Profiles for the binding of radiolabeled nucleotides to HprT and Gmk, GTP synthesis enzymes, were, similarly, taken to be curvilinear with respect to the logarithm of the protein concentration. However, the profiles are again much better represented as multiphasic than as curvilinear (the P values range from 0.047 to <0.001 for each of the 8 experiments for binding of ppGpp and pppGpp to HprT). The binding of GTP to HprT and ...
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 be 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
Full Text Available YIL092W - Putative protein of unknown function; green fluorescent protein (GFP)-fusion protein l ... t (1) Rows with this bait as prey (0) YGL122C NAB2 Nuclear ... polyadenylated RNA-binding protein required for nu ... mRNA export and poly(A) tail length control; binds nuclear ... pore protein Mlp1p; autoregulates mRNA levels; rel ...
Hatzios, Stavroula-Artemis K.; Ringgaard, Simon; Davis, Brigid; Waldor, Matthew K.
The luciferase protein fragment complementation assay is a powerful tool for studying protein-protein interactions. Two inactive fragments of luciferase are genetically fused to interacting proteins, and when these two proteins interact, the luciferase fragments can reversibly associate and reconstitute enzyme activity. Though this technology has been used extensively in live eukaryotic cells, split luciferase complementation has not yet been applied to studies of dynamic protein-protein inte...
cAMP response element-binding protein (CREB)-binding protein (CBP) plays an important role as a general co-integrator of multiple signaling pathways and interacts with a large number of transcription factors and co-factors, through its numerous protein-binding domains. To identify nuclear factors associated with CBP in developing orofacial tissue, a yeast two-hybrid screen of a cDNA library derived from orofacial tissue from gestational day 11 to 13 mouse embryos was conducted. Using the carboxy terminus (amino acid residues 1676-2441) of CBP as bait, several novel proteins that bind CBP were identified, including an Msx-interacting-zinc finger protein, CDC42 interaction protein 4/thyroid hormone receptor interactor 10, SH3-domain GRB2-like 1, CCR4-NOT transcription complex subunit 3, adaptor protein complex AP-1 β1 subunit, eukaryotic translation initiation factor 2B subunit 1 (α), and cyclin G-associated kinase. Results of the yeast two-hybrid screen were confirmed by glutathione S-transferase pull-down assays. The identification of these proteins as novel CBP-binding partners allows exploration of new mechanisms by which CBP regulates and integrates diverse cell signaling pathways
Kipper, Sarit; Avrahami, Dorit; Bajorek, Monika; Gerber, Doron
We present a high-throughput microfluidics platform to identify novel host cell binding partners of respiratory syncytial virus (RSV) matrix (M) protein. The device consists of thousands of reaction chambers controlled by micro-mechanical valves. The microfluidic device is mated to a microarray-printed custom-made gene library. These genes are then transcribed and translated on-chip, resulting in a protein array ready for binding to RSV M protein.Even small viral proteome, such as that of RSV, presents a challenge due to the fact that viral proteins are usually multifunctional and thus their interaction with the host is complex. Protein microarrays technology allows the interrogation of protein-protein interactions, which could possibly overcome obstacles by using conventional high throughput methods. Using microfluidics platform we have identified new host interactors of M involved in various cellular pathways. A number of microfluidics based assays have already provided novel insights into the virus-host interactome, and the results have important implications for future antiviral strategies aimed at targets of viral protein interactions with the host. PMID:27464694
Full Text Available It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a "module" in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a "module". In a self-consistent manner, proteins are grouped into "functional roles" if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function
Albrecht von Brunn
Full Text Available The severe acute respiratory syndrome coronavirus (SARS-CoV genome is predicted to encode 14 functional open reading frames, leading to the expression of up to 30 structural and non-structural protein products. The functions of a large number of viral ORFs are poorly understood or unknown. In order to gain more insight into functions and modes of action and interaction of the different proteins, we cloned the viral ORFeome and performed a genome-wide analysis for intraviral protein interactions and for intracellular localization. 900 pairwise interactions were tested by yeast-two-hybrid matrix analysis, and more than 65 positive non-redundant interactions, including six self interactions, were identified. About 38% of interactions were subsequently confirmed by CoIP in mammalian cells. Nsp2, nsp8 and ORF9b showed a wide range of interactions with other viral proteins. Nsp8 interacts with replicase proteins nsp2, nsp5, nsp6, nsp7, nsp8, nsp9, nsp12, nsp13 and nsp14, indicating a crucial role as a major player within the replication complex machinery. It was shown by others that nsp8 is essential for viral replication in vitro, whereas nsp2 is not. We show that also accessory protein ORF9b does not play a pivotal role for viral replication, as it can be deleted from the virus displaying normal plaque sizes and growth characteristics in Vero cells. However, it can be expected to be important for the virus-host interplay and for pathogenicity, due to its large number of interactions, by enhancing the global stability of the SARS proteome network, or play some unrealized role in regulating protein-protein interactions. The interactions identified provide valuable material for future studies.
Full Text Available Most biological processes are regulated through complex networks of transient protein interactions where a globular domain in one protein recognizes a linear peptide from another, creating a relatively small contact interface. Although sufficient to ensure binding, these linear motifs alone are usually too short to achieve the high specificity observed, and additional contacts are often encoded in the residues surrounding the motif (i.e. the context. Here, we systematically identified all instances of peptide-mediated protein interactions of known three-dimensional structure and used them to investigate the individual contribution of motif and context to the global binding energy. We found that, on average, the context is responsible for roughly 20% of the binding and plays a crucial role in determining interaction specificity, by either improving the affinity with the native partner or impeding non-native interactions. We also studied and quantified the topological and energetic variability of interaction interfaces, finding a much higher heterogeneity in the context residues than in the consensus binding motifs. Our analysis partially reveals the molecular mechanisms responsible for the dynamic nature of peptide-mediated interactions, and suggests a global evolutionary mechanism to maximise the binding specificity. Finally, we investigated the viability of non-native interactions and highlight cases of potential cross-reaction that might compensate for individual protein failure and establish backup circuits to increase the robustness of cell networks.
Lei GUO; Ying ZHANG; Yan-chun CHE; Wen-juan WU; Wei-zhong LI; Li-chun WANG; Yun LIAO; Long-ding LIU; Qi-han LI
An interaction between the HSV-1 UL25 capsid protein and cellular microtubule-associated protein was found using a yeast two-hybrid screen and β-D-galactosidase activity assays. Immunofluorescence microscopy of the UL25 protein demonstrated its co-localization with cellular microtubule-associated protein in the plasma membrane. Further investigations with deletion mutants suggest that UL25 is likely to have a function in the nucleus.
Yang, L; Zhang, J; Che, X; Gao, Y Q
Computational studies of protein and small molecule (protein-ligand/enzyme-substrate) interactions become more and more important in biological science and drug discovery. Computer modeling can provide molecular details of the processes such as conformational change, binding, and transportation of small molecules/proteins, which are not easily to be captured in experiments. In this chapter, we discussed simulation studies of both protein and small molecules from three aspects: conformation sampling, transportations of small molecules in enzymes, and enzymatic reactions involving small molecules. Both methodology developments and examples of simulation studies in this field were presented. PMID:27497167
Samanta, Manoj Pratim; Liang, Shoudan
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.
Yang, Lei; Tang, Xianglong
Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO) annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP) and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning. PMID:24578640
Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.
SUN Jingchun; XU Jinlin; CAO Jianping; LIU Qi; GUO Xiaokui; SHI Tieliu; LI Yixue
Leptospira interrogans serovar Lai is a pathogenic bacterium that causes a spirochetal zoonosis in humans and some animals. With its complete genome sequence available, it is possible to analyze protein-protein interactions from a whole- genome standpoint. Here we combine four recently developed computational approaches (gene fusion method, gene neighbor method, phylogenetic profiles method, and operon method) to predict protein-pro- tein interaction networks of Leptospira interrogans strain Lai. Through comprehensive analysis on in- teractions among proteins of motility and chemotaxis system, signal transduction, lipopolysaccaride bio- synthesis and a series of proteins related to adhesion and invasion, we provided information for further studying on its pathogenic mechanism. In addition, we also assigned 203 previously uncharacterized proteins with possible functions based on the known functions of its interacting partners. This work is helpful for further investigating L. interrogans strain Lai.
Hansen, Jan; Platten, Florian; Wagner, Dana; Egelhaaf, Stefan U
Cosolvents are routinely used to modulate the (thermal) stability of proteins and, hence, their interactions with proteins have been studied intensely. However, less is known about their specific effects on protein-protein interactions, which we characterize in terms of the protein phase behavior. We analyze the phase behavior of lysozyme solutions in the presence of sodium chloride (NaCl), guanidine hydrochloride (GuHCl), glycerol, and dimethyl sulfoxide (DMSO). We experimentally determined the crystallization boundary (XB) and, in combination with data on the cloud-point temperatures (CPTs), the crystallization gap. In agreement with other studies, our data indicate that the additives might affect the protein phase behavior through electrostatic screening and additive-specific contributions. At high salt concentrations, where electrostatic interactions are screened, both the CPT and the XB are found to be linear functions of the additive concentration. Their slopes quantify the additive-specific changes of the phase behavior and thus of the protein-protein interactions. While the specific effect of NaCl is to induce attractions between proteins, DMSO, glycerol and GuHCl (with increasing strength) weaken attractions and/or induce repulsions. Except for DMSO, changes of the CPT are stronger than those of the XB. Furthermore, the crystallization gap widens in the case of GuHCl and glycerol and narrows in the case of NaCl. We relate these changes to colloidal interaction models, namely square-well and patchy interactions. PMID:27020538
Lin, Ti-Yu; Li, Bor-Ran; Tsai, Sheng-Ta; Chen, Chien-Wei; Chen, Chung-Hsuan; Chen, Yit-Tsong; Pan, Chien-Yuan
Understanding how proteins interact with each other is the basis for studying the biological mechanisms behind various physiological activities. Silicon nanowire field-effect transistors (SiNW-FETs) are sensitive sensors used to detect biomolecular interactions in real-time. However, the majority of the applications that use SiNW-FETs are for known interactions between different molecules. To explore the capability of SiNW-FETs as fast screening devices to identify unknown interacting molecules, we applied mass spectrometry (MS) to analyze molecules reversibly bound to the SiNW-FETs. Calmodulin (CaM) is a Ca(2+)-sensing protein that is ubiquitously expressed in cells and its interaction with target molecules is Ca(2+)-dependent. By modifying the SiNW-FET surface with glutathione, glutathione S-transferase (GST)-tagged CaM binds reversibly to the SiNW-FET. We first verified the Ca(2+)-dependent interaction between GST-CaM and purified troponin I, which is involved in muscle contraction, through the conductance changes of the SiNW-FET. Furthermore, the cell lysate containing overexpressed Ca(2+)/CaM-dependent protein kinase IIα induced a conductance change in the GST-CaM-modified SiNW-FET. The bound proteins were eluted and subsequently identified by MS as CaM and kinase. In another example, candidate proteins from neuronal cell lysates interacting with calneuron I (CalnI), a CaM-like protein, were captured with a GST-CalnI-modified SiNW-FET. The proteins that interacted with CalnI were eluted and verified by MS. The Ca(2+)-dependent interaction between GST-CalnI and one of the candidates, heat shock protein 70, was re-confirmed via the SiNW-FET measurement. Our results demonstrate the effectiveness of combining MS with SiNW-FETs to quickly screen interacting molecules from cell lysates. PMID:23235921
Fragile X syndrome is the most common form of inherited mental retardation disease,resulting from absent of expression of its disease gene FMR1.To study the function of the fragile X mental retardation protein (FMRP) through protein/protein interaction,a mouse embryo cDNA library was screened by the yeast two-hybrid system.A clone was found to interact specifically with FMRP.The cDNA of this clone ( Genbank accession number af102875 ) encoded a protein highly homologous to human G/T mismatch-specific DNA thymine glycosylase ( hTDG ).Interactions between various alternatively spliced FMRP isoforms and a series of mTDG deletion proteins were further studied in the yeast two-hybrid system and their interaction amino acid regions were determined.Interaction between FMRP and TDG existed inside exon 13 of FMRP ( amino acid residue 397-425 ) and around amino acid residue 122-346 of TDG.These results will be helpful to the study of the biological role of FMRP.
Grossmann, Arndt; Benlasfer, Nouhad; Birth, Petra; Hegele, Anna; Wachsmuth, Franziska; Apelt, Luise; Stelzl, Ulrich
Post-translational protein modifications, such as tyrosine phosphorylation, regulate protein–protein interactions (PPIs) critical for signal processing and cellular phenotypes. We extended an established yeast two-hybrid system employing human protein kinases for the analyses of phospho-tyrosine (pY)-dependent PPIs in a direct experimental, large-scale approach. We identified 292 mostly novel pY-dependent PPIs which showed high specificity with respect to kinases and interacting proteins and validated a large fraction in co-immunoprecipitation experiments from mammalian cells. About one-sixth of the interactions are mediated by known linear sequence binding motifs while the majority of pY-PPIs are mediated by other linear epitopes or governed by alternative recognition modes. Network analysis revealed that pY-mediated recognition events are tied to a highly connected protein module dedicated to signaling and cell growth pathways related to cancer. Using binding assays, protein complementation and phenotypic readouts to characterize the pY-dependent interactions of TSPAN2 (tetraspanin 2) and GRB2 or PIK3R3 (p55γ), we exemplarily provide evidence that the two pY-dependent PPIs dictate cellular cancer phenotypes. PMID:25814554
Full Text Available Abstract Background To understand the energetics of the interaction between protein and DNA we analyzed 39 crystallographically characterized complexes with the HINT (Hydropathic INTeractions computational model. HINT is an empirical free energy force field based on solvent partitioning of small molecules between water and 1-octanol. Our previous studies on protein-ligand complexes demonstrated that free energy predictions were significantly improved by taking into account the energetic contribution of water molecules that form at least one hydrogen bond with each interacting species. Results An initial correlation between the calculated HINT scores and the experimentally determined binding free energies in the protein-DNA system exhibited a relatively poor r2 of 0.21 and standard error of ± 1.71 kcal mol-1. However, the inclusion of 261 waters that bridge protein and DNA improved the HINT score-free energy correlation to an r2 of 0.56 and standard error of ± 1.28 kcal mol-1. Analysis of the water role and energy contributions indicate that 46% of the bridging waters act as linkers between amino acids and nucleotide bases at the protein-DNA interface, while the remaining 54% are largely involved in screening unfavorable electrostatic contacts. Conclusion This study quantifies the key energetic role of bridging waters in protein-DNA associations. In addition, the relevant role of hydrophobic interactions and entropy in driving protein-DNA association is indicated by analyses of interaction character showing that, together, the favorable polar and unfavorable polar/hydrophobic-polar interactions (i.e., desolvation mostly cancel.
Pike Andrew D
Full Text Available Abstract Background Two fifths of the world's population is at risk from dengue. The absence of effective drugs and vaccines leaves vector control as the primary intervention tool. Understanding dengue virus (DENV host interactions is essential for the development of novel control strategies. The availability of genome sequences for both human and mosquito host greatly facilitates genome-wide studies of DENV-host interactions. Results We developed the first draft of the mosquito protein interaction network using a computational approach. The weighted network includes 4,214 Aedes aegypti proteins with 10,209 interactions, among which 3,500 proteins are connected into an interconnected scale-free network. We demonstrated the application of this network for the further annotation of mosquito proteins and dissection of pathway crosstalk. Using three datasets based on physical interaction assays, genome-wide RNA interference (RNAi screens and microarray assays, we identified 714 putative DENV-associated mosquito proteins. An integrated analysis of these proteins in the network highlighted four regions consisting of highly interconnected proteins with closely related functions in each of replication/transcription/translation (RTT, immunity, transport and metabolism. Putative DENV-associated proteins were further selected for validation by RNAi-mediated gene silencing, and dengue viral titer in mosquito midguts was significantly reduced for five out of ten (50.0% randomly selected genes. Conclusions Our results indicate the presence of common host requirements for DENV in mosquitoes and humans. We discuss the significance of our findings for pharmacological intervention and genetic modification of mosquitoes for blocking dengue transmission.
Full Text Available Abstract Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP" have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this review, we address the individual strengths and weaknesses of both approaches and provide an outlook about new directions and possible future developments for both techniques.
Full Text Available YNL152W INN1 Essential protein that associates with the contractile actomyosin ring... Bait description Essential protein that associates with the contractile actomyosin ring, required for ingre
Full Text Available YHR180W - Dubious open reading ... frame unlikely to encode a protein, based on available experiment ... 80W Bait gene name - Bait description Dubious open reading ... frame unlikely to encode a protein, based on avail ...
Full Text Available YCL046W - Dubious open reading ... frame unlikely to encode a protein, based on available experiment ... 46W Bait gene name - Bait description Dubious open reading ... frame unlikely to encode a protein, based on avail ...
Full Text Available vity; forms hollow, sphere-shaped oligomers that suppress unfolded proteins aggregation; oligomer activation...chaperone activity; forms hollow, sphere-shaped oligomers that suppress unfolded proteins aggregation; oligo
Full Text Available , sphere-shaped oligomers that suppress unfolded proteins aggregation; oligomer a...tein (sHSP) with chaperone activity; forms hollow, sphere-shaped oligomers that suppress unfolded proteins aggregation
Full Text Available ity; forms hollow, sphere-shaped oligomers that suppress unfolded proteins aggregation; oligomer activation ...erone activity; forms hollow, sphere-shaped oligomers that suppress unfolded proteins aggregation; oligomer
Full Text Available 9C ADY3 Protein required for spore wall formation, thought to mediate assembly of...DY3 Prey description Protein required for spore wall formation, thought to mediate assembly of a Don1p-conta
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly... Bait ORF YDL239C Bait gene name ADY3 Bait description Protein required for spore wall formation, thought
Full Text Available ption induced under cell wall stress; protein levels are reduced under anaerobic conditions; originally thought...iption induced under cell wall stress; protein levels are reduced under anaerobic conditions; originally thought
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...cription Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing struct
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...iption Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structur
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...C Bait ORF YDL239C Bait gene name ADY3 Bait description Protein required for spore wall formation, thought
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...39C Bait ORF YDL239C Bait gene name ADY3 Bait description Protein required for spore wall formation, thought
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...239C Bait gene name ADY3 Bait description Protein required for spore wall formation, thought to mediate asse
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...ption Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...it gene name ADY3 Bait description Protein required for spore wall formation, thought to mediate assembly of
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...ait ORF YDL239C Bait gene name ADY3 Bait description Protein required for spore wall formation, thought to m
Full Text Available YDL239C ADY3 Protein required for spore wall formation, thought to mediate assembly...cription Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing struct
Full Text Available oxidoreductase; mitochondrial matrix protein involved in the synthesis/assembly of iron-sulfur centers; mono...oreductase; mitochondrial matrix protein involved in the synthesis/assembly of iron-sulfur centers; monothio
Full Text Available ity (BRITE) - Alternative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ...
Full Text Available y (0) YLR112W - Dubious open reading frame unlikely to encode a protein, based on...e name - Prey description Dubious open reading frame unlikely to encode a protein, based on available experi
Full Text Available encoding membrane-associated proteins; involved in localizing the Arp2/3 complex to mitochondria; overexpression causes...ed proteins; involved in localizing the Arp2/3 complex to mitochondria; overexpression causes increased sens
Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ng of integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly s
Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ntegral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesi
Full Text Available ilarity (BRITE) - Alternative path with 1 intervening protein (YPD) 2 Alternative path with 2 intervening proteins (YPD) 8 IST hit 9 IST hit in the opposite bait/prey orientation - ...
Full Text Available ity (BRITE) - Alternative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 19 IST hit in the opposite bait/prey orientation -1 ...
Full Text Available larity (BRITE) - Alternative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 55 IST hit in the opposite bait/prey orientation - ...
Full Text Available ity (BRITE) - Alternative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ...
Full Text Available YMR316W DIA1 Protein of unknown function, involved in invasive and pseudohyphal gro... of unknown function, involved in invasive and pseudohyphal growth; green fluorescent protein (GFP)-fusion p
Full Text Available YPR083W MDM36 Protein required for normal mitochondrial morphology ... and inheritance Rows with thi ... cription Protein required for normal mitochondrial morphology ... and inheritance Rows with this bait as bait Rows w ...
Full Text Available -purification experiments; putative F-box protein; analysis of integrated high-throughput datasets predicts ...ments; putative F-box protein; analysis of integrated high-throughput datasets predicts involvement in ubiqu
Full Text Available he peptidase family M18; often used as a marker protein in studies of autophagy a... to the peptidase family M18; often used as a marker protein in studies of autophagy and cytosol to vacuole
Full Text Available encoding membrane-associated proteins; involved in localizing the Arp2/3 complex to mitochondria; overexpression causes...encoding membrane-associated proteins; involved in localizing the Arp2/3 complex to mitochondria; overexpression causes
Full Text Available YPR126C - Dubious open reading frame unlikely to encode a functional protein, based on available experimenta...ubious open reading frame unlikely to encode a functional protein, based on available experimental and compa
Full Text Available 0) YDR203W - Dubious open reading frame unlikely to encode a functional protein, based on availab...y gene name - Prey description Dubious open reading frame unlikely to encode a functional protein, based on availab
Full Text Available y (0) YJL086C - Dubious open reading frame unlikely to encode a protein, based on availab... reading frame unlikely to encode a protein, based on available experimental and comparative sequence data;
Full Text Available YPR136C - Dubious open reading frame unlikely to encode a protein, based on available experimental and compa...e name - Prey description Dubious open reading frame unlikely to encode a protein, based on available experi
Full Text Available 0) YDR008C - Dubious open reading frame unlikely to encode a protein, based on availab... - Prey description Dubious open reading frame unlikely to encode a protein, based on available experimental
Full Text Available YOR318C - Dubious open reading frame unlikely to encode a protein, based on available experimental and compa...likely to encode a protein, based on available experimental and comparative seque
Full Text Available 0) YHR130C - Dubious open reading frame unlikely to encode a functional protein, based on availab...y gene name - Prey description Dubious open reading frame unlikely to encode a functional protein, based on availab
Full Text Available 7) Rows with this bait as prey (0) YDR455C - Dubious open reading frame unlikely to encode a protein, based on availab...ous open reading frame unlikely to encode a protein, based on available experimen
Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R
Better predictive ability of salt and buffer effects on protein-protein interactions requires separating out contributions due to ionic screening, protein charge neutralization by ion binding, and salting-in(out) behavior. We have carried out a systematic study by measuring protein-protein interactions for a monoclonal antibody over an ionic strength range of 25 to 525 mM at 4 pH values (5, 6.5, 8, and 9) in solutions containing sodium chloride, calcium chloride, sodium sulfate, or sodium thiocyante. The salt ions are chosen so as to represent a range of affinities for protein charged and noncharged groups. The results are compared to effects of various buffers including acetate, citrate, phosphate, histidine, succinate, or tris. In low ionic strength solutions, anion binding affinity is reflected by the ability to reduce protein-protein repulsion, which follows the order thiocyanate > sulfate > chloride. The sulfate specific effect is screened at the same ionic strength required to screen the pH dependence of protein-protein interactions indicating sulfate binding only neutralizes protein charged groups. Thiocyanate specific effects occur over a larger ionic strength range reflecting adsorption to charged and noncharged regions of the protein. The latter leads to salting-in behavior and, at low pH, a nonmonotonic interaction profile with respect to sodium thiocyanate concentration. The effects of thiocyanate can not be rationalized in terms of only neutralizing double layer forces indicating the presence of an additional short-ranged protein-protein attraction at moderate ionic strength. Conversely, buffer specific effects can be explained through a charge neutralization mechanism, where buffers with greater valency are more effective at reducing double layer forces at low pH. Citrate binding at pH 6.5 leads to protein charge inversion and the formation of attractive electrostatic interactions. Throughout the report, we highlight similarities in the measured
Seebeck, Birte; Reulecke, Ingo; Kämper, Andreas; Rarey, Matthias
The accurate modeling of metal coordination geometries plays an important role for structure-based drug design applied to metalloenzymes. For the development of a new metal interaction model, we perform a statistical analysis of metal interaction geometries that are relevant to protein-ligand complexes. A total of 43,061 metal sites of the Protein Data Bank (PDB), containing amongst others magnesium, calcium, zinc, iron, manganese, copper, cadmium, cobalt, and nickel, were evaluated according to their metal coordination geometry. Based on statistical analysis, we derived a model for the automatic calculation and definition of metal interaction geometries for the purpose of molecular docking analyses. It includes the identification of the metal-coordinating ligands, the calculation of the coordination geometry and the superposition of ideal polyhedra to identify the optimal positions for free coordination sites. The new interaction model was integrated in the docking software FlexX and evaluated on a data set of 103 metalloprotein-ligand complexes, which were extracted from the PDB. In a first step, the quality of the automatic calculation of the metal coordination geometry was analyzed. In 74% of the cases, the correct prediction of the coordination geometry could be determined on the basis of the protein structure alone. Secondly, the new metal interaction model was tested in terms of predicting protein-ligand complexes. In the majority of test cases, the new interaction model resulted in an improved docking accuracy of the top ranking placements. PMID:18041759
Benson, J D; Lawande, R; Howley, P M
Papillomavirus early gene expression is regulated by the virus gene-encoded E2 proteins. The best-characterized E2 protein, encoded by bovine papillomavirus type 1 (BPV-1), has been shown to interact with basal transcription factor IIB (TFIIB) and the TATA binding protein basal transcription factor (N. M. Rank and P. F. Lambert, J. Virol. 69:6323-6334, 1995). We demonstrate that the potent E2 transcriptional activator protein encoded by a gene of human PV type 16 also interacts with TFIIB in ...
Full Text Available for cytokinesis; septins recruit proteins to the neck and can act as a barrier to diffusion at the membrane,...required for cytokinesis; septins recruit proteins to the neck and can act as a barrier to diffusion at the ...ired for cytokinesis; septins recruit proteins to the neck and can act as a barrier to diffusion at the memb...ed for cytokinesis; septins recruit proteins to the neck and can act as a barrier to diffusion at the membra
Full Text Available description Protein component of the axial elements of the synaptonemal complex, involved in chromosom...YLR263W RED1 Protein component of the axial elements of the synaptonemal complex, involved in chromosom...ins (YPD) 0 IST hit 4 IST hit in the opposite bait/prey orientation - ... ...ins; regulates chromatid cohesion, chromosome segregation, APC-mediated proteolysis, DNA repli...cription Ubiquitin-like protein of the SUMO family, conjugated to lysine residues of target proteins; regulates chrom
Full Text Available YBR170C NPL4 Endoplasmic reticulum and nuclear membrane protein, forms a complex with Cdc48p and ... ecognition of polyubiquitinated proteins and their presentation ... to the 26S proteasome for degradation; involved in ... ecognition of polyubiquitinated proteins and their presentation ... to the 26S proteasome for degradation; involved in ...
Full Text Available YPR029C APL4 Gamma-adaptin, large subunit of the clathrin-associated protein (AP-1) complex; bin ... is involved in protein sorting at the trans-Golgi network ; homolog of the sigma subunit of the mammalian cla ... is involved in protein sorting at the trans-Golgi network ; homolog of the sigma subunit of the mammalian cla ...
Full Text Available YDR190C RVB1 Essential protein involved in transcription regulation; component of chromatin remo ... rred to as pontin; member of the RUVB-like protein family ... Rows with this bait as bait (1) Rows with this bai ... rred to as reptin; member of the RUVB-like protein family ... Rows with this prey as prey (1) Rows with this pre ...
Full Text Available YLR423C ATG17 Scaffold protein responsible for phagophore assembly site organization ; regulatory ... d protein responsible for phagophore assembly site organization ; regulatory subunit of an autophagy-specific compl ... d protein responsible for phagophore assembly site organization ; regulatory subunit of an autophagy-specific compl ...
Qin, Yangzhong; Wang, Lijuan; Zhong, Dongping
Protein hydration is essential to its structure, dynamics, and function, but water-protein interactions have not been directly observed in real time at physiological temperature to our awareness. By using a tryptophan scan with femtosecond spectroscopy, we simultaneously measured the hydration water dynamics and protein side-chain motions with temperature dependence. We observed the heterogeneous hydration dynamics around the global protein surface with two types of coupled motions, collective water/side-chain reorientation in a few picoseconds and cooperative water/side-chain restructuring in tens of picoseconds. The ultrafast dynamics in hundreds of femtoseconds is from the outer-layer, bulk-type mobile water molecules in the hydration shell. We also found that the hydration water dynamics are always faster than protein side-chain relaxations but with the same energy barriers, indicating hydration shell fluctuations driving protein side-chain motions on the picosecond time scales and thus elucidating their ultimate relationship. PMID:27339138
Qin, Yangzhong; Wang, Lijuan; Zhong, Dongping
Protein hydration is essential to its structure, dynamics, and function, but water–protein interactions have not been directly observed in real time at physiological temperature to our awareness. By using a tryptophan scan with femtosecond spectroscopy, we simultaneously measured the hydration water dynamics and protein side-chain motions with temperature dependence. We observed the heterogeneous hydration dynamics around the global protein surface with two types of coupled motions, collective water/side-chain reorientation in a few picoseconds and cooperative water/side-chain restructuring in tens of picoseconds. The ultrafast dynamics in hundreds of femtoseconds is from the outer-layer, bulk-type mobile water molecules in the hydration shell. We also found that the hydration water dynamics are always faster than protein side-chain relaxations but with the same energy barriers, indicating hydration shell fluctuations driving protein side-chain motions on the picosecond time scales and thus elucidating their ultimate relationship. PMID:27339138
Full Text Available The High Mobility Group A (HMGA proteins, a family of DNA architectural factors, by interacting with different proteins play crucial roles in neoplastic transformation of a wide range of tissues. Therefore, the search for HMGA-interacting partners was carried out by several laboratories in order to investigate the mechanisms underlying HMGA-dependent tumorigenesis. Three of the several HMGA-binding proteins are discussed in this review. These are the Chromobox family protein (chromobox protein homolog 7, CBX7, the homeodomain interacting protein kinase 2 (HIPK2 and the POZ/domain and Kruppel zinc finger family member, PATZ. All of them play a critical role in tumorigenesis, and may also be independent markers of cancer. Their activities are linked to cell cycle, apoptosis and senescence. In this review, we discuss the properties of each protein, including their effect on HMGA1 functions, and propose a model accounting for how their activities might be coordinated.
Zeng, Liping; Yin, Yue; You, Chenjiang; Pan, Qianli; Xu, Duo; Jin, Taijie; Zhang, Bailong; Ma, Hong
Plants have evolved a large number of transcription factors (TF), which are enriched among duplicate genes, highlighting their roles in complex regulatory networks. The APETALA2/EREBP-like genes constitute a large plant TF family and participate in development and stress responses. To probe the conservation and divergence of AP2/EREBP genes, we analyzed the duplication patterns of this family in Brassicaceae and identified interacting proteins of representative Arabidopsis AP2/EREBP proteins. We found that many AP2/EREBP duplicates generated early in Brassicaceae history were quickly lost, but many others were retained in all tested Brassicaceae species, suggesting early functional divergence followed by persistent conservation. In addition, the sequences of the AP2 domain and exon numbers were highly conserved in rosids. Furthermore, we used 16 A. thaliana AP2/EREBP proteins as baits in yeast screens and identified 1,970 potential AP2/EREBP-interacting proteins, with a small subset of interactions verified in planta. Many AP2 genes also exhibit reduced expression in an anther-defective mutant, providing a possible link to developmental regulation. The putative AP2-interacting proteins participate in many functions in development and stress responses, including photomorphogenesis, flower development, pathogenesis, drought and cold responses, abscisic acid and auxin signaling. Our results present the AP2/EREBP evolution patterns in Brassicaceae, and support a proposed interaction network of AP2/EREBP proteins and their putative interacting proteins for further study. PMID:26472270
D’Agostino, Tommaso [Dipartimento di Fisica, Università di Palermo, Via Archirafi 36, 90123 Palermo (Italy); Solana, José Ramón [Departamento de Física Aplicada, Universidad de Cantabria, 39005 Santander (Spain); Emanuele, Antonio, E-mail: firstname.lastname@example.org [Dipartimento di Fisica, Università di Palermo, Via Archirafi 36, 90123 Palermo (Italy)
Highlights: ► We propose a model of effective protein–protein interaction embedding solvent effects. ► A previous square-well model is enhanced by giving to the interaction a free energy character. ► The temperature dependence of the interaction is due to entropic effects of the solvent. ► The validity of the original SW model is extended to entropy driven phase transitions. ► We get good fits for lysozyme and haemoglobin spinodal data taken from literature. - Abstract: Statistical thermodynamics of protein solutions is often studied in terms of simple, microscopic models of particles interacting via pairwise potentials. Such modelling can reproduce the short range structure of protein solutions at equilibrium and predict thermodynamics instabilities of these systems. We introduce a square well model of effective protein–protein interaction that embeds the solvent’s action. We modify an existing model  by considering a well depth having an explicit dependence on temperature, i.e. an explicit free energy character, thus encompassing the statistically relevant configurations of solvent molecules around proteins. We choose protein solutions exhibiting demixing upon temperature decrease (lysozyme, enthalpy driven) and upon temperature increase (haemoglobin, entropy driven). We obtain satisfactory fits of spinodal curves for both the two proteins without adding any mean field term, thus extending the validity of the original model. Our results underline the solvent role in modulating or stretching the interaction potential.
WANG Hui; LIU Xing-lou; SHU Sai-nan; HUANG Yong-jian; FANG Feng
Background Murine cytomegalovirus (MCMV) early protein M112-113 is involved in viral DNA replication and believed to play a crucial role in the viral pathogenesis.To investigate the biological function of M112-113 protein in the pathogenesis of the brain disorders caused by cytomegalovirus (CMV),a screening for proteins interacting with M112-113 was performed by a yeast two-hybrid system.Methods Bait plasmid pGBKT7-M112-113 was constructed and transformed into AH109 yeast.After confirmation of the expression of MCMV M112-113 in yeast,the bait yeast was mated with a prey yeast containing mouse brain cDNA library plasmid to screen the proteins interacting with M112-113.Interactions between M112-113 and the obtained proteins were verified by yeast two-hybrid assay and chemiluminescent co-immunoprecipitaion.Results Two proteins interacting with M112-113 were identified,including metastasis-associated 1 (MTA1) and zinc finger,CCHC domain containing 18 (ZCCHC18).M112-113 protein could interact with MTA1 or ZCCHC18 in yeast and mammalian cells.Conclusion The interactions of M112-113 with MTA1 or ZCCHC18 may be related to the pathogenesis of MCMV-associated disease in central nervous system.
Nourani, Esmaeil; Khunjush, Farshad; Durmuş, Saliha
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. PMID:27072625
Full Text Available Abstract Background The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'. These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex. Results We have applied here normalized interface propensity (NIP values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value, and the advantage of not requiring any prior structural knowledge of the complex. Conclusion The NIP values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.
Full Text Available Abstract Background Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs. They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO. Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity. Results We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS, to compute semantic similarity between GO terms annotated to proteins in interaction datasets. Our algorithm, considers unequal depth of biological knowledge representation in different branches of the GO graph. The central idea is to divide the GO graph into sub-graphs and score PPIs higher if participating proteins belong to the same sub-graph as compared to if they belong to different sub-graphs. Conclusions The TCSS algorithm performs better than other semantic similarity measurement techniques that we evaluated in terms of their performance on distinguishing true from false protein interactions, and correlation with gene expression and protein families. We show an average improvement of 4.6 times the F1 score over Resnik, the next best method, on our Saccharomyces cerevisiae PPI dataset and 2 times on our Homo sapiens PPI dataset using cellular component, biological process and molecular function GO annotations.
Wu, Jiawen [Department of Neurology, Vanderbilt University School of Medicine (United States); Peng, Dungeng [Department of Biochemistry, Vanderbilt University School of Medicine (United States); Voehler, Markus [Center for Structural Biology, Vanderbilt University (United States); Sanders, Charles R. [Department of Biochemistry, Vanderbilt University School of Medicine (United States); Center for Structural Biology, Vanderbilt University (United States); Li, Jun, E-mail: email@example.com [Department of Neurology, Vanderbilt University School of Medicine (United States); Tennessee Valley Healthcare System (TVHS) – Nashville VA (United States)
Highlights: •SVIP (small p97/VCP-interacting protein) co-localizes with myelin basic protein (MBP) in compact myelin. •We determined that SVIP is an intrinsically disordered protein (IDP). •The helical content of SVIP increases dramatically during its interaction with negatively charged lipid membrane. •This study provides structural insight into interactions between SVIP and myelin membranes. -- Abstract: SVIP (small p97/VCP-interacting protein) was initially identified as one of many cofactors regulating the valosin containing protein (VCP), an AAA+ ATPase involved in endoplasmic-reticulum-associated protein degradation (ERAD). Our previous study showed that SVIP is expressed exclusively in the nervous system. In the present study, SVIP and VCP were seen to be co-localized in neuronal cell bodies. Interestingly, we also observed that SVIP co-localizes with myelin basic protein (MBP) in compact myelin, where VCP was absent. Furthermore, using nuclear magnetic resonance (NMR) and circular dichroism (CD) spectroscopic measurements, we determined that SVIP is an intrinsically disordered protein (IDP). However, upon binding to the surface of membranes containing a net negative charge, the helical content of SVIP increases dramatically. These findings provide structural insight into interactions between SVIP and myelin membranes.
Full Text Available YPL002C SNF8 Component of the ESCRT-II complex, which is involved in ubiquitin-dependent sorting of protein...s into the endosome; appears to be functionally related to SNF7; involved in glucose der... ESCRT-II complex, which is involved in ubiquitin-dependent sorting of proteins into the end... ubiquitin-dependent sorting of proteins into the endosome; appears to be functi...-dependent sorting of proteins into the endosome Rows with this prey as prey Rows with
Full Text Available on of ER to Golgi transport vesicles; component of the TRAPP (transport protein particle) complex Rows wit...njunction with SNARE proteins in targeting and fusion of ER to Golgi transport vesicles; compon...rt protein particle (TRAPP) complex of the cis-Golgi which mediates vesicle docking and fusi...rvening proteins (YPD) 1 IST hit 4 IST hit in the opposite bait/prey orientation - ... ...YBR254C TRS20 One of 10 subunits of the transport protein particle (TRAPP) complex
Full Text Available on of ER to Golgi transport vesicles; component of the TRAPP (transport protein particle) complex Rows wit...cription One of 10 subunits of the transport protein particle (TRAPP) complex of the cis-Golgi which mediates vesi...ins in targeting and fusion of ER to Golgi transport vesicles; component of the TRAPP (transport prote...in particle (TRAPP) complex of the cis-Golgi which mediates vesicle docking and fusi...rvening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 9 IST hit in the opposite bait/prey orientation - ...
Tang, HaiLin; Zhong, Fan; Liu, Wei; He, FuChu; Xie, HongWei
Integration of pathway and protein-protein interaction (PPI) data can provide more information that could lead to new biological insights. PPIs are usually represented by a simple binary model, whereas pathways are represented by more complicated models. We developed a series of rules for transforming protein interactions from pathway to binary model, and the protein interactions from seven pathway databases, including PID, BioCarta, Reactome, NetPath, INOH, SPIKE and KEGG, were transformed based on these rules. These pathway-derived binary protein interactions were integrated with PPIs from other five PPI databases including HPRD, IntAct, BioGRID, MINT and DIP, to develop integrated dataset (named PathPPI). More detailed interaction type and modification information on protein interactions can be preserved in PathPPI than other existing datasets. Comparison analysis results indicate that most of the interaction overlaps values (O AB) among these pathway databases were less than 5%, and these databases must be used conjunctively. The PathPPI data was provided at http://proteomeview.hupo.org.cn/PathPPI/PathPPI.html. PMID:25591449
Bickerton George R
Full Text Available Abstract Background Structural studies are increasingly providing huge amounts of information on multi-protein assemblies. Although a complete understanding of cellular processes will be dependent on an explicit characterization of the intermolecular interactions that underlie these assemblies and mediate molecular recognition, these are not well described by standard representations. Results Here we present PICCOLO, a comprehensive relational database capturing the details of structurally characterized protein-protein interactions. Interactions are described at the level of interacting pairs of atoms, residues and polypeptide chains, with the physico-chemical nature of the interactions being characterized. Distance and angle terms are used to distinguish 12 different interaction types, including van der Waals contacts, hydrogen bonds and hydrophobic contacts. The explicit aim of PICCOLO is to underpin large-scale analyses of the properties of protein-protein interfaces. This is exemplified by an analysis of residue propensity and interface contact preferences derived from a much larger data set than previously reported. However, PICCOLO also supports detailed inspection of particular systems of interest. Conclusions The current PICCOLO database comprises more than 260 million interacting atom pairs from 38,202 protein complexes. A web interface for the database is available at http://www-cryst.bioc.cam.ac.uk/piccolo.
Zhang, Hao; Yu, Dandan; Sun, Jing; Guo, Huiyuan; Ding, Qingbo; Liu, Ruihai; Ren, Fazheng
Phenolics-rich foods such as fruit juices and coffee are often consumed with milk. In this study, the interactions of α-lactalbumin and β-lactoglobulin with the phenolic acids (chlorogenic acid, caffeic acid, ferulic acid, and coumalic acid) were examined. Fluorescence, CD, and FTIR spectroscopies were used to analyze the binding modes, binding constants, and the effects of complexation on the conformation of whey protein. The results showed that binding constants of each whey protein-phenolic acid interaction ranged from 4 × 105 to 7 × 106 M-n and the number of binding sites n ranged from 1.28 ± 0.13 to 1.54 ± 0.34. Because of these interactions, the conformation of whey protein was altered, with a significant reduction in the amount of α-helix and an increase in the amounts of β-sheet and turn structures.
Louise Stenstrup Holm
Full Text Available PEGylation is a strategy used by the pharmaceutical industry to prolong systemic circulation of protein drugs, whereas formulation excipients are used for stabilization of proteins during storage. Here we investigate the role of PEGylation in protein stabilization by formulation excipients that preferentially interact with the protein.The model protein hen egg white lysozyme was doubly PEGylated on two lysines with 5 kDa linear PEGs (mPEG-succinimidyl valerate, MW 5000 and studied in the absence and presence of preferentially excluded sucrose and preferentially bound guanine hydrochloride. Structural characterization by far- and near-UV circular dichroism spectroscopy was supplemented by investigation of protein thermal stability with the use of differential scanning calorimetry, far and near-UV circular dichroism and fluorescence spectroscopy. It was found that PEGylated lysozyme was stabilized by the preferentially excluded excipient and destabilized by the preferentially bound excipient in a similar manner as lysozyme. However, compared to lysozyme in all cases the melting transition was lower by up to a few degrees and the calorimetric melting enthalpy was decreased to half the value for PEGylated lysozyme. The ratio between calorimetric and van't Hoff enthalpy suggests that our PEGylated lysozyme is a dimer.The PEGylated model protein displayed similar stability responses to the addition of preferentially active excipients. This suggests that formulation principles using preferentially interacting excipients are similar for PEGylated and non-PEGylated proteins.
Jillian L Blatti
Full Text Available Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP and thioesterase (TE govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.
Full Text Available 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.
During sporulation of Bacillus subtilis, several proteins were shown to interact with GTP in specific ways. UV light was used to cross-link [α-32P]GTP to proteins in cell extracts at different stages of growth. After electrophoresis, 11 bands of radioactivity were found in vegetative cells, 4 more appeared during sporulation, and only 9 remained in mature spores. Based on the labeling pattern with or without UV light to cross-link either [α-32P]GTP or [γ-32P]GTP, 11 bands of radioactivity were apparent guanine nucleotide-binding proteins, and 5 bands appeared to be phosphorylated and/or guanylated. Similar results were found with Bacillus megaterium. Assuming the GTP might be a type of signal for sporulation, it could interact with and regulate proteins by at least three mechanisms
Full Text Available The protein-protein interaction network (PIN is a useful tool for systematic investigation of the complex biological activities in the cell. With the increasing interests on the proteome-wide interaction networks, PINs have been reconstructed for many species, including virus, bacteria, plants, animals, and humans. With the development of biological techniques, the reconstruction methods of PIN are further improved. PIN has gradually penetrated many fields in biological research. In this work we systematically reviewed the development of PIN in the past fifteen years, with respect to its reconstruction and application of function annotation, subsystem investigation, evolution analysis, hub protein analysis, and regulation mechanism analysis. Due to the significant role of PIN in the in-depth exploration of biological process mechanisms, PIN will be preferred by more and more researchers for the systematic study of the protein systems in various kinds of organisms.
The objectives of this report are to: Develop novel site-specific protein labeling chemistries for assaying protein-protein interactions in MR-1; and development of a novel optical acquisition and data analysis method for characterizing protein-protein interactions in MR-1 model systems. Our work on analyzing protein-protein interactions in MR-1 is divided in four areas: (1) expression and labeling of MR-1 proteins; (2) general scheme for site-specific fluorescent labeling of expressed proteins; (3) methodology development for monitoring protein-protein interactions; and (4) study of protein-protein interactions in MR-1. In this final report, we give an account for our advances in all areas.
Full Text Available in localizes to the cell periphery, cytoplasm, bud, and bud neck; interacts with Crm1p in two-hybrid assay; ... periphery, cytoplasm, bud, and bud neck; interacts with Crm1p in two-hybrid assay
Jessica B Hostetler
Full Text Available 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.We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further suggesting that the proteins
Hens, Korneel; Feuz, Jean-Daniel; Isakova, Alina; Iagovitina, Antonina; Massouras, Andreas; Bryois, Julien; Callaerts, Patrick; Celniker, Susan E.; Deplancke, Bart
Drosophila melanogaster has one of the best characterized metazoan genomes in terms of functionally annotated regulatory elements. To explore how these elements contribute to gene regulation in the context of gene regulatory networks, we need convenient tools to identify the proteins that bind to them. Here, we present the development and validation of a highly automated protein-DNA interaction detection method, enabling the high-throughput yeast one-hybrid-based screening of DNA elements ver...
Sayed Mohammad Ebrahim Sahraeian; Byung-Jun Yoon
In this work, we introduce a novel network synthesis model that can generate families of evolutionarily related synthetic protein-protein interaction (PPI) networks. Given an ancestral network, the proposed model generates the network family according to a hypothetical phylogenetic tree, where the descendant networks are obtained through duplication and divergence of their ancestors, followed by network growth using network evolution models. We demonstrate that this network synthesis model ca...
Metzler, R.; Ambjörnsson, T.; Lomholt, Michael Andersen;
Optical tweezers, atomic force microscopes, patch clamping, or fluorescence techniques make it possible to study both the equilibrium conformations and dynamics of single DNA molecules as well as their interaction with binding proteins. In this paper we address the dynamics of local DNA denaturat...... report recent findings on the search process of proteins for a specific target on the DNA. © 2006 Materials Research Society....
It is currently widely accepted that the understanding of complex cell functions depends on an integrated network theoretical approach and not on an isolated view of the different molecular agents. Aim of this thesis was the examination of topological properties that mirror known biological aspects by depicting the human protein network with methods from graph- and network theory. The presented network is a partial human interactome of 9222 proteins and 36324 interactions, consisting of singl...
Addadi, L; Weiner, S
Acidic matrix macromolecules are intimately involved in biological crystal growth. In vitro experiments, in which crystals of calcium dicarboxylate salts were grown in the presence of aspartic acid-rich proteins, revealed a stereochemical property common to all the interacting faces. Calcite crystals are nucleated on stereochemically analogous faces when proteins are adsorbed onto a rigid substrate. The importance of this property in biomineralization is discussed.
Full Text Available Abstract Background Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have produced unprecedented opportunities for detecting proteins' essentialities from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. However, the network topology-based centrality measures are very sensitive to the robustness of network. Therefore, a new robust essential protein discovery method would be of great value. Results In this paper, we propose a new centrality measure, named PeC, based on the integration of protein-protein interaction and gene expression data. The performance of PeC is validated based on the protein-protein interaction network of Saccharomyces cerevisiae. The experimental results show that the predicted precision of PeC clearly exceeds that of the other fifteen previously proposed centrality measures: Degree Centrality (DC, Betweenness Centrality (BC, Closeness Centrality (CC, Subgraph Centrality (SC, Eigenvector Centrality (EC, Information Centrality (IC, Bottle Neck (BN, Density of Maximum Neighborhood Component (DMNC, Local Average Connectivity-based method (LAC, Sum of ECC (SoECC, Range-Limited Centrality (RL, L-index (LI, Leader Rank (LR, Normalized α-Centrality (NC, and Moduland-Centrality (MC. Especially, the improvement of PeC over the classic centrality measures (BC, CC, SC, EC, and BN is more than 50% when predicting no more than 500 proteins. Conclusions We demonstrate that the integration of protein-protein interaction network and gene expression data can help improve the precision of predicting essential proteins. The new centrality measure, PeC, is an effective essential protein discovery method.
Jiwen eYang; Sebastian Alexander Wagner; Petra eBeli
Protein-protein interactions are at the core of all cellular functions and dynamic alterations in protein interactions regulate cellular signaling. In the last decade, mass spectrometry-based proteomics has delivered unprecedented insights into human protein interaction networks. Affinity purification-mass spectrometry has been extensively employed for focused and high-throughput studies of steady state protein-protein interactions. Future challenges remain in mapping transient protein intera...
Zahiri, Javad; Bozorgmehr, Joseph Hannon; Masoudi-Nejad, Ali
Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computation...
Dwiputra, D.; Hidayat, W.; Khairani, R.; Zen, F. P.
Interactions between DNA binding protein and specific base pairs of nucleic acid is critical for biological process. We propose a new model of DNA-protein interactions to depict the dynamics of specific DNA-protein interactions. Hydrogen bonds (H-bonds) are, among the other intermolecular interactions in DNA, the most distinctive in term of specificity of molecular bonds. As H-bonds account for specificity, we only consider the dynamics affected by H-bonds between DNA base pairs and H-bonds connecting protein side chains and DNA. The H-bonds are modelled by Morse potentials and coupling terms in the Hamiltonian of coupled oscillators resembling a coupling between planar DNA chain and a protein molecule. In this paper we give a perturbative approach as an attempt for a soliton solution. The solution is in the form of nonlinear travelling wave having the amplitudes satisfying coupled nonlinear Schrodinger equations and is interpreted as the mediator for nonlocal transmittance of biological information in DNA.
Selth, Luke A; Close, Pierre; Svejstrup, Jesper Q
The crucial roles played by RNA-binding proteins in all aspects of RNA metabolism, particularly in the regulation of transcription, have become increasingly evident. Moreover, other factors that do not directly interact with RNA molecules can nevertheless function proximally to RNA polymerases and...... have significant effects on gene expression. RNA immunoprecipitation (RIP) is a powerful technique used to detect direct and indirect interactions between individual proteins and specific RNA molecules in vivo. Here, we describe RIP methods for both yeast and mammalian cells....
Hai-Xia Yang; Geng-Lin Jin; Ling Meng; Jian-Zhi Zhang; Wen-Bin Liu; Cheng-Chao Shou
AIM: To identify the proteins interacting with nucleostemin (NS), thereby gaining an insight into the function of NS.METHODS: Yeast two-hybrid assay was performed to screen a human placenta cDNA library with the full length of NS as a bait. X-Gal assay and β-galactosidase filter assay were subsequently conducted to check the positive clones and the gene was identified by DNA sequencing.To further confirm the interaction of two proteins, the DNA fragment coding NS and the DNA fragment isolated from the positive clone were inserted into the mammalian expression vector pcDNA3 and pcDNA3-myc, respectively.Then, two plasmids were cotransfected into the COS-7 cells by DEAE-dextron. The total protein from the cotransfected cells was extracted and coimmunoprecipitation and Western blot were performed with suitable antibodies sequentially.RESULTS: Two positive clones that interacted with NS were obtained from human placenta cDNA library. One was an alpha isoform of human protein phosphatase 2 regulatory subunit B (B56) (PPP2R5A) and the other was a novel gene being highly homologous to the gene associated with spondylo paralysis. The co-immunoprecipitation also showed that NS specifically interacted with PPP2R5A.CONCLUSION: NS and PPP2R5A interact in yeast and mammalian cells, respectively, which is helpful for addressing the function of NS in cancer development and progression.
Alocci, Davide, E-mail: firstname.lastname@example.org [Department of Biotechnology, Chemistry and Pharmacy, University of Siena, via A. Fiorentina 1, 53100 Siena (Italy); Bernini, Andrea, E-mail: email@example.com [Department of Biotechnology, Chemistry and Pharmacy, University of Siena, via A. Fiorentina 1, 53100 Siena (Italy); Niccolai, Neri, E-mail: firstname.lastname@example.org [Department of Biotechnology, Chemistry and Pharmacy, University of Siena, via A. Fiorentina 1, 53100 Siena (Italy); SienaBioGrafix Srl, via A. Fiorentina 1, 53100 Siena (Italy)
Highlights: •3D atom depth analysis is proposed to identify different layers in protein structures. •Amino acid contents for each layers have been analyzed for a large protein dataset. •Charged amino acids in the most external layer are present at very different extents. •Atom depth indexes of K residues reflect their side chains flexibility. •Mobile surface charges can be responsible for long range protein–protein recognition. -- Abstract: The systematic analysis of amino acid distribution, performed inside a large set of resolved protein structures, sheds light on possible mechanisms driving non random protein–protein approaches. Protein Data Bank entries have been selected using as filters a series of restrictions ensuring that the shape of protein surface is not modified by interactions with large or small ligands. 3D atom depth has been evaluated for all the atoms of the 2,410 selected structures. The amino acid relative population in each of the structural layers formed by grouping atoms on the basis of their calculated depths, has been evaluated. We have identified seven structural layers, the inner ones reproducing the core of proteins and the outer one incorporating their most protruding moieties. Quantitative analysis of amino acid contents of structural layers identified, as expected, different behaviors. Atoms of Q, R, K, N, D residues are increasingly more abundant in going from core to surfaces. An opposite trend is observed for V, I, L, A, C, and G. An intermediate behavior is exhibited by P, S, T, M, W, H, F and Y. The outer structural layer hosts predominantly E and K residues whose charged moieties, protruding from outer regions of the protein surface, reorient free from steric hindrances, determining specific electrodynamics maps. This feature may represent a protein signature for long distance effects, driving the formation of encounter complexes and the eventual short distance approaches that are required for protein–protein
Full Text Available Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP. Many domains are known, though comparatively few linear motifs have been discovered. Their short length (three to eight residues, and the fact that they often reside in disordered regions in proteins makes them difficult to detect through sequence comparison or experiment. Nevertheless, each new motif provides critical molecular details of how interaction networks are constructed, and can explain how one protein is able to bind to very different partners. Here we show that binding motifs can be detected using data from genome-scale interaction studies, and thus avoid the normally slow discovery process. Our approach based on motif over-representation in non-homologous sequences, rediscovers known motifs and predicts dozens of others. Direct binding experiments reveal that two predicted motifs are indeed protein-binding modules: a DxxDxxxD protein phosphatase 1 binding motif with a KD of 22 microM and a VxxxRxYS motif that binds Translin with a KD of 43 microM. We estimate that there are dozens or even hundreds of linear motifs yet to be discovered that will give molecular insight into protein networks and greatly illuminate cellular processes.
De Las Rivas, Javier; Fontanillo, Celia
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. PMID:22908212
Full Text Available Abstract Background Cerebral malaria is a form of human malaria wherein Plasmodium falciparum-infected red blood cells adhere to the blood capillaries in the brain, potentially leading to coma and death. Interactions between parasite and host proteins are important in understanding the pathogenesis of this deadly form of malaria. It is, therefore, necessary to study available protein-protein interactions to identify lesser known interactions that could throw light on key events of cerebral malaria. Methods Sequestration, haemostasis dysfunction, systemic inflammation and neuronal damage are key processes of cerebral malaria. Key events were identified from literature as being crucial to these processes. An integrated interactome was created using available experimental and predicted datasets as well as from literature. Interactions from this interactome were filtered based on Gene Ontology and tissue-specific annotations, and further analysed for relevance to the key events. Results PfEMP1 presentation, platelet activation and astrocyte dysfunction were identified as the key events influencing the disease. 48896 host-parasite along with other host-parasite, host-host and parasite-parasite protein-protein interactions obtained from a disease-specific corpus were combined to form an integrated interactome. Filtering of the interactome resulted in five host-parasite PPI, six parasite-parasite and two host-host PPI. The analysis of these interactions revealed the potential significance of apolipoproteins and temperature/Hsp expression on efficient PfEMP1 presentation; role of MSP-1 in platelet activation; effect of parasite proteins in TGF-β regulation and the role of albumin in astrocyte dysfunction. Conclusions This work links key host-parasite, parasite-parasite and host-host protein-protein interactions to key processes of cerebral malaria and generates hypotheses for disease pathogenesis based on a filtered interaction dataset. These
Bosque, Gabriel; Folch-Fortuny, Abel; Picó, Jesús; Ferrer, Alberto; Santiago, F Elena
Background One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new...
Ru Shen; Xiaosheng Wang; Chittibabu Guda
Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological networ...
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.; Legrain, Pierre
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 geno...
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.; Legrain, Pierre
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 (L¯ike 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 ge...
Wang, Z.; Li, J.; Dang, R; Liang, L; J. Lin
Network pharmacology is a new and hot concept in drug discovery for its ability to investigate the complexity of polypharmacology, and becomes more and more important in drug development. Here we report a protein pharmacology interaction network database (PhIN), aiming to assist multitarget drug discovery by providing comprehensive and flexible network pharmacology analysis. Overall, PhIN contains 1,126,060 target–target interaction pairs in terms of shared compounds and 3,428,020 pairs in te...
Traister, Alexandra; Lu, Mingliang; Coles, John G; Maynes, Jason T
Using hearts from mice overexpressing integrin linked kinase (ILK) behind the cardiac specific promoter αMHC, we have performed immunoprecipitation and mass spectrometry to identify novel ILK protein:protein interactions that regulate cardiomyocyte activity and calcium flux. Integrin linked kinase complexes were captured from mouse heart lysates using a commercial antibody, with subsequent liquid chromatography tandem mass spectral analysis. Interacting partners were identified using the MASCOT server, and important interactions verified using reverse immunoprecipitation and mass spectrometry. All ILK interacting proteins were identified in a non-biased manner, and are stored in the ProteomeXchange Consortium via the PRIDE partner repository (reference ID PRIDE: PXD001053). The functional role of identified ILK interactions in cardiomyocyte function and arrhythmia were subsequently confirmed in human iPSC-cardiomyocytes. PMID:27408918
Full Text Available YNL201C PSY2 Putative subunit of an evolutionarily conserved protein phosphatase co...s prey (0) YBL046W PSY4 Putative regulatory subunit of an evolutionarily conserve...ne name PSY2 Bait description Putative subunit of an evolutionarily conserved protein phosphatase complex co...gene name PSY4 Prey description Putative regulatory subunit of an evolutionarily conserved protein phosphata
Full Text Available YOR220W RCN2 Protein of unknown function; green fluorescent protein (GFP)-fusion protein localiz ... prey as prey (2) Rows with this prey as bait (1) 5 42 ... 3 5 0 0 0 0 0 - - - - - 0 0 3 - Show YOR220W Bait ... ature on bait （YPD） 5 Literature on prey （YPD） 42 ... Literature shared by bait and prey 3 Literature sh ...
G Jack Peterson
Full Text Available We model the evolution of eukaryotic protein-protein interaction (PPI networks. In our model, PPI networks evolve by two known biological mechanisms: (1 Gene duplication, which is followed by rapid diversification of duplicate interactions. (2 Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1 PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2 Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3 Unlike social networks, which have a shrinking diameter (degree of maximum separation over time, PPI networks are predicted to grow in diameter. (4 The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.
Full Text Available RPGR-interacting protein 1 (RPGRIP1 is mutated in the eye disease Leber congenital amaurosis (LCA and its structural homolog, RPGRIP1-like (RPGRIP1L, is mutated in many different ciliopathies. Both are multidomain proteins that are predicted to interact with retinitis pigmentosa G-protein regulator (RPGR. RPGR is mutated in X-linked retinitis pigmentosa and is located in photoreceptors and primary cilia. We solved the crystal structure of the complex between the RPGR-interacting domain (RID of RPGRIP1 and RPGR and demonstrate that RPGRIP1L binds to RPGR similarly. RPGRIP1 binding to RPGR affects the interaction with PDEδ, the cargo shuttling factor for prenylated ciliary proteins. RPGRIP1-RID is a C2 domain with a canonical β sandwich structure that does not bind Ca2+ and/or phospholipids and thus constitutes a unique type of protein-protein interaction module. Judging from the large number of C2 domains in most of the ciliary transition zone proteins identified thus far, the structure presented here seems to constitute a cilia-specific module that is present in multiprotein transition zone complexes.
Full Text Available YPL204W HRR25 Protein kinase involved in regulating diverse events including vesicu...cription Protein kinase involved in regulating diverse events including vesicular traffickin...PD） 0 Co-induced by （YPD） - Co-repressed by （YPD） - Not affected by（YPD） - Interologs - Expression similarity (BRITE) - Alternative... path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 6 IST hit in the opposite bait/prey orientation - ... ... functionality of all four spindle pole bodies during meiosis II; not required for meiotic rec
Full Text Available h this bait as prey (0) YDL002C NHP10 Protein related to mammalian high mobility group proteins; li...scription Protein related to mammalian high mobility group proteins; likely component of the INO80 complex, ...YLR052W IES3 Subunit of the INO80 chromatin remodeling complex Rows with this bait as bait (3) Rows wit...kely component of the INO80 complex, which is an ATP-dependent chromatin-remodeling complex Rows wit...- - - 0 0 10 - Show YLR052W Bait ORF YLR052W Bait gene name IES3 Bait description Subunit of the INO80 chromatin remodeli
Full Text Available ere uncapping and elongation, transcription; component of the EKC/KEOPS protein complex wit...e uncapping and elongation, transcription; component of the EKC/KEOPS protein complex with Kae1p, Cgi121p, P...rnative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 22 IST hit in the opposite bait/prey orientation - ... ...e involved in the degradation of ubiquitinated substrates; recruited to the GAL1-10 promoter region upon ind...he degradation of ubiquitinated substrates; recruited to the GAL1-10 promoter region upon induction of transcription Rows wit
Full Text Available YEL062W NPR2 Component, with Npr3p, of an evolutionarily conserved complex that mediates...cription Component, with Npr3p, of an evolutionarily conserved complex that mediates downregulation of TOR Comp... central plaque periphery; forms a complex with a nuclear envelope protein Mps2p and SPB components Spc29p a...lex with a nuclear envelope protein Mps2p and SPB components Spc29p and Kar1p; required for mit...rnative path with 1 intervening protein (YPD) 0 Alternative path with 2 intervening proteins (YPD) 0 IST hit 3 IST hit in the opposite bait/prey orientation - ...
Full Text Available he peptidase family M18; often used as a marker protein in studies of autophagy and cytosol to vacuole targe...; often used as a marker protein in studies of autophagy and cytosol to vacuole targeting (CVT) pathway Rows...e yscI; zinc metalloproteinase that belongs to the peptidase family M18; often used as a marker protein in studies...t belongs to the peptidase family M18; often used as a marker protein in studies of autophagy and cytosol to
Full Text Available YCL020W - Retrotransposon TYA Gag gene co-transcribed with TYB Pol; translated as TYA or TYA-TYB ... psid protein that is the structural constituent of virus -like particles (VLPs); similar to retroviral Gag R ... psid protein that is the structural constituent of virus -like particles (VLPs); similar to retroviral Gag R ... psid protein that is the structural constituent of virus -like particles (VLPs); similar to retroviral Gag R ... psid protein that is the structural constituent of virus -like particles (VLPs); similar to retroviral Gag R ...
Full Text Available Protein-protein interactions are important layers of regulation in all kingdoms of life. Identification and characterization of these interactions is one challenging task of the post-genomic era and crucial for understanding of molecular processes within a cell. Several methods have been successfully employed during the past decades to identify protein-protein interactions in bacteria, but most of them include tedious and time-consuming manipulations of DNA. In contrast, the MultiSite Gateway system is a fast tool for transfer of multiple DNA fragments between plasmids enabling simultaneous and site directed cloning of up to four fragments into one construct. Here we developed a new set of Gateway vectors including custom made entry vectors and modular Destination vectors for studying protein-protein interactions via Fluorescence Resonance Energy Transfer (FRET, Bacterial two Hybrid (B2H and split Gaussia luciferase (Gluc, as well as for fusions with SNAP-tag and HaloTag for dual-color super-resolution microscopy. As proof of principle, we characterized the interaction between the Salmonella effector SipA and its chaperone InvB via split Gluc and B2H approach. The suitability for FRET analysis as well as functionality of fusions with SNAP- and HaloTag could be demonstrated by studying the transient interaction between chemotaxis response regulator CheY and its phosphatase CheZ.
Barbi, Maria; PAILLUSSON, Fabien
The mechanism allowing a protein to search of a target sequence on DNA is currently described as an intermittent process composed of 3D diffusion in bulk and 1D diffusion along the DNA molecule. Due to the relevant charge of protein and DNA, electrostatic interaction should play a crucial role during this search. In this paper, we explicitly derive the mean field theory allowing for a description of the protein-DNA electrostatics in solution. This approach leads to a unified model of the sear...
Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.
Millar A Harvey
Full Text Available Abstract Intact protein complexes can be separated by apparent molecular mass using a standard polyacrylamide gel electrophoresis system combining mild detergents and the dye Coomassie Blue. Referring to the blue coloured gel and the gentle method of solubilization yielding native and enzymatically active protein complexes, this technique has been named Blue-Native Polyacrylamide Gel-Electrophoresis (BN-PAGE. BN-PAGE has become the method of choice for the investigation of the respiratory protein complexes of the electron transfer chains of a range of organisms, including bacteria, yeasts, animals and plants. It allows the separation in two dimensions of extremely hydrophobic protein sets for analysis and also provides information on their native interactions. In this review we discuss the capabilities of BN-PAGE in proteomics and the wider investigation of protein:protein interactions with a focus on its use and potential in plant science.
Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa
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
Full Text Available Apoptosis and autophagy are distinct biological processes, each driven by a different set of protein-protein interactions, with significant crosstalk via direct interactions among apoptotic and autophagic proteins. To measure the global profile of these interactions, we adapted the Gaussia luciferase protein-fragment complementation assay (GLuc PCA, which monitors binding between proteins fused to complementary fragments of a luciferase reporter. A library encompassing 63 apoptotic and autophagic proteins was constructed for the analysis of ∼3,600 protein-pair combinations. This generated a detailed landscape of the apoptotic and autophagic modules and points of interface between them, identifying 46 previously unknown interactions. One of these interactions, between DAPK2, a Ser/Thr kinase that promotes autophagy, and 14-3-3τ, was further investigated. We mapped the region responsible for 14-3-3τ binding and proved that this interaction inhibits DAPK2 dimerization and activity. This proof of concept underscores the power of the GLuc PCA platform for the discovery of biochemical pathways within the cell death network.
Full Text Available Smoking is the primary cause of lung cancer and is linked to 85% of lung cancer cases. However, how lung cancer develops in patients with smoking history remains unclear. Systems approaches that combine human protein-protein interaction (PPI networks and gene expression data are superior to traditional methods. We performed these systems to determine the role that smoking plays in lung cancer development and used the support vector machine (SVM model to predict PPIs. By defining expression variance (EV, we found 520 dynamic proteins (EV>0.4 using data from the Human Protein Reference Database and Gene Expression Omnibus Database, and built 7 dynamic PPI subnetworks of lung cancer in patients with smoking history. We also determined the primary functions of each subnetwork: signal transduction, apoptosis, and cell migration and adhesion for subnetwork A; cell-sustained angiogenesis for subnetwork B; apoptosis for subnetwork C; and, finally, signal transduction and cell replication and proliferation for subnetworks D-G. The probability distribution of the degree of dynamic protein and static protein differed, clearly showing that the dynamic proteins were not the core proteins which widely connected with their neighbor proteins. There were high correlations among the dynamic proteins, suggesting that the dynamic proteins tend to form specific dynamic modules. We also found that the dynamic proteins were only correlated with the expression of selected proteins but not all neighbor proteins when cancer occurred.
Alting, A.C.; Hamer, R.J.; Kruif, de C.G.
We identified the contribution of covalent and noncovalent interactions to the scaling behavior of the structural and rheological properties in a cold gelling protein system. The system we studied consisted of two types of whey protein aggregates, equal in size but different in the amount of accessi
Aamodt, A.; Magnus, E.M.; Hollung, K.; Uhlen, A.K.; Færgestad, E.M.
The effects of protein composition, protein content, diacetyl tartaric acid ester of monoglycerides (DATEM), and their interaction on dough and bread characteristics were studied by small- and pilot-scale hearth bread baking, dough rheological testing using the Kieffer extensibility rig, and size di
Full Text Available The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article.
Full Text Available 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.
Hartmann-Petersen, Rasmus; Gordon, Colin
The commercial availability of instruments, such as Biacore, that are capable of monitoring surface plasmon resonance (SPR) has greatly simplified the quantification of protein-protein interactions. Already, this technique has been used for some studies of the ubiquitin-proteasome system. Here we...
Song, Gaoyuan; Walley, Justin W.
Pathogen infection triggers complex molecular perturbations within host cells that results in either resistance or susceptibility. Protein acetylation is an emerging biochemical modification that appears to play central roles during host–pathogen interactions. To date, research in this area has focused on two main themes linking protein acetylation to plant immune signaling. Firstly, it has been established that proper gene expression during defense responses requires modulation of histone acetylation within target gene promoter regions. Second, some pathogens can deliver effector molecules that encode acetyltransferases directly within the host cell to modify acetylation of specific host proteins. Collectively these findings suggest that the acetylation level for a range of host proteins may be modulated to alter the outcome of pathogen infection. This review will focus on summarizing our current understanding of the roles of protein acetylation in plant defense and highlight the utility of proteomics approaches to uncover the complete repertoire of acetylation changes triggered by pathogen infection. PMID:27066055
Riboflavin (VB2), a vitamin that is a natural constituent of living organisms, plays an important role in the process of metabolism and it is essential for normal cellular functions and growth. As an endogenous photosensitizer, riboflavin induces photooxidation damages to cells of skin and eye, causing inflammation, accelerated aging and mutation. The photodynamic actions of riboflavin on DNA have been studied extensively, however, its photodynamic actions on protein and enzyme are less studied due to the complex types and structures of proteins, and less attentions have been paid to photosensitive protein damages than DNA. In our lab, the interactions between riboflavin and serum albumin and lysozyme have been carried out by using transient absorption spectrometry, emission spectrometer analysis and electrophoresis techniques. It was found that stable state products and transient process of photosensitive damage to proteins were closely relative to concentration of riboflavin, time of irradiation and the atmosphere of the solutions. The results indicates that proteins can be photosensitive damaged by riboflavin irradiated by UV lights. Riboflavin can quench the intrinsic fluorescence of protein. Both dynamic and static quenching are simultaneous involved. The binding constants, the kinetics and spectroscopic properties of riboflavin interaction with albumin and lysozyme have also been investigated. Mechanisms of the photosensitive damages to proteins were discussed. The experiments also indicated that antioxidants such as melatonin and chlorogenic acid can reduce the damage of lysozyme effectively. (authors)
França Gustavo S
Full Text Available Abstract Background Physical protein-protein interaction (PPI is a critical phenomenon for the function of most proteins in living organisms and a significant fraction of PPIs are the result of domain-domain interactions. Exon shuffling, intron-mediated recombination of exons from existing genes, is known to have been a major mechanism of domain shuffling in metazoans. Thus, we hypothesized that exon shuffling could have a significant influence in shaping the topology of PPI networks. Results We tested our hypothesis by compiling exon shuffling and PPI data from six eukaryotic species: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Cryptococcus neoformans and Arabidopsis thaliana. For all four metazoan species, genes enriched in exon shuffling events presented on average higher vertex degree (number of interacting partners in PPI networks. Furthermore, we verified that a set of protein domains that are simultaneously promiscuous (known to interact to multiple types of other domains, self-interacting (able to interact with another copy of themselves and abundant in the genomes presents a stronger signal for exon shuffling. Conclusions Exon shuffling appears to have been a recurrent mechanism for the emergence of new PPIs along metazoan evolution. In metazoan genomes, exon shuffling also promoted the expansion of some protein domains. We speculate that their promiscuous and self-interacting properties may have been decisive for that expansion.
Eric A Yen
Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and
Yen, Eric A; Tsay, Aaron; Waldispuhl, Jerome; Vogel, Jackie
Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and visualization of the hidden
The major goal of this study was to develop an experimental proteomics approach for deciphering protein complexes and protein interaction networks in the budding and fission yeasts. Key steps of the employed analytical routine, including the purification of complexes and mass spectrometric identification of their subunits, were investigated in detail. Archiving, storage and handling of polyacylamide gels, visualization of protein bands and their effect on the efficiency of in-gel digestion an...
Dielectric properties of an aqueous lysozyme solution were calculated from 2 ns long MD simulations in the temperature range of 150-300 K and an 4 ns long simulation at 300 K. Static and frequency dependent dielectric constants of the system were calculated from auto- and cross-correlations of its three components (protein, water, ions). Cole-Cole plots for protein, water and the total solution were obtained. Emergence of an intense protein-water interaction above the dynamical transition bet...
Ding Don; Tong Weida; Fang Hong; Ye Yanbin; Su Zhenqiang; Guo Li; Liu Zhichao; Martha Venkata-Swamy; Xu Xiaowei
Abstract Background Protein-protein interactions (PPIs) are a critical component for many underlying biological processes. A PPI network can provide insight into the mechanisms of these processes, as well as the relationships among different proteins and toxicants that are potentially involved in the processes. There are many PPI databases publicly available, each with a specific focus. The challenge is how to effectively combine their contents to generate a robust and biologically relevant P...
Jianhua eYang; Kim eOsman; Mudassar eIqbal; Stekel, Dov J; Zewei eLuo; Armstrong, Susan J; Franklin, F. Chris H.
Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI) data are available from the major PPI databases. It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa ...
Gillis, Jesse; Ballouz, Sara; Pavlidis, Paul
Networks constructed from aggregated protein-protein interaction data are commonplace in biology. But the studies these data are derived from were conducted with their own hypotheses and foci. Focusing on data from budding yeast present in BioGRID, we determine that many of the downstream signals present in network data are significantly impacted by biases in the original data. We determine the degree to which selection bias in favor of biologically interesting bait proteins goes down with st...
Eileen Marie Hanna; Nazar Zaki; Amr Amin
Developing suitable methods for the detection of protein complexes in protein interaction networks continues to be an intriguing area of research. The importance of this objective originates from the fact that protein complexes are key players in most cellular processes. The more complexes we identify, the better we can understand normal as well as abnormal molecular events. Up till now, various computational methods were designed for this purpose. However, despite their notable performance, ...
Blanco, Marco A.; Sahin, Eric; Robinson, Anne S.; Roberts, Christopher J.
Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semi-quantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as t...
Jillian L Blatti; Joris Beld; Behnke, Craig A; Michael Mendez; Mayfield, Stephen P; Burkart, Michael D.
Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking...
Studying the effects of NPs on proteins may help understanding potential biological injuries such as changes in protein fibrillation, exposure of new antigenic epitopes, and loss of function such as enzymatic activity impairment. In this mini-review we present recent data which help understand the basis of NP-protein interactions and their subsequent potential effects on key mediators of biological functions such as enzymes.
Hu, Yufang; Doudevski, Ivo; Wood, Denise; Moscarello, Mario; Husted, Cynthia; Genain, Claude; Zasadzinski, Joseph A.; Israelachvili, Jacob
This report describes force measurements and atomic force microscope imaging of lipid-protein interactions that determine the structure of a model membrane system that closely mimics the myelin sheath. Our results suggest that noncovalent, mainly electrostatic and hydrophobic, interactions are responsible for the multilamellar structure and stability of myelin. We find that myelin basic protein acts as a lipid coupler between two apposed bilayers and as a lipid "hole-filler," effectively preventing defect holes from developing. From our protein-mediated-adhesion and force-distance measurements, we develop a simple quantitative model that gives a reasonably accurate picture of the molecular mechanism and adhesion of bilayer-bridging proteins by means of noncovalent interactions. The results and model indicate that optimum myelin adhesion and stability depend on the difference between, rather than the product of, the opposite charges on the lipid bilayers and myelin basic protein, as well as on the repulsive forces associated with membrane fluidity, and that small changes in any of these parameters away from the synergistically optimum values can lead to large changes in the adhesion or even its total elimination. Our results also show that the often-asked question of which membrane species, the lipids or the proteins, are the "important ones" may be misplaced. Both components work synergistically to provide the adhesion and overall structure. A better appreciation of the mechanism of this synergy may allow for a better understanding of stacked and especially myelin membrane structures and may lead to better treatments for demyelinating diseases such as multiple sclerosis. lipid-protein interactions | myelin membrane structure | membrane adhesion | membrane regeneration/healing | demyelinating diseases
Peri, Claudio; Morra, Giulia; Colombo, Giorgio
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
Linda S Kaltenbach
Full Text Available Huntington's disease (HD is a fatal neurodegenerative condition caused by expansion of the polyglutamine tract in the huntingtin (Htt protein. Neuronal toxicity in HD is thought to be, at least in part, a consequence of protein interactions involving mutant Htt. We therefore hypothesized that genetic modifiers of HD neurodegeneration should be enriched among Htt protein interactors. To test this idea, we identified a comprehensive set of Htt interactors using two complementary approaches: high-throughput yeast two-hybrid screening and affinity pull down followed by mass spectrometry. This effort led to the identification of 234 high-confidence Htt-associated proteins, 104 of which were found with the yeast method and 130 with the pull downs. We then tested an arbitrary set of 60 genes encoding interacting proteins for their ability to behave as genetic modifiers of neurodegeneration in a Drosophila model of HD. This high-content validation assay showed that 27 of 60 orthologs tested were high-confidence genetic modifiers, as modification was observed with more than one allele. The 45% hit rate for genetic modifiers seen among the interactors is an order of magnitude higher than the 1%-4% typically observed in unbiased genetic screens. Genetic modifiers were similarly represented among proteins discovered using yeast two-hybrid and pull-down/mass spectrometry methods, supporting the notion that these complementary technologies are equally useful in identifying biologically relevant proteins. Interacting proteins confirmed as modifiers of the neurodegeneration phenotype represent a diverse array of biological functions, including synaptic transmission, cytoskeletal organization, signal transduction, and transcription. Among the modifiers were 17 loss-of-function suppressors of neurodegeneration, which can be considered potential targets for therapeutic intervention. Finally, we show that seven interacting proteins from among 11 tested were able to
Full Text Available encoding membrane-associated proteins; involved in localizing the Arp2/3 complex to mitochondria; overexpression causes...h mRNAs encoding membrane-associated proteins; involved in localizing the Arp2/3 complex to mitochondria; overexpression causes
Full Text Available YKR100C SKG1 Transmembrane protein with a role in cell wall polymer composition; lo...position; localizes on the inner surface of the plasma membrane at the bud and in t...RF YKR100C Bait gene name SKG1 Bait description Transmembrane protein with a role in cell wall polymer com