Composite Structural Motifs of Binding Sites for Delineating Biological Functions of Proteins

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Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures. PMID:22347478

Structural and energetic study of cation-π-cation interactions in proteins.

Science.gov (United States)

Pinheiro, Silvana; Soteras, Ignacio; Gelpí, Josep Lluis; Dehez, François; Chipot, Christophe; Luque, F Javier; Curutchet, Carles

2017-04-12

Cation-π interactions of aromatic rings and positively charged groups are among the most important interactions in structural biology. The role and energetic characteristics of these interactions are well established. However, the occurrence of cation-π-cation interactions is an unexpected motif, which raises intriguing questions about its functional role in proteins. We present a statistical analysis of the occurrence, composition and geometrical preferences of cation-π-cation interactions identified in a set of non-redundant protein structures taken from the Protein Data Bank. Our results demonstrate that this structural motif is observed at a small, albeit non-negligible frequency in proteins, and suggest a preference to establish cation-π-cation motifs with Trp, followed by Tyr and Phe. Furthermore, we have found that cation-π-cation interactions tend to be highly conserved, which supports their structural or functional role. Finally, we have performed an energetic analysis of a representative subset of cation-π-cation complexes combining quantum-chemical and continuum solvation calculations. Our results point out that the protein environment can strongly screen the cation-cation repulsion, leading to an attractive interaction in 64% of the complexes analyzed. Together with the high degree of conservation observed, these results suggest a potential stabilizing role in the protein fold, as demonstrated recently for a miniature protein (Craven et al., J. Am. Chem. Soc. 2016, 138, 1543). From a computational point of view, the significant contribution of non-additive three-body terms challenges the suitability of standard additive force fields for describing cation-π-cation motifs in molecular simulations.

The function of communities in protein interaction networks at multiple scales

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Jones Nick S

2010-07-01

Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

A multi-angular mass spectrometric view at cyclic nucleotide signaling proteins : Structure/function and protein interactions of cAMP- and cGMP-dependent protein kinase

NARCIS (Netherlands)

Scholten, A.

2006-01-01

The primary focus of this thesis is the two kinases PKA and PKG, cAMP and cGMP dependent protein kinase respectively. PKA and PKG are studied both at structure/function level as well as at the level of interaction with other proteins in tissue. Our primary methods are all based on mass spectrometry.

Cold-set globular protein gels: Interactions, structure and rheology as a function of protein concentration.

NARCIS (Netherlands)

Alting, A.C.; Hamer, R.J.; Kruif, de C.G.

2003-01-01

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

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

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Srinivasan Narayanaswamy

2010-06-01

Full Text Available Abstract Background Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results In the present analysis, starting from Cα positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens.

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

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

2017-06-21

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

Predicting and validating protein interactions using network structure.

Directory of Open Access Journals (Sweden)

Pao-Yang Chen

2008-07-01

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.

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

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

2006-11-15

In this study, we investigate what types of interactions are specific to their biological function, and what types of interactions are persistent regardless of their functional category in transient protein-protein heterocomplexes. This is the first approach to analyze protein-protein interfaces systematically at the molecular interaction level in the context of protein functions. We perform systematic analysis at the molecular interaction level using classification and feature subset selection technique prevalent in the field of pattern recognition. To represent the physicochemical properties of protein-protein interfaces, we design 18 molecular interaction types using canonical and noncanonical interactions. Then, we construct input vector using the frequency of each interaction type in protein-protein interface. We analyze the 131 interfaces of transient protein-protein heterocomplexes in PDB: 33 protease-inhibitors, 52 antibody-antigens, 46 signaling proteins including 4 cyclin dependent kinase and 26 G-protein. Using kNN classification and feature subset selection technique, we show that there are specific interaction types based on their functional category, and such interaction types are conserved through the common binding mechanism, rather than through the sequence or structure conservation. The extracted interaction types are C(alpha)-- H...O==C interaction, cation...anion interaction, amine...amine interaction, and amine...cation interaction. With these four interaction types, we achieve the classification success rate up to 83.2% with leave-one-out cross-validation at k = 15. Of these four interaction types, C(alpha)--H...O==C shows binding specificity for protease-inhibitor complexes, while cation-anion interaction is predominant in signaling complexes. The amine ... amine and amine...cation interaction give a minor contribution to the classification accuracy. When combined with these two interactions, they increase the accuracy by 3.8%. In the case of

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

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

2012-07-01

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

Holistic Approach to Partial Covalent Interactions in Protein Structure Prediction and Design with Rosetta.

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Combs, Steven A; Mueller, Benjamin K; Meiler, Jens

2018-05-29

Partial covalent interactions (PCIs) in proteins, which include hydrogen bonds, salt bridges, cation-π, and π-π interactions, contribute to thermodynamic stability and facilitate interactions with other biomolecules. Several score functions have been developed within the Rosetta protein modeling framework that identify and evaluate these PCIs through analyzing the geometry between participating atoms. However, we hypothesize that PCIs can be unified through a simplified electron orbital representation. To test this hypothesis, we have introduced orbital based chemical descriptors for PCIs into Rosetta, called the PCI score function. Optimal geometries for the PCIs are derived from a statistical analysis of high-quality protein structures obtained from the Protein Data Bank (PDB), and the relative orientation of electron deficient hydrogen atoms and electron-rich lone pair or π orbitals are evaluated. We demonstrate that nativelike geometries of hydrogen bonds, salt bridges, cation-π, and π-π interactions are recapitulated during minimization of protein conformation. The packing density of tested protein structures increased from the standard score function from 0.62 to 0.64, closer to the native value of 0.70. Overall, rotamer recovery improved when using the PCI score function (75%) as compared to the standard Rosetta score function (74%). The PCI score function represents an improvement over the standard Rosetta score function for protein model scoring; in addition, it provides a platform for future directions in the analysis of small molecule to protein interactions, which depend on partial covalent interactions.

The construction of an amino acid network for understanding protein structure and function.

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Yan, Wenying; Zhou, Jianhong; Sun, Maomin; Chen, Jiajia; Hu, Guang; Shen, Bairong

2014-06-01

Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein-protein interactions, and for understanding communication within and between proteins.

Recognition of functional sites in protein structures.

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Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J

2004-06-04

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.

A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.

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Agrawal, Neeraj J; Helk, Bernhard; Trout, Bernhardt L

2014-01-21

Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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

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Sony Malhotra

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.

Proteins with Novel Structure, Function and Dynamics

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Pohorille, Andrew

2014-01-01

Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.

Structural study of surfactant-dependent interaction with protein

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-24

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

Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

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Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

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.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

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.

STRING 8--a global view on proteins and their functional interactions in 630 organisms

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Kuhn, Michael; Stark, Manuel

2008-01-01

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein inter......Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein......-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set...... of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures...

Unveiling protein functions through the dynamics of the interaction network.

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Irene Sendiña-Nadal

Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

Structure homology and interaction redundancy for discovering virus–host protein interactions

Science.gov (United States)

de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-01-01

Virus–host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication. PMID:24008843

Structure homology and interaction redundancy for discovering virus-host protein interactions.

Science.gov (United States)

de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-10-01

Virus-host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication.

Wiki-pi: a web-server of annotated human protein-protein interactions to aid in discovery of protein function.

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Naoki Orii

Full Text Available Protein-protein interactions (PPIs are the basis of biological functions. Knowledge of the interactions of a protein can help understand its molecular function and its association with different biological processes and pathways. Several publicly available databases provide comprehensive information about individual proteins, such as their sequence, structure, and function. There also exist databases that are built exclusively to provide PPIs by curating them from published literature. The information provided in these web resources is protein-centric, and not PPI-centric. The PPIs are typically provided as lists of interactions of a given gene with links to interacting partners; they do not present a comprehensive view of the nature of both the proteins involved in the interactions. A web database that allows search and retrieval based on biomedical characteristics of PPIs is lacking, and is needed. We present Wiki-Pi (read Wiki-π, a web-based interface to a database of human PPIs, which allows users to retrieve interactions by their biomedical attributes such as their association to diseases, pathways, drugs and biological functions. Each retrieved PPI is shown with annotations of both of the participant proteins side-by-side, creating a basis to hypothesize the biological function facilitated by the interaction. Conceptually, it is a search engine for PPIs analogous to PubMed for scientific literature. Its usefulness in generating novel scientific hypotheses is demonstrated through the study of IGSF21, a little-known gene that was recently identified to be associated with diabetic retinopathy. Using Wiki-Pi, we infer that its association to diabetic retinopathy may be mediated through its interactions with the genes HSPB1, KRAS, TMSB4X and DGKD, and that it may be involved in cellular response to external stimuli, cytoskeletal organization and regulation of molecular activity. The website also provides a wiki-like capability allowing users

Connecting Protein Structure to Intermolecular Interactions: A Computer Modeling Laboratory

Science.gov (United States)

Abualia, Mohammed; Schroeder, Lianne; Garcia, Megan; Daubenmire, Patrick L.; Wink, Donald J.; Clark, Ginevra A.

2016-01-01

An understanding of protein folding relies on a solid foundation of a number of critical chemical concepts, such as molecular structure, intra-/intermolecular interactions, and relating structure to function. Recent reports show that students struggle on all levels to achieve these understandings and use them in meaningful ways. Further, several…

Functional diversification of structurally alike NLR proteins in plants.

Science.gov (United States)

Chakraborty, Joydeep; Jain, Akansha; Mukherjee, Dibya; Ghosh, Suchismita; Das, Sampa

2018-04-01

In due course of evolution many pathogens alter their effector molecules to modulate the host plants' metabolism and immune responses triggered upon proper recognition by the intracellular nucleotide-binding oligomerization domain containing leucine-rich repeat (NLR) proteins. Likewise, host plants have also evolved with diversified NLR proteins as a survival strategy to win the battle against pathogen invasion. NLR protein indeed detects pathogen derived effector proteins leading to the activation of defense responses associated with programmed cell death (PCD). In this interactive process, genome structure and plasticity play pivotal role in the development of innate immunity. Despite being quite conserved with similar biological functions in all eukaryotes, the intracellular NLR immune receptor proteins happen to be structurally distinct. Recent studies have made progress in identifying transcriptional regulatory complexes activated by NLR proteins. In this review, we attempt to decipher the intracellular NLR proteins mediated surveillance across the evolutionarily diverse taxa, highlighting some of the recent updates on NLR protein compartmentalization, molecular interactions before and after activation along with insights into the finer role of these receptor proteins to combat invading pathogens upon their recognition. Latest information on NLR sensors, helpers and NLR proteins with integrated domains in the context of plant pathogen interactions are also discussed. Copyright © 2018 Elsevier B.V. All rights reserved.

Topology-function conservation in protein-protein interaction networks.

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Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

2015-05-15

Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

Science.gov (United States)

Li, Tao; Li, Qian-Zhong

2012-11-07

RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

Interaction of ATP with a small heat shock protein from Mycobacterium leprae: effect on its structure and function.

Science.gov (United States)

Nandi, Sandip Kumar; Chakraborty, Ayon; Panda, Alok Kumar; Ray, Sougata Sinha; Kar, Rajiv Kumar; Bhunia, Anirban; Biswas, Ashis

2015-03-01

Adenosine-5'-triphosphate (ATP) is an important phosphate metabolite abundantly found in Mycobacterium leprae bacilli. This pathogen does not derive ATP from its host but has its own mechanism for the generation of ATP. Interestingly, this molecule as well as several antigenic proteins act as bio-markers for the detection of leprosy. One such bio-marker is the 18 kDa antigen. This 18 kDa antigen is a small heat shock protein (HSP18) whose molecular chaperone function is believed to help in the growth and survival of the pathogen. But, no evidences of interaction of ATP with HSP18 and its effect on the structure and chaperone function of HSP18 are available in the literature. Here, we report for the first time evidences of "HSP18-ATP" interaction and its consequences on the structure and chaperone function of HSP18. TNP-ATP binding experiment and surface plasmon resonance measurement showed that HSP18 interacts with ATP with a sub-micromolar binding affinity. Comparative sequence alignment between M. leprae HSP18 and αB-crystallin identified the sequence 49KADSLDIDIE58 of HSP18 as the Walker-B ATP binding motif. Molecular docking studies revealed that β4-β8 groove/strands as an ATP interactive region in M. leprae HSP18. ATP perturbs the tertiary structure of HSP18 mildly and makes it less susceptible towards tryptic cleavage. ATP triggers exposure of additional hydrophobic patches at the surface of HSP18 and induces more stability against chemical and thermal denaturation. In vitro aggregation and thermal inactivation assays clearly revealed that ATP enhances the chaperone function of HSP18. Our studies also revealed that the alteration in the chaperone function of HSP18 is reversible and is independent of ATP hydrolysis. As the availability and binding of ATP to HSP18 regulates its chaperone function, this functional inflection may play an important role in the survival of M. leprae in hosts.

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

Science.gov (United States)

DeBlasio, Stacy L; Johnson, Richard; Sweeney, Michelle M; Karasev, Alexander; Gray, Stewart M; MacCoss, Michael J; Cilia, Michelle

2015-06-01

Potato leafroll virus (PLRV) produces a readthrough protein (RTP) via translational readthrough of the coat protein amber stop codon. The RTP functions as a structural component of the virion and as a nonincorporated protein in concert with numerous insect and plant proteins to regulate virus movement/transmission and tissue tropism. Affinity purification coupled to quantitative MS was used to generate protein interaction networks for a PLRV mutant that is unable to produce the read through domain (RTD) and compared to the known wild-type PLRV protein interaction network. By quantifying differences in the protein interaction networks, we identified four distinct classes of PLRV-plant interactions: those plant and nonstructural viral proteins interacting with assembled coat protein (category I); plant proteins in complex with both coat protein and RTD (category II); plant proteins in complex with the RTD (category III); and plant proteins that had higher affinity for virions lacking the RTD (category IV). Proteins identified as interacting with the RTD are potential candidates for regulating viral processes that are mediated by the RTP such as phloem retention and systemic movement and can potentially be useful targets for the development of strategies to prevent infection and/or viral transmission of Luteoviridae species that infect important crop species. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computational design of proteins with novel structure and functions

International Nuclear Information System (INIS)

Yang Wei; Lai Lu-Hua

2016-01-01

Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence–structure–function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein–protein interactions. Challenges and future prospects of this field are also discussed. (topical review)

Functional aspects of protein flexibility

DEFF Research Database (Denmark)

Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B

2009-01-01

this into an intuitive perception of protein function is challenging. Flexibility is of overwhelming importance for protein function, and the changes in protein structure during interactions with binding partners can be dramatic. The present review addresses protein flexibility, focusing on protein-ligand interactions...

Structural symmetry and protein function.

Science.gov (United States)

Goodsell, D S; Olson, A J

2000-01-01

The majority of soluble and membrane-bound proteins in modern cells are symmetrical oligomeric complexes with two or more subunits. The evolutionary selection of symmetrical oligomeric complexes is driven by functional, genetic, and physicochemical needs. Large proteins are selected for specific morphological functions, such as formation of rings, containers, and filaments, and for cooperative functions, such as allosteric regulation and multivalent binding. Large proteins are also more stable against denaturation and have a reduced surface area exposed to solvent when compared with many individual, smaller proteins. Large proteins are constructed as oligomers for reasons of error control in synthesis, coding efficiency, and regulation of assembly. Symmetrical oligomers are favored because of stability and finite control of assembly. Several functions limit symmetry, such as interaction with DNA or membranes, and directional motion. Symmetry is broken or modified in many forms: quasisymmetry, in which identical subunits adopt similar but different conformations; pleomorphism, in which identical subunits form different complexes; pseudosymmetry, in which different molecules form approximately symmetrical complexes; and symmetry mismatch, in which oligomers of different symmetries interact along their respective symmetry axes. Asymmetry is also observed at several levels. Nearly all complexes show local asymmetry at the level of side chain conformation. Several complexes have reciprocating mechanisms in which the complex is asymmetric, but, over time, all subunits cycle through the same set of conformations. Global asymmetry is only rarely observed. Evolution of oligomeric complexes may favor the formation of dimers over complexes with higher cyclic symmetry, through a mechanism of prepositioned pairs of interacting residues. However, examples have been found for all of the crystallographic point groups, demonstrating that functional need can drive the evolution of

Aquaporin Protein-Protein Interactions

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Jennifer Virginia Roche

2017-10-01

Full Text Available Aquaporins are tetrameric membrane-bound channels that facilitate transport of water and other small solutes across cell membranes. In eukaryotes, they are frequently regulated by gating or trafficking, allowing for the cell to control membrane permeability in a specific manner. Protein–protein interactions play crucial roles in both regulatory processes and also mediate alternative functions such as cell adhesion. In this review, we summarize recent knowledge about aquaporin protein–protein interactions; dividing the interactions into three types: (1 interactions between aquaporin tetramers; (2 interactions between aquaporin monomers within a tetramer (hetero-tetramerization; and (3 transient interactions with regulatory proteins. We particularly focus on the structural aspects of the interactions, discussing the small differences within a conserved overall fold that allow for aquaporins to be differentially regulated in an organism-, tissue- and trigger-specific manner. A deep knowledge about these differences is needed to fully understand aquaporin function and regulation in many physiological processes, and may enable design of compounds targeting specific aquaporins for treatment of human disease.

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

Science.gov (United States)

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

Surface dynamics in allosteric regulation of protein-protein interactions: modulation of calmodulin functions by Ca2+.

Directory of Open Access Journals (Sweden)

Yosef Y Kuttner

2013-04-01

Full Text Available Knowledge of the structural basis of protein-protein interactions (PPI is of fundamental importance for understanding the organization and functioning of biological networks and advancing the design of therapeutics which target PPI. Allosteric modulators play an important role in regulating such interactions by binding at site(s orthogonal to the complex interface and altering the protein's propensity for complex formation. In this work, we apply an approach recently developed by us for analyzing protein surfaces based on steered molecular dynamics simulation (SMD to the study of the dynamic properties of functionally distinct conformations of a model protein, calmodulin (CaM, whose ability to interact with target proteins is regulated by the presence of the allosteric modulator Ca(2+. Calmodulin is a regulatory protein that acts as an intracellular Ca(2+ sensor to control a wide variety of cellular processes. We demonstrate that SMD analysis is capable of pinpointing CaM surfaces implicated in the recognition of both the allosteric modulator Ca(2+ and target proteins. Our analysis of changes in the dynamic properties of the CaM backbone elicited by Ca(2+ binding yielded new insights into the molecular mechanism of allosteric regulation of CaM-target interactions.

Mapping Protein-Protein Interactions by Quantitative Proteomics

DEFF Research Database (Denmark)

Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy

2010-01-01

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.......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...

Transcription Factor Functional Protein-Protein Interactions in Plant Defense Responses

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Murilo S. Alves

2014-03-01

Full Text Available Responses to biotic stress in plants lead to dramatic reprogramming of gene expression, favoring stress responses at the expense of normal cellular functions. Transcription factors are master regulators of gene expression at the transcriptional level, and controlling the activity of these factors alters the transcriptome of the plant, leading to metabolic and phenotypic changes in response to stress. The functional analysis of interactions between transcription factors and other proteins is very important for elucidating the role of these transcriptional regulators in different signaling cascades. In this review, we present an overview of protein-protein interactions for the six major families of transcription factors involved in plant defense: basic leucine zipper containing domain proteins (bZIP, amino-acid sequence WRKYGQK (WRKY, myelocytomatosis related proteins (MYC, myeloblastosis related proteins (MYB, APETALA2/ ETHYLENE-RESPONSIVE ELEMENT BINDING FACTORS (AP2/EREBP and no apical meristem (NAM, Arabidopsis transcription activation factor (ATAF, and cup-shaped cotyledon (CUC (NAC. We describe the interaction partners of these transcription factors as molecular responses during pathogen attack and the key components of signal transduction pathways that take place during plant defense responses. These interactions determine the activation or repression of response pathways and are crucial to understanding the regulatory networks that modulate plant defense responses.

RACK1, A Multifaceted Scaffolding Protein: Structure and Function

LENUS (Irish Health Repository)

Adams, David R

2011-10-06

Abstract The Receptor for Activated C Kinase 1 (RACK1) is a member of the tryptophan-aspartate repeat (WD-repeat) family of proteins and shares significant homology to the β subunit of G-proteins (Gβ). RACK1 adopts a seven-bladed β-propeller structure which facilitates protein binding. RACK1 has a significant role to play in shuttling proteins around the cell, anchoring proteins at particular locations and in stabilising protein activity. It interacts with the ribosomal machinery, with several cell surface receptors and with proteins in the nucleus. As a result, RACK1 is a key mediator of various pathways and contributes to numerous aspects of cellular function. Here, we discuss RACK1 gene and structure and its role in specific signaling pathways, and address how posttranslational modifications facilitate subcellular location and translocation of RACK1. This review condenses several recent studies suggesting a role for RACK1 in physiological processes such as development, cell migration, central nervous system (CN) function and circadian rhythm as well as reviewing the role of RACK1 in disease.

Semantic integration to identify overlapping functional modules in protein interaction networks

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Ramanathan Murali

2007-07-01

Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules 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 functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

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Zhao Yi

2010-12-01

Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

Science.gov (United States)

Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

2014-01-01

Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

Topological and functional properties of the small GTPases protein interaction network.

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Anna Delprato

Full Text Available Small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran regulate key cellular processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. A great deal of experimental evidence supports the existence of signaling cascades and feedback loops within and among the small GTPase subfamilies suggesting that these proteins function in a coordinated and cooperative manner. The interplay occurs largely through association with bi-partite regulatory and effector proteins but can also occur through the active form of the small GTPases themselves. In order to understand the connectivity of the small GTPases signaling routes, a systems-level approach that analyzes data describing direct and indirect interactions was used to construct the small GTPases protein interaction network. The data were curated from the Search Tool for the Retrieval of Interacting Genes (STRING database and include only experimentally validated interactions. The network method enables the conceptualization of the overall structure as well as the underlying organization of the protein-protein interactions. The interaction network described here is comprised of 778 nodes and 1943 edges and has a scale-free topology. Rac1, Cdc42, RhoA, and HRas are identified as the hubs. Ten sub-network motifs are also identified in this study with themes in apoptosis, cell growth/proliferation, vesicle traffic, cell adhesion/junction dynamics, the nicotinamide adenine dinucleotide phosphate (NADPH oxidase response, transcription regulation, receptor-mediated endocytosis, gene silencing, and growth factor signaling. Bottleneck proteins that bridge signaling paths and proteins that overlap in multiple small GTPase networks are described along with the functional annotation of all proteins in the network.

Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung-Hou; Shin, Dong Hae; Hou, Jingtong; Chandonia, John-Marc; Das, Debanu; Choi, In-Geol; Kim, Rosalind; Kim, Sung-Hou

2007-09-02

Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

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

Science.gov (United States)

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

2017-04-11

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

Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.

Science.gov (United States)

Liu, Zhihai; Su, Minyi; Han, Li; Liu, Jie; Yang, Qifan; Li, Yan; Wang, Renxiao

2017-02-21

In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole spectrum of protein-ligand interaction scoring functions have been developed. Regardless of their technical difference, scoring functions all need data sets combining protein-ligand complex structures and binding affinity data for parametrization and validation. However, data sets of this kind used to be rather limited in terms of size and quality. On the other hand, standard metrics for evaluating scoring function used to be ambiguous. Scoring functions are often tested in molecular docking or even virtual screening trials, which do not directly reflect the genuine quality of scoring functions. Collectively, these underlying obstacles have impeded the invention of more advanced scoring functions. In this Account, we describe our long-lasting efforts to overcome these obstacles, which involve two related projects. On the first project, we have created the PDBbind database. It is the first database that systematically annotates the protein-ligand complexes in the Protein Data Bank (PDB) with experimental binding data. This database has been updated annually since its first public release in 2004. The latest release (version 2016) provides binding data for 16 179 biomolecular complexes in PDB. Data sets provided by PDBbind have been applied to many computational and statistical studies on protein-ligand interaction and various subjects. In particular, it has become a major data resource for scoring function development. On the second project, we have established the Comparative Assessment of Scoring Functions (CASF) benchmark for scoring function evaluation. Our key idea is to decouple the "scoring" process from the "sampling" process, so scoring functions can be tested in a relatively pure context to reflect their quality. In our

Structural and Functional Annotation of Hypothetical Proteins of O139

Directory of Open Access Journals (Sweden)

Md. Saiful Islam

2015-06-01

Full Text Available In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

Structuring detergents for extracting and stabilizing functional membrane proteins.

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Rima Matar-Merheb

Full Text Available BACKGROUND: Membrane proteins are privileged pharmaceutical targets for which the development of structure-based drug design is challenging. One underlying reason is the fact that detergents do not stabilize membrane domains as efficiently as natural lipids in membranes, often leading to a partial to complete loss of activity/stability during protein extraction and purification and preventing crystallization in an active conformation. METHODOLOGY/PRINCIPAL FINDINGS: Anionic calix[4]arene based detergents (C4Cn, n=1-12 were designed to structure the membrane domains through hydrophobic interactions and a network of salt bridges with the basic residues found at the cytosol-membrane interface of membrane proteins. These compounds behave as surfactants, forming micelles of 5-24 nm, with the critical micellar concentration (CMC being as expected sensitive to pH ranging from 0.05 to 1.5 mM. Both by 1H NMR titration and Surface Tension titration experiments, the interaction of these molecules with the basic amino acids was confirmed. They extract membrane proteins from different origins behaving as mild detergents, leading to partial extraction in some cases. They also retain protein functionality, as shown for BmrA (Bacillus multidrug resistance ATP protein, a membrane multidrug-transporting ATPase, which is particularly sensitive to detergent extraction. These new detergents allow BmrA to bind daunorubicin with a Kd of 12 µM, a value similar to that observed after purification using dodecyl maltoside (DDM. They preserve the ATPase activity of BmrA (which resets the protein to its initial state after drug efflux much more efficiently than SDS (sodium dodecyl sulphate, FC12 (Foscholine 12 or DDM. They also maintain in a functional state the C4Cn-extracted protein upon detergent exchange with FC12. Finally, they promote 3D-crystallization of the membrane protein. CONCLUSION/SIGNIFICANCE: These compounds seem promising to extract in a functional state

Structural fragment clustering reveals novel structural and functional motifs in α-helical transmembrane proteins

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Vassilev Boris

2010-04-01

Full Text Available Abstract Background A large proportion of an organism's genome encodes for membrane proteins. Membrane proteins are important for many cellular processes, and several diseases can be linked to mutations in them. With the tremendous growth of sequence data, there is an increasing need to reliably identify membrane proteins from sequence, to functionally annotate them, and to correctly predict their topology. Results We introduce a technique called structural fragment clustering, which learns sequential motifs from 3D structural fragments. From over 500,000 fragments, we obtain 213 statistically significant, non-redundant, and novel motifs that are highly specific to α-helical transmembrane proteins. From these 213 motifs, 58 of them were assigned to function and checked in the scientific literature for a biological assessment. Seventy percent of the motifs are found in co-factor, ligand, and ion binding sites, 30% at protein interaction interfaces, and 12% bind specific lipids such as glycerol or cardiolipins. The vast majority of motifs (94% appear across evolutionarily unrelated families, highlighting the modularity of functional design in membrane proteins. We describe three novel motifs in detail: (1 a dimer interface motif found in voltage-gated chloride channels, (2 a proton transfer motif found in heme-copper oxidases, and (3 a convergently evolved interface helix motif found in an aspartate symporter, a serine protease, and cytochrome b. Conclusions Our findings suggest that functional modules exist in membrane proteins, and that they occur in completely different evolutionary contexts and cover different binding sites. Structural fragment clustering allows us to link sequence motifs to function through clusters of structural fragments. The sequence motifs can be applied to identify and characterize membrane proteins in novel genomes.

MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

KAUST Repository

Kosinski, Jan; Barbato, Alessandro; Tramontano, Anna

2013-01-01

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships.

KAUST Repository

Kosinski, Jan

2013-02-08

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

DEFF Research Database (Denmark)

Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

2011-01-01

Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

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

Science.gov (United States)

Li, Hui; Liu, Chunmei

2014-06-14

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

NAPS: Network Analysis of Protein Structures

Science.gov (United States)

Chakrabarty, Broto; Parekh, Nita

2016-01-01

Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

Structure-function of proteins interacting with the alpha1 pore-forming subunit of high voltage-activated calcium channel

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Alan eNeely

2014-06-01

Full Text Available Openings of high-voltage-activated calcium channels lead to a transient increase in calcium concentration that in turn activate a plethora of cellular functions, including muscle contraction, secretion and gene transcription. To coordinate all these responses calcium channels form supramolecular assemblies containing effectors and regulatory proteins that couple calcium influx to the downstream signal cascades and to feedback elements. According to the original biochemical characterization of skeletal muscle Dihydropyridine receptors, high-voltage-activated calcium channels are multi-subunit protein complexes consisting of a pore-forming subunit (α1 associated with four additional polypeptide chains β, α2, δ and γ, often referred to as accessory subunits. Twenty-five years after the first purification of a high-voltage calcium channel, the concept of a flexible stoichiometry to expand the repertoire of mechanisms that regulate calcium channel influx has emerged. Several other proteins have been identified that associate directly with the α1-subunit, including calmodulin and multiple members of the small and large GTPase family. Some of these proteins only interact with a subset of α1-subunits and during specific stages of biogenesis. More strikingly, most of the α1-subunit interacting proteins, such as the β-subunit and small GTPases, regulate both gating and trafficking through a variety of mechanisms. Modulation of channel activity covers almost all biophysical properties of the channel. Likewise, regulation of the number of channels in the plasma membrane is performed by altering the release of the α1-subunit from the endoplasmic reticulum, by reducing its degradation or enhancing its recycling back to the cell surface. In this review, we discuss the structural basis, interplay and functional role of selected proteins that interact with the central pore-forming subunit of high-voltage-activated calcium channels.

Structure-function of proteins interacting with the α1 pore-forming subunit of high-voltage-activated calcium channels

Science.gov (United States)

Neely, Alan; Hidalgo, Patricia

2014-01-01

Openings of high-voltage-activated (HVA) calcium channels lead to a transient increase in calcium concentration that in turn activate a plethora of cellular functions, including muscle contraction, secretion and gene transcription. To coordinate all these responses calcium channels form supramolecular assemblies containing effectors and regulatory proteins that couple calcium influx to the downstream signal cascades and to feedback elements. According to the original biochemical characterization of skeletal muscle Dihydropyridine receptors, HVA calcium channels are multi-subunit protein complexes consisting of a pore-forming subunit (α1) associated with four additional polypeptide chains β, α2, δ, and γ, often referred to as accessory subunits. Twenty-five years after the first purification of a high-voltage calcium channel, the concept of a flexible stoichiometry to expand the repertoire of mechanisms that regulate calcium channel influx has emerged. Several other proteins have been identified that associate directly with the α1-subunit, including calmodulin and multiple members of the small and large GTPase family. Some of these proteins only interact with a subset of α1-subunits and during specific stages of biogenesis. More strikingly, most of the α1-subunit interacting proteins, such as the β-subunit and small GTPases, regulate both gating and trafficking through a variety of mechanisms. Modulation of channel activity covers almost all biophysical properties of the channel. Likewise, regulation of the number of channels in the plasma membrane is performed by altering the release of the α1-subunit from the endoplasmic reticulum, by reducing its degradation or enhancing its recycling back to the cell surface. In this review, we discuss the structural basis, interplay and functional role of selected proteins that interact with the central pore-forming subunit of HVA calcium channels. PMID:24917826

The Structure and Function of Non-Collagenous Bone Proteins

Science.gov (United States)

Hook, Magnus

1997-01-01

The long-term goal for this program is to determine the structural and functional relationships of bone proteins and proteins that interact with bone. This information will used to design useful pharmacological compounds that will have a beneficial effect in osteoporotic patients and in the osteoporotic-like effects experienced on long duration space missions. The first phase of this program, funded under a cooperative research agreement with NASA through the Texas Medical Center, aimed to develop powerful recombinant expression systems and purification methods for production of large amounts of target proteins. Proteins expressed in sufficient'amount and purity would be characterized by a variety of structural methods, and made available for crystallization studies. In order to increase the likelihood of crystallization and subsequent high resolution solution of structures, we undertook to develop expression of normal and mutant forms of proteins by bacterial and mammalian cells. In addition to the main goals of this program, we would also be able to provide reagents for other related studies, including development of anti-fibrotic and anti-metastatic therapeutics.

A discriminatory function for prediction of protein-DNA interactions based on alpha shape modeling.

Science.gov (United States)

Zhou, Weiqiang; Yan, Hong

2010-10-15

Protein-DNA interaction has significant importance in many biological processes. However, the underlying principle of the molecular recognition process is still largely unknown. As more high-resolution 3D structures of protein-DNA complex are becoming available, the surface characteristics of the complex become an important research topic. In our work, we apply an alpha shape model to represent the surface structure of the protein-DNA complex and developed an interface-atom curvature-dependent conditional probability discriminatory function for the prediction of protein-DNA interaction. The interface-atom curvature-dependent formalism captures atomic interaction details better than the atomic distance-based method. The proposed method provides good performance in discriminating the native structures from the docking decoy sets, and outperforms the distance-dependent formalism in terms of the z-score. Computer experiment results show that the curvature-dependent formalism with the optimal parameters can achieve a native z-score of -8.17 in discriminating the native structure from the highest surface-complementarity scored decoy set and a native z-score of -7.38 in discriminating the native structure from the lowest RMSD decoy set. The interface-atom curvature-dependent formalism can also be used to predict apo version of DNA-binding proteins. These results suggest that the interface-atom curvature-dependent formalism has a good prediction capability for protein-DNA interactions. The code and data sets are available for download on http://www.hy8.com/bioinformatics.htm kenandzhou@hotmail.com.

Structural similarity-based predictions of protein interactions between HIV-1 and Homo sapiens

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Gomez Shawn M

2010-04-01

Full Text Available Abstract Background In the course of infection, viruses such as HIV-1 must enter a cell, travel to sites where they can hijack host machinery to transcribe their genes and translate their proteins, assemble, and then leave the cell again, all while evading the host immune system. Thus, successful infection depends on the pathogen's ability to manipulate the biological pathways and processes of the organism it infects. Interactions between HIV-encoded and human proteins provide one means by which HIV-1 can connect into cellular pathways to carry out these survival processes. Results We developed and applied a computational approach to predict interactions between HIV and human proteins based on structural similarity of 9 HIV-1 proteins to human proteins having known interactions. Using functional data from RNAi studies as a filter, we generated over 2000 interaction predictions between HIV proteins and 406 unique human proteins. Additional filtering based on Gene Ontology cellular component annotation reduced the number of predictions to 502 interactions involving 137 human proteins. We find numerous known interactions as well as novel interactions showing significant functional relevance based on supporting Gene Ontology and literature evidence. Conclusions Understanding the interplay between HIV-1 and its human host will help in understanding the viral lifecycle and the ways in which this virus is able to manipulate its host. The results shown here provide a potential set of interactions that are amenable to further experimental manipulation as well as potential targets for therapeutic intervention.

Structure and Function of Caltrin (cium ansport hibitor Proteins

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Ernesto Javier Grasso

2017-12-01

Full Text Available Caltrin ( cal cium tr ansport in hibitor is a family of small and basic proteins of the mammalian seminal plasma which bind to sperm cells during ejaculation and inhibit the extracellular Ca 2+ uptake, preventing the premature acrosomal exocytosis and hyperactivation when sperm cells ascend through the female reproductive tract. The binding of caltrin proteins to specific areas of the sperm surface suggests the existence of caltrin receptors, or precise protein-phospholipid arrangements in the sperm membrane, distributed in the regions where Ca 2+ influx may take place. However, the molecular mechanisms of recognition and interaction between caltrin and spermatozoa have not been elucidated. Therefore, the aim of this article is to describe in depth the known structural features and functional properties of caltrin proteins, to find out how they may possibly interact with the sperm membranes to control the intracellular signaling that trigger physiological events required for fertilization.

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

Science.gov (United States)

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

2008-09-01

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

A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling

DEFF Research Database (Denmark)

Blagoev, B.; Kratchmarova, I.; Ong, S.E.

2003-01-01

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...

Membrane proteins bind lipids selectively to modulate their structure and function.

Science.gov (United States)

Laganowsky, Arthur; Reading, Eamonn; Allison, Timothy M; Ulmschneider, Martin B; Degiacomi, Matteo T; Baldwin, Andrew J; Robinson, Carol V

2014-06-05

Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to determine the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate, in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar experiments identify AmtB as being highly selective for phosphatidylglycerol, prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resolution structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane

Bam35 tectivirus intraviral interaction map unveils new function and localization of phage ORFan proteins.

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Berjón-Otero, Mónica; Lechuga, Ana; Mehla, Jitender; Uetz, Peter; Salas, Margarita; Redrejo-Rodríguez, Modesto

2017-07-26

Tectiviridae comprises a group of tail-less, icosahedral, membrane-containing bacteriophages that can be divided into two groups by their hosts, either Gram-negative or Gram-positive bacteria. While the first group is composed of PRD1 and nearly identical well characterized lytic viruses, the second one includes more variable temperate phages, like GIL16 or Bam35, whose hosts are Bacillus cereus and related Gram-positive bacteria.In the genome of Bam35, nearly half of the 32 annotated open reading frames (ORFs) have no homologs in databases (ORFans), being putative proteins of unknown function, which hinders the understanding of their biology. With the aim of increasing the knowledge of the viral proteome, we carried out a comprehensive yeast two-hybrid analysis among all the putative proteins encoded by the Bam35 genome. The resulting protein interactome comprises 76 unique interactions among 24 proteins, of which 12 have an unknown function. These results suggested that the P17 protein is the minor capsid protein of Bam35 and P24 is the penton protein, being the latter also supported by iterative threading protein modeling. Moreover, the inner membrane transglycosylase protein P26 could have an additional structural role. We also detected interactions involving non-structural proteins, such as the DNA binding protein P1 and the genome terminal protein (P4), which was confirmed by co-immunoprecipitation of recombinant proteins. Altogether, our results provide a functional view of the Bam35 viral proteome, with a focus on the composition and organization of the viral particle. IMPORTANCE Tail-less viruses of the family Tectiviridae can infect commensal and pathogenic Gram-positive and Gram-negative bacteria. Moreover, they have been proposed to be at the evolutionary origin of several groups of large eukaryotic DNA viruses and self-replicating plasmids. However, due to their ancient origin and complex diversity, many tectiviral proteins are ORFans of unknown

Functional classification of protein structures by local structure matching in graph representation.

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Mills, Caitlyn L; Garg, Rohan; Lee, Joslynn S; Tian, Liang; Suciu, Alexandru; Cooperman, Gene; Beuning, Penny J; Ondrechen, Mary Jo

2018-03-31

As a result of high-throughput protein structure initiatives, over 14,400 protein structures have been solved by structural genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP-Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP-Func method to our previously reported method, structurally aligned local sites of activity (SALSA), using the ribulose phosphate binding barrel (RPBB), 6-hairpin glycosidase (6-HG), and Concanavalin A-like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP-Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP-Func methods to predict function. Forty-one SG proteins in the RPBB superfamily, nine SG proteins in the 6-HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. © 2018 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Roles of water in protein structure and function studied by molecular liquid theory.

Science.gov (United States)

Imai, Takashi

2009-01-01

The roles of water in the structure and function of proteins have not been completely elucidated. Although molecular simulation has been widely used for the investigation of protein structure and function, it is not always useful for elucidating the roles of water because the effect of water ranges from atomic to thermodynamic level. The three-dimensional reference interaction site model (3D-RISM) theory, which is a statistical-mechanical theory of molecular liquids, can yield the solvation structure at the atomic level and calculate the thermodynamic quantities from the intermolecular potentials. In the last few years, the author and coworkers have succeeded in applying the 3D-RISM theory to protein aqueous solution systems and demonstrated that the theory is useful for investigating the roles of water. This article reviews some of the recent applications and findings, which are concerned with molecular recognition by protein, protein folding, and the partial molar volume of protein which is related to the pressure effect on protein.

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

Science.gov (United States)

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

Structure/Function Analysis of Protein-Protein Interactions and Role of Dynamic Motions in Mercuric Ion Reductase

Energy Technology Data Exchange (ETDEWEB)

Miller, Susan M.

2005-05-18

This report summarizes the activities and findings of our structure/function studies of the bacterial detoxification enzyme mercuric ion reductase. The objectives of the work were to obtain crystal structure information for the catalytic core of this enzyme, use the information to investigate the importance of specific parts of the enzyme to its function, and investigate the role of one domain of the enzyme in its function within cells. We describe the accomplishments towards these goals including many structures of the wild type and mutant forms of the enzyme that highlight its interactions with its Hg(II) substrate, elucidation of the role of the N-terminal domain in vitro and in vivo, and elucidation of the roles of at two conserved residues in the core in the mechanism of catalysis.

Studying Membrane Protein Structure and Function Using Nanodiscs

DEFF Research Database (Denmark)

Huda, Pie

The structure and dynamic of membrane proteins can provide valuable information about general functions, diseases and effects of various drugs. Studying membrane proteins are a challenge as an amphiphilic environment is necessary to stabilise the protein in a functionally and structurally relevant...... form. This is most typically achieved through the use of detergent based reconstitution systems. However, time and again such systems fail to provide a suitable environment causing aggregation and inactivation. Nanodiscs are self-assembled lipoproteins containing two membrane scaffold proteins...... and a lipid bilayer in defined nanometer size, which can act as a stabiliser for membrane proteins. This enables both functional and structural investigation of membrane proteins in a detergent free environment which is closer to the native situation. Understanding the self-assembly of nanodiscs is important...

Intercellular protein-protein interactions at synapses.

Science.gov (United States)

Yang, Xiaofei; Hou, Dongmei; Jiang, Wei; Zhang, Chen

2014-06-01

Chemical synapses are asymmetric intercellular junctions through which neurons send nerve impulses to communicate with other neurons or excitable cells. The appropriate formation of synapses, both spatially and temporally, is essential for brain function and depends on the intercellular protein-protein interactions of cell adhesion molecules (CAMs) at synaptic clefts. The CAM proteins link pre- and post-synaptic sites, and play essential roles in promoting synapse formation and maturation, maintaining synapse number and type, accumulating neurotransmitter receptors and ion channels, controlling neuronal differentiation, and even regulating synaptic plasticity directly. Alteration of the interactions of CAMs leads to structural and functional impairments, which results in many neurological disorders, such as autism, Alzheimer's disease and schizophrenia. Therefore, it is crucial to understand the functions of CAMs during development and in the mature neural system, as well as in the pathogenesis of some neurological disorders. Here, we review the function of the major classes of CAMs, and how dysfunction of CAMs relates to several neurological disorders.

The contact activation proteins: a structure/function overview

NARCIS (Netherlands)

Meijers, J. C.; McMullen, B. A.; Bouma, B. N.

1992-01-01

In recent years, extensive knowledge has been obtained on the structure/function relationships of blood coagulation proteins. In this overview, we present recent developments on the structure/function relationships of the contact activation proteins: factor XII, high molecular weight kininogen,

Structure and Functions of Linker Histones.

Science.gov (United States)

Lyubitelev, A V; Nikitin, D V; Shaytan, A K; Studitsky, V M; Kirpichnikov, M P

2016-03-01

Linker histones such as variants H1, H5, and other similar proteins play an important role in regulation of chromatin structure and dynamics. However, interactions of linker histones with DNA and proteins, as well as specific functions of their different variants, are poorly studied. This is because they acquire tertiary structure only when interacting with a nucleosome, and because of limitations of currently available methods. However, deeper investigation of linker histones and their interactions with other proteins will address a number of important questions - from structure of compacted chromatin to regulation of early embryogenesis. In this review, structures of histone H1 variants and its interaction with chromatin DNA are considered. A possible functional significance of different H1 variants, a role of these proteins in maintaining interphase chromatin structure, and interactions of linker histones with other cellular proteins are also discussed.

Integration of Structural Dynamics and Molecular Evolution via Protein Interaction Networks: A New Era in Genomic Medicine

Science.gov (United States)

Kumar, Avishek; Butler, Brandon M.; Kumar, Sudhir; Ozkan, S. Banu

2016-01-01

Summary Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. PMID:26684487

Structure and function of nanoparticle-protein conjugates

International Nuclear Information System (INIS)

Aubin-Tam, M-E; Hamad-Schifferli, K

2008-01-01

Conjugation of proteins to nanoparticles has numerous applications in sensing, imaging, delivery, catalysis, therapy and control of protein structure and activity. Therefore, characterizing the nanoparticle-protein interface is of great importance. A variety of covalent and non-covalent linking chemistries have been reported for nanoparticle attachment. Site-specific labeling is desirable in order to control the protein orientation on the nanoparticle, which is crucial in many applications such as fluorescence resonance energy transfer. We evaluate methods for successful site-specific attachment. Typically, a specific protein residue is linked directly to the nanoparticle core or to the ligand. As conjugation often affects the protein structure and function, techniques to probe structure and activity are assessed. We also examine how molecular dynamics simulations of conjugates would complete those experimental techniques in order to provide atomistic details on the effect of nanoparticle attachment. Characterization studies of nanoparticle-protein complexes show that the structure and function are influenced by the chemistry of the nanoparticle ligand, the nanoparticle size, the nanoparticle material, the stoichiometry of the conjugates, the labeling site on the protein and the nature of the linkage (covalent versus non-covalent)

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

Directory of Open Access Journals (Sweden)

Yushen Du

2016-11-01

Full Text Available Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp, we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

A conserved mammalian protein interaction network.

Directory of Open Access Journals (Sweden)

Åsa Pérez-Bercoff

Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

Globular and disordered – the non-identical twins in protein-protein interactions

Directory of Open Access Journals (Sweden)

Kaare eTeilum

2015-07-01

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.

Dendrimer-protein interactions versus dendrimer-based nanomedicine.

Science.gov (United States)

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

2017-04-01

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

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

Science.gov (United States)

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

2016-02-15

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

Chlamydia trachomatis protein CT009 is a structural and functional homolog to the key morphogenesis component RodZ and interacts with division septal plane localized MreB.

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Kemege, Kyle E; Hickey, John M; Barta, Michael L; Wickstrum, Jason; Balwalli, Namita; Lovell, Scott; Battaile, Kevin P; Hefty, P Scott

2015-02-01

Cell division in Chlamydiae is poorly understood as apparent homologs to most conserved bacterial cell division proteins are lacking and presence of elongation (rod shape) associated proteins indicate non-canonical mechanisms may be employed. The rod-shape determining protein MreB has been proposed as playing a unique role in chlamydial cell division. In other organisms, MreB is part of an elongation complex that requires RodZ for proper function. A recent study reported that the protein encoded by ORF CT009 interacts with MreB despite low sequence similarity to RodZ. The studies herein expand on those observations through protein structure, mutagenesis and cellular localization analyses. Structural analysis indicated that CT009 shares high level of structural similarity to RodZ, revealing the conserved orientation of two residues critical for MreB interaction. Substitutions eliminated MreB protein interaction and partial complementation provided by CT009 in RodZ deficient Escherichia coli. Cellular localization analysis of CT009 showed uniform membrane staining in Chlamydia. This was in contrast to the localization of MreB, which was restricted to predicted septal planes. MreB localization to septal planes provides direct experimental observation for the role of MreB in cell division and supports the hypothesis that it serves as a functional replacement for FtsZ in Chlamydia. © 2014 John Wiley & Sons Ltd.

Chlamydia trachomatis protein CT009 is a structural and functional homolog to the key morphogenesis component RodZ and interacts with division septal plane localized MreB

Science.gov (United States)

Kemege, Kyle E.; Hickey, John M.; Barta, Michael L.; Wickstrum, Jason; Balwalli, Namita; Lovell, Scott; Battaile, Kevin P.; Hefty, P. Scott

2015-01-01

Summary Cell division in Chlamydiae is poorly understood as apparent homologs to most conserved bacterial cell division proteins are lacking and presence of elongation (rod shape) associated proteins indicate non-canonical mechanisms may be employed. The rod-shape determining protein MreB has been proposed as playing a unique role in chlamydial cell division. In other organisms, MreB is part of an elongation complex that requires RodZ for proper function. A recent study reported that the protein encoded by ORF CT009 interacts with MreB despite low sequence similarity to RodZ. The studies herein expand on those observations through protein structure, mutagenesis, and cellular localization analyses. Structural analysis indicated that CT009 shares high level of structural similarity to RodZ, revealing the conserved orientation of two residues critical for MreB interaction. Substitutions eliminated MreB protein interaction and partial complementation provided by CT009 in RodZ deficient E. coli. Cellular localization analysis of CT009 showed uniform membrane staining in Chlamydia. This was in contrast to the localization of MreB, which was restricted to predicted septal planes. MreB localization to septal planes provides direct experimental observation for the role of MreB in cell division and supports the hypothesis that it serves as a functional replacement for FtsZ in Chlamydia. PMID:25382739

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

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Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein. In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

Structure of metabotropic glutamate receptor C-terminal domains in contact with interacting proteins

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Ralf eEnz

2012-04-01

Full Text Available Metabotropic glutamate receptors (mGluRs regulate intracellular signal pathways that control several physiological tasks, including neuronal excitability, learning and memory. This is achieved by the formation of synaptic signal complexes, in which mGluRs assemble with functionally related proteins such as enzymes, scaffolds and cytoskeletal anchor proteins. Thus, mGluR associated proteins actively participate in the regulation of glutamatergic neurotransmission. Importantly, dysfunction of mGluRs and interacting proteins may lead to impaired signal transduction and finally result in neurological disorders, e.g. night blindness, addiction, epilepsy, schizophrenia, autism spectrum disorders and Parkinson´s disease. In contrast to solved crystal structures of extracellular N-terminal domains of some mGluR types, only a few studies analyzed the conformation of intracellular receptor domains. Intracellular C-termini of most mGluR types are subject to alternative splicing and can be further modified by phosphorylation and SUMOylation. In this way, diverse interaction sites for intracellular proteins that bind to and regulate the glutamate receptors are generated. Indeed, most of the known mGluR binding partners interact with the receptors´ C-terminal domains. Within the last years, different laboratories analyzed the structure of these domains and described the geometry of the contact surface between mGluR C-termini and interacting proteins. Here, I will review recent progress in the structure characterization of mGluR C-termini and provide an up-to-date summary of the geometry of these domains in contact with binding partners.

Structural insights, protein-ligand interactions and spectroscopic characterization of isoformononetin

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Srivastava, Anubha; Singh, Harshita; Mishra, Rashmi; Dev, Kapil; Tandon, Poonam; Maurya, Rakesh

2017-04-01

Isoformononetin, a methoxylated isoflavone present in medicinal plants, has non-estrogenic bone forming effect via differential mitogen-activated protein kinase (MAPK) signaling. Spectroscopic (FT-Raman, FT-IR, UV-vis and NMR spectra) and quantum chemical calculations using density functional theory (DFT) and 6-311++G(d,p) as a large basis set have been employed to study the structural and electronic properties of isoformononetin. A detailed conformational analysis is performed to determine the stability among conformers and the various possibilities of intramolecular hydrogen bonding formation. Molecular docking studies with different protein kinases were performed on isoformononetin and previously studied isoflavonoid, formononetin in order to understand their inhibitory nature and the effect of functional groups on osteogenic or osteoporosis associated proteins. It is found that the oxygen atoms of methoxy, hydroxyl groups attached to phenyl rings R1, R3 and carbonyl group attached to pyran ring R2, play a major role in binding with the protein kinases that is responsible for the osteoporosis; however, no hydrophobic interactions are observed between rings of ligand and protein. The electronic properties such as HOMO and LUMO energies were determined by time-dependent TD-DFT which predict that conformer II is a little bit more stable and chemically low reactive than conformer I of isoformononetin. To estimate the structure-activity relationship, the molecular electrostatic potential (MEP) surface map, and reactivity descriptors are calculated from the optimized geometry of the molecule. From these results, it is also found that isoformononetin is kinetically more stable, less toxic, weak electrophile and chemically less reactive than formononetin. The atoms in molecules and natural bond orbital analysis are applied for the detailed analysis of intra and intermolecular hydrogen bonding interactions.

Structure-function correlations of pulmonary surfactant protein SP-B and the saposin-like family of proteins.

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Olmeda, Bárbara; García-Álvarez, Begoña; Pérez-Gil, Jesús

2013-03-01

Pulmonary surfactant is a lipid-protein complex secreted by the respiratory epithelium of mammalian lungs, which plays an essential role in stabilising the alveolar surface and so reducing the work of breathing. The surfactant protein SP-B is part of this complex, and is strictly required for the assembly of pulmonary surfactant and its extracellular development to form stable surface-active films at the air-liquid alveolar interface, making the lack of SP-B incompatible with life. In spite of its physiological importance, a model for the structure and the mechanism of action of SP-B is still needed. The sequence of SP-B is homologous to that of the saposin-like family of proteins, which are membrane-interacting polypeptides with apparently diverging activities, from the co-lipase action of saposins to facilitate the degradation of sphingolipids in the lysosomes to the cytolytic actions of some antibiotic proteins, such as NK-lysin and granulysin or the amoebapore of Entamoeba histolytica. Numerous studies on the interactions of these proteins with membranes have still not explained how a similar sequence and a potentially related fold can sustain such apparently different activities. In the present review, we have summarised the most relevant features of the structure, lipid-protein and protein-protein interactions of SP-B and the saposin-like family of proteins, as a basis to propose an integrated model and a common mechanistic framework of the apparent functional versatility of the saposin fold.

Integration of structural dynamics and molecular evolution via protein interaction networks: a new era in genomic medicine.

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Kumar, Avishek; Butler, Brandon M; Kumar, Sudhir; Ozkan, S Banu

2015-12-01

Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structure-function analysis and genetic interactions of the SmG, SmE, and SmF subunits of the yeast Sm protein ring.

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Schwer, Beate; Kruchten, Joshua; Shuman, Stewart

2016-09-01

A seven-subunit Sm protein ring forms a core scaffold of the U1, U2, U4, and U5 snRNPs that direct pre-mRNA splicing. Using human snRNP structures to guide mutagenesis in Saccharomyces cerevisiae, we gained new insights into structure-function relationships of the SmG, SmE, and SmF subunits. An alanine scan of 19 conserved amino acids of these three proteins, comprising the Sm RNA binding sites or inter-subunit interfaces, revealed that, with the exception of Arg74 in SmF, none are essential for yeast growth. Yet, for SmG, SmE, and SmF, as for many components of the yeast spliceosome, the effects of perturbing protein-RNA and protein-protein interactions are masked by built-in functional redundancies of the splicing machine. For example, tests for genetic interactions with non-Sm splicing factors showed that many benign mutations of SmG, SmE, and SmF (and of SmB and SmD3) were synthetically lethal with null alleles of U2 snRNP subunits Lea1 and Msl1. Tests of pairwise combinations of SmG, SmE, SmF, SmB, and SmD3 alleles highlighted the inherent redundancies within the Sm ring, whereby simultaneous mutations of the RNA binding sites of any two of the Sm subunits are lethal. Our results suggest that six intact RNA binding sites in the Sm ring suffice for function but five sites may not. © 2016 Schwer et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Function and structure of GFP-like proteins in the protein data bank.

Science.gov (United States)

Ong, Wayne J-H; Alvarez, Samuel; Leroux, Ivan E; Shahid, Ramza S; Samma, Alex A; Peshkepija, Paola; Morgan, Alicia L; Mulcahy, Shawn; Zimmer, Marc

2011-04-01

The RCSB protein databank contains 266 crystal structures of green fluorescent proteins (GFP) and GFP-like proteins. This is the first systematic analysis of all the GFP-like structures in the pdb. We have used the pdb to examine the function of fluorescent proteins (FP) in nature, aspects of excited state proton transfer (ESPT) in FPs, deformation from planarity of the chromophore and chromophore maturation. The conclusions reached in this review are that (1) The lid residues are highly conserved, particularly those on the "top" of the β-barrel. They are important to the function of GFP-like proteins, perhaps in protecting the chromophore or in β-barrel formation. (2) The primary/ancestral function of GFP-like proteins may well be to aid in light induced electron transfer. (3) The structural prerequisites for light activated proton pumps exist in many structures and it's possible that like bioluminescence, proton pumps are secondary functions of GFP-like proteins. (4) In most GFP-like proteins the protein matrix exerts a significant strain on planar chromophores forcing most GFP-like proteins to adopt non-planar chromophores. These chromophoric deviations from planarity play an important role in determining the fluorescence quantum yield. (5) The chemospatial characteristics of the chromophore cavity determine the isomerization state of the chromophore. The cavities of highlighter proteins that can undergo cis/trans isomerization have chemospatial properties that are common to both cis and trans GFP-like proteins.

Analysis of intraviral protein-protein interactions of the SARS coronavirus ORFeome.

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Albrecht von Brunn

2007-05-01

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.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

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Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is

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

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

2017-10-03

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

Patchwork structure-function analysis of the Sendai virus matrix protein.

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Mottet-Osman, Geneviève; Miazza, Vincent; Vidalain, Pierre-Olivier; Roux, Laurent

2014-09-01

Paramyxoviruses contain a bi-lipidic envelope decorated by two transmembrane glycoproteins and carpeted on the inner surface with a layer of matrix proteins (M), thought to bridge the glycoproteins with the viral nucleocapsids. To characterize M structure-function features, a set of M domains were mutated or deleted. The genes encoding these modified M were incorporated into recombinant Sendai viruses and expressed as supplemental proteins. Using a method of integrated suppression complementation system (ISCS), the functions of these M mutants were analyzed in the context of the infection. Cellular membrane association, localization at the cell periphery, nucleocapsid binding, cellular protein interactions and promotion of viral particle formation were characterized in relation with the mutations. At the end, lack of nucleocapsid binding go together with lack of cell surface localization and both features definitely correlate with loss of M global function estimated by viral particle production. Copyright © 2014 Elsevier Inc. All rights reserved.

Conformational transitions and interactions underlying the function of membrane embedded receptor protein kinases.

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Bocharov, Eduard V; Sharonov, Georgy V; Bocharova, Olga V; Pavlov, Konstantin V

2017-09-01

Among membrane receptors, the single-span receptor protein kinases occupy a broad but specific functional niche determined by distinctive features of the underlying transmembrane signaling mechanisms that are briefly overviewed on the basis of some of the most representative examples, followed by a more detailed discussion of several hierarchical levels of organization and interactions involved. All these levels, including single-molecule interactions (e.g., dimerization, liganding, chemical modifications), local processes (e.g. lipid membrane perturbations, cytoskeletal interactions), and larger scale phenomena (e.g., effects of membrane surface shape or electrochemical potential gradients) appear to be closely integrated to achieve the observed diversity of the receptor functioning. Different species of receptor protein kinases meet their specific functional demands through different structural features defining their responses to stimulation, but certain common patterns exist. Signaling by receptor protein kinases is typically associated with the receptor dimerization and clustering, ligand-induced rearrangements of receptor domains through allosteric conformational transitions with involvement of lipids, release of the sequestered lipids, restriction of receptor diffusion, cytoskeleton and membrane shape remodeling. Understanding of complexity and continuity of the signaling processes can help identifying currently neglected opportunities for influencing the receptor signaling with potential therapeutic implications. This article is part of a Special Issue entitled: Interactions between membrane receptors in cellular membranes edited by Kalina Hristova. Copyright © 2017 Elsevier B.V. All rights reserved.

DNA mimic proteins: functions, structures, and bioinformatic analysis.

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Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J

2014-05-13

DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.

Small sets of interacting proteins suggest functional linkage mechanisms via Bayesian analogical reasoning.

Science.gov (United States)

Airoldi, Edoardo M; Heller, Katherine A; Silva, Ricardo

2011-07-01

Proteins and protein complexes coordinate their activity to execute cellular functions. In a number of experimental settings, including synthetic genetic arrays, genetic perturbations and RNAi screens, scientists identify a small set of protein interactions of interest. A working hypothesis is often that these interactions are the observable phenotypes of some functional process, which is not directly observable. Confirmatory analysis requires finding other pairs of proteins whose interaction may be additional phenotypical evidence about the same functional process. Extant methods for finding additional protein interactions rely heavily on the information in the newly identified set of interactions. For instance, these methods leverage the attributes of the individual proteins directly, in a supervised setting, in order to find relevant protein pairs. A small set of protein interactions provides a small sample to train parameters of prediction methods, thus leading to low confidence. We develop RBSets, a computational approach to ranking protein interactions rooted in analogical reasoning; that is, the ability to learn and generalize relations between objects. Our approach is tailored to situations where the training set of protein interactions is small, and leverages the attributes of the individual proteins indirectly, in a Bayesian ranking setting that is perhaps closest to propensity scoring in mathematical psychology. We find that RBSets leads to good performance in identifying additional interactions starting from a small evidence set of interacting proteins, for which an underlying biological logic in terms of functional processes and signaling pathways can be established with some confidence. Our approach is scalable and can be applied to large databases with minimal computational overhead. Our results suggest that analogical reasoning within a Bayesian ranking problem is a promising new approach for real-time biological discovery. Java code is available at

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

Science.gov (United States)

Hu, Xiaotang; Li, Hongbin

2014-10-01

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

Usher protein functions in hair cells and photoreceptors

OpenAIRE

Cosgrove, Dominic; Zallocchi, Marisa

2013-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber,...

The simulation approach to lipid-protein interactions.

Science.gov (United States)

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

2013-01-01

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

A method for partitioning the information contained in a protein sequence between its structure and function.

Science.gov (United States)

Possenti, Andrea; Vendruscolo, Michele; Camilloni, Carlo; Tiana, Guido

2018-05-23

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Analysis of Protein-Membrane Interactions

DEFF Research Database (Denmark)

Kemmer, Gerdi Christine

Cellular membranes are complex structures, consisting of hundreds of different lipids and proteins. These membranes act as barriers between distinct environments, constituting hot spots for many essential functions of the cell, including signaling, energy conversion, and transport. These functions....... 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...... 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...

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

Science.gov (United States)

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

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

Directory of Open Access Journals (Sweden)

Jaume Torres

2015-06-01

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.

Structure and function of A41, a vaccinia virus chemokine binding protein.

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Mohammad W Bahar

2008-01-01

Full Text Available The vaccinia virus (VACV A41L gene encodes a secreted 30 kDa glycoprotein that is nonessential for virus replication but affects the host response to infection. The A41 protein shares sequence similarity with another VACV protein that binds CC chemokines (called vCKBP, or viral CC chemokine inhibitor, vCCI, and strains of VACV lacking the A41L gene induced stronger CD8+ T-cell responses than control viruses expressing A41. Using surface plasmon resonance, we screened 39 human and murine chemokines and identified CCL21, CCL25, CCL26 and CCL28 as A41 ligands, with Kds of between 8 nM and 118 nM. Nonetheless, A41 was ineffective at inhibiting chemotaxis induced by these chemokines, indicating it did not block the interaction of these chemokines with their receptors. However the interaction of A41 and chemokines was inhibited in a dose-dependent manner by heparin, suggesting that A41 and heparin bind to overlapping sites on these chemokines. To better understand the mechanism of action of A41 its crystal structure was solved to 1.9 A resolution. The protein has a globular beta sandwich structure similar to that of the poxvirus vCCI family of proteins, but there are notable structural differences, particularly in surface loops and electrostatic charge distribution. Structural modelling suggests that the binding paradigm as defined for the vCCI-chemokine interaction is likely to be conserved between A41 and its chemokine partners. Additionally, sequence analysis of chemokines binding to A41 identified a signature for A41 binding. The biological and structural data suggest that A41 functions by forming moderately strong (nM interactions with certain chemokines, sufficient to interfere with chemokine-glycosaminoglycan interactions at the cell surface (microM-nM and thereby to destroy the chemokine concentration gradient, but not strong enough to disrupt the (pM chemokine-chemokine receptor interactions.

Functional mapping of protein-protein interactions in an enzyme complex by directed evolution.

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Kathrin Roderer

Full Text Available The shikimate pathway enzyme chorismate mutase converts chorismate into prephenate, a precursor of Tyr and Phe. The intracellular chorismate mutase (MtCM of Mycobacterium tuberculosis is poorly active on its own, but becomes >100-fold more efficient upon formation of a complex with the first enzyme of the shikimate pathway, 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase (MtDS. The crystal structure of the enzyme complex revealed involvement of C-terminal MtCM residues with the MtDS interface. Here we employed evolutionary strategies to probe the tolerance to substitution of the C-terminal MtCM residues from positions 84-90. Variants with randomized positions were subjected to stringent selection in vivo requiring productive interactions with MtDS for survival. Sequence patterns identified in active library members coincide with residue conservation in natural chorismate mutases of the AroQδ subclass to which MtCM belongs. An Arg-Gly dyad at positions 85 and 86, invariant in AroQδ sequences, was intolerant to mutation, whereas Leu88 and Gly89 exhibited a preference for small and hydrophobic residues in functional MtCM-MtDS complexes. In the absence of MtDS, selection under relaxed conditions identifies positions 84-86 as MtCM integrity determinants, suggesting that the more C-terminal residues function in the activation by MtDS. Several MtCM variants, purified using a novel plasmid-based T7 RNA polymerase gene expression system, showed that a diminished ability to physically interact with MtDS correlates with reduced activatability and feedback regulatory control by Tyr and Phe. Mapping critical protein-protein interaction sites by evolutionary strategies may pinpoint promising targets for drugs that interfere with the activity of protein complexes.

Functional mapping of protein-protein interactions in an enzyme complex by directed evolution.

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Roderer, Kathrin; Neuenschwander, Martin; Codoni, Giosiana; Sasso, Severin; Gamper, Marianne; Kast, Peter

2014-01-01

The shikimate pathway enzyme chorismate mutase converts chorismate into prephenate, a precursor of Tyr and Phe. The intracellular chorismate mutase (MtCM) of Mycobacterium tuberculosis is poorly active on its own, but becomes >100-fold more efficient upon formation of a complex with the first enzyme of the shikimate pathway, 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase (MtDS). The crystal structure of the enzyme complex revealed involvement of C-terminal MtCM residues with the MtDS interface. Here we employed evolutionary strategies to probe the tolerance to substitution of the C-terminal MtCM residues from positions 84-90. Variants with randomized positions were subjected to stringent selection in vivo requiring productive interactions with MtDS for survival. Sequence patterns identified in active library members coincide with residue conservation in natural chorismate mutases of the AroQδ subclass to which MtCM belongs. An Arg-Gly dyad at positions 85 and 86, invariant in AroQδ sequences, was intolerant to mutation, whereas Leu88 and Gly89 exhibited a preference for small and hydrophobic residues in functional MtCM-MtDS complexes. In the absence of MtDS, selection under relaxed conditions identifies positions 84-86 as MtCM integrity determinants, suggesting that the more C-terminal residues function in the activation by MtDS. Several MtCM variants, purified using a novel plasmid-based T7 RNA polymerase gene expression system, showed that a diminished ability to physically interact with MtDS correlates with reduced activatability and feedback regulatory control by Tyr and Phe. Mapping critical protein-protein interaction sites by evolutionary strategies may pinpoint promising targets for drugs that interfere with the activity of protein complexes.

A Structural Perspective on the Modulation of Protein-Protein Interactions with Small Molecules.

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Demirel, Habibe Cansu; Dogan, Tunca; Tuncbag, Nurcan

2018-05-31

Protein-protein interactions (PPIs) are the key components in many cellular processes including signaling pathways, enzymatic reactions and epigenetic regulation. Abnormal interactions of some proteins may be pathogenic and cause various disorders including cancer and neurodegenerative diseases. Although inhibiting PPIs with small molecules is a challenging task, it gained an increasing interest because of its strong potential for drug discovery and design. The knowledge of the interface as well as the structural and chemical characteristics of the PPIs and their roles in the cellular pathways are necessary for a rational design of small molecules to modulate PPIs. In this study, we review the recent progress in the field and detail the physicochemical properties of PPIs including binding hot spots with a focus on structural methods. Then, we review recent approaches for structural prediction of PPIs. Finally, we revisit the concept of targeting PPIs in a systems biology perspective and we refer to the non-structural approaches, usually employed when the structural information is not present. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structural deformation upon protein-protein interaction: a structural alphabet approach.

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Martin, Juliette; Regad, Leslie; Lecornet, Hélène; Camproux, Anne-Claude

2008-02-28

In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

Structural deformation upon protein-protein interaction: A structural alphabet approach

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Lecornet Hélène

2008-02-01

Full Text Available Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%. This proportion is even greater in the interface regions (41%. Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Conclusion Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

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Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

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Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

Functional modules by relating protein interaction networks and gene expression.

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Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Probing hydrogen bonding interactions and proton transfer in proteins

Science.gov (United States)

Nie, Beining

Scope and method of study. Hydrogen bonding is a fundamental element in protein structure and function. Breaking a single hydrogen bond may impair the stability of a protein. It is therefore important to probe dynamic changes in hydrogen bonding interactions during protein folding and function. Time-resolved Fourier transform infrared spectroscopy is highly sensitive to hydrogen bonding interactions. However, it lacks quantitative correlation between the vibrational frequencies and the number, type, and strength of hydrogen bonding interactions of ionizable and polar residues. We employ quantum physics theory based ab initio calculations to study the effects of hydrogen bonding interactions on vibrational frequencies of Asp, Glu, and Tyr residues and to develop vibrational spectral markers for probing hydrogen bonding interactions using infrared spectroscopy. In addition, proton transfer process plays a crucial role in a wide range of energy transduction, signal transduction, and enzymatic reactions. We study the structural basis for proton transfer using photoactive yellow protein as an excellent model system. Molecular dynamics simulation is employed to investigate the structures of early intermediate states. Quantum theory based ab initio calculations are used to study the impact of hydrogen bond interactions on proton affinity and proton transfer. Findings and conclusions. Our extensive density function theory based calculations provide rich structural, spectral, and energetic information on hydrogen bonding properties of protonated side chain groups of Asp/Glu and Tyr. We developed vibrational spectral markers and 2D FTIR spectroscopy for structural characterization on the number and the type of hydrogen bonding interactions of the COOH group of Asp/Glu and neutral phenolic group of Tyr. These developments greatly enhance the power of time-resolved FTIR spectroscopy as a major experimental tool for structural characterization of functionally important

Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

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Peiying Ruan

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

Protein annotation from protein interaction networks and Gene Ontology.

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Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Crystal Structure of the Human, FIC-Domain Containing Protein HYPE and Implications for Its Functions

Science.gov (United States)

Bunney, Tom D.; Cole, Ambrose R.; Broncel, Malgorzata; Esposito, Diego; Tate, Edward W.; Katan, Matilda

2014-01-01

Summary Protein AMPylation, the transfer of AMP from ATP to protein targets, has been recognized as a new mechanism of host-cell disruption by some bacterial effectors that typically contain a FIC-domain. Eukaryotic genomes also encode one FIC-domain protein, HYPE, which has remained poorly characterized. Here we describe the structure of human HYPE, solved by X-ray crystallography, representing the first structure of a eukaryotic FIC-domain protein. We demonstrate that HYPE forms stable dimers with structurally and functionally integrated FIC-domains and with TPR-motifs exposed for protein-protein interactions. As HYPE also uniquely possesses a transmembrane helix, dimerization is likely to affect its positioning and function in the membrane vicinity. The low rate of autoAMPylation of the wild-type HYPE could be due to autoinhibition, consistent with the mechanism proposed for a number of putative FIC AMPylators. Our findings also provide a basis to further consider possible alternative cofactors of HYPE and distinct modes of target-recognition. PMID:25435325

Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

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Peng Liu

2015-01-01

Full Text Available 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 network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

Quality assessment of protein model-structures based on structural and functional similarities.

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Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and

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

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

2011-01-01

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

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

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

2013-03-01

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

Scoring protein interaction decoys using exposed residues (SPIDER): a novel multibody interaction scoring function based on frequent geometric patterns of interfacial residues.

Science.gov (United States)

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2012-08-01

Accurate prediction of the structure of protein-protein complexes in computational docking experiments remains a formidable challenge. It has been recognized that identifying native or native-like poses among multiple decoys is the major bottleneck of the current scoring functions used in docking. We have developed a novel multibody pose-scoring function that has no theoretical limit on the number of residues contributing to the individual interaction terms. We use a coarse-grain representation of a protein-protein complex where each residue is represented by its side chain centroid. We apply a computational geometry approach called Almost-Delaunay tessellation that transforms protein-protein complexes into a residue contact network, or an undirectional graph where vertex-residues are nodes connected by edges. This treatment forms a family of interfacial graphs representing a dataset of protein-protein complexes. We then employ frequent subgraph mining approach to identify common interfacial residue patterns that appear in at least a subset of native protein-protein interfaces. The geometrical parameters and frequency of occurrence of each "native" pattern in the training set are used to develop the new SPIDER scoring function. SPIDER was validated using standard "ZDOCK" benchmark dataset that was not used in the development of SPIDER. We demonstrate that SPIDER scoring function ranks native and native-like poses above geometrical decoys and that it exceeds in performance a popular ZRANK scoring function. SPIDER was ranked among the top scoring functions in a recent round of CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods. Copyright © 2012 Wiley Periodicals, Inc.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

Science.gov (United States)

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Interactive protein manipulation

International Nuclear Information System (INIS)

2003-01-01

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

Our interests in protein-protein interactions

Indian Academy of Sciences (India)

protein interactions. Evolution of P-P partnerships. Evolution of P-P structures. Evolutionary dynamics of P-P interactions. Dynamics of P-P interaction network. Host-pathogen interactions. CryoEM mapping of gigantic protein assemblies.

Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

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Oyang Yen-Jen

2010-10-01

Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

Large-scale prediction of drug-target interactions using protein sequences and drug topological structures

Energy Technology Data Exchange (ETDEWEB)

Cao Dongsheng [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Liu Shao [Xiangya Hospital, Central South University, Changsha 410008 (China); Xu Qingsong [School of Mathematical Sciences and Computing Technology, Central South University, Changsha 410083 (China); Lu Hongmei; Huang Jianhua [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Hu Qiannan [Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, and Wuhan University School of Pharmaceutical Sciences, Wuhan 430071 (China); Liang Yizeng, E-mail: yizeng_liang@263.net [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China)

2012-11-08

Highlights: Black-Right-Pointing-Pointer Drug-target interactions are predicted using an extended SAR methodology. Black-Right-Pointing-Pointer A drug-target interaction is regarded as an event triggered by many factors. Black-Right-Pointing-Pointer Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. Black-Right-Pointing-Pointer Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug-target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug-target interactions in a timely manner. In this article, we aim at extending current structure-activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug-target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug-target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug

Interaction of the chaperone calreticulin with proteins and peptides of different structural classes

DEFF Research Database (Denmark)

Duus, K; Sandhu, N; Jørgensen, C S

2009-01-01

The interaction of calreticulin with native and denatured forms and polypeptides in proteolytic digests of proteins representing structural classes of all-alpha-helix (hemoglobin, serum albumin), all-beta-sheet (IgG) and alpha-helix + beta-sheets (lysozyme, ovalbumin) was investigated. The binding...... of calreticulin to denatured proteins was found to depend on conformation and structural class of the protein. No interaction was observed with the native proteins, whereas binding was seen for the denatured proteins, the order of interaction being lysozyme = IgG > ovalbumin >> hemoglobin = serum albumin....... Moreover, the interaction between calreticulin and the heat-denatured proteins depended on the temperature and time used for denaturation and the degree of proteolytic fragmentation. Calreticulin bound well to peptides in proteolytic digests from protease K or chymotrypsin treatment of lysozyme, Ig...

Protein-protein interaction site predictions with three-dimensional probability distributions of interacting atoms on protein surfaces.

Directory of Open Access Journals (Sweden)

Ching-Tai Chen

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

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

Science.gov (United States)

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

2012-01-01

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

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

NARCIS (Netherlands)

Visscher, Koen M.; Kastritis, Panagiotis L.|info:eu-repo/dai/nl/315886668; Bonvin, Alexandre M J J|info:eu-repo/dai/nl/113691238

2015-01-01

Protein-protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure-based drug design methods, as well as design of de novo

Interactive protein manipulation

Energy Technology Data Exchange (ETDEWEB)

SNCrivelli@lbl.gov

2003-07-01

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.

The unique architecture and function of cellulose-interacting proteins in oomycetes revealed by genomic and structural analyses

Directory of Open Access Journals (Sweden)

Larroque Mathieu

2012-11-01

Full Text Available Abstract Background Oomycetes are fungal-like microorganisms evolutionary distinct from true fungi, belonging to the Stramenopile lineage and comprising major plant pathogens. Both oomycetes and fungi express proteins able to interact with cellulose, a major component of plant and oomycete cell walls, through the presence of carbohydrate-binding module belonging to the family 1 (CBM1. Fungal CBM1-containing proteins were implicated in cellulose degradation whereas in oomycetes, the Cellulose Binding Elicitor Lectin (CBEL, a well-characterized CBM1-protein from Phytophthora parasitica, was implicated in cell wall integrity, adhesion to cellulosic substrates and induction of plant immunity. Results To extend our knowledge on CBM1-containing proteins in oomycetes, we have conducted a comprehensive analysis on 60 fungi and 7 oomycetes genomes leading to the identification of 518 CBM1-containing proteins. In plant-interacting microorganisms, the larger number of CBM1-protein coding genes is expressed by necrotroph and hemibiotrophic pathogens, whereas a strong reduction of these genes is observed in symbionts and biotrophs. In fungi, more than 70% of CBM1-containing proteins correspond to enzymatic proteins in which CBM1 is associated with a catalytic unit involved in cellulose degradation. In oomycetes more than 90% of proteins are similar to CBEL in which CBM1 is associated with a non-catalytic PAN/Apple domain, known to interact with specific carbohydrates or proteins. Distinct Stramenopile genomes like diatoms and brown algae are devoid of CBM1 coding genes. A CBM1-PAN/Apple association 3D structural modeling was built allowing the identification of amino acid residues interacting with cellulose and suggesting the putative interaction of the PAN/Apple domain with another type of glucan. By Surface Plasmon Resonance experiments, we showed that CBEL binds to glycoproteins through galactose or N-acetyl-galactosamine motifs. Conclusions This study

Staphylococcal Immune Evasion Proteins: Structure, Function, and Host Adaptation.

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Koymans, Kirsten J; Vrieling, Manouk; Gorham, Ronald D; van Strijp, Jos A G

2017-01-01

Staphylococcus aureus is a successful human and animal pathogen. Its pathogenicity is linked to its ability to secrete a large amount of virulence factors. These secreted proteins interfere with many critical components of the immune system, both innate and adaptive, and hamper proper immune functioning. In recent years, numerous studies have been conducted in order to understand the molecular mechanism underlying the interaction of evasion molecules with the host immune system. Structural studies have fundamentally contributed to our understanding of the mechanisms of action of the individual factors. Furthermore, such studies revealed one of the most striking characteristics of the secreted immune evasion molecules: their conserved structure. Despite high-sequence variability, most immune evasion molecules belong to a small number of structural categories. Another remarkable characteristic is that S. aureus carries most of these virulence factors on mobile genetic elements (MGE) or ex-MGE in its accessory genome. Coevolution of pathogen and host has resulted in immune evasion molecules with a highly host-specific function and prevalence. In this review, we explore how these shared structures and genomic locations relate to function and host specificity. This is discussed in the context of therapeutic options for these immune evasion molecules in infectious as well as in inflammatory diseases.

Predicting Structure and Function for Novel Proteins of an Extremophilic Iron Oxidizing Bacterium

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Wheeler, K.; Zemla, A.; Banfield, J.; Thelen, M.

2007-12-01

provide details for a working hypothesis of electron flow within the biofilm's major bacterium. Nearly 7% of the novel proteins contain tetratrico peptide repeat (TPR) modules, a protein-protein interaction domain that participates in signal transduction and a wide variety of other cellular functions. Like many biofilms, the various organisms in this community use unknown mechanisms to communicate, relying upon each other for survival. Especially interesting is evidence that most of these novel TPR proteins are located in the extracellular or membrane fractions, suggesting their role in intracellular communication. (1) Ram et al, 2005, Science 308:1915-20, "Community Proteomics of a Natural Microbial Biofilm" (2) Zemla et al, 2005, Nucleic Acids Res 33 (Web Server issue):W111-5, "AS2TS system for protein structure modeling and analysis" This work was funded by the DOE Genomics: GTL Program and was performed under the auspices of the DOE by the University of California, Lawrence Livermore National Laboratory under contract W-7405-Eng-48.

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

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Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and

Structure modification and functionality of whey proteins: quantitative structure-activity relationship approach.

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Nakai, S; Li-Chan, E

1985-10-01

According to the original idea of quantitative structure-activity relationship, electric, hydrophobic, and structural parameters should be taken into consideration for elucidating functionality. Changes in these parameters are reflected in the property of protein solubility upon modification of whey proteins by heating. Although solubility is itself a functional property, it has been utilized to explain other functionalities of proteins. However, better correlations were obtained when hydrophobic parameters of the proteins were used in conjunction with solubility. Various treatments reported in the literature were applied to whey protein concentrate in an attempt to obtain whipping and gelling properties similar to those of egg white. Mapping simplex optimization was used to search for the best results. Improvement in whipping properties by pepsin hydrolysis may have been due to higher protein solubility, and good gelling properties resulting from polyphosphate treatment may have been due to an increase in exposable hydrophobicity. However, the results of angel food cake making were still unsatisfactory.

Structural and functional characterization of the recombinant death domain from death-associated protein kinase.

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Dioletis, Evangelos; Dingley, Andrew J; Driscoll, Paul C

2013-01-01

Death-associated protein kinase (DAPk) is a calcium/calmodulin-regulated Ser/Thr-protein kinase that functions at an important point of integration for cell death signaling pathways. DAPk has a structurally unique multi-domain architecture, including a C-terminally positioned death domain (DD) that is a positive regulator of DAPk activity. In this study, recombinant DAPk-DD was observed to aggregate readily and could not be prepared in sufficient yield for structural analysis. However, DAPk-DD could be obtained as a soluble protein in the form of a translational fusion protein with the B1 domain of streptococcal protein G. In contrast to other DDs that adopt the canonical six amphipathic α-helices arranged in a compact fold, the DAPk-DD was found to possess surprisingly low regular secondary structure content and an absence of a stable globular fold, as determined by circular dichroism (CD), NMR spectroscopy and a temperature-dependent fluorescence assay. Furthermore, we measured the in vitro interaction between extracellular-regulated kinase-2 (ERK2) and various recombinant DAPk-DD constructs. Despite the low level of structural order, the recombinant DAPk-DD retained the ability to interact with ERK2 in a 1∶1 ratio with a K d in the low micromolar range. Only the full-length DAPk-DD could bind ERK2, indicating that the apparent 'D-motif' located in the putative sixth helix of DAPk-DD is not sufficient for ERK2 recognition. CD analysis revealed that binding of DAPk-DD to ERK2 is not accompanied by a significant change in secondary structure. Taken together our data argue that the DAPk-DD, when expressed in isolation, does not adopt a classical DD fold, yet in this state retains the capacity to interact with at least one of its binding partners. The lack of a stable globular structure for the DAPk-DD may reflect either that its folding would be supported by interactions absent in our experimental set-up, or a limitation in the structural bioinformatics

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-01-01

operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching

Candida albicans Agglutinin-Like Sequence (Als) Family Vignettes: A Review of Als Protein Structure and Function

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Hoyer, Lois L.; Cota, Ernesto

2016-01-01

Approximately two decades have passed since the description of the first gene in the Candida albicans ALS (agglutinin-like sequence) family. Since that time, much has been learned about the composition of the family and the function of its encoded cell-surface glycoproteins. Solution of the structure of the Als adhesive domain provides the opportunity to evaluate the molecular basis for protein function. This review article is formatted as a series of fundamental questions and explores the diversity of the Als proteins, as well as their role in ligand binding, aggregative effects, and attachment to abiotic surfaces. Interaction of Als proteins with each other, their functional equivalence, and the effects of protein abundance on phenotypic conclusions are also examined. Structural features of Als proteins that may facilitate invasive function are considered. Conclusions that are firmly supported by the literature are presented while highlighting areas that require additional investigation to reveal basic features of the Als proteins, their relatedness to each other, and their roles in C. albicans biology. PMID:27014205

Structure determination of the functional domain interaction of a chimeric nonribosomal peptide synthetase from a challenging crystal with noncrystallographic translational symmetry

Energy Technology Data Exchange (ETDEWEB)

Sundlov, Jesse A.; Gulick, Andrew M., E-mail: gulick@hwi.buffalo.edu [University at Buffalo, 700 Ellicott Street, Buffalo, NY 14203 (United States)

2013-08-01

The structure of the functional interaction of NRPS adenylation and carrier protein domains, trapped with a mechanism-based inhibitor, is described. Crystals exhibit translational non-crystallographic symmetry, which challenged structure determination and refinement. The nonribosomal peptide synthetases (NRPSs) are a family of modular proteins that contain multiple catalytic domains joined in a single protein. Together, these domains work to produce chemically diverse peptides, including compounds with antibiotic activity or that play a role in iron acquisition. Understanding the structural mechanisms that govern the domain interactions has been a long-standing goal. During NRPS synthesis, amino-acid substrates are loaded onto integrated carrier protein domains through the activity of NRPS adenylation domains. The structures of two adenylation domain–carrier protein domain complexes have recently been determined in an effort that required the use of a mechanism-based inhibitor to trap the domain interaction. Here, the continued analysis of these proteins is presented, including a higher resolution structure of an engineered di-domain protein containing the EntE adenylation domain fused with the carrier protein domain of its partner EntB. The protein crystallized in a novel space group in which molecular replacement and refinement were challenged by noncrystallographic pseudo-translational symmetry. The structure determination and how the molecular packing impacted the diffraction intensities are reported. Importantly, the structure illustrates that in this new crystal form the functional interface between the adenylation domain and the carrier protein domain remains the same as that observed previously. At a resolution that allows inclusion of water molecules, additional interactions are observed between the two protein domains and between the protein and its ligands. In particular, a highly solvated region that surrounds the carrier protein cofactor is described.

Structure determination of the functional domain interaction of a chimeric nonribosomal peptide synthetase from a challenging crystal with noncrystallographic translational symmetry

International Nuclear Information System (INIS)

Sundlov, Jesse A.; Gulick, Andrew M.

2013-01-01

The structure of the functional interaction of NRPS adenylation and carrier protein domains, trapped with a mechanism-based inhibitor, is described. Crystals exhibit translational non-crystallographic symmetry, which challenged structure determination and refinement. The nonribosomal peptide synthetases (NRPSs) are a family of modular proteins that contain multiple catalytic domains joined in a single protein. Together, these domains work to produce chemically diverse peptides, including compounds with antibiotic activity or that play a role in iron acquisition. Understanding the structural mechanisms that govern the domain interactions has been a long-standing goal. During NRPS synthesis, amino-acid substrates are loaded onto integrated carrier protein domains through the activity of NRPS adenylation domains. The structures of two adenylation domain–carrier protein domain complexes have recently been determined in an effort that required the use of a mechanism-based inhibitor to trap the domain interaction. Here, the continued analysis of these proteins is presented, including a higher resolution structure of an engineered di-domain protein containing the EntE adenylation domain fused with the carrier protein domain of its partner EntB. The protein crystallized in a novel space group in which molecular replacement and refinement were challenged by noncrystallographic pseudo-translational symmetry. The structure determination and how the molecular packing impacted the diffraction intensities are reported. Importantly, the structure illustrates that in this new crystal form the functional interface between the adenylation domain and the carrier protein domain remains the same as that observed previously. At a resolution that allows inclusion of water molecules, additional interactions are observed between the two protein domains and between the protein and its ligands. In particular, a highly solvated region that surrounds the carrier protein cofactor is described

Structure and function of small heat shock/alpha-crystallin proteins: established concepts and emerging ideas.

Science.gov (United States)

MacRae, T H

2000-06-01

Small heat shock/alpha-crystallin proteins are defined by conserved sequence of approximately 90 amino acid residues, termed the alpha-crystallin domain, which is bounded by variable amino- and carboxy-terminal extensions. These proteins form oligomers, most of uncertain quaternary structure, and oligomerization is prerequisite to their function as molecular chaperones. Sequence modelling and physical analyses show that the secondary structure of small heat shock/alpha-crystallin proteins is predominately beta-pleated sheet. Crystallography, site-directed spin-labelling and yeast two-hybrid selection demonstrate regions of secondary structure within the alpha-crystallin domain that interact during oligomer assembly, a process also dependent on the amino terminus. Oligomers are dynamic, exhibiting subunit exchange and organizational plasticity, perhaps leading to functional diversity. Exposure of hydrophobic residues by structural modification facilitates chaperoning where denaturing proteins in the molten globule state associate with oligomers. The flexible carboxy-terminal extension contributes to chaperone activity by enhancing the solubility of small heat shock/alpha-crystallin proteins. Site-directed mutagenesis has yielded proteins where the effect of the change on structure and function depends upon the residue modified, the organism under study and the analytical techniques used. Most revealing, substitution of a conserved arginine residue within the alpha-crystallin domain has a major impact on quaternary structure and chaperone action probably through realignment of beta-sheets. These mutations are linked to inherited diseases. Oligomer size is regulated by a stress-responsive cascade including MAPKAP kinase 2/3 and p38. Phosphorylation of small heat shock/alpha-crystallin proteins has important consequences within stressed cells, especially for microfilaments.

Computational design, construction, and characterization of a set of specificity determining residues in protein-protein interactions.

Science.gov (United States)

Nagao, Chioko; Izako, Nozomi; Soga, Shinji; Khan, Samia Haseeb; Kawabata, Shigeki; Shirai, Hiroki; Mizuguchi, Kenji

2012-10-01

Proteins interact with different partners to perform different functions and it is important to elucidate the determinants of partner specificity in protein complex formation. Although methods for detecting specificity determining positions have been developed previously, direct experimental evidence for these amino acid residues is scarce, and the lack of information has prevented further computational studies. In this article, we constructed a dataset that is likely to exhibit specificity in protein complex formation, based on available crystal structures and several intuitive ideas about interaction profiles and functional subclasses. We then defined a "structure-based specificity determining position (sbSDP)" as a set of equivalent residues in a protein family showing a large variation in their interaction energy with different partners. We investigated sequence and structural features of sbSDPs and demonstrated that their amino acid propensities significantly differed from those of other interacting residues and that the importance of many of these residues for determining specificity had been verified experimentally. Copyright © 2012 Wiley Periodicals, Inc.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

Science.gov (United States)

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Prediction of Protein–Protein Interactions by Evidence Combining Methods

Directory of Open Access Journals (Sweden)

Ji-Wei Chang

2016-11-01

Full Text Available Most cellular functions involve proteins’ features based on their physical interactions with other partner proteins. Sketching a map of protein–protein interactions (PPIs is therefore an important inception step towards understanding the basics of cell functions. Several experimental techniques operating in vivo or in vitro have made significant contributions to screening a large number of protein interaction partners, especially high-throughput experimental methods. However, computational approaches for PPI predication supported by rapid accumulation of data generated from experimental techniques, 3D structure definitions, and genome sequencing have boosted the map sketching of PPIs. In this review, we shed light on in silico PPI prediction methods that integrate evidence from multiple sources, including evolutionary relationship, function annotation, sequence/structure features, network topology and text mining. These methods are developed for integration of multi-dimensional evidence, for designing the strategies to predict novel interactions, and for making the results consistent with the increase of prediction coverage and accuracy.

Protein complex prediction in large ontology attributed protein-protein interaction networks.

Science.gov (United States)

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

Geometrical comparison of two protein structures using Wigner-D functions.

Science.gov (United States)

Saberi Fathi, S M; White, Diana T; Tuszynski, Jack A

2014-10-01

In this article, we develop a quantitative comparison method for two arbitrary protein structures. This method uses a root-mean-square deviation characterization and employs a series expansion of the protein's shape function in terms of the Wigner-D functions to define a new criterion, which is called a "similarity value." We further demonstrate that the expansion coefficients for the shape function obtained with the help of the Wigner-D functions correspond to structure factors. Our method addresses the common problem of comparing two proteins with different numbers of atoms. We illustrate it with a worked example. © 2014 Wiley Periodicals, Inc.

Scoring protein relationships in functional interaction networks predicted from sequence data.

Directory of Open Access Journals (Sweden)

Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

2004 Structural, Function and Evolutionary Genomics

Energy Technology Data Exchange (ETDEWEB)

Douglas L. Brutlag Nancy Ryan Gray

2005-03-23

This Gordon conference will cover the areas of structural, functional and evolutionary genomics. It will take a systematic approach to genomics, examining the evolution of proteins, protein functional sites, protein-protein interactions, regulatory networks, and metabolic networks. Emphasis will be placed on what we can learn from comparative genomics and entire genomes and proteomes.

Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network

Directory of Open Access Journals (Sweden)

Jun Pan

2014-01-01

Full Text Available Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.

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

Science.gov (United States)

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

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

The ER stress sensor PERK luminal domain functions as a molecular chaperone to interact with misfolded proteins

Energy Technology Data Exchange (ETDEWEB)

Wang, Peng; Li, Jingzhi; Sha, Bingdong

2016-11-29

PERK is one of the major sensor proteins which can detect the protein-folding imbalance generated by endoplasmic reticulum (ER) stress. It remains unclear how the sensor protein PERK is activated by ER stress. It has been demonstrated that the PERK luminal domain can recognize and selectively interact with misfolded proteins but not native proteins. Moreover, the PERK luminal domain may function as a molecular chaperone to directly bind to and suppress the aggregation of a number of misfolded model proteins. The data strongly support the hypothesis that the PERK luminal domain can interact directly with misfolded proteins to induce ER stress signaling. To illustrate the mechanism by which the PERK luminal domain interacts with misfolded proteins, the crystal structure of the human PERK luminal domain was determined to 3.2 Å resolution. Two dimers of the PERK luminal domain constitute a tetramer in the asymmetric unit. Superimposition of the PERK luminal domain molecules indicated that the β-sandwich domain could adopt multiple conformations. It is hypothesized that the PERK luminal domain may utilize its flexible β-sandwich domain to recognize and interact with a broad range of misfolded proteins.

Ionic protein-lipid interaction at the plasma membrane: what can the charge do?

Science.gov (United States)

Li, Lunyi; Shi, Xiaoshan; Guo, Xingdong; Li, Hua; Xu, Chenqi

2014-03-01

Phospholipids are the major components of cell membranes, but they have functional roles beyond forming lipid bilayers. In particular, acidic phospholipids form microdomains in the plasma membrane and can ionically interact with proteins via polybasic sequences, which can have functional consequences for the protein. The list of proteins regulated by ionic protein-lipid interaction has been quickly expanding, and now includes membrane proteins, cytoplasmic soluble proteins, and viral proteins. Here we review how acidic phospholipids in the plasma membrane regulate protein structure and function via ionic interactions, and how Ca(2+) regulates ionic protein-lipid interactions via direct and indirect mechanisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Three-Dimensional Structural Aspects of Protein–Polysaccharide Interactions

Directory of Open Access Journals (Sweden)

Masamichi Nagae

2014-03-01

Full Text Available Linear polysaccharides are typically composed of repeating mono- or disaccharide units and are ubiquitous among living organisms. Polysaccharide diversity arises from chain-length variation, branching, and additional modifications. Structural diversity is associated with various physiological functions, which are often regulated by cognate polysaccharide-binding proteins. Proteins that interact with linear polysaccharides have been identified or developed, such as galectins and polysaccharide-specific antibodies, respectively. Currently, data is accumulating on the three-dimensional structure of polysaccharide-binding proteins. These proteins are classified into two types: exo-type and endo-type. The former group specifically interacts with the terminal units of polysaccharides, whereas the latter with internal units. In this review, we describe the structural aspects of exo-type and endo-type protein-polysaccharide interactions. Further, we discuss the structural basis for affinity and specificity enhancement in the face of inherently weak binding interactions.

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

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

2011-06-01

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

Genome-wide analysis of protein-protein interactions and involvement of viral proteins in SARS-CoV replication.

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Ji'an Pan

Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

Prediction of localization and interactions of apoptotic proteins

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Matula Pavel

2009-07-01

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.

Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

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Inbar Yuval

2010-07-01

Full Text Available Abstract Background Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design. Results Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 Å for all residues and 0.73 Å for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions. Conclusions Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

Protein structure similarity from principle component correlation analysis

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Chou James

2006-01-01

Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

General and specific lipid-protein interactions in Na,K-ATPase.

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Cornelius, F; Habeck, M; Kanai, R; Toyoshima, C; Karlish, S J D

2015-09-01

The molecular activity of Na,K-ATPase and other P2 ATPases like Ca(2+)-ATPase is influenced by the lipid environment via both general (physical) and specific (chemical) interactions. Whereas the general effects of bilayer structure on membrane protein function are fairly well described and understood, the importance of the specific interactions has only been realized within the last decade due particularly to the growing field of membrane protein crystallization, which has shed new light on the molecular details of specific lipid-protein interactions. It is a remarkable observation that specific lipid-protein interactions seem to be evolutionarily conserved, and conformations of specifically bound lipids at the lipid-protein surface within the membrane are similar in crystal structures determined with different techniques and sources of the protein, despite the rather weak lipid-protein interaction energy. Studies of purified detergent-soluble recombinant αβ or αβFXYD Na,K-ATPase complexes reveal three separate functional effects of phospholipids and cholesterol with characteristic structural selectivity. The observations suggest that these three effects are exerted at separate binding sites for phophatidylserine/cholesterol (stabilizing), polyunsaturated phosphatidylethanolamine (stimulatory), and saturated PC or sphingomyelin/cholesterol (inhibitory), which may be located within three lipid-binding pockets identified in recent crystal structures of Na,K-ATPase. The findings point to a central role of direct and specific interactions of different phospholipids and cholesterol in determining both stability and molecular activity of Na,K-ATPase and possible implications for physiological regulation by membrane lipid composition. This article is part of a special issue titled "Lipid-Protein Interactions." Copyright © 2015 Elsevier B.V. All rights reserved.

Structural and Function Prediction of Musa acuminata subsp. Malaccensis Protein

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Anum Munir

2016-03-01

Full Text Available Hypothetical proteins (HPs are the proteins whose presence has been anticipated, yet in vivo function has not been built up. Illustrating the structural and functional privileged insights of these HPs might likewise prompt a superior comprehension of the protein-protein associations or networks in diverse types of life. Bananas (Musa acuminata spp., including sweet and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister grouped to the all-around considered Poales, which incorporate oats. Bananas are crucial for nourishment security in numerous tropical and subtropical nations and the most prominent organic product in industrialized nations. In the present study, the hypothetical protein of M. acuminata (Banana was chosen for analysis and modeling by distinctive bioinformatics apparatuses and databases. As indicated by primary and secondary structure analysis, XP_009393594.1 is a stable hydrophobic protein containing a noteworthy extent of α-helices; Homology modeling was done utilizing SWISS-MODEL server where the templates identity with XP_009393594.1 protein was less which demonstrated novelty of our protein. Ab initio strategy was conducted to produce its 3D structure. A few evaluations of quality assessment and validation parameters determined the generated protein model as stable with genuinely great quality. Functional analysis was completed by ProtFun 2.2, and KEGG (KAAS, recommended that the hypothetical protein is a transcription factor with cytoplasmic domain as zinc finger. The protein was observed to be vital for translation process, involved in metabolism, signaling and cellular processes, genetic information processing and Zinc ion binding. It is suggested that further test approval would help to anticipate the structures and functions of other uncharacterized proteins of different plants and living being.

Protein-Ligand Empirical Interaction Components for Virtual Screening.

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Yan, Yuna; Wang, Weijun; Sun, Zhaoxi; Zhang, John Z H; Ji, Changge

2017-08-28

A major shortcoming of empirical scoring functions is that they often fail to predict binding affinity properly. Removing false positives of docking results is one of the most challenging works in structure-based virtual screening. Postdocking filters, making use of all kinds of experimental structure and activity information, may help in solving the issue. We describe a new method based on detailed protein-ligand interaction decomposition and machine learning. Protein-ligand empirical interaction components (PLEIC) are used as descriptors for support vector machine learning to develop a classification model (PLEIC-SVM) to discriminate false positives from true positives. Experimentally derived activity information is used for model training. An extensive benchmark study on 36 diverse data sets from the DUD-E database has been performed to evaluate the performance of the new method. The results show that the new method performs much better than standard empirical scoring functions in structure-based virtual screening. The trained PLEIC-SVM model is able to capture important interaction patterns between ligand and protein residues for one specific target, which is helpful in discarding false positives in postdocking filtering.

Taking advantage of local structure descriptors to analyze interresidue contacts in protein structures and protein complexes.

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Martin, Juliette; Regad, Leslie; Etchebest, Catherine; Camproux, Anne-Claude

2008-11-15

Interresidue protein contacts in proteins structures and at protein-protein interface are classically described by the amino acid types of interacting residues and the local structural context of the contact, if any, is described using secondary structures. In this study, we present an alternate analysis of interresidue contact using local structures defined by the structural alphabet introduced by Camproux et al. This structural alphabet allows to describe a 3D structure as a sequence of prototype fragments called structural letters, of 27 different types. Each residue can then be assigned to a particular local structure, even in loop regions. The analysis of interresidue contacts within protein structures defined using Voronoï tessellations reveals that pairwise contact specificity is greater in terms of structural letters than amino acids. Using a simple heuristic based on specificity score comparison, we find that 74% of the long-range contacts within protein structures are better described using structural letters than amino acid types. The investigation is extended to a set of protein-protein complexes, showing that the similar global rules apply as for intraprotein contacts, with 64% of the interprotein contacts best described by local structures. We then present an evaluation of pairing functions integrating structural letters to decoy scoring and show that some complexes could benefit from the use of structural letter-based pairing functions.

VPAC receptors: structure, molecular pharmacology and interaction with accessory proteins.

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Couvineau, Alain; Laburthe, Marc

2012-05-01

The vasoactive intestinal peptide (VIP) is a neuropeptide with wide distribution in both central and peripheral nervous systems, where it plays important regulatory role in many physiological processes. VIP displays a large biological functions including regulation of exocrine secretions, hormone release, fetal development, immune responses, etc. VIP appears to exert beneficial effect in neuro-degenerative and inflammatory diseases. The mechanism of action of VIP implicates two subtypes of receptors (VPAC1 and VPAC2), which are members of class B receptors belonging to the super-family of GPCR. This article reviews the current knowledge regarding the structure and molecular pharmacology of VPAC receptors. The structure-function relationship of VPAC1 receptor has been extensively studied, allowing to understand the molecular basis for receptor affinity, specificity, desensitization and coupling to adenylyl cyclase. Those studies have clearly demonstrated the crucial role of the N-terminal ectodomain (N-ted) of VPAC1 receptor in VIP recognition. By using different approaches including directed mutagenesis, photoaffinity labelling, NMR, molecular modelling and molecular dynamic simulation, it has been shown that the VIP molecule interacts with the N-ted of VPAC1 receptor, which is itself structured as a 'Sushi' domain. VPAC1 receptor also interacts with a few accessory proteins that play a role in cell signalling of receptors. Recent advances in the structural characterization of VPAC receptor and more generally of class B GPCRs will lead to the design of new molecules, which could have considerable interest for the treatment of inflammatory and neuro-degenerative diseases. © 2011 The Authors. British Journal of Pharmacology © 2011 The British Pharmacological Society.

Functional interaction between the N- and C-terminal domains of murine leukemia virus surface envelope protein

International Nuclear Information System (INIS)

Lu, C.-W.; Roth, Monica J.

2003-01-01

A series of murine leukemia viruses (MuLVs) with chimeric envelope proteins (Env) was generated to map functional interactions between the N- and the C-terminal domains of surface proteins (SU). All these chimeras have the 4070A amphotropic receptor-binding region flanked by various lengths of Moloney ecotropic N- and C-terminal Env. A charged residue, E49 (E16 on the mature protein), was identified at the N-terminals of Moloney MuLV SU that is important for the interaction with the C-terminal domain of the SU. The region that interacts with E49 was localized between junction 4 (R265 of M-MuLV Env) and junction 6 (L374 of M-MuLV Env) of SU. Sequencing the viable chimeric Env virus populations identified residues within the SU protein that improved the replication kinetics of the input chimeric Env viruses. Mutations in the C-domain of SU (G387E/R, L435I, L442P) were found to improve chimera IV4, which displayed a delayed onset of replication. The replication of AE6, containing a chimeric junction in the SU C-terminus, was improved by mutations in the N-domain (N40H, E80K), the proline-rich region (Q252R), or the transmembrane protein (L538N). Altogether, these observations provide insights into the structural elements required for Env function

Structures composing protein domains.

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Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel; Hudeček, Jiří

2013-08-01

This review summarizes available data concerning intradomain structures (IS) such as functionally important amino acid residues, short linear motifs, conserved or disordered regions, peptide repeats, broadly occurring secondary structures or folds, etc. IS form structural features (units or elements) necessary for interactions with proteins or non-peptidic ligands, enzyme reactions and some structural properties of proteins. These features have often been related to a single structural level (e.g. primary structure) mostly requiring certain structural context of other levels (e.g. secondary structures or supersecondary folds) as follows also from some examples reported or demonstrated here. In addition, we deal with some functionally important dynamic properties of IS (e.g. flexibility and different forms of accessibility), and more special dynamic changes of IS during enzyme reactions and allosteric regulation. Selected notes concern also some experimental methods, still more necessary tools of bioinformatic processing and clinically interesting relationships. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

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Stefan M Ivanov

Full Text Available An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

Protein-protein interactions in paralogues: Electrostatics modulates specificity on a conserved steric scaffold.

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Ivanov, Stefan M; Cawley, Andrew; Huber, Roland G; Bond, Peter J; Warwicker, Jim

2017-01-01

An improved knowledge of protein-protein interactions is essential for better understanding of metabolic and signaling networks, and cellular function. Progress tends to be based on structure determination and predictions using known structures, along with computational methods based on evolutionary information or detailed atomistic descriptions. We hypothesized that for the case of interactions across a common interface, between proteins from a pair of paralogue families or within a family of paralogues, a relatively simple interface description could distinguish between binding and non-binding pairs. Using binding data for several systems, and large-scale comparative modeling based on known template complex structures, it is found that charge-charge interactions (for groups bearing net charge) are generally a better discriminant than buried non-polar surface. This is particularly the case for paralogue families that are less divergent, with more reliable comparative modeling. We suggest that electrostatic interactions are major determinants of specificity in such systems, an observation that could be used to predict binding partners.

Information assessment on predicting protein-protein interactions

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Gerstein Mark

2004-10-01

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

HCVpro: Hepatitis C virus protein interaction database

KAUST Repository

Kwofie, Samuel K.

2011-12-01

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.

DUF581 is plant specific FCS-like zinc finger involved in protein-protein interaction.

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Muhammed Jamsheer K

Full Text Available Zinc fingers are a ubiquitous class of protein domain with considerable variation in structure and function. Zf-FCS is a highly diverged group of C2-C2 zinc finger which is present in animals, prokaryotes and viruses, but not in plants. In this study we identified that a plant specific domain of unknown function, DUF581 is a zf-FCS type zinc finger. Based on HMM-HMM comparison and signature motif similarity we named this domain as FCS-Like Zinc finger (FLZ domain. A genome wide survey identified that FLZ domain containing genes are bryophytic in origin and this gene family is expanded in spermatophytes. Expression analysis of selected FLZ gene family members of A. thaliana identified an overlapping expression pattern suggesting a possible redundancy in their function. Unlike the zf-FCS domain, the FLZ domain found to be highly conserved in sequence and structure. Using a combination of bioinformatic and protein-protein interaction tools, we identified that FLZ domain is involved in protein-protein interaction.

Probing protein interactions with hydrogen/deuterium exchange and mass spectrometry—A review

International Nuclear Information System (INIS)

Percy, Andrew J.; Rey, Martial; Burns, Kyle M.; Schriemer, David C.

2012-01-01

Highlights: ► Protein chemistry generates mass shifts useful for structure–function studies. ► H/DX supports a powerful mass shift method for protein interaction analysis. ► H/DX mass shifts are useful for determining binding data (K d , off-rates). ► Improved H/DX–MS workflows can accommodate complex protein systems. - Abstract: Assessing the functional outcome of protein interactions in structural terms is a goal of structural biology, however most techniques have a limited capacity for making structure–function determinations with both high resolution and high throughput. Mass spectrometry can be applied as a reader of protein chemistries in order to fill this void, and enable methodologies whereby protein structure–function determinations may be made on a proteome-wide level. Protein hydrogen/deuterium exchange (H/DX) offers a chemical labeling strategy suitable for tracking changes in “dynamic topography” and thus represents a powerful means of monitoring protein structure–function relationships. This review presents the exchange method in the context of interaction analysis. Applications involving interface detection, quantitation of binding, and conformational responses to ligation are discussed, and commentary on recent analytical developments is provided.

Functions and structures of eukaryotic recombination proteins

International Nuclear Information System (INIS)

Ogawa, Tomoko

1994-01-01

We have found that Rad51 and RecA Proteins form strikingly similar structures together with dsDNA and ATP. Their right handed helical nucleoprotein filaments extend the B-form DNA double helixes to 1.5 times in length and wind the helix. The similarity and uniqueness of their structures must reflect functional homologies between these proteins. Therefore, it is highly probable that similar recombination proteins are present in various organisms of different evolutional states. We have succeeded to clone RAD51 genes from human, mouse, chicken and fission yeast genes, and found that the homologues are widely distributed in eukaryotes. The HsRad51 and MmRad51 or ChRad51 proteins consist of 339 amino acids differing only by 4 or 12 amino acids, respectively, and highly homologous to both yeast proteins, but less so to Dmcl. All of these proteins are homologous to the region from residues 33 to 240 of RecA which was named ''homologous core. The homologous core is likely to be responsible for functions common for all of them, such as the formation of helical nucleoprotein filament that is considered to be involved in homologous pairing in the recombination reaction. The mouse gene is transcribed at a high level in thymus, spleen, testis, and ovary, at lower level in brain and at a further lower level in some other tissues. It is transcribed efficiently in recombination active tissues. A clear functional difference of Rad51 homologues from RecA was suggested by the failure of heterologous genes to complement the deficiency of Scrad51 mutants. This failure seems to reflect the absence of a compatible partner, such as ScRad52 protein in the case of ScRad51 protein, between different species. Thus, these discoveries play a role of the starting point to understand the fundamental gene targeting in mammalian cells and in gene therapy. (J.P.N.)

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

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He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the

Structure-function analysis of RBP-J-interacting and tubulin-associated (RITA) reveals regions critical for repression of Notch target genes.

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Tabaja, Nassif; Yuan, Zhenyu; Oswald, Franz; Kovall, Rhett A

2017-06-23

The Notch pathway is a cell-to-cell signaling mechanism that is essential for tissue development and maintenance, and aberrant Notch signaling has been implicated in various cancers, congenital defects, and cardiovascular diseases. Notch signaling activates the expression of target genes, which are regulated by the transcription factor CSL (CBF1/RBP-J, Su(H), Lag-1). CSL interacts with both transcriptional corepressor and coactivator proteins, functioning as both a repressor and activator, respectively. Although Notch activation complexes are relatively well understood at the structural level, less is known about how CSL interacts with corepressors. Recently, a new RBP-J (mammalian CSL ortholog)-interacting protein termed RITA has been identified and shown to export RBP-J out of the nucleus, thereby leading to the down-regulation of Notch target gene expression. However, the molecular details of RBP-J/RITA interactions are unclear. Here, using a combination of biochemical/cellular, structural, and biophysical techniques, we demonstrate that endogenous RBP-J and RITA proteins interact in cells, map the binding regions necessary for RBP-J·RITA complex formation, and determine the X-ray structure of the RBP-J·RITA complex bound to DNA. To validate the structure and glean more insights into function, we tested structure-based RBP-J and RITA mutants with biochemical/cellular assays and isothermal titration calorimetry. Whereas our structural and biophysical studies demonstrate that RITA binds RBP-J similarly to the RAM (RBP-J-associated molecule) domain of Notch, our biochemical and cellular assays suggest that RITA interacts with additional regions in RBP-J. Taken together, these results provide molecular insights into the mechanism of RITA-mediated regulation of Notch signaling, contributing to our understanding of how CSL functions as a transcriptional repressor of Notch target genes. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

3Drefine: an interactive web server for efficient protein structure refinement.

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Bhattacharya, Debswapna; Nowotny, Jackson; Cao, Renzhi; Cheng, Jianlin

2016-07-08

3Drefine is an interactive web server for consistent and computationally efficient protein structure refinement with the capability to perform web-based statistical and visual analysis. The 3Drefine refinement protocol utilizes iterative optimization of hydrogen bonding network combined with atomic-level energy minimization on the optimized model using a composite physics and knowledge-based force fields for efficient protein structure refinement. The method has been extensively evaluated on blind CASP experiments as well as on large-scale and diverse benchmark datasets and exhibits consistent improvement over the initial structure in both global and local structural quality measures. The 3Drefine web server allows for convenient protein structure refinement through a text or file input submission, email notification, provided example submission and is freely available without any registration requirement. The server also provides comprehensive analysis of submissions through various energy and statistical feedback and interactive visualization of multiple refined models through the JSmol applet that is equipped with numerous protein model analysis tools. The web server has been extensively tested and used by many users. As a result, the 3Drefine web server conveniently provides a useful tool easily accessible to the community. The 3Drefine web server has been made publicly available at the URL: http://sysbio.rnet.missouri.edu/3Drefine/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Exploring protein dynamics space: the dynasome as the missing link between protein structure and function.

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Ulf Hensen

Full Text Available Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics.

Large-scale prediction of drug–target interactions using protein sequences and drug topological structures

International Nuclear Information System (INIS)

Cao Dongsheng; Liu Shao; Xu Qingsong; Lu Hongmei; Huang Jianhua; Hu Qiannan; Liang Yizeng

2012-01-01

Highlights: ► Drug–target interactions are predicted using an extended SAR methodology. ► A drug–target interaction is regarded as an event triggered by many factors. ► Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. ► Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug–target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug–target interactions in a timely manner. In this article, we aim at extending current structure–activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug–target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug–target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug–target interactions, and show a general compatibility between the new scheme and current SAR

Structure of Plasmodium falciparum orotate phosphoribosyltransferase with autologous inhibitory protein–protein interactions

International Nuclear Information System (INIS)

Kumar, Shiva; Krishnamoorthy, Kalyanaraman; Mudeppa, Devaraja G.; Rathod, Pradipsinh K.

2015-01-01

P. falciparum orotate phosphoribosyltransferase, a potential target for antimalarial drugs and a conduit for prodrugs, crystallized as a structure with eight molecules per asymmetric unit that included some unique parasite-specific auto-inhibitory interactions between catalytic dimers. The most severe form of malaria is caused by the obligate parasite Plasmodium falciparum. Orotate phosphoribosyltransferase (OPRTase) is the fifth enzyme in the de novo pyrimidine-synthesis pathway in the parasite, which lacks salvage pathways. Among all of the malaria de novo pyrimidine-biosynthesis enzymes, the structure of P. falciparum OPRTase (PfOPRTase) was the only one unavailable until now. PfOPRTase that could be crystallized was obtained after some low-complexity sequences were removed. Four catalytic dimers were seen in the asymmetic unit (a total of eight polypeptides). In addition to revealing unique amino acids in the PfOPRTase active sites, asymmetric dimers in the larger structure pointed to novel parasite-specific protein–protein interactions that occlude the catalytic active sites. The latter could potentially modulate PfOPRTase activity in parasites and possibly provide new insights for blocking PfOPRTase functions

Structure of Plasmodium falciparum orotate phosphoribosyltransferase with autologous inhibitory protein–protein interactions

Energy Technology Data Exchange (ETDEWEB)

Kumar, Shiva; Krishnamoorthy, Kalyanaraman; Mudeppa, Devaraja G.; Rathod, Pradipsinh K., E-mail: rathod@chem.washington.edu [University of Washington, Seattle, WA 98195 (United States)

2015-04-21

P. falciparum orotate phosphoribosyltransferase, a potential target for antimalarial drugs and a conduit for prodrugs, crystallized as a structure with eight molecules per asymmetric unit that included some unique parasite-specific auto-inhibitory interactions between catalytic dimers. The most severe form of malaria is caused by the obligate parasite Plasmodium falciparum. Orotate phosphoribosyltransferase (OPRTase) is the fifth enzyme in the de novo pyrimidine-synthesis pathway in the parasite, which lacks salvage pathways. Among all of the malaria de novo pyrimidine-biosynthesis enzymes, the structure of P. falciparum OPRTase (PfOPRTase) was the only one unavailable until now. PfOPRTase that could be crystallized was obtained after some low-complexity sequences were removed. Four catalytic dimers were seen in the asymmetic unit (a total of eight polypeptides). In addition to revealing unique amino acids in the PfOPRTase active sites, asymmetric dimers in the larger structure pointed to novel parasite-specific protein–protein interactions that occlude the catalytic active sites. The latter could potentially modulate PfOPRTase activity in parasites and possibly provide new insights for blocking PfOPRTase functions.

The pilus usher controls protein interactions via domain masking and is functional as an oligomer.

Science.gov (United States)

Werneburg, Glenn T; Henderson, Nadine S; Portnoy, Erica B; Sarowar, Samema; Hultgren, Scott J; Li, Huilin; Thanassi, David G

2015-07-01

The chaperone-usher (CU) pathway assembles organelles termed pili or fimbriae in Gram-negative bacteria. Type 1 pili expressed by uropathogenic Escherichia coli are prototypical structures assembled by the CU pathway. Biogenesis of pili by the CU pathway requires a periplasmic chaperone and an outer-membrane protein termed the usher (FimD). We show that the FimD C-terminal domains provide the high-affinity substrate-binding site but that these domains are masked in the resting usher. Domain masking requires the FimD plug domain, which serves as a switch controlling usher activation. We demonstrate that usher molecules can act in trans for pilus biogenesis, providing conclusive evidence for a functional usher oligomer. These results reveal mechanisms by which molecular machines such as the usher regulate and harness protein-protein interactions and suggest that ushers may interact in a cooperative manner during pilus assembly in bacteria.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

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Eric A Yen

2014-05-01

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

Influence of degree correlations on network structure and stability in protein-protein interaction networks

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Zimmer Ralf

2007-08-01

Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

Proteomic analysis of FUS interacting proteins provides insights into FUS function and its role in ALS.

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Kamelgarn, Marisa; Chen, Jing; Kuang, Lisha; Arenas, Alexandra; Zhai, Jianjun; Zhu, Haining; Gal, Jozsef

2016-10-01

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease. Mutations in the Fused in Sarcoma/Translocated in Liposarcoma (FUS/TLS) gene cause a subset of familial ALS cases and are also implicated in sporadic ALS. FUS is typically localized to the nucleus. The ALS-related FUS mutations cause cytoplasmic mis-localization and the formation of stress granule-like structures. Abnormal cytoplasmic FUS localization was also found in a subset of frontotemporal dementia (FTLD) cases without FUS mutations. To better understand the function of FUS, we performed wild-type and mutant FUS pull-downs followed by proteomic identification of the interacting proteins. The FUS interacting partners we identified are involved in multiple pathways, including chromosomal organization, transcription, RNA splicing, RNA transport, localized translation, and stress response. FUS interacted with hnRNPA1 and Matrin-3, RNA binding proteins whose mutations were also reported to cause familial ALS, suggesting that hnRNPA1 and Matrin-3 may play common pathogenic roles with FUS. The FUS interactions displayed varied RNA dependence. Numerous FUS interacting partners that we identified are components of exosomes. We found that FUS itself was present in exosomes, suggesting that the secretion of FUS might contribute to the cell-to-cell spreading of FUS pathology. FUS interacting proteins were sequestered into the cytoplasmic mutant FUS inclusions that could lead to their mis-regulation or loss of function, contributing to ALS pathogenesis. Our results provide insights into the physiological functions of FUS as well as important pathways where mutant FUS can interfere with cellular processes and potentially contribute to the pathogenesis of ALS. Copyright © 2016 Elsevier B.V. All rights reserved.

Receptor-interacting protein (RIP) kinase family

Science.gov (United States)

Zhang, Duanwu; Lin, Juan; Han, Jiahuai

2010-01-01

Receptor-interacting protein (RIP) kinases are a group of threonine/serine protein kinases with a relatively conserved kinase domain but distinct non-kinase regions. A number of different domain structures, such as death and caspase activation and recruitment domain (CARD) domains, were found in different RIP family members, and these domains should be keys in determining the specific function of each RIP kinase. It is known that RIP kinases participate in different biological processes, including those in innate immunity, but their downstream substrates are largely unknown. This review will give an overview of the structures and functions of RIP family members, and an update of recent progress in RIP kinase research. PMID:20383176

Structures and Corresponding Functions of Five Types of Picornaviral 2A Proteins

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Xiaoyao Yang

2017-07-01

Full Text Available Among the few non-structural proteins encoded by the picornaviral genome, the 2A protein is particularly special, irrespective of structure or function. During the evolution of the Picornaviridae family, the 2A protein has been highly non-conserved. We believe that the 2A protein in this family can be classified into at least five distinct types according to previous studies. These five types are (A chymotrypsin-like 2A, (B Parechovirus-like 2A, (C hepatitis-A-virus-like 2A, (D Aphthovirus-like 2A, and (E 2A sequence of the genus Cardiovirus. We carried out a phylogenetic analysis and found that there was almost no homology between each type. Subsequently, we aligned the sequences within each type and found that the functional motifs in each type are highly conserved. These different motifs perform different functions. Therefore, in this review, we introduce the structures and functions of these five types of 2As separately. Based on the structures and functions, we provide suggestions to combat picornaviruses. The complexity and diversity of the 2A protein has caused great difficulties in functional and antiviral research. In this review, researchers can find useful information on the 2A protein and thus conduct improved antiviral research.

The crystal structure of the Dachshund domain of human SnoN reveals flexibility in the putative protein interaction surface.

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Tomas Nyman

2010-09-01

Full Text Available The human SnoN is an oncoprotein that interacts with several transcription-regulatory proteins such as the histone-deacetylase, N-CoR containing co-repressor complex and Smad proteins. This study presents the crystal structure of the Dachshund homology domain of human SnoN. The structure reveals a groove composed of conserved residues with characteristic properties of a protein-interaction surface. A comparison of the 12 monomers in the asymmetric unit reveals the presence of two major conformations: an open conformation with a well accessible groove and a tight conformation with a less accessible groove. The variability in the backbone between the open and the tight conformations matches the differences seen in previously determined structures of individual Dachshund homology domains, suggesting a general plasticity within this fold family. The flexibility observed in the putative protein binding groove may enable SnoN to recognize multiple interaction partners.This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available in Text S1.

Structure of the SPRY domain of the human RNA helicase DDX1, a putative interaction platform within a DEAD-box protein

Energy Technology Data Exchange (ETDEWEB)

Kellner, Julian N.; Meinhart, Anton, E-mail: anton.meinhart@mpimf-heidelberg.mpg.de [Max Planck Institute for Medical Research, Jahnstrasse 29, 69120 Heidelberg (Germany)

2015-08-25

The structure of the SPRY domain of the human RNA helicase DDX1 was determined at 2.0 Å resolution. The SPRY domain provides a putative protein–protein interaction platform within DDX1 that differs from other SPRY domains in its structure and conserved regions. The human RNA helicase DDX1 in the DEAD-box family plays an important role in RNA processing and has been associated with HIV-1 replication and tumour progression. Whereas previously described DEAD-box proteins have a structurally conserved core, DDX1 shows a unique structural feature: a large SPRY-domain insertion in its RecA-like consensus fold. SPRY domains are known to function as protein–protein interaction platforms. Here, the crystal structure of the SPRY domain of human DDX1 (hDSPRY) is reported at 2.0 Å resolution. The structure reveals two layers of concave, antiparallel β-sheets that stack onto each other and a third β-sheet beneath the β-sandwich. A comparison with SPRY-domain structures from other eukaryotic proteins showed that the general β-sandwich fold is conserved; however, differences were detected in the loop regions, which were identified in other SPRY domains to be essential for interaction with cognate partners. In contrast, in hDSPRY these loop regions are not strictly conserved across species. Interestingly, though, a conserved patch of positive surface charge is found that may replace the connecting loops as a protein–protein interaction surface. The data presented here comprise the first structural information on DDX1 and provide insights into the unique domain architecture of this DEAD-box protein. By providing the structure of a putative interaction domain of DDX1, this work will serve as a basis for further studies of the interaction network within the hetero-oligomeric complexes of DDX1 and of its recruitment to the HIV-1 Rev protein as a viral replication factor.

Usher protein functions in hair cells and photoreceptors.

Science.gov (United States)

Cosgrove, Dominic; Zallocchi, Marisa

2014-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber, the tip link, and the linkages that anchor the taller stereocilia's actin cytoskeleton core to the shorter adjacent stereocilia and the elusive mechanotransduction channels, explaining the deafness phenotype when these molecular interactions are perturbed. The conundrum is that photoreceptors lack a synonymous mechanotransduction apparatus, and so a common theory for Usher protein function in the two neurosensory cell types affected in Usher syndrome is lacking. Recent evidence linking photoreceptor cell dysfunction in the shaker 1 mouse model for Usher syndrome to light-induced protein translocation defects, combined with localization of an Usher protein interactome at the periciliary region of the photoreceptors suggests Usher proteins might regulate protein trafficking between the inner and outer segments of photoreceptors. A distinct Usher protein complex is trafficked to the ribbon synapses of hair cells, and synaptic defects have been reported in Usher mutants in both hair cells and photoreceptors. This review aims to clarify what is known about Usher protein function at the synaptic and apical poles of hair cells and photoreceptors and the prospects for identifying a unifying pathobiological mechanism to explain deaf/blindness in Usher syndrome. Copyright © 2013 Elsevier Ltd. All rights reserved.

Association of papillomavirus E6 proteins with either MAML1 or E6AP clusters E6 proteins by structure, function, and evolutionary relatedness.

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Nicole Brimer

2017-12-01

Full Text Available Papillomavirus E6 proteins bind to LXXLL peptide motifs displayed on targeted cellular proteins. Alpha genus HPV E6 proteins associate with the cellular ubiquitin ligase E6AP (UBE3A, by binding to an LXXLL peptide (ELTLQELLGEE displayed by E6AP, thereby stimulating E6AP ubiquitin ligase activity. Beta, Gamma, and Delta genera E6 proteins bind a similar LXXLL peptide (WMSDLDDLLGS on the cellular transcriptional co-activator MAML1 and thereby repress Notch signaling. We expressed 45 different animal and human E6 proteins from diverse papillomavirus genera to ascertain the overall preference of E6 proteins for E6AP or MAML1. E6 proteins from all HPV genera except Alpha preferentially interacted with MAML1 over E6AP. Among animal papillomaviruses, E6 proteins from certain ungulate (SsPV1 from pigs and cetacean (porpoises and dolphins hosts functionally resembled Alpha genus HPV by binding and targeting the degradation of E6AP. Beta genus HPV E6 proteins functionally clustered with Delta, Pi, Tau, Gamma, Chi, Mu, Lambda, Iota, Dyokappa, Rho, and Dyolambda E6 proteins to bind and repress MAML1. None of the tested E6 proteins physically and functionally interacted with both MAML1 and E6AP, indicating an evolutionary split. Further, interaction of an E6 protein was insufficient to activate degradation of E6AP, indicating that E6 proteins that target E6AP co-evolved to separately acquire both binding and triggering of ubiquitin ligase activation. E6 proteins with similar biological function clustered together in phylogenetic trees and shared structural features. This suggests that the divergence of E6 proteins from either MAML1 or E6AP binding preference is a major event in papillomavirus evolution.

Ion pairs in non-redundant protein structures

Indian Academy of Sciences (India)

Ion pairs contribute to several functions including the activity of catalytic triads, fusion of viral membranes, stability in thermophilic proteins and solvent–protein interactions. Furthermore, they have the ability to affect the stability of protein structures and are also a part of the forces that act to hold monomers together.

Use of the Operon Structure of the C. elegans Genome as a Tool to Identify Functionally Related Proteins

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Silvia Dossena

2013-12-01

Full Text Available One of the most pressing challenges in the post genomic era is the identification and characterization of protein-protein interactions (PPIs, as these are essential in understanding the cellular physiology of health and disease. Experimental techniques suitable for characterizing PPIs (X-ray crystallography or nuclear magnetic resonance spectroscopy, among others are usually laborious, time-consuming and often difficult to apply to membrane proteins, and therefore require accurate prediction of the candidate interacting partners. High-throughput experimental methods (yeast two-hybrid and affinity purification succumb to the same shortcomings, and can also lead to high rates of false positive and negative results. Therefore, reliable tools for predicting PPIs are needed. The use of the operon structure in the eukaryote Caenorhabditis elegans genome is a valuable, though underserved, tool for identifying physically or functionally interacting proteins. Based on the concept that genes organized in the same operon may encode physically or functionally related proteins, this algorithm is easy to be applied and, importantly, gives a limited number of candidate partners of a given protein, allowing for focused experimental verification. Moreover, this approach can be successfully used to predict PPIs in the human system, including those of membrane proteins.

An impedance function approach for soil-structure interaction analyses including structure-to-structure interaction effects

International Nuclear Information System (INIS)

Gantayat, A.; Kamil, H.

1981-01-01

The dynamic soil-structure and structure-to-structure interaction effects may be determined in one of the two ways: by modeling the entire soil-structure system by a finite-element model, or by using a frequency-dependent (or frequency-independent) impedance function approach. In seismic design of nuclear power plant structures, the normal practice is to use the first approach because of its simplicity and easy availability of computer codes to perform such analyses. However, in the finite-element approach, because of the size and cost restrictions, the three-dimensional behavior of the entire soil-structure system and the radiation damping in soil are only approximately included by using a two-dimensional finite-element mesh. In using the impedance function approach, the soil-structure analyses can be performed in four steps: (a) determination of the dynamic properties of the fixed base superstructure, (b) determination of foundation and structure impedance matrices and input motions, (c) evaluation of foundation motion, (d) analysis of the fixed base superstructure using computed foundation motion. (orig./RW)

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

Science.gov (United States)

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

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

Structural interaction and functional regulation of polycystin-2 by filamin.

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Qian Wang

Full Text Available Filamins are important actin cross-linking proteins implicated in scaffolding, membrane stabilization and signal transduction, through interaction with ion channels, receptors and signaling proteins. Here we report the physical and functional interaction between filamins and polycystin-2, a TRP-type cation channel mutated in 10-15% patients with autosomal dominant polycystic kidney disease. Yeast two-hybrid and GST pull-down experiments demonstrated that the C-termini of filamin isoforms A, B and C directly bind to both the intracellular N- and C-termini of polycystin-2. Reciprocal co-immunoprecipitation experiments showed that endogenous polycystin-2 and filamins are in the same complexes in renal epithelial cells and human melanoma A7 cells. We then examined the effect of filamin on polycystin-2 channel function by electrophysiology studies with a lipid bilayer reconstitution system and found that filamin-A substantially inhibits polycystin-2 channel activity. Our study indicates that filamins are important regulators of polycystin-2 channel function, and further links actin cytoskeletal dynamics to the regulation of this channel protein.

Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity.

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Guan-Feng Wang

2015-02-01

Full Text Available Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR. Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC, a nucleotide binding (NB-ARC and a leucine rich repeat (LRR domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.

Molecular and functional analyses of a maize autoactive NB-LRR protein identify precise structural requirements for activity.

Science.gov (United States)

Wang, Guan-Feng; Ji, Jiabing; El-Kasmi, Farid; Dangl, Jeffery L; Johal, Guri; Balint-Kurti, Peter J

2015-02-01

Plant disease resistance is often mediated by nucleotide binding-leucine rich repeat (NLR) proteins which remain auto-inhibited until recognition of specific pathogen-derived molecules causes their activation, triggering a rapid, localized cell death called a hypersensitive response (HR). Three domains are recognized in one of the major classes of NLR proteins: a coiled-coil (CC), a nucleotide binding (NB-ARC) and a leucine rich repeat (LRR) domains. The maize NLR gene Rp1-D21 derives from an intergenic recombination event between two NLR genes, Rp1-D and Rp1-dp2 and confers an autoactive HR. We report systematic structural and functional analyses of Rp1 proteins in maize and N. benthamiana to characterize the molecular mechanism of NLR activation/auto-inhibition. We derive a model comprising the following three main features: Rp1 proteins appear to self-associate to become competent for activity. The CC domain is signaling-competent and is sufficient to induce HR. This can be suppressed by the NB-ARC domain through direct interaction. In autoactive proteins, the interaction of the LRR domain with the NB-ARC domain causes de-repression and thus disrupts the inhibition of HR. Further, we identify specific amino acids and combinations thereof that are important for the auto-inhibition/activity of Rp1 proteins. We also provide evidence for the function of MHD2, a previously uncharacterized, though widely conserved NLR motif. This work reports several novel insights into the precise structural requirement for NLR function and informs efforts towards utilizing these proteins for engineering disease resistance.

BLAST-based structural annotation of protein residues using Protein Data Bank.

Science.gov (United States)

Singh, Harinder; Raghava, Gajendra P S

2016-01-25

In the era of next-generation sequencing where thousands of genomes have been already sequenced; size of protein databases is growing with exponential rate. Structural annotation of these proteins is one of the biggest challenges for the computational biologist. Although, it is easy to perform BLAST search against Protein Data Bank (PDB) but it is difficult for a biologist to annotate protein residues from BLAST search. A web-server StarPDB has been developed for structural annotation of a protein based on its similarity with known protein structures. It uses standard BLAST software for performing similarity search of a query protein against protein structures in PDB. This server integrates wide range modules for assigning different types of annotation that includes, Secondary-structure, Accessible surface area, Tight-turns, DNA-RNA and Ligand modules. Secondary structure module allows users to predict regular secondary structure states to each residue in a protein. Accessible surface area predict the exposed or buried residues in a protein. Tight-turns module is designed to predict tight turns like beta-turns in a protein. DNA-RNA module developed for predicting DNA and RNA interacting residues in a protein. Similarly, Ligand module of server allows one to predicted ligands, metal and nucleotides ligand interacting residues in a protein. In summary, this manuscript presents a web server for comprehensive annotation of a protein based on similarity search. It integrates number of visualization tools that facilitate users to understand structure and function of protein residues. This web server is available freely for scientific community from URL http://crdd.osdd.net/raghava/starpdb .

Prediction and characterization of protein-protein interaction networks in swine

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Wang Fen

2012-01-01

Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

Direct interactions of the five known Fanconi anaemia proteins suggest a common functional pathway.

Science.gov (United States)

Medhurst, A L; Huber, P A; Waisfisz, Q; de Winter , J P; Mathew, C G

2001-02-15

Fanconi anaemia (FA) is an autosomal recessive inherited disorder associated with a progressive aplastic anaemia, diverse congenital abnormalities and cancer. The condition is genetically heterogeneous, with at least seven complementation groups (A-G) described. Cells from individuals who are homozygous for mutations in FA genes are characterized by chromosomal instability and hypersensitivity to DNA interstrand crosslinking agents. These features suggest a possible role for the encoded proteins in the recognition or repair of these lesions, but neither their function nor whether they operate in a concerted or discrete functional pathways is known. The recent cloning of the FANCF and FANCE genes has allowed us to investigate the interaction of the proteins encoded by five of the seven complementation groups of FA. We used the yeast two-hybrid system and co-immunoprecipitation analysis to test the 10 possible pairs of proteins for direct interaction. In addition to the previously described binding of FANCA to FANCG, we now demonstrate direct interaction of FANCF with FANCG, of FANCC with FANCE and a weaker interaction of FANCE with both FANCA and FANCG. These findings show that the newly identified FANCE protein is an integral part of the FA pathway, and support the concept of a functional link between all known proteins encoded by the genes that are mutated in this disorder. These proteins may act either as a multimeric complex or by sequential recruitment of subsets of the proteins in a common pathway that protects the genomic integrity of mammalian cells.

From Sequence and Forces to Structure, Function and Evolution of Intrinsically Disordered Proteins

Science.gov (United States)

Forman-Kay, Julie D.; Mittag, Tanja

2015-01-01

Intrinsically disordered proteins (IDPs), which lack persistent structure, are a challenge to structural biology due to the inapplicability of standard methods for characterization of folded proteins as well as their deviation from the dominant structure/function paradigm. Their widespread presence and involvement in biological function, however, has spurred the growing acceptance of the importance of IDPs and the development of new tools for studying their structure, dynamics and function. The interplay of folded and disordered domains or regions for function and the existence of a continuum of protein states with respect to conformational energetics, motional timescales and compactness is shaping a unified understanding of structure-dynamics-disorder/function relationships. On the 20th anniversary of this journal, Structure, we provide a historical perspective on the investigation of IDPs and summarize the sequence features and physical forces that underlie their unique structural, functional and evolutionary properties. PMID:24010708

Receptor-interacting protein (RIP) kinase family

OpenAIRE

Zhang, Duanwu; Lin, Juan; Han, Jiahuai

2010-01-01

Receptor-interacting protein (RIP) kinases are a group of threonine/serine protein kinases with a relatively conserved kinase domain but distinct non-kinase regions. A number of different domain structures, such as death and caspase activation and recruitment domain (CARD) domains, were found in different RIP family members, and these domains should be keys in determining the specific function of each RIP kinase. It is known that RIP kinases participate in different biological processes, incl...

Analysis of Protein-RNA and Protein-Peptide Interactions in Equine Infectious Anemia

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae-Hyung [Iowa State Univ., Ames, IA (United States)

2007-01-01

Macromolecular interactions are essential for virtually all cellular functions including signal transduction processes, metabolic processes, regulation of gene expression and immune responses. This dissertation focuses on the characterization of two important macromolecular interactions involved in the relationship between Equine Infectious Anemia Virus (EIAV) and its host cell in horse: (1) the interaction between the EIAV Rev protein and its binding site, the Rev-responsive element (RRE) and (2) interactions between equine MHC class I molecules and epitope peptides derived from EIAV proteins. EIAV, one of the most divergent members of the lentivirus family, has a single-stranded RNA genome and carries several regulatory and structural proteins within its viral particle. Rev is an essential EIAV regulatory encoded protein that interacts with the viral RRE, a specific binding site in the viral mRNA. Using a combination of experimental and computational methods, the interactions between EIAV Rev and RRE were characterized in detail. EIAV Rev was shown to have a bipartite RNA binding domain contain two arginine rich motifs (ARMs). The RRE secondary structure was determined and specific structural motifs that act as cis-regulatory elements for EIAV Rev-RRE interaction were identified. Interestingly, a structural motif located in the high affinity Rev binding site is well conserved in several diverse lentiviral genoes, including HIV-1. Macromolecular interactions involved in the immune response of the horse to EIAV infection were investigated by analyzing complexes between MHC class I proteins and epitope peptides derived from EIAV Rev, Env and Gag proteins. Computational modeling results provided a mechanistic explanation for the experimental finding that a single amino acid change in the peptide binding domain of the quine MHC class I molecule differentially affectes the recognitino of specific epitopes by EIAV-specific CTL. Together, the findings in this

Heparan sulfate proteoglycans: structure, protein interactions and cell signaling

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Juliana L. Dreyfuss

2009-09-01

Full Text Available Heparan sulfate proteoglycans are ubiquitously found at the cell surface and extracellular matrix in all the animal species. This review will focus on the structural characteristics of the heparan sulfate proteoglycans related to protein interactions leading to cell signaling. The heparan sulfate chains due to their vast structural diversity are able to bind and interact with a wide variety of proteins, such as growth factors, chemokines, morphogens, extracellular matrix components, enzymes, among others. There is a specificity directing the interactions of heparan sulfates and target proteins, regarding both the fine structure of the polysaccharide chain as well precise protein motifs. Heparan sulfates play a role in cellular signaling either as receptor or co-receptor for different ligands, and the activation of downstream pathways is related to phosphorylation of different cytosolic proteins either directly or involving cytoskeleton interactions leading to gene regulation. The role of the heparan sulfate proteoglycans in cellular signaling and endocytic uptake pathways is also discussed.Proteoglicanos de heparam sulfato são encontrados tanto superfície celular quanto na matriz extracelular em todas as espécies animais. Esta revisão tem enfoque nas características estruturais dos proteoglicanos de heparam sulfato e nas interações destes proteoglicanos com proteínas que levam à sinalização celular. As cadeias de heparam sulfato, devido a sua variedade estrutural, são capazes de se ligar e interagir com ampla gama de proteínas, como fatores de crescimento, quimiocinas, morfógenos, componentes da matriz extracelular, enzimas, entreoutros. Existe uma especificidade estrutural que direciona as interações dos heparam sulfatos e proteínas alvo. Esta especificidade está relacionada com a estrutura da cadeia do polissacarídeo e os motivos conservados da cadeia polipeptídica das proteínas envolvidas nesta interação. Os heparam

p15PAF is an intrinsically disordered protein with nonrandom structural preferences at sites of interaction with other proteins.

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De Biasio, Alfredo; Ibáñez de Opakua, Alain; Cordeiro, Tiago N; Villate, Maider; Merino, Nekane; Sibille, Nathalie; Lelli, Moreno; Diercks, Tammo; Bernadó, Pau; Blanco, Francisco J

2014-02-18

We present to our knowledge the first structural characterization of the proliferating-cell-nuclear-antigen-associated factor p15(PAF), showing that it is monomeric and intrinsically disordered in solution but has nonrandom conformational preferences at sites of protein-protein interactions. p15(PAF) is a 12 kDa nuclear protein that acts as a regulator of DNA repair during DNA replication. The p15(PAF) gene is overexpressed in several types of human cancer. The nearly complete NMR backbone assignment of p15(PAF) allowed us to measure 86 N-H(N) residual dipolar couplings. Our residual dipolar coupling analysis reveals nonrandom conformational preferences in distinct regions, including the proliferating-cell-nuclear-antigen-interacting protein motif (PIP-box) and the KEN-box (recognized by the ubiquitin ligase that targets p15(PAF) for degradation). In accordance with these findings, analysis of the (15)N R2 relaxation rates shows a relatively reduced mobility for the residues in these regions. The agreement between the experimental small angle x-ray scattering curve of p15(PAF) and that computed from a statistical coil ensemble corrected for the presence of local secondary structural elements further validates our structural model for p15(PAF). The coincidence of these transiently structured regions with protein-protein interaction and posttranslational modification sites suggests a possible role for these structures as molecular recognition elements for p15(PAF). Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

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Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

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Barradas-Bautista, Didier; Fernández-Recio, Juan

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

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Didier Barradas-Bautista

Full Text Available Next-generation sequencing (NGS technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

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Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

Structure and function of homodomain-leucine zipper (HD-Zip) proteins.

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Elhiti, Mohamed; Stasolla, Claudio

2009-02-01

Homeodomain-leucine zipper (HD-Zip) proteins are transcription factors unique to plants and are encoded by more than 25 genes in Arabidopsis thaliana. Based on sequence analyses these proteins have been classified into four distinct groups: HD-Zip I-IV. HD-Zip proteins are characterized by the presence of two functional domains; a homeodomain (HD) responsible for DNA binding and a leucine zipper domain (Zip) located immediately C-terminal to the homeodomain and involved in protein-protein interaction. Despite sequence similarities HD-ZIP proteins participate in a variety of processes during plant growth and development. HD-Zip I proteins are generally involved in responses related to abiotic stress, abscisic acid (ABA), blue light, de-etiolation and embryogenesis. HD-Zip II proteins participate in light response, shade avoidance and auxin signalling. Members of the third group (HD-Zip III) control embryogenesis, leaf polarity, lateral organ initiation and meristem function. HD-Zip IV proteins play significant roles during anthocyanin accumulation, differentiation of epidermal cells, trichome formation and root development.

Protein-protein interactions as a strategy towards protein-specific drug design: the example of ataxin-1.

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Cesira de Chiara

Full Text Available A main challenge for structural biologists is to understand the mechanisms that discriminate between molecular interactions and determine function. Here, we show how partner recognition of the AXH domain of the transcriptional co-regulator ataxin-1 is fine-tuned by a subtle balance between self- and hetero-associations. Ataxin-1 is the protein responsible for the hereditary spinocerebellar ataxia type 1, a disease linked to protein aggregation and transcriptional dysregulation. Expansion of a polyglutamine tract is essential for ataxin-1 aggregation, but the sequence-wise distant AXH domain plays an important aggravating role in the process. The AXH domain is also a key element for non-aberrant function as it intervenes in interactions with multiple protein partners. Previous data have shown that AXH is dimeric in solution and forms a dimer of dimers when crystallized. By solving the structure of a complex of AXH with a peptide from the interacting transcriptional repressor CIC, we show that the dimer interface of AXH is displaced by the new interaction and that, when blocked by the CIC peptide AXH aggregation and misfolding are impaired. This is a unique example in which palindromic self- and hetero-interactions within a sequence with chameleon properties discriminate the partner. We propose a drug design strategy for the treatment of SCA1 that is based on the information gained from the AXH/CIC complex.

A specific interdomain interaction preserves the structural and binding properties of the ModA protein from the phytopathogen Xanthomonas citri domain interaction and transport in ModA.

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Santacruz-Perez, Carolina; Pegos, Vanessa Rodrigues; Honorato, Rodrigo V; Verli, Hugo; Lindahl, Erik; Barbosa, João Alexandre Ribeiro Gonçalves; Balan, Andrea

2013-11-01

The periplasmic-binding proteins in ATP-binding cassette systems (ABC Transporters) are responsible for the capture and delivery of ligands to their specific transporters, triggering a series of ATP-driven conformational changes that leads to the transport of the ligand. Structurally consisting of two lobes, the proteins change conformation after interaction with the ligand. The structure of the molybdate-binding protein (ModA) from Xanthomonas citri, bound to molybdate, was previously solved by our group and an interdomain interaction, mediated by a salt bridge between K127 and D59, apparently supports the binding properties and keeps the domains closed. To determinate the importance of this interaction, we built two ModA mutants, K127S and D59A, and analysed their functional and structural properties. Based on a set of spectroscopic experiments, crystallisation trials, structure determination and molecular dynamics (MD) simulations, we showed that the salt bridge is essential to maintain the structure and binding properties. Additionally, the MD simulations revealed that this mutant adopted a more compact structure that packed down the ligand-binding pocket. From the closed bound to open structure, the positioning of the helices forming the dipole and the salt bridge are essential to induce an intermediate state. Copyright © 2013 Elsevier Inc. All rights reserved.

Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

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Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

2017-09-21

Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

In silico studies on structure-function of DNA GCC- box binding domain of brassica napus DREB1 protein

International Nuclear Information System (INIS)

Qamarunnisa, S.; Hussain, M.

2012-01-01

DREB1 is a transcriptional factor, which selectively binds with the promoters of the genes involved in stress response in the plants. Homology of DREB protein and its binding element have been detected in the genome of many plants. However, only a few reports exist that discusses the binding properties of this protein with the gene (s) promoter. In the present study, we have undertaken studies exploring the structure-function relationship of Brassica napus DREB1. Multiple sequence alignment, protein homology modeling and intermolecular docking of GCC-box binding domain (GBD) of the said protein was carried out using atomic coordinates of GBD from Arabdiopsis thaliana and GCC-box containing DNA respectively. Similarities and/or identities in multiple, sequence alignment, particularly at the functionally important amino acids, strongly suggested the binding specificity of B. napus DREB1 to GCC-box. Similarly, despite 56% sequence homology, tertiary structures of both template and modeled protein were found to be extremely similar as indicated by root mean square deviation of 0.34 A. More similarities were established between GBD of both A. thaliana and B. napus DREB1 by conducting protein docking with the DNA containing GCC-box. It appears that both proteins interact through their beta-sheet with the major DNA groove including both nitrogen bases and phosphate and sugar moieties. Additionally, in most cases the interacting residues were also found to be identical. Briefly, this study attempts to elucidate the molecular basis of DREB1 interaction with its target sequence in the promoter. (author)

Fundamental Characteristics of AAA+ Protein Family Structure and Function.

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Miller, Justin M; Enemark, Eric J

2016-01-01

Many complex cellular events depend on multiprotein complexes known as molecular machines to efficiently couple the energy derived from adenosine triphosphate hydrolysis to the generation of mechanical force. Members of the AAA+ ATPase superfamily (ATPases Associated with various cellular Activities) are critical components of many molecular machines. AAA+ proteins are defined by conserved modules that precisely position the active site elements of two adjacent subunits to catalyze ATP hydrolysis. In many cases, AAA+ proteins form a ring structure that translocates a polymeric substrate through the central channel using specialized loops that project into the central channel. We discuss the major features of AAA+ protein structure and function with an emphasis on pivotal aspects elucidated with archaeal proteins.

Highlights on distinctive structural and functional properties of HTLV Tax proteins

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Romanelli, Maria Grazia; Diani, Erica; Bergamo, Elisa; Casoli, Claudio; Ciminale, Vincenzo; Bex, Françoise; Bertazzoni, Umberto

2013-01-01

Human T cell leukemia viruses (HTLVs) are complex human retroviruses of the Deltaretrovirus genus. Four types have been identified thus far, with HTLV-1 and HTLV-2 much more prevalent than HTLV-3 or HTLV-4. HTLV-1 and HTLV-2 possess strictly related genomic structures, but differ significantly in pathogenicity, as HTLV-1 is the causative agent of adult T cell leukemia and of HTLV-associated myelopathy/tropical spastic paraparesis, whereas HTLV-2 is not associated with neoplasia. HTLVs code for a protein named Tax that is responsible for enhancing viral expression and drives cell transformation. Much effort has been invested to dissect the impact of Tax on signal transduction pathways and to identify functional differences between the HTLV Tax proteins that may explain the distinct oncogenic potential of HTLV-1 and HTLV-2. This review summarizes our current knowledge of Tax-1 and Tax-2 with emphasis on their structure, role in activation of the NF-κB (nuclear factor kappa-B) pathway, and interactions with host factors. PMID:24058363

Chromosome-wise Protein Interaction Patterns and Their Impact on Functional Implications of Large-Scale Genomic Aberrations

DEFF Research Database (Denmark)

Kirk, Isa Kristina; Weinhold, Nils; Belling, Kirstine González-Izarzugaza

2017-01-01

Gene copy-number changes influence phenotypes through gene-dosage alteration and subsequent changes of protein complex stoichiometry. Human trisomies where gene copy numbers are increased uniformly over entire chromosomes provide generic cases for studying these relationships. In most trisomies......, gene and protein level alterations have fatal consequences. We used genome-wide protein-protein interaction data to identify chromosome-specific patterns of protein interactions. We found that some chromosomes encode proteins that interact infrequently with each other, chromosome 21 in particular. We...... combined the protein interaction data with transcriptome data from human brain tissue to investigate how this pattern of global interactions may affect cellular function. We identified highly connected proteins that also had coordinated gene expression. These proteins were associated with important...

Can infrared spectroscopy provide information on protein-protein interactions?

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Haris, Parvez I

2010-08-01

For most biophysical techniques, characterization of protein-protein interactions is challenging; this is especially true with methods that rely on a physical phenomenon that is common to both of the interacting proteins. Thus, for example, in IR spectroscopy, the carbonyl vibration (1600-1700 cm(-1)) associated with the amide bonds from both of the interacting proteins will overlap extensively, making the interpretation of spectral changes very complicated. Isotope-edited infrared spectroscopy, where one of the interacting proteins is uniformly labelled with (13)C or (13)C,(15)N has been introduced as a solution to this problem, enabling the study of protein-protein interactions using IR spectroscopy. The large shift of the amide I band (approx. 45 cm(-1) towards lower frequency) upon (13)C labelling of one of the proteins reveals the amide I band of the unlabelled protein, enabling it to be used as a probe for monitoring conformational changes. With site-specific isotopic labelling, structural resolution at the level of individual amino acid residues can be achieved. Furthermore, the ability to record IR spectra of proteins in diverse environments means that isotope-edited IR spectroscopy can be used to structurally characterize difficult systems such as protein-protein complexes bound to membranes or large insoluble peptide/protein aggregates. In the present article, examples of application of isotope-edited IR spectroscopy for studying protein-protein interactions are provided.

Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

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Sers Christine T

2010-12-01

Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

Structure, Function, Self-Assembly and Origin of Simple Membrane Proteins

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Pohorille, Andrew

2003-01-01

Integral membrane proteins perform such essential cellular functions as transport of ions, nutrients and waste products across cell walls, transduction of environmental signals, regulation of cell fusion, recognition of other cells, energy capture and its conversion into high-energy compounds. In fact, 30-40% of genes in modem organisms codes for membrane proteins. Although contemporary membrane proteins or their functional assemblies can be quite complex, their transmembrane fragments are usually remarkably simple. The most common structural motif for these fragments is a bundle of alpha-helices, but occasionally it could be a beta-barrel. In a series of molecular dynamics computer simulations we investigated self-organizing properties of simple membrane proteins based on these structural motifs. Specifically, we studied folding and insertion into membranes of short, nonpolar or amphiphatic peptides. We also investigated glycophorin A, a peptide that forms sequence-specific dimers, and a transmembrane aggregate of four identical alpha-helices that forms an efficient and selective voltage-gated proton channel was investigated. Many peptides are attracted to water-membrane interfaces. Once at the interface, nonpolar peptides spontaneously fold to a-helices. Whenever the sequence permits, peptides that contain both polar and nonpolar amino also adopt helical structures, in which polar and nonpolar amino acid side chains are immersed in water and membrane, respectively. Specific identity of side chains is less important. Helical peptides at the interface could insert into the membrane and adopt a transmembrane conformation. However, insertion of a single helix is unfavorable because polar groups in the peptide become completely dehydrated upon insertion. The unfavorable free energy of insertion can be regained by spontaneous association of peptides in the membrane. The first step in this process is the formation of dimers, although the most common are aggregates of 4

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

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Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

2015-10-01

Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

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

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

2015-01-01

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

Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

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Susan Khor

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

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

Science.gov (United States)

Khor, Susan

2014-01-01

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

Structural Refinement of Proteins by Restrained Molecular Dynamics Simulations with Non-interacting Molecular Fragments.

Directory of Open Access Journals (Sweden)

Rong Shen

2015-10-01

Full Text Available The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels, each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good

Selection of peptides interfering with protein-protein interaction.

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

2009-01-01

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

Sequence motifs in MADS transcription factors responsible for specificity and diversification of protein-protein interaction.

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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

Structural basis for target protein recognition by the protein disulfide reductase thioredoxin

DEFF Research Database (Denmark)

Maeda, Kenji; Hägglund, Per; Finnie, Christine

2006-01-01

Thioredoxin is ubiquitous and regulates various target proteins through disulfide bond reduction. We report the structure of thioredoxin (HvTrxh2 from barley) in a reaction intermediate complex with a protein substrate, barley alpha-amylase/subtilisin inhibitor (BASI). The crystal structure...... of this mixed disulfide shows a conserved hydrophobic motif in thioredoxin interacting with a sequence of residues from BASI through van der Waals contacts and backbone-backbone hydrogen bonds. The observed structural complementarity suggests that the recognition of features around protein disulfides plays...... a major role in the specificity and protein disulfide reductase activity of thioredoxin. This novel insight into the function of thioredoxin constitutes a basis for comprehensive understanding of its biological role. Moreover, comparison with structurally related proteins shows that thioredoxin shares...

DIBS: a repository of disordered binding sites mediating interactions with ordered proteins.

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Schad, Eva; Fichó, Erzsébet; Pancsa, Rita; Simon, István; Dosztányi, Zsuzsanna; Mészáros, Bálint

2018-02-01

Intrinsically Disordered Proteins (IDPs) mediate crucial protein-protein interactions, most notably in signaling and regulation. As their importance is increasingly recognized, the detailed analyses of specific IDP interactions opened up new opportunities for therapeutic targeting. Yet, large scale information about IDP-mediated interactions in structural and functional details are lacking, hindering the understanding of the mechanisms underlying this distinct binding mode. Here, we present DIBS, the first comprehensive, curated collection of complexes between IDPs and ordered proteins. DIBS not only describes by far the highest number of cases, it also provides the dissociation constants of their interactions, as well as the description of potential post-translational modifications modulating the binding strength and linear motifs involved in the binding. Together with the wide range of structural and functional annotations, DIBS will provide the cornerstone for structural and functional studies of IDP complexes. DIBS is freely accessible at http://dibs.enzim.ttk.mta.hu/. The DIBS application is hosted by Apache web server and was implemented in PHP. To enrich querying features and to enhance backend performance a MySQL database was also created. dosztanyi@caesar.elte.hu or bmeszaros@caesar.elte.hu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

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Carson M Andorf

Full Text Available 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.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.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.We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

Functional requirements of AID's higher order structures and their interaction with RNA-binding proteins.

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Mondal, Samiran; Begum, Nasim A; Hu, Wenjun; Honjo, Tasuku

2016-03-15

Activation-induced cytidine deaminase (AID) is essential for the somatic hypermutation (SHM) and class-switch recombination (CSR) of Ig genes. Although both the N and C termini of AID have unique functions in DNA cleavage and recombination, respectively, during SHM and CSR, their molecular mechanisms are poorly understood. Using a bimolecular fluorescence complementation (BiFC) assay combined with glycerol gradient fractionation, we revealed that the AID C terminus is required for a stable dimer formation. Furthermore, AID monomers and dimers form complexes with distinct heterogeneous nuclear ribonucleoproteins (hnRNPs). AID monomers associate with DNA cleavage cofactor hnRNP K whereas AID dimers associate with recombination cofactors hnRNP L, hnRNP U, and Serpine mRNA-binding protein 1. All of these AID/ribonucleoprotein associations are RNA-dependent. We propose that AID's structure-specific cofactor complex formations differentially contribute to its DNA-cleavage and recombination functions.

Pedagogical Interaction in High School, the Structural and Functional Model of Pedagogical Interaction

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Semenova, Larissa A.; Kazantseva, Anastassiya I.; Sergeyeva, Valeriya V.; Raklova, Yekaterina M.; Baiseitova, Zhanar B.

2016-01-01

The study covers the problems of pedagogical technologies and their experimental implementation in the learning process. The theoretical aspects of the "student-teacher" interaction are investigated. A structural and functional model of pedagogical interaction is offered, which determines the conditions for improving pedagogical…

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

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

2013-03-01

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

Specific interaction with cardiolipin triggers functional activation of Dynamin-Related Protein 1.

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Itsasne Bustillo-Zabalbeitia

Full Text Available Dynamin-Related Protein 1 (Drp1, a large GTPase of the dynamin superfamily, is required for mitochondrial fission in healthy and apoptotic cells. Drp1 activation is a complex process that involves translocation from the cytosol to the mitochondrial outer membrane (MOM and assembly into rings/spirals at the MOM, leading to membrane constriction/division. Similar to dynamins, Drp1 contains GTPase (G, bundle signaling element (BSE and stalk domains. However, instead of the lipid-interacting Pleckstrin Homology (PH domain present in the dynamins, Drp1 contains the so-called B insert or variable domain that has been suggested to play an important role in Drp1 regulation. Different proteins have been implicated in Drp1 recruitment to the MOM, although how MOM-localized Drp1 acquires its fully functional status remains poorly understood. We found that Drp1 can interact with pure lipid bilayers enriched in the mitochondrion-specific phospholipid cardiolipin (CL. Building on our previous study, we now explore the specificity and functional consequences of this interaction. We show that a four lysine module located within the B insert of Drp1 interacts preferentially with CL over other anionic lipids. This interaction dramatically enhances Drp1 oligomerization and assembly-stimulated GTP hydrolysis. Our results add significantly to a growing body of evidence indicating that CL is an important regulator of many essential mitochondrial functions.

Enhance the performance of current scoring functions with the aid of 3D protein-ligand interaction fingerprints.

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Liu, Jie; Su, Minyi; Liu, Zhihai; Li, Jie; Li, Yan; Wang, Renxiao

2017-07-18

In structure-based drug design, binding affinity prediction remains as a challenging goal for current scoring functions. Development of target-biased scoring functions provides a new possibility for tackling this problem, but this approach is also associated with certain technical difficulties. We previously reported the Knowledge-Guided Scoring (KGS) method as an alternative approach (BMC Bioinformatics, 2010, 11, 193-208). The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding data of an appropriate reference complex, so the error in binding affinity prediction can be reduced effectively. In this study, we have developed an upgraded version, i.e. KGS2, by employing 3D protein-ligand interaction fingerprints in reference selection. KGS2 was evaluated in combination with four scoring functions (X-Score, ChemPLP, ASP, and GoldScore) on five drug targets (HIV-1 protease, carbonic anhydrase 2, beta-secretase 1, beta-trypsin, and checkpoint kinase 1). In the in situ scoring test, considerable improvements were observed in most cases after application of KGS2. Besides, the performance of KGS2 was always better than KGS in all cases. In the more challenging molecular docking test, application of KGS2 also led to improved structure-activity relationship in some cases. KGS2 can be applied as a convenient "add-on" to current scoring functions without the need to re-engineer them, and its application is not limited to certain target proteins as customized scoring functions. As an interpolation method, its accuracy in principle can be improved further with the increasing knowledge of protein-ligand complex structures and binding affinity data. We expect that KGS2 will become a practical tool for enhancing the performance of current scoring functions in binding affinity prediction. The KGS2 software is available upon contacting the authors.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

International Nuclear Information System (INIS)

Nielsen, Anders Lade

2009-01-01

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of γ-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as β-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

Energy Technology Data Exchange (ETDEWEB)

Nielsen, Anders Lade, E-mail: aln@humgen.au.dk [Department of Human Genetics, The Bartholin Building, University of Aarhus, DK-8000 Aarhus C (Denmark)

2009-10-23

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of {gamma}-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as {beta}-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

Science.gov (United States)

Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

2018-03-10

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

Computer analysis of protein functional sites projection on exon structure of genes in Metazoa.

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Medvedeva, Irina V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2015-01-01

Study of the relationship between the structural and functional organization of proteins and their coding genes is necessary for an understanding of the evolution of molecular systems and can provide new knowledge for many applications for designing proteins with improved medical and biological properties. It is well known that the functional properties of proteins are determined by their functional sites. Functional sites are usually represented by a small number of amino acid residues that are distantly located from each other in the amino acid sequence. They are highly conserved within their functional group and vary significantly in structure between such groups. According to this facts analysis of the general properties of the structural organization of the functional sites at the protein level and, at the level of exon-intron structure of the coding gene is still an actual problem. One approach to this analysis is the projection of amino acid residue positions of the functional sites along with the exon boundaries to the gene structure. In this paper, we examined the discontinuity of the functional sites in the exon-intron structure of genes and the distribution of lengths and phases of the functional site encoding exons in vertebrate genes. We have shown that the DNA fragments coding the functional sites were in the same exons, or in close exons. The observed tendency to cluster the exons that code functional sites which could be considered as the unit of protein evolution. We studied the characteristics of the structure of the exon boundaries that code, and do not code, functional sites in 11 Metazoa species. This is accompanied by a reduced frequency of intercodon gaps (phase 0) in exons encoding the amino acid residue functional site, which may be evidence of the existence of evolutionary limitations to the exon shuffling. These results characterize the features of the coding exon-intron structure that affect the functionality of the encoded protein and

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

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

2016-01-01

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

Structural anatomy of telomere OB proteins.

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Horvath, Martin P

2011-10-01

Telomere DNA-binding proteins protect the ends of chromosomes in eukaryotes. A subset of these proteins are constructed with one or more OB folds and bind with G+T-rich single-stranded DNA found at the extreme termini. The resulting DNA-OB protein complex interacts with other telomere components to coordinate critical telomere functions of DNA protection and DNA synthesis. While the first crystal and NMR structures readily explained protection of telomere ends, the picture of how single-stranded DNA becomes available to serve as primer and template for synthesis of new telomere DNA is only recently coming into focus. New structures of telomere OB fold proteins alongside insights from genetic and biochemical experiments have made significant contributions towards understanding how protein-binding OB proteins collaborate with DNA-binding OB proteins to recruit telomerase and DNA polymerase for telomere homeostasis. This review surveys telomere OB protein structures alongside highly comparable structures derived from replication protein A (RPA) components, with the goal of providing a molecular context for understanding telomere OB protein evolution and mechanism of action in protection and synthesis of telomere DNA.

Manipulating fatty acid biosynthesis in microalgae for biofuel through protein-protein interactions.

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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.

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

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Garner, Amanda L; Janda, Kim D

2011-01-01

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

Structure-function analysis of the retinoblastoma tumor suppressor protein – is the whole a sum of its parts?

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Dick Frederick A

2007-09-01

Full Text Available Abstract Biochemical analysis of the retinoblastoma protein's function has received considerable attention since it was cloned just over 20 years ago. During this time pRB has emerged as a key regulator of the cell division cycle and its ability to block proliferation is disrupted in the vast majority of human cancers. Much has been learned about the regulation of E2F transcription factors by pRB in the cell cycle. However, many questions remain unresolved and researchers continue to explore this multifunctional protein. In particular, understanding how its biochemical functions contribute to its role as a tumor suppressor remains to be determined. Since pRB has been shown to function as an adaptor molecule that links different proteins together, or to particular promoters, analyzing pRB by disrupting individual protein interactions holds tremendous promise in unraveling the intricacies of its function. Recently, crystal structures have reported how pRB interacts with some of its molecular partners. This information has created the possibility of rationally separating pRB functions by studying mutants that disrupt individual binding sites. This review will focus on literature that investigates pRB by isolating functions based on binding sites within the pocket domain. This article will also discuss the prospects for using this approach to further explore the unknown functions of pRB.

The identification and functional annotation of RNA structures conserved in vertebrates

DEFF Research Database (Denmark)

Seemann, Ernst Stefan; Mirza, Aashiq Hussain; Hansen, Claus

2017-01-01

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for Conserved RNA Structures (CRSs), leveraging structure-b......-structured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality.......Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for Conserved RNA Structures (CRSs), leveraging structure......-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ~516k human genomic regions containing CRSs. We find that a substantial fraction of human-mouse CRS regions (i) co-localize consistently with binding sites of the same RNA binding proteins...

Text mining improves prediction of protein functional sites.

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Karin M Verspoor

Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

Text Mining Improves Prediction of Protein Functional Sites

Science.gov (United States)

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Mutagenesis Objective Search and Selection Tool (MOSST: an algorithm to predict structure-function related mutations in proteins

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Asenjo Juan A

2011-04-01

Full Text Available Abstract Background Functionally relevant artificial or natural mutations are difficult to assess or predict if no structure-function information is available for a protein. This is especially important to correctly identify functionally significant non-synonymous single nucleotide polymorphisms (nsSNPs or to design a site-directed mutagenesis strategy for a target protein. A new and powerful methodology is proposed to guide these two decision strategies, based only on conservation rules of physicochemical properties of amino acids extracted from a multiple alignment of a protein family where the target protein belongs, with no need of explicit structure-function relationships. Results A statistical analysis is performed over each amino acid position in the multiple protein alignment, based on different amino acid physical or chemical characteristics, including hydrophobicity, side-chain volume, charge and protein conformational parameters. The variances of each of these properties at each position are combined to obtain a global statistical indicator of the conservation degree of each property. Different types of physicochemical conservation are defined to characterize relevant and irrelevant positions. The differences between statistical variances are taken together as the basis of hypothesis tests at each position to search for functionally significant mutable sites and to identify specific mutagenesis targets. The outcome is used to statistically predict physicochemical consensus sequences based on different properties and to calculate the amino acid propensities at each position in a given protein. Hence, amino acid positions are identified that are putatively responsible for function, specificity, stability or binding interactions in a family of proteins. Once these key functional positions are identified, position-specific statistical distributions are applied to divide the 20 common protein amino acids in each position of the protein

Interplay between grain structure and protein adsorption on functional response of osteoblasts: ultrafine-grained versus coarse-grained substrates.

Science.gov (United States)

Misra, R D K; Nune, C; Pesacreta, T C; Somani, M C; Karjalainen, L P

2013-01-01

The rapid adsorption of proteins is the starting and primary biological response that occurs when a biomedical device is implanted in the physiological system. The biological response, however, depends on the surface characteristics of the device. Considering the significant interest in nano-/ultrafine surfaces and nanostructured coatings, we describe here, the interplay between grain structure and protein adsorption (bovine serum albumin: BSA) on osteoblasts functions by comparing nanograined/ultrafine-grained (NG/UFG) and coarse-grained (CG: grain size in the micrometer range) substrates by investigating cell-substrate interactions. The protein adsorption on NG/UFG surface was beneficial in favorably modulating biological functions including cell attachment, proliferation, and viability, whereas the effect was less pronounced on protein adsorbed CG surface. Additionally, immunofluorescence studies demonstrated stronger vinculin signals associated with actin stress fibers in the outer regions of the cells and cellular extensions on protein adsorbed NG/UFG surface. The functional response followed the sequence: NG/UFG(BSA) > NG/UFG > CG(BSA) > CG. The differences in the cellular response on bare and protein adsorbed NG/UFG and CG surfaces are attributed to cumulative contribution of grain structure and degree of hydrophilicity. The study underscores the potential advantages of protein adsorption on artificial biomedical devices to enhance the bioactivity and regulate biological functions. Copyright © 2012 Wiley Periodicals, Inc.

Essential multimeric enzymes in kinetoplastid parasites: A host of potentially druggable protein-protein interactions.

Science.gov (United States)

Wachsmuth, Leah M; Johnson, Meredith G; Gavenonis, Jason

2017-06-01

Parasitic diseases caused by kinetoplastid parasites of the genera Trypanosoma and Leishmania are an urgent public health crisis in the developing world. These closely related species possess a number of multimeric enzymes in highly conserved pathways involved in vital functions, such as redox homeostasis and nucleotide synthesis. Computational alanine scanning of these protein-protein interfaces has revealed a host of potentially ligandable sites on several established and emerging anti-parasitic drug targets. Analysis of interfaces with multiple clustered hotspots has suggested several potentially inhibitable protein-protein interactions that may have been overlooked by previous large-scale analyses focusing solely on secondary structure. These protein-protein interactions provide a promising lead for the development of new peptide and macrocycle inhibitors of these enzymes.

Imperfect DNA mirror repeats in the gag gene of HIV-1 (HXB2 identify key functional domains and coincide with protein structural elements in each of the mature proteins

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Lang Dorothy M

2007-10-01

Full Text Available Abstract Background A DNA mirror repeat is a sequence segment delimited on the basis of its containing a center of symmetry on a single strand, e.g. 5'-GCATGGTACG-3'. It is most frequently described in association with a functionally significant site in a genomic sequence, and its occurrence is regarded as noteworthy, if not unusual. However, imperfect mirror repeats (IMRs having ≥ 50% symmetry are common in the protein coding DNA of monomeric proteins and their distribution has been found to coincide with protein structural elements – helices, β sheets and turns. In this study, the distribution of IMRs is evaluated in a polyprotein – to determine whether IMRs may be related to the position or order of protein cleavage or other hierarchal aspects of protein function. The gag gene of HIV-1 [GenBank:K03455] was selected for the study because its protein motifs and structural components are well documented. Results There is a highly specific relationship between IMRs and structural and functional aspects of the Gag polyprotein. The five longest IMRs in the polyprotein translate a key functional segment in each of the five cleavage products. Throughout the protein, IMRs coincide with functionally significant segments of the protein. A detailed annotation of the protein, which combines structural, functional and IMR data illustrates these associations. There is a significant statistical correlation between the ends of IMRs and the ends of PSEs in each of the mature proteins. Weakly symmetric IMRs (≥ 33% are related to cleavage positions and processes. Conclusion The frequency and distribution of IMRs in HIV-1 Gag indicates that DNA symmetry is a fundamental property of protein coding DNA and that different levels of symmetry are associated with different functional aspects of the gene and its protein. The interaction between IMRs and protein structure and function is precise and interwoven over the entire length of the polyprotein. The

Application of empirical hydration distribution functions around polar atoms for assessing hydration structures of proteins

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Matsuoka, Daisuke; Nakasako, Masayoshi

2013-01-01

Highlights: ► Empirical distribution functions of water molecules in protein hydration are made. ► The functions measure how hydrogen-bond geometry in hydration deviate from ideal. ► The functions assess experimentally identified hydration structures of protein. - Abstract: To quantitatively characterize hydrogen-bond geometry in local hydration structures of proteins, we constructed a set of empirical hydration distribution functions (EHDFs) around polar protein atoms in the main and side chains of 11 types of hydrophilic amino acids (D. Matsuoka, M. Nakasako, Journal of Physical Chemistry B 113 (2009) 11274). The functions are the ensemble average of possible hydration patterns around the polar atoms, and describe the anisotropic deviations from ideal hydrogen bond geometry. In addition, we defined probability distribution function of hydration water molecules (PDFH) over the hydrophilic surface of a protein as the sum of EHDFs of solvent accessible polar protein atoms. The functions envelop most of hydration sites identified in crystal structures of proteins (D. Matsuoka, M. Nakasako, Journal of Physical Chemistry B 114 (2010) 4652). Here we propose the application of EHDFs and PDFHs for assessing crystallographically identified hydration structures of proteins. First, hydration water molecules are classified with respect to the geometry in hydrogen bonds in referring EHDFs. Difference Fourier electron density map weighted by PDFH of protein is proposed to identify easily density peaks as candidates of hydration water molecules. A computer program implementing those ideas was developed and used for assessing hydration structures of proteins

Computational structural and functional analysis of hypothetical proteins of Staphylococcus aureus

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