Predicting protein complex geometries with a neural network.

PubMed

Chae, Myong-Ho; Krull, Florian; Lorenzen, Stephan; Knapp, Ernst-Walter

2010-03-01

A major challenge of the protein docking problem is to define scoring functions that can distinguish near-native protein complex geometries from a large number of non-native geometries (decoys) generated with noncomplexed protein structures (unbound docking). In this study, we have constructed a neural network that employs the information from atom-pair distance distributions of a large number of decoys to predict protein complex geometries. We found that docking prediction can be significantly improved using two different types of polar hydrogen atoms. To train the neural network, 2000 near-native decoys of even distance distribution were used for each of the 185 considered protein complexes. The neural network normalizes the information from different protein complexes using an additional protein complex identity input neuron for each complex. The parameters of the neural network were determined such that they mimic a scoring funnel in the neighborhood of the native complex structure. The neural network approach avoids the reference state problem, which occurs in deriving knowledge-based energy functions for scoring. We show that a distance-dependent atom pair potential performs much better than a simple atom-pair contact potential. We have compared the performance of our scoring function with other empirical and knowledge-based scoring functions such as ZDOCK 3.0, ZRANK, ITScore-PP, EMPIRE, and RosettaDock. In spite of the simplicity of the method and its functional form, our neural network-based scoring function achieves a reasonable performance in rigid-body unbound docking of proteins. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-06-01

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

Protein complex purification from Thermoplasma acidophilum using a phage display library.

PubMed

Hubert, Agnes; Mitani, Yasuo; Tamura, Tomohiro; Boicu, Marius; Nagy, István

2014-03-01

We developed a novel protein complex isolation method using a single-chain variable fragment (scFv) based phage display library in a two-step purification procedure. We adapted the antibody-based phage display technology which has been developed for single target proteins to a protein mixture containing about 300 proteins, mostly subunits of Thermoplasma acidophilum complexes. T. acidophilum protein specific phages were selected and corresponding scFvs were expressed in Escherichia coli. E. coli cell lysate containing the expressed His-tagged scFv specific against one antigen protein and T. acidophilum crude cell lysate containing intact target protein complexes were mixed, incubated and subjected to protein purification using affinity and size exclusion chromatography steps. This method was confirmed to isolate intact particles of thermosome and proteasome suitable for electron microscopy analysis and provides a novel protein complex isolation strategy applicable to organisms where no genetic tools are available. Copyright © 2013 Elsevier B.V. All rights reserved.

Exposure of DNA bases induced by the interaction of DNA and calf thymus DNA helix-destabilizing protein.

PubMed Central

Kohwi-Shigematsu, T; Enomoto, T; Yamada, M A; Nakanishi, M; Tsuboi, M

1978-01-01

The reaction of chloroacetaldehyde with adenine bases in DNA to give a fluorescent product was used to study the availability to intermolecular reaction of positions 1 and 6 of adenine in DNA complexes with calf thymus DNA helix-destabilizing protein. No inhibition of this reaction was observed when heat-denatured DNA was complexed with the protein at a protein/DNA weight ratio of 10:1, compared to free DNA. On the contrary, the same reaction was inhibited markedly for denatured DNA in the presence of calf thymus histone HI at protein/DNA weight ratio of 2:1. Furthermore, the exchange rate for hydrogens of amino and imide groups of DNA bases in DNA strands with deuterium in the solvent was totally unaffected upon complexing of DNA with the DNA helix-destabilizing protein as examined by stopped-flow ultraviolet spectroscopy. These results indicate that the DNA helix-destabilizing protein forms a complex with single-stranded DNA, leaving DNA bases uncovered by the protein. The fluorescence intensity of DNA pretreated with chloroacetaldehyde was amplified by nearly 3-fold upon addition of the DNA helix-destabilizing protein. The possibility of "unstacking" of DNA bases induced by the protein is discussed. PMID:216994

Strong Plasmonic Enhancement of a Single Peridinin-Chlorophyll a-Protein Complex on DNA Origami-Based Optical Antennas.

PubMed

Kaminska, Izabela; Bohlen, Johann; Mackowski, Sebastian; Tinnefeld, Philip; Acuna, Guillermo P

2018-02-27

In this contribution, we fabricate hybrid constructs based on a natural light-harvesting complex, peridinin-chlorophyll a-protein, coupled to dimer optical antennas self-assembled with the help of the DNA origami technique. This approach enables controlled positioning of individual complexes at the hotspot of the optical antennas based on large, colloidal gold and silver nanoparticles. Our approach allows us to selectively excite the different pigments present in the harvesting complex, reaching a fluorescence enhancement of 500-fold. This work expands the range of self-assembled functional hybrid constructs for harvesting sunlight and can be further developed for other pigment-proteins and proteins.

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

PubMed

Wan, Cuihong; Liu, Jian; Fong, Vincent; Lugowski, Andrew; Stoilova, Snejana; Bethune-Waddell, Dylan; Borgeson, Blake; Havugimana, Pierre C; Marcotte, Edward M; Emili, Andrew

2013-04-09

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-06-15

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

Kinetics and thermodynamics of irreversible inhibition of matrix metalloproteinase 2 by a Co(III) Schiff base complex

PubMed Central

Harney, Allison S.; Sole, Laura B.

2012-01-01

Cobalt(III) Schiff base complexes have been used as potent inhibitors of protein function through the coordination to histidine residues essential for activity. The kinetics and thermodynamics of the binding mechanism of Co(acacen)(NH3)2Cl [Co(acacen); where H2acacen is bis(acetylacetone)ethylenediimine] enzyme inhibition has been examined through the inactivation of matrix metalloproteinase 2 (MMP-2) protease activity. Co(acacen) is an irreversible inhibitor that exhibits time- and concentration-dependent inactivation of MMP-2. Co(acacen) inhibition of MMP-2 is temperature-dependent, with the inactivation increasing with temperature. Examination of the formation of the transition state for the MMP-2/Co(acacen) complex was determined to have a positive entropy component indicative of greater disorder in the MMP-2/Co(acacen) complex than in the reactants. With further insight into the mechanism of Co(acacen) complexes, Co(III) Schiff base complex protein inactivators can be designed to include features regulating activity and protein specificity. This approach is widely applicable to protein targets that have been identified to have clinical significance, including matrix metalloproteinases. The mechanistic information elucidated here further emphasizes the versatility and utility of Co(III) Schiff base complexes as customizable protein inhibitors. PMID:22729838

Protein-Protein Docking in Drug Design and Discovery.

PubMed

Kaczor, Agnieszka A; Bartuzi, Damian; Stępniewski, Tomasz Maciej; Matosiuk, Dariusz; Selent, Jana

2018-01-01

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Affinity proteomics to study endogenous protein complexes: Pointers, pitfalls, preferences and perspectives

PubMed Central

LaCava, John; Molloy, Kelly R.; Taylor, Martin S.; Domanski, Michal; Chait, Brian T.; Rout, Michael P.

2015-01-01

Dissecting and studying cellular systems requires the ability to specifically isolate distinct proteins along with the co-assembled constituents of their associated complexes. Affinity capture techniques leverage high affinity, high specificity reagents to target and capture proteins of interest along with specifically associated proteins from cell extracts. Affinity capture coupled to mass spectrometry (MS)-based proteomic analyses has enabled the isolation and characterization of a wide range of endogenous protein complexes. Here, we outline effective procedures for the affinity capture of protein complexes, highlighting best practices and common pitfalls. PMID:25757543

Sequence-Based Prediction of RNA-Binding Residues in Proteins.

PubMed

Walia, Rasna R; El-Manzalawy, Yasser; Honavar, Vasant G; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Over-expression and purification strategies for recombinant multi-protein oligomers: a case study of Mycobacterium tuberculosis σ/anti-σ factor protein complexes.

PubMed

Thakur, Krishan Gopal; Jaiswal, Ravi Kumar; Shukla, Jinal K; Praveena, T; Gopal, B

2010-12-01

The function of a protein in a cell often involves coordinated interactions with one or several regulatory partners. It is thus imperative to characterize a protein both in isolation as well as in the context of its complex with an interacting partner. High resolution structural information determined by X-ray crystallography and Nuclear Magnetic Resonance offer the best route to characterize protein complexes. These techniques, however, require highly purified and homogenous protein samples at high concentration. This requirement often presents a major hurdle for structural studies. Here we present a strategy based on co-expression and co-purification to obtain recombinant multi-protein complexes in the quantity and concentration range that can enable hitherto intractable structural projects. The feasibility of this strategy was examined using the σ factor/anti-σ factor protein complexes from Mycobacterium tuberculosis. The approach was successful across a wide range of σ factors and their cognate interacting partners. It thus appears likely that the analysis of these complexes based on variations in expression constructs and procedures for the purification and characterization of these recombinant protein samples would be widely applicable for other multi-protein systems. Copyright © 2010 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

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

Oligomerization of G protein-coupled receptors: computational methods.

PubMed

Selent, J; Kaczor, A A

2011-01-01

Recent research has unveiled the complexity of mechanisms involved in G protein-coupled receptor (GPCR) functioning in which receptor dimerization/oligomerization may play an important role. Although the first high-resolution X-ray structure for a likely functional chemokine receptor dimer has been deposited in the Protein Data Bank, the interactions and mechanisms of dimer formation are not yet fully understood. In this respect, computational methods play a key role for predicting accurate GPCR complexes. This review outlines computational approaches focusing on sequence- and structure-based methodologies as well as discusses their advantages and limitations. Sequence-based approaches that search for possible protein-protein interfaces in GPCR complexes have been applied with success in several studies, but did not yield always consistent results. Structure-based methodologies are a potent complement to sequence-based approaches. For instance, protein-protein docking is a valuable method especially when guided by experimental constraints. Some disadvantages like limited receptor flexibility and non-consideration of the membrane environment have to be taken into account. Molecular dynamics simulation can overcome these drawbacks giving a detailed description of conformational changes in a native-like membrane. Successful prediction of GPCR complexes using computational approaches combined with experimental efforts may help to understand the role of dimeric/oligomeric GPCR complexes for fine-tuning receptor signaling. Moreover, since such GPCR complexes have attracted interest as potential drug target for diverse diseases, unveiling molecular determinants of dimerization/oligomerization can provide important implications for drug discovery.

Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations

PubMed Central

Seeliger, Daniel; de Groot, Bert L.

2010-01-01

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 Å backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 Å backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available. PMID:20066034

Discovering protein complexes in protein interaction networks via exploring the weak ties effect

PubMed Central

2012-01-01

Background Studying protein complexes is very important in biological processes since it helps reveal the structure-functionality relationships in biological networks and much attention has been paid to accurately predict protein complexes from the increasing amount of protein-protein interaction (PPI) data. Most of the available algorithms are based on the assumption that dense subgraphs correspond to complexes, failing to take into account the inherence organization within protein complex and the roles of edges. Thus, there is a critical need to investigate the possibility of discovering protein complexes using the topological information hidden in edges. Results To provide an investigation of the roles of edges in PPI networks, we show that the edges connecting less similar vertices in topology are more significant in maintaining the global connectivity, indicating the weak ties phenomenon in PPI networks. We further demonstrate that there is a negative relation between the weak tie strength and the topological similarity. By using the bridges, a reliable virtual network is constructed, in which each maximal clique corresponds to the core of a complex. By this notion, the detection of the protein complexes is transformed into a classic all-clique problem. A novel core-attachment based method is developed, which detects the cores and attachments, respectively. A comprehensive comparison among the existing algorithms and our algorithm has been made by comparing the predicted complexes against benchmark complexes. Conclusions We proved that the weak tie effect exists in the PPI network and demonstrated that the density is insufficient to characterize the topological structure of protein complexes. Furthermore, the experimental results on the yeast PPI network show that the proposed method outperforms the state-of-the-art algorithms. The analysis of detected modules by the present algorithm suggests that most of these modules have well biological significance in context of complexes, suggesting that the roles of edges are critical in discovering protein complexes. PMID:23046740

A Novel Algorithm for Detecting Protein Complexes with the Breadth First Search

PubMed Central

Tang, Xiwei; Wang, Jianxin; Li, Min; He, Yiming; Pan, Yi

2014-01-01

Most biological processes are carried out by protein complexes. A substantial number of false positives of the protein-protein interaction (PPI) data can compromise the utility of the datasets for complexes reconstruction. In order to reduce the impact of such discrepancies, a number of data integration and affinity scoring schemes have been devised. The methods encode the reliabilities (confidence) of physical interactions between pairs of proteins. The challenge now is to identify novel and meaningful protein complexes from the weighted PPI network. To address this problem, a novel protein complex mining algorithm ClusterBFS (Cluster with Breadth-First Search) is proposed. Based on the weighted density, ClusterBFS detects protein complexes of the weighted network by the breadth first search algorithm, which originates from a given seed protein used as starting-point. The experimental results show that ClusterBFS performs significantly better than the other computational approaches in terms of the identification of protein complexes. PMID:24818139

Investigation of a protein complex network

NASA Astrophysics Data System (ADS)

Mashaghi, A. R.; Ramezanpour, A.; Karimipour, V.

2004-09-01

The budding yeast Saccharomyces cerevisiae is the first eukaryote whose genome has been completely sequenced. It is also the first eukaryotic cell whose proteome (the set of all proteins) and interactome (the network of all mutual interactions between proteins) has been analyzed. In this paper we study the structure of the yeast protein complex network in which weighted edges between complexes represent the number of shared proteins. It is found that the network of protein complexes is a small world network with scale free behavior for many of its distributions. However we find that there are no strong correlations between the weights and degrees of neighboring complexes. To reveal non-random features of the network we also compare it with a null model in which the complexes randomly select their proteins. Finally we propose a simple evolutionary model based on duplication and divergence of proteins.

Nicotine affects protein complex rearrangement in Caenorhabditis elegans cells.

PubMed

Sobkowiak, Robert; Zielezinski, Andrzej; Karlowski, Wojciech M; Lesicki, Andrzej

2017-10-01

Nicotine may affect cell function by rearranging protein complexes. We aimed to determine nicotine-induced alterations of protein complexes in Caenorhabditis elegans (C. elegans) cells, thereby revealing links between nicotine exposure and protein complex modulation. We compared the proteomic alterations induced by low and high nicotine concentrations (0.01 mM and 1 mM) with the control (no nicotine) in vivo by using mass spectrometry (MS)-based techniques, specifically the cetyltrimethylammonium bromide (CTAB) discontinuous gel electrophoresis coupled with liquid chromatography (LC)-MS/MS and spectral counting. As a result, we identified dozens of C. elegans proteins that are present exclusively or in higher abundance in either nicotine-treated or untreated worms. Based on these results, we report a possible network that captures the key protein components of nicotine-induced protein complexes and speculate how the different protein modules relate to their distinct physiological roles. Using functional annotation of detected proteins, we hypothesize that the identified complexes can modulate the energy metabolism and level of oxidative stress. These proteins can also be involved in modulation of gene expression and may be crucial in Alzheimer's disease. The findings reported in our study reveal putative intracellular interactions of many proteins with the cytoskeleton and may contribute to the understanding of the mechanisms of nicotinic acetylcholine receptor (nAChR) signaling and trafficking in cells.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.

PubMed

Labbé, Céline M; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O; Pajeva, Ilza; Miteva, Maria A

2017-07-03

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation

NASA Astrophysics Data System (ADS)

Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

2012-12-01

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation.

PubMed

Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

2012-12-07

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces

DOE PAGES

Bordner, Andrew J.; Gorin, Andrey A.

2008-05-12

Here, protein-protein interactions are ubiquitous and essential for cellular processes. High-resolution X-ray crystallographic structures of protein complexes can elucidate the details of their function and provide a basis for many computational and experimental approaches. Here we demonstrate that existing annotations of protein complexes, including those provided by the Protein Data Bank (PDB) itself, contain a significant fraction of incorrect annotations. Results: We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster ismore » relevant based on a diverse set of properties; and (4) finally combining these scores for each entry in order to predict the complex structure. Unlike previous annotation methods, consistent prediction of complexes with identical or almost identical protein content is insured. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions.« less

Bioengineering strategies to generate artificial protein complexes.

PubMed

Kim, Heejae; Siu, Ka-Hei; Raeeszadeh-Sarmazdeh, Maryam; Sun, Qing; Chen, Qi; Chen, Wilfred

2015-08-01

For many applications, increasing synergy between distinct proteins through organization is important for the specificity, regulation, and overall reaction efficiency. Although there are many examples of protein complexes in nature, a generalized method to create these complexes remains elusive. Many conventional techniques such as random chemical conjugation, physical adsorption onto surfaces, and encapsulation within matrices are imprecise approaches and can lead to deactivation of protein native functionalities. More "bio-friendly" approaches such as genetically fused proteins and biological scaffolds often can result in low yields and low complex stability. Alternatively, site-specific protein conjugation or ligation can generate artificial protein complexes that preserve the native functionalities of protein domains and maintain stability through covalent bonds. In this review, we describe three distinct methods to synthesize artificial protein complexes (genetic incorPoration of unnatural amino acids to introduce bio-orthogonal azide and alkyne groups to proteins, split-intein based expressed protein ligation, and sortase mediated ligation) and highlight interesting applications for each technique. © 2015 Wiley Periodicals, Inc.

Dilution of protein-surfactant complexes: a fluorescence study.

PubMed

Azadi, Glareh; Chauhan, Anuj; Tripathi, Anubhav

2013-09-01

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

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

NASA Astrophysics Data System (ADS)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

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

PubMed

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.

PROCOS: computational analysis of protein-protein complexes.

PubMed

Fink, Florian; Hochrein, Jochen; Wolowski, Vincent; Merkl, Rainer; Gronwald, Wolfram

2011-09-01

One of the main challenges in protein-protein docking is a meaningful evaluation of the many putative solutions. Here we present a program (PROCOS) that calculates a probability-like measure to be native for a given complex. In contrast to scores often used for analyzing complex structures, the calculated probabilities offer the advantage of providing a fixed range of expected values. This will allow, in principle, the comparison of models corresponding to different targets that were solved with the same algorithm. Judgments are based on distributions of properties derived from a large database of native and false complexes. For complex analysis PROCOS uses these property distributions of native and false complexes together with a support vector machine (SVM). PROCOS was compared to the established scoring schemes of ZRANK and DFIRE. Employing a set of experimentally solved native complexes, high probability values above 50% were obtained for 90% of these structures. Next, the performance of PROCOS was tested on the 40 binary targets of the Dockground decoy set, on 14 targets of the RosettaDock decoy set and on 9 targets that participated in the CAPRI scoring evaluation. Again the advantage of using a probability-based scoring system becomes apparent and a reasonable number of near native complexes was found within the top ranked complexes. In conclusion, a novel fully automated method is presented that allows the reliable evaluation of protein-protein complexes. Copyright © 2011 Wiley Periodicals, Inc.

A unified view of base excision repair: lesion-dependent protein complexes regulated by post-translational modification

PubMed Central

Almeida, Karen H.; Sobol, Robert W.

2007-01-01

Base excision repair (BER) proteins act upon a significantly broad spectrum of DNA lesions that result from endogenous and exogenous sources. Multiple sub-pathways of BER (short-path or long-patch) and newly designated DNA repair pathways (e.g., SSBR and NIR) that utilize BER proteins complicate any comprehensive understanding of BER and its role in genome maintenance, chemotherapeutic response, neurodegeneration, cancer or aging. Herein, we propose a unified model of BER, comprised of three functional processes: Lesion Recognition/Strand Scission, Gap Tailoring and DNA Synthesis/Ligation, each represented by one or more multiprotein complexes and coordinated via the XRCC1/DNA Ligase III and PARP1 scaffold proteins. BER therefore may be represented by a series of repair complexes that assemble at the site of the DNA lesion and mediates repair in a coordinated fashion involving protein-protein interactions that dictate subsequent steps or sub-pathway choice. Complex formation is influenced by post-translational protein modifications that arise from the cellular state or the DNA damage response, providing an increase in specificity and efficiency to the BER pathway. In this review, we have summarized the reported BER protein-protein interactions and protein post-translational modifications and discuss the impact on DNA repair capacity and complex formation. PMID:17337257

RECURSIVE PROTEIN MODELING: A DIVIDE AND CONQUER STRATEGY FOR PROTEIN STRUCTURE PREDICTION AND ITS CASE STUDY IN CASP9

PubMed Central

CHENG, JIANLIN; EICKHOLT, JESSE; WANG, ZHENG; DENG, XIN

2013-01-01

After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of structural modeling, two types of modeling techniques — template-based modeling and template-free modeling — have been developed. Template-based modeling can often generate a moderate- to high-resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling, such as fragment-based assembly, may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e. certain) and template-free (i.e. uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can signicantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction. PMID:22809379

Stability and immunogenicity of hypoallergenic peanut protein-polyphenol complexes during in vitro pepsin digestion.

PubMed

Plundrich, Nathalie J; White, Brittany L; Dean, Lisa L; Davis, Jack P; Foegeding, E Allen; Lila, Mary Ann

2015-07-01

Allergenic peanut proteins are relatively resistant to digestion, and if digested, metabolized peptides tend to remain large and immunoreactive, triggering allergic reactions in sensitive individuals. In this study, the stability of hypoallergenic peanut protein-polyphenol complexes was evaluated during simulated in vitro gastric digestion. When digested with pepsin, the basic subunit of the peanut allergen Ara h 3 was more rapidly hydrolyzed in peanut protein-cranberry or green tea polyphenol complexes compared to uncomplexed peanut flour. Ara h 2 was also hydrolyzed more quickly in the peanut protein-cranberry polyphenol complex than in uncomplexed peanut flour. Peptides from peanut protein-cranberry polyphenol complexes and peanut protein-green tea polyphenol complexes were substantially less immunoreactive (based on their capacity to bind to peanut-specific IgE from patient plasma) compared to peptides from uncomplexed peanut flour. These results suggest that peanut protein-polyphenol complexes may be less immunoreactive passing through the digestive tract in vivo, contributing to their attenuated allergenicity.

Addressing recent docking challenges: A hybrid strategy to integrate template-based and free protein-protein docking.

PubMed

Yan, Yumeng; Wen, Zeyu; Wang, Xinxiang; Huang, Sheng-You

2017-03-01

Protein-protein docking is an important computational tool for predicting protein-protein interactions. With the rapid development of proteomics projects, more and more experimental binding information ranging from mutagenesis data to three-dimensional structures of protein complexes are becoming available. Therefore, how to appropriately incorporate the biological information into traditional ab initio docking has been an important issue and challenge in the field of protein-protein docking. To address these challenges, we have developed a Hybrid DOCKing protocol of template-based and template-free approaches, referred to as HDOCK. The basic procedure of HDOCK is to model the structures of individual components based on the template complex by a template-based method if a template is available; otherwise, the component structures will be modeled based on monomer proteins by regular homology modeling. Then, the complex structure of the component models is predicted by traditional protein-protein docking. With the HDOCK protocol, we have participated in the CPARI experiment for rounds 28-35. Out of the 25 CASP-CAPRI targets for oligomer modeling, our HDOCK protocol predicted correct models for 16 targets, ranking one of the top algorithms in this challenge. Our docking method also made correct predictions on other CAPRI challenges such as protein-peptide binding for 6 out of 8 targets and water predictions for 2 out of 2 targets. The advantage of our hybrid docking approach over pure template-based docking was further confirmed by a comparative evaluation on 20 CASP-CAPRI targets. Proteins 2017; 85:497-512. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

RNA Replicon Delivery via Lipid-Complexed PRINT Protein Particles

PubMed Central

Xu, Jing; Luft, J. Christopher; Yi, Xianwen; Tian, Shaomin; Owens, Gary; Wang, Jin; Johnson, Ashley; Berglund, Peter; Smith, Jonathan; Napier, Mary E.; DeSimone, Joseph M.

2013-01-01

Herein we report the development of a non-viral lipid-complexed PRINT® (particle replication in non-wetting templates) protein particle system (LPP particle) for RNA replicon delivery with a view towards RNA replicon-based vaccination. Cylindrical bovine serum albumin (BSA) particles (diameter (d) 1 µm, height (h) 1 µm) loaded with RNA replicon and stabilized with a fully reversible disulfide cross-linker were fabricated using PRINT technology. Highly efficient delivery of the particles to Vero cells was achieved by complexing particles with a mixture of 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) lipids. Our data suggest that: 1) this lipid-complexed protein particle is a promising system for delivery of RNA replicon-based vaccines, and 2) it is necessary to use a degradable cross-linker for successful delivery of RNA replicon via protein-based particles. PMID:23924216

(PS)2: protein structure prediction server version 3.0.

PubMed

Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

2015-07-01

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

PubMed

Pan, Joshua; Meyers, Robin M; Michel, Brittany C; Mashtalir, Nazar; Sizemore, Ann E; Wells, Jonathan N; Cassel, Seth H; Vazquez, Francisca; Weir, Barbara A; Hahn, William C; Marsh, Joseph A; Tsherniak, Aviad; Kadoch, Cigall

2018-05-23

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2012-06-21

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

Comparative Network-Based Recovery Analysis and Proteomic Profiling of Neurological Changes in Valproic Acid-Treated Mice

PubMed Central

2013-01-01

Despite its prominence for characterization of complex mixtures, LC–MS/MS frequently fails to identify many proteins. Network-based analysis methods, based on protein–protein interaction networks (PPINs), biological pathways, and protein complexes, are useful for recovering non-detected proteins, thereby enhancing analytical resolution. However, network-based analysis methods do come in varied flavors for which the respective efficacies are largely unknown. We compare the recovery performance and functional insights from three distinct instances of PPIN-based approaches, viz., Proteomics Expansion Pipeline (PEP), Functional Class Scoring (FCS), and Maxlink, in a test scenario of valproic acid (VPA)-treated mice. We find that the most comprehensive functional insights, as well as best non-detected protein recovery performance, are derived from FCS utilizing real biological complexes. This outstrips other network-based methods such as Maxlink or Proteomics Expansion Pipeline (PEP). From FCS, we identified known biological complexes involved in epigenetic modifications, neuronal system development, and cytoskeletal rearrangements. This is congruent with the observed phenotype where adult mice showed an increase in dendritic branching to allow the rewiring of visual cortical circuitry and an improvement in their visual acuity when tested behaviorally. In addition, PEP also identified a novel complex, comprising YWHAB, NR1, NR2B, ACTB, and TJP1, which is functionally related to the observed phenotype. Although our results suggest different network analysis methods can produce different results, on the whole, the findings are mutually supportive. More critically, the non-overlapping information each provides can provide greater holistic understanding of complex phenotypes. PMID:23557376

The Prediction of Botulinum Toxin Structure Based on in Silico and in Vitro Analysis

NASA Astrophysics Data System (ADS)

Suzuki, Tomonori; Miyazaki, Satoru

2011-01-01

Many of biological system mediated through protein-protein interactions. Knowledge of protein-protein complex structure is required for understanding the function. The determination of huge size and flexible protein-protein complex structure by experimental studies remains difficult, costly and five-consuming, therefore computational prediction of protein structures by homolog modeling and docking studies is valuable method. In addition, MD simulation is also one of the most powerful methods allowing to see the real dynamics of proteins. Here, we predict protein-protein complex structure of botulinum toxin to analyze its property. These bioinformatics methods are useful to report the relation between the flexibility of backbone structure and the activity.

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

PubMed Central

Madaoui, Hocine; Guerois, Raphaël

2008-01-01

Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of protein–protein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein–protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact. PMID:18511568

HomPPI: a class of sequence homology based protein-protein interface prediction methods

PubMed Central

2011-01-01

Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners. PMID:21682895

Modeling complexes of modeled proteins.

PubMed

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Structure-Based Characterization of Multiprotein Complexes

PubMed Central

Wiederstein, Markus; Gruber, Markus; Frank, Karl; Melo, Francisco; Sippl, Manfred J.

2014-01-01

Summary Multiprotein complexes govern virtually all cellular processes. Their 3D structures provide important clues to their biological roles, especially through structural correlations among protein molecules and complexes. The detection of such correlations generally requires comprehensive searches in databases of known protein structures by means of appropriate structure-matching techniques. Here, we present a high-speed structure search engine capable of instantly matching large protein oligomers against the complete and up-to-date database of biologically functional assemblies of protein molecules. We use this tool to reveal unseen structural correlations on the level of protein quaternary structure and demonstrate its general usefulness for efficiently exploring complex structural relationships among known protein assemblies. PMID:24954616

Optimization of protein-protein docking for predicting Fc-protein interactions.

PubMed

Agostino, Mark; Mancera, Ricardo L; Ramsland, Paul A; Fernández-Recio, Juan

2016-11-01

The antibody crystallizable fragment (Fc) is recognized by effector proteins as part of the immune system. Pathogens produce proteins that bind Fc in order to subvert or evade the immune response. The structural characterization of the determinants of Fc-protein association is essential to improve our understanding of the immune system at the molecular level and to develop new therapeutic agents. Furthermore, Fc-binding peptides and proteins are frequently used to purify therapeutic antibodies. Although several structures of Fc-protein complexes are available, numerous others have not yet been determined. Protein-protein docking could be used to investigate Fc-protein complexes; however, improved approaches are necessary to efficiently model such cases. In this study, a docking-based structural bioinformatics approach is developed for predicting the structures of Fc-protein complexes. Based on the available set of X-ray structures of Fc-protein complexes, three regions of the Fc, loosely corresponding to three turns within the structure, were defined as containing the essential features for protein recognition and used as restraints to filter the initial docking search. Rescoring the filtered poses with an optimal scoring strategy provided a success rate of approximately 80% of the test cases examined within the top ranked 20 poses, compared to approximately 20% by the initial unrestrained docking. The developed docking protocol provides a significant improvement over the initial unrestrained docking and will be valuable for predicting the structures of currently undetermined Fc-protein complexes, as well as in the design of peptides and proteins that target Fc. Copyright © 2016 John Wiley & Sons, Ltd.

Predicting protein complexes using a supervised learning method combined with local structural information.

PubMed

Dong, Yadong; Sun, Yongqi; Qin, Chao

2018-01-01

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins

PubMed Central

de Beauchene, Isaure Chauvot; de Vries, Sjoerd J.; Zacharias, Martin

2016-01-01

Abstract Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins. PMID:27131381

Construction of ontology augmented networks for protein complex prediction.

PubMed

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

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Quantitative Analysis of Endocytic Recycling of Membrane Proteins by Monoclonal Antibody-Based Recycling Assays.

PubMed

Blagojević Zagorac, Gordana; Mahmutefendić, Hana; Maćešić, Senka; Karleuša, Ljerka; Lučin, Pero

2017-03-01

In this report, we present an analysis of several recycling protocols based on labeling of membrane proteins with specific monoclonal antibodies (mAbs). We analyzed recycling of membrane proteins that are internalized by clathrin-dependent endocytosis, represented by the transferrin receptor, and by clathrin-independent endocytosis, represented by the Major Histocompatibility Class I molecules. Cell surface membrane proteins were labeled with mAbs and recycling of mAb:protein complexes was determined by several approaches. Our study demonstrates that direct and indirect detection of recycled mAb:protein complexes at the cell surface underestimate the recycling pool, especially for clathrin-dependent membrane proteins that are rapidly reinternalized after recycling. Recycling protocols based on the capture of recycled mAb:protein complexes require the use of the Alexa Fluor 488 conjugated secondary antibodies or FITC-conjugated secondary antibodies in combination with inhibitors of endosomal acidification and degradation. Finally, protocols based on the capture of recycled proteins that are labeled with Alexa Fluor 488 conjugated primary antibodies and quenching of fluorescence by the anti-Alexa Fluor 488 displayed the same quantitative assessment of recycling as the antibody-capture protocols. J. Cell. Physiol. 232: 463-476, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

PubMed Central

Walia, Rasna R.; EL-Manzalawy, Yasser; Honavar, Vasant G.; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein–RNA complexes is important for understanding the molecular determinants of protein–RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein–RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein–RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner. PMID:27787829

Discovering functional interdependence relationship in PPI networks for protein complex identification.

PubMed

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation, PCIFI was used to identify protein complexes in real PPI network data and the protein complexes it found were matched against those that were previously known in MIPS. The results show that PCIFI can be an effective technique for the identification of protein complexes. The protein complexes it found can match more known protein complexes with a smaller false-alarm rate and can provide useful insights into the understanding of the functional interdependence relationships between proteins in protein complexes.

Electrostatic design of protein-protein association rates.

PubMed

Schreiber, Gideon; Shaul, Yossi; Gottschalk, Kay E

2006-01-01

De novo design and redesign of proteins and protein complexes have made promising progress in recent years. Here, we give an overview of how to use available computer-based tools to design proteins to bind faster and tighter to their protein-complex partner by electrostatic optimization between the two proteins. Electrostatic optimization is possible because of the simple relation between the Debye-Huckel energy of interaction between a pair of proteins and their rate of association. This can be used for rapid, structure-based calculations of the electrostatic attraction between the two proteins in the complex. Using these principles, we developed two computer programs that predict the change in k(on), and as such the affinity, on introducing charged mutations. The two programs have a web interface that is available at www.weizmann.ac.il/home/bcges/PARE.html and http://bip.weizmann.ac.il/hypare. When mutations leading to charge optimization are introduced outside the physical binding site, the rate of dissociation is unchanged and therefore the change in k(on) parallels that of the affinity. This design method was evaluated on a number of different protein complexes resulting in binding rates and affinities of hundreds of fold faster and tighter compared to wild type. In this chapter, we demonstrate the procedure and go step by step over the methodology of using these programs for protein-association design. Finally, the way to easily implement the principle of electrostatic design for any protein complex of choice is shown.

Characterization of Native Protein Complexes and Protein Isoform Variation Using Size-fractionation-based Quantitative Proteomics*

PubMed Central

Kirkwood, Kathryn J.; Ahmad, Yasmeen; Larance, Mark; Lamond, Angus I.

2013-01-01

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community. PMID:24043423

Characterization of native protein complexes and protein isoform variation using size-fractionation-based quantitative proteomics.

PubMed

Kirkwood, Kathryn J; Ahmad, Yasmeen; Larance, Mark; Lamond, Angus I

2013-12-01

Proteins form a diverse array of complexes that mediate cellular function and regulation. A largely unexplored feature of such protein complexes is the selective participation of specific protein isoforms and/or post-translationally modified forms. In this study, we combined native size-exclusion chromatography (SEC) with high-throughput proteomic analysis to characterize soluble protein complexes isolated from human osteosarcoma (U2OS) cells. Using this approach, we have identified over 71,500 peptides and 1,600 phosphosites, corresponding to over 8,000 proteins, distributed across 40 SEC fractions. This represents >50% of the predicted U2OS cell proteome, identified with a mean peptide sequence coverage of 27% per protein. Three biological replicates were performed, allowing statistical evaluation of the data and demonstrating a high degree of reproducibility in the SEC fractionation procedure. Specific proteins were detected interacting with multiple independent complexes, as typified by the separation of distinct complexes for the MRFAP1-MORF4L1-MRGBP interaction network. The data also revealed protein isoforms and post-translational modifications that selectively associated with distinct subsets of protein complexes. Surprisingly, there was clear enrichment for specific Gene Ontology terms associated with differential size classes of protein complexes. This study demonstrates that combined SEC/MS analysis can be used for the system-wide annotation of protein complexes and to predict potential isoform-specific interactions. All of these SEC data on the native separation of protein complexes have been integrated within the Encyclopedia of Proteome Dynamics, an online, multidimensional data-sharing resource available to the community.

Molecular Simulation-Based Structural Prediction of Protein Complexes in Mass Spectrometry: The Human Insulin Dimer

PubMed Central

Li, Jinyu; Rossetti, Giulia; Dreyer, Jens; Raugei, Simone; Ippoliti, Emiliano; Lüscher, Bernhard; Carloni, Paolo

2014-01-01

Protein electrospray ionization (ESI) mass spectrometry (MS)-based techniques are widely used to provide insight into structural proteomics under the assumption that non-covalent protein complexes being transferred into the gas phase preserve basically the same intermolecular interactions as in solution. Here we investigate the applicability of this assumption by extending our previous structural prediction protocol for single proteins in ESI-MS to protein complexes. We apply our protocol to the human insulin dimer (hIns2) as a test case. Our calculations reproduce the main charge and the collision cross section (CCS) measured in ESI-MS experiments. Molecular dynamics simulations for 0.075 ms show that the complex maximizes intermolecular non-bonded interactions relative to the structure in water, without affecting the cross section. The overall gas-phase structure of hIns2 does exhibit differences with the one in aqueous solution, not inferable from a comparison with calculated CCS. Hence, care should be exerted when interpreting ESI-MS proteomics data based solely on NMR and/or X-ray structural information. PMID:25210764

Principles of assembly reveal a periodic table of protein complexes.

PubMed

Ahnert, Sebastian E; Marsh, Joseph A; Hernández, Helena; Robinson, Carol V; Teichmann, Sarah A

2015-12-11

Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization in protein complexes. We first examined the fundamental steps by which protein complexes can assemble, using experimental and structure-based characterization of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, enable a natural organization of protein complexes into a periodic table. On the basis of this table, we can accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. These results have important implications for quaternary structure prediction, modeling, and engineering. Copyright © 2015, American Association for the Advancement of Science.

Subunit Organisation of In Vitro Reconstituted HOPS and CORVET Multisubunit Membrane Tethering Complexes

PubMed Central

Guo, Zhong; Johnston, Wayne; Kovtun, Oleksiy; Mureev, Sergey; Bröcker, Cornelia; Ungermann, Christian; Alexandrov, Kirill

2013-01-01

Biochemical and structural analysis of macromolecular protein assemblies remains challenging due to technical difficulties in recombinant expression, engineering and reconstitution of multisubunit complexes. Here we use a recently developed cell-free protein expression system based on the protozoan Leishmania tarentolae to produce in vitro all six subunits of the 600 kDa HOPS and CORVET membrane tethering complexes. We demonstrate that both subcomplexes and the entire HOPS complex can be reconstituted in vitro resulting in a comprehensive subunit interaction map. To our knowledge this is the largest eukaryotic protein complex in vitro reconstituted to date. Using the truncation and interaction analysis, we demonstrate that the complex is assembled through short hydrophobic sequences located in the C-terminus of the individual Vps subunits. Based on this data we propose a model of the HOPS and CORVET complex assembly that reconciles the available biochemical and structural data. PMID:24312556

Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs.

PubMed

Várnai, Csilla; Burkoff, Nikolas S; Wild, David L

2017-01-01

Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs.

Rule-based modeling and simulations of the inner kinetochore structure.

PubMed

Tschernyschkow, Sergej; Herda, Sabine; Gruenert, Gerd; Döring, Volker; Görlich, Dennis; Hofmeister, Antje; Hoischen, Christian; Dittrich, Peter; Diekmann, Stephan; Ibrahim, Bashar

2013-09-01

Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins. Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts. Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores. Copyright © 2013 Elsevier Ltd. All rights reserved.

Genetic code expansion for multiprotein complex engineering.

PubMed

Koehler, Christine; Sauter, Paul F; Wawryszyn, Mirella; Girona, Gemma Estrada; Gupta, Kapil; Landry, Jonathan J M; Fritz, Markus Hsi-Yang; Radic, Ksenija; Hoffmann, Jan-Erik; Chen, Zhuo A; Zou, Juan; Tan, Piau Siong; Galik, Bence; Junttila, Sini; Stolt-Bergner, Peggy; Pruneri, Giancarlo; Gyenesei, Attila; Schultz, Carsten; Biskup, Moritz Bosse; Besir, Hueseyin; Benes, Vladimir; Rappsilber, Juri; Jechlinger, Martin; Korbel, Jan O; Berger, Imre; Braese, Stefan; Lemke, Edward A

2016-12-01

We present a baculovirus-based protein engineering method that enables site-specific introduction of unique functionalities in a eukaryotic protein complex recombinantly produced in insect cells. We demonstrate the versatility of this efficient and robust protein production platform, 'MultiBacTAG', (i) for the fluorescent labeling of target proteins and biologics using click chemistries, (ii) for glycoengineering of antibodies, and (iii) for structure-function studies of novel eukaryotic complexes using single-molecule Förster resonance energy transfer as well as site-specific crosslinking strategies.

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

Quantification of dynamic protein complexes using Renilla luciferase fragment complementation applied to protein kinase A activities in vivo.

PubMed

Stefan, E; Aquin, S; Berger, N; Landry, C R; Nyfeler, B; Bouvier, M; Michnick, S W

2007-10-23

The G protein-coupled receptor (GPCR) superfamily represents the most important class of pharmaceutical targets. Therefore, the characterization of receptor cascades and their ligands is a prerequisite to discovering novel drugs. Quantification of agonist-induced second messengers and downstream-coupled kinase activities is central to characterization of GPCRs or other pathways that converge on GPCR-mediated signaling. Furthermore, there is a need for simple, cell-based assays that would report on direct or indirect actions on GPCR-mediated effectors of signaling. More generally, there is a demand for sensitive assays to quantify alterations of protein complexes in vivo. We describe the development of a Renilla luciferase (Rluc)-based protein fragment complementation assay (PCA) that was designed specifically to investigate dynamic protein complexes. We demonstrate these features for GPCR-induced disassembly of protein kinase A (PKA) regulatory and catalytic subunits, a key effector of GPCR signaling. Taken together, our observations show that the PCA allows for direct and accurate measurements of live changes of absolute values of protein complex assembly and disassembly as well as cellular imaging and dynamic localization of protein complexes. Moreover, the Rluc-PCA has a sufficiently high signal-to-background ratio to identify endogenously expressed Galpha(s) protein-coupled receptors. We provide pharmacological evidence that the phosphodiesterase-4 family selectively down-regulates constitutive beta-2 adrenergic- but not vasopressin-2 receptor-mediated PKA activities. Our results show that the sensitivity of the Rluc-PCA simplifies the recording of pharmacological profiles of GPCR-based candidate drugs and could be extended to high-throughput screens to identify novel direct modulators of PKA or upstream components of GPCR signaling cascades.

Structure-based characterization of multiprotein complexes.

PubMed

Wiederstein, Markus; Gruber, Markus; Frank, Karl; Melo, Francisco; Sippl, Manfred J

2014-07-08

Multiprotein complexes govern virtually all cellular processes. Their 3D structures provide important clues to their biological roles, especially through structural correlations among protein molecules and complexes. The detection of such correlations generally requires comprehensive searches in databases of known protein structures by means of appropriate structure-matching techniques. Here, we present a high-speed structure search engine capable of instantly matching large protein oligomers against the complete and up-to-date database of biologically functional assemblies of protein molecules. We use this tool to reveal unseen structural correlations on the level of protein quaternary structure and demonstrate its general usefulness for efficiently exploring complex structural relationships among known protein assemblies. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Identifying protein complexes in PPI network using non-cooperative sequential game.

PubMed

Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta

2017-08-21

Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.

A general and fast scoring function for protein-ligand interactions: a simplified potential approach.

PubMed

Muegge, I; Martin, Y C

1999-03-11

A fast, simplified potential-based approach is presented that estimates the protein-ligand binding affinity based on the given 3D structure of a protein-ligand complex. This general, knowledge-based approach exploits structural information of known protein-ligand complexes extracted from the Brookhaven Protein Data Bank and converts it into distance-dependent Helmholtz free interaction energies of protein-ligand atom pairs (potentials of mean force, PMF). The definition of an appropriate reference state and the introduction of a correction term accounting for the volume taken by the ligand were found to be crucial for deriving the relevant interaction potentials that treat solvation and entropic contributions implicitly. A significant correlation between experimental binding affinities and computed score was found for sets of diverse protein-ligand complexes and for sets of different ligands bound to the same target. For 77 protein-ligand complexes taken from the Brookhaven Protein Data Bank, the calculated score showed a standard deviation from observed binding affinities of 1.8 log Ki units and an R2 value of 0.61. The best results were obtained for the subset of 16 serine protease complexes with a standard deviation of 1.0 log Ki unit and an R2 value of 0.86. A set of 33 inhibitors modeled into a crystal structure of HIV-1 protease yielded a standard deviation of 0.8 log Ki units from measured inhibition constants and an R2 value of 0.74. In contrast to empirical scoring functions that show similar or sometimes better correlation with observed binding affinities, our method does not involve deriving specific parameters that fit the observed binding affinities of protein-ligand complexes of a given training set. We compared the performance of the PMF score, Böhm's score (LUDI), and the SMOG score for eight different test sets of protein-ligand complexes. It was found that for the majority of test sets the PMF score performs best. The strength of the new approach presented here lies in its generality as no knowledge about measured binding affinities is needed to derive atomic interaction potentials. The use of the new scoring function in docking studies is outlined.

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

PubMed

Armean, Irina M; Lilley, Kathryn S; Trotter, Matthew W B; Pilkington, Nicholas C V; Holden, Sean B

2018-06-01

Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontology (GO) being one of the most successful projects. Several PPI evaluation algorithms have been based on the application of probabilistic frameworks or machine learning algorithms to GO properties. Here, we introduce a new training set design and machine learning based approach that combines dependent heterogeneous protein annotations from the entire ontology to evaluate putative co-complex protein interactions determined by empirical studies. PPI annotations are built combinatorically using corresponding GO terms and InterPro annotation. We use a S.cerevisiae high-confidence complex dataset as a positive training set. A series of classifiers based on Maximum Entropy and support vector machines (SVMs), each with a composite counterpart algorithm, are trained on a series of training sets. These achieve a high performance area under the ROC curve of ≤0.97, outperforming go2ppi-a previously established prediction tool for protein-protein interactions (PPI) based on Gene Ontology (GO) annotations. https://github.com/ima23/maxent-ppi. sbh11@cl.cam.ac.uk. Supplementary data are available at Bioinformatics online.

Structural Mechanism behind Distinct Efficiency of Oct4/Sox2 Proteins in Differentially Spaced DNA Complexes

PubMed Central

Yesudhas, Dhanusha; Anwar, Muhammad Ayaz; Panneerselvam, Suresh; Durai, Prasannavenkatesh; Shah, Masaud; Choi, Sangdun

2016-01-01

The octamer-binding transcription factor 4 (Oct4) and sex-determining region Y (SRY)-box 2 (Sox2) proteins induce various transcriptional regulators to maintain cellular pluripotency. Most Oct4/Sox2 complexes have either 0 base pairs (Oct4/Sox20bp) or 3 base pairs (Oct4/Sox23bp) separation between their DNA-binding sites. Results from previous biochemical studies have shown that the complexes separated by 0 base pairs are associated with a higher pluripotency rate than those separated by 3 base pairs. Here, we performed molecular dynamics (MD) simulations and calculations to determine the binding free energy and per-residue free energy for the Oct4/Sox20bp and Oct4/Sox23bp complexes to identify structural differences that contribute to differences in induction rate. Our MD simulation results showed substantial differences in Oct4/Sox2 domain movements, as well as secondary-structure changes in the Oct4 linker region, suggesting a potential reason underlying the distinct efficiencies of these complexes during reprogramming. Moreover, we identified key residues and hydrogen bonds that potentially facilitate protein-protein and protein-DNA interactions, in agreement with previous experimental findings. Consequently, our results confess that differential spacing of the Oct4/Sox2 DNA binding sites can determine the magnitude of transcription of the targeted genes during reprogramming. PMID:26790000

PLI: a web-based tool for the comparison of protein-ligand interactions observed on PDB structures.

PubMed

Gallina, Anna Maria; Bisignano, Paola; Bergamino, Maurizio; Bordo, Domenico

2013-02-01

A large fraction of the entries contained in the Protein Data Bank describe proteins in complex with low molecular weight molecules such as physiological compounds or synthetic drugs. In many cases, the same molecule is found in distinct protein-ligand complexes. There is an increasing interest in Medicinal Chemistry in comparing protein binding sites to get insight on interactions that modulate the binding specificity, as this structural information can be correlated with other experimental data of biochemical or physiological nature and may help in rational drug design. The web service protein-ligand interaction presented here provides a tool to analyse and compare the binding pockets of homologous proteins in complex with a selected ligand. The information is deduced from protein-ligand complexes present in the Protein Data Bank and stored in the underlying database. Freely accessible at http://bioinformatics.istge.it/pli/.

Cellulosome-based, Clostridium-derived multi-functional enzyme complexes for advanced biotechnology tool development: advances and applications.

PubMed

Hyeon, Jeong Eun; Jeon, Sang Duck; Han, Sung Ok

2013-11-01

The cellulosome is one of nature's most elegant and elaborate nanomachines and a key biological and biotechnological macromolecule that can be used as a multi-functional protein complex tool. Each protein module in the cellulosome system is potentially useful in an advanced biotechnology application. The high-affinity interactions between the cohesin and dockerin domains can be used in protein-based biosensors to improve both sensitivity and selectivity. The scaffolding protein includes a carbohydrate-binding module (CBM) that attaches strongly to cellulose substrates and facilitates the purification of proteins fused with the dockerin module through a one-step CBM purification method. Although the surface layer homology (SLH) domain of CbpA is not present in other strains, replacement of the cell surface anchoring domain allows a foreign protein to be displayed on the surface of other strains. The development of a hydrolysis enzyme complex is a useful strategy for consolidated bioprocessing (CBP), enabling microorganisms with biomass hydrolysis activity. Thus, the development of various configurations of multi-functional protein complexes for use as tools in whole-cell biocatalyst systems has drawn considerable attention as an attractive strategy for bioprocess applications. This review provides a detailed summary of the current achievements in Clostridium-derived multi-functional complex development and the impact of these complexes in various areas of biotechnology. Copyright © 2013 Elsevier Inc. All rights reserved.

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Proof of concept of a "greener" protein purification/enrichment method based on carboxylate-terminated carbosilane dendrimer-protein interactions.

PubMed

González-García, Estefanía; Maly, Marek; de la Mata, Francisco Javier; Gómez, Rafael; Marina, María Luisa; García, María Concepción

2016-11-01

Protein sample preparation is a critical and an unsustainable step since it involves the use of tedious methods that usually require high amount of solvents. The development of new materials offers additional opportunities in protein sample preparation. This work explores, for the first time, the potential application of carboxylate-terminated carbosilane dendrimers to the purification/enrichment of proteins. Studies on dendrimer binding to proteins, based on protein fluorescence intensity and emission wavelengths measurements, demonstrated the interaction between carboxylate-terminated carbosilane dendrimers and proteins at all tested pH levels. Interactions were greatly affected by the protein itself, pH, and dendrimer concentration and generation. Especially interesting was the interaction at acidic pH since it resulted in a significant protein precipitation. Dendrimer-protein interactions were modeled observing stable complexes for all proteins. Carboxylate-terminated carbosilane dendrimers at acidic pH were successfully used in the purification/enrichment of proteins extracted from a complex sample. Graphical Abstract Images showing the growing turbidity of solutions containing a mixture of proteins (lysozyme, myoglobin, and BSA) at different protein:dendrimer ratios (1:0, 1:1, 1:8, and 1:20) at acidic pH and SDS-PAGE profiles of the corresponsing supernatants. Comparison of SDS-PAGE profiles for the pellets obtained during the purification of proteins present in a complex sample using a conventional "no-clean" method based on acetone precipitation and the proposed "greener" method using carboxylate-terminated carbosilane dendrimer at a 1:20 protein:dendrimer ratio.

Protein-Protein Interface and Disease: Perspective from Biomolecular Networks.

PubMed

Hu, Guang; Xiao, Fei; Li, Yuqian; Li, Yuan; Vongsangnak, Wanwipa

Protein-protein interactions are involved in many important biological processes and molecular mechanisms of disease association. Structural studies of interfacial residues in protein complexes provide information on protein-protein interactions. Characterizing protein-protein interfaces, including binding sites and allosteric changes, thus pose an imminent challenge. With special focus on protein complexes, approaches based on network theory are proposed to meet this challenge. In this review we pay attention to protein-protein interfaces from the perspective of biomolecular networks and their roles in disease. We first describe the different roles of protein complexes in disease through several structural aspects of interfaces. We then discuss some recent advances in predicting hot spots and communication pathway analysis in terms of amino acid networks. Finally, we highlight possible future aspects of this area with respect to both methodology development and applications for disease treatment.

Synthesis, characterization of α-amino acid Schiff base derived Ru/Pt complexes: Induces cytotoxicity in HepG2 cell via protein binding and ROS generation

NASA Astrophysics Data System (ADS)

Alsalme, Ali; Laeeq, Sameen; Dwivedi, Sourabh; Khan, Mohd. Shahnawaz; Al Farhan, Khalid; Musarrat, Javed; Khan, Rais Ahmad

2016-06-01

We have synthesized two new complexes of platinum (1) and ruthenium (2) with α-amino acid, L-alanine, and 2,3-dihydroxybenzaldehyde derived Schiff base (L). The ligand and both complexes were characterized by using elemental analysis and several other spectroscopic techniques viz; IR, 1H, 13C NMR, EPR, and ESI-MS. Furthermore, the protein-binding ability of synthesized complexes was monitored by UV-visible, fluorescence and circular dichroism techniques with a model protein, human serum albumin (HSA). Both the PtL2 and RuL2 complexes displayed significant binding towards HSA. Also, in vitro cytotoxicity assay for both complexes was carried out on human hepatocellular carcinoma cancer (HepG2) cell line. The results showed concentration-dependent inhibition of cell viability. Moreover, the generation of reactive oxygen species was also evaluated, and results exhibited substantial role in cytotoxicity.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces.

PubMed

Bordner, Andrew J; Gorin, Andrey A

2008-05-12

Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB). We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster is relevant based on a diverse set of properties; and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS) website (see Availability and requirements section). Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

Intracellular delivery of universal proteins using a lysine headgroup containing cationic liposomes: deciphering the uptake mechanism.

PubMed

Sarker, Satya Ranjan; Hokama, Ryosuke; Takeoka, Shinji

2014-01-06

An amino acid-based cationic lipid having a TFA counterion (trifluoroacetic acid counterion) in the lysine headgroup was used to deliver functional proteins into human cervical cancer cells, HeLa, in the presence of serum. Proteins used in the study were fluorescein isothiocyanate (FITC) labeled bovine serum albumin, mouse anti-F actin antibody [NH3], and goat anti mouse IgG conjugated with FITC. The formation of liposome/protein complexes was confirmed using native polyacrylamide gel electrophoresis. Furthermore, the complexes were characterized in terms of their size and zeta potential at different pH values and found to be responsive to changes in pH. The highest delivery efficiency of the liposome/albumin complexes was 99% at 37 °C. The liposomes effectively delivered albumin and antibodies as confirmed by confocal laser scanning microscopy (CLSM). Inhibition studies showed that the cellular uptake mechanism of the complexes was via caveolae-mediated endocytosis, and the proteins were subsequently released from either the early endosomes or the caveosomes as suggested by CLSM. Thus, lysine-based cationic liposomes can be a useful tool for intracellular protein delivery.

An automated method for finding molecular complexes in large protein interaction networks

PubMed Central

Bader, Gary D; Hogue, Christopher WV

2003-01-01

Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from . PMID:12525261

GBA manager: an online tool for querying low-complexity regions in proteins.

PubMed

Bandyopadhyay, Nirmalya; Kahveci, Tamer

2010-01-01

Abstract We developed GBA Manager, an online software that facilitates the Graph-Based Algorithm (GBA) we proposed in our earlier work. GBA identifies the low-complexity regions (LCR) of protein sequences. GBA exploits a similarity matrix, such as BLOSUM62, to compute the complexity of the subsequences of the input protein sequence. It uses a graph-based algorithm to accurately compute the regions that have low complexities. GBA Manager is a user friendly web-service that enables online querying of protein sequences using GBA. In addition to querying capabilities of the existing GBA algorithm, GBA Manager computes the p-values of the LCR identified. The p-value gives an estimate of the possibility that the region appears by chance. GBA Manager presents the output in three different understandable formats. GBA Manager is freely accessible at http://bioinformatics.cise.ufl.edu/GBA/GBA.htm .

Evidence for functional pre-coupled complexes of receptor heteromers and adenylyl cyclase.

PubMed

Navarro, Gemma; Cordomí, Arnau; Casadó-Anguera, Verónica; Moreno, Estefanía; Cai, Ning-Sheng; Cortés, Antoni; Canela, Enric I; Dessauer, Carmen W; Casadó, Vicent; Pardo, Leonardo; Lluís, Carme; Ferré, Sergi

2018-03-28

G protein-coupled receptors (GPCRs), G proteins and adenylyl cyclase (AC) comprise one of the most studied transmembrane cell signaling pathways. However, it is unknown whether the ligand-dependent interactions between these signaling molecules are based on random collisions or the rearrangement of pre-coupled elements in a macromolecular complex. Furthermore, it remains controversial whether a GPCR homodimer coupled to a single heterotrimeric G protein constitutes a common functional unit. Using a peptide-based approach, we here report evidence for the existence of functional pre-coupled complexes of heteromers of adenosine A 2A receptor and dopamine D 2 receptor homodimers coupled to their cognate Gs and Gi proteins and to subtype 5 AC. We also demonstrate that this macromolecular complex provides the necessary frame for the canonical Gs-Gi interactions at the AC level, sustaining the ability of a Gi-coupled GPCR to counteract AC activation mediated by a Gs-coupled GPCR.

Protein-protein interaction networks (PPI) and complex diseases

PubMed Central

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

2014-01-01

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

Mapping monomeric threading to protein-protein structure prediction.

PubMed

Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

2013-03-25

The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD <2.5 Å by SPRING is 134% and 167% higher than these competing methods. SPRING is controlled with ZDOCK on 77 docking benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

Stacking interactions in PUF-RNA complexes

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

Yiling Koh, Yvonne; Wang, Yeming; Qiu, Chen

2012-07-02

Stacking interactions between amino acids and bases are common in RNA-protein interactions. Many proteins that regulate mRNAs interact with single-stranded RNA elements in the 3' UTR (3'-untranslated region) of their targets. PUF proteins are exemplary. Here we focus on complexes formed between a Caenorhabditis elegans PUF protein, FBF, and its cognate RNAs. Stacking interactions are particularly prominent and involve every RNA base in the recognition element. To assess the contribution of stacking interactions to formation of the RNA-protein complex, we combine in vivo selection experiments with site-directed mutagenesis, biochemistry, and structural analysis. Our results reveal that the identities of stackingmore » amino acids in FBF affect both the affinity and specificity of the RNA-protein interaction. Substitutions in amino acid side chains can restrict or broaden RNA specificity. We conclude that the identities of stacking residues are important in achieving the natural specificities of PUF proteins. Similarly, in PUF proteins engineered to bind new RNA sequences, the identity of stacking residues may contribute to 'target' versus 'off-target' interactions, and thus be an important consideration in the design of proteins with new specificities.« less

Identification of amino acids that promote specific and rigid TAR RNA-tat protein complex formation.

PubMed

Edwards, Thomas E; Robinson, Bruce H; Sigurdsson, Snorri Th

2005-03-01

The Tat protein and the transactivation responsive (TAR) RNA form an essential complex in the HIV lifecycle, and mutations in the basic region of the Tat protein alter this RNA-protein molecular recognition. Here, EPR spectroscopy was used to identify amino acids, flanking an essential arginine of the Tat protein, which contribute to specific and rigid TAR-Tat complex formation by monitoring changes in the mobility of nitroxide spin-labeled TAR RNA nucleotides upon binding. Arginine to lysine N-terminal mutations did not affect TAR RNA interfacial dynamics. In contrast, C-terminal point mutations, R56 in particular, affected the mobility of nucleotides U23 and U38, which are involved in a base-triple interaction in the complex. This report highlights the role of dynamics in specific molecular complex formation and demonstrates the ability of EPR spectroscopy to study interfacial dynamics of macromolecular complexes.

Complementarity of stability patches at the interfaces of protein complexes: Implication for the structural organization of energetic hot spots.

PubMed

Kuttner, Yosef Y; Engel, Stanislav

2018-02-01

A rational design of protein complexes with defined functionalities and of drugs aimed at disrupting protein-protein interactions requires fundamental understanding of the mechanisms underlying the formation of specific protein complexes. Efforts to develop efficient small-molecule or protein-based binders often exploit energetic hot spots on protein surfaces, namely, the interfacial residues that provide most of the binding free energy in the complex. The molecular basis underlying the unusually high energy contribution of the hot spots remains obscure, and its elucidation would facilitate the design of interface-targeted drugs. To study the nature of the energetic hot spots, we analyzed the backbone dynamic properties of contact surfaces in several protein complexes. We demonstrate that, in most complexes, the backbone dynamic landscapes of interacting surfaces form complementary "stability patches," in which static areas from the opposing surfaces superimpose, and that these areas are predominantly located near the geometric center of the interface. We propose that a diminished enthalpy-entropy compensation effect augments the degree to which residues positioned within the complementary stability patches contribute to complex affinity, thereby giving rise to the energetic hot spots. These findings offer new insights into the nature of energetic hot spots and the role that backbone dynamics play in facilitating intermolecular recognition. Mapping the interfacial stability patches may provide guidance for protein engineering approaches aimed at improving the stability of protein complexes and could facilitate the design of ligands that target complex interfaces. © 2017 Wiley Periodicals, Inc.

Monitoring of the Enzymatic Degradation of Protein Corona and Evaluating the Accompanying Cytotoxicity of Nanoparticles.

PubMed

Ma, Zhifang; Bai, Jing; Jiang, Xiue

2015-08-19

Established nanobio interactions face the challenge that the formation of nanoparticle-protein corona complexes shields the inherent properties of the nanoparticles and alters the manner of the interactions between nanoparticles and biological systems. Therefore, many studies have focused on protein corona-mediated nanoparticle binding, internalization, and intracellular transportation. However, there are a few studies to pay attention to if the corona encounters degradation after internalization and how the degradation of the protein corona affects cytotoxicity. To fill this gap, we prepared three types of off/on complexes based on gold nanoparticles (Au NPs) and dye-labeled serum proteins and studied the extracellular and intracellular proteolytic processes of protein coronas as well as their accompanying effects on cytotoxicity through multiple evaluation mechanisms, including cell viability, adenosine triphosphate (ATP) content, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS). The proteolytic process was confirmed by recovery of the fluorescence of the dye-labeled protein molecules that was initially quenched by Au NPs. Our results indicate that the degradation rate of protein corona is dependent on the type of the protein based on systematical evaluation of the extracellular and intracellular degradation processes of the protein coronas formed by human serum albumin (HSA), γ-globulin (HGG), and serum fibrinogen (HSF). Degradation is the fastest for HSA corona and the slowest for HSF corona. Notably, we also find that the Au NP-HSA corona complex induces lower cell viability, slower ATP production, lower MMP, and higher ROS levels. The cytotoxicity of the nanoparticle-protein corona complex may be associated with the protein corona degradation process. All of these results will enrich the database of cytotoxicity induced by nanomaterial-protein corona complexes.

Structurally related hydrazone-based metal complexes with different antitumor activities variably induce apoptotic cell death.

PubMed

Megger, Dominik A; Rosowski, Kristin; Radunsky, Christian; Kösters, Jutta; Sitek, Barbara; Müller, Jens

2017-04-05

Three new complexes bearing the tridentate hydrazone-based ligand 2-(2-(1-(pyridin-2-yl)ethylidene)hydrazinyl)pyridine (L) were synthesized and structurally characterized. Biological tests indicate that the Zn(ii) complex [ZnCl 2 (L)] is of low cytotoxicity against the hepatocellular carcinoma cell line HepG2. In contrast, the Cu(ii) and Mn(ii) complexes [CuCl 2 (L)] and [MnCl 2 (L)] are highly cytotoxic with EC 50 values of 1.25 ± 0.01 μM and 20 ± 1 μM, respectively. A quantitative proteome analysis reveals that treatment of the cells with the Cu(ii) complex leads to a significantly altered abundance of 102 apoptosis-related proteins, whereas 38 proteins were up- or down-regulated by the Mn(ii) complex. A closer inspection of those proteins regulated only by the Cu(ii) complex suggests that the superior cytotoxic activity of this complex is likely to be related to an initiation of the caspase-independent cell death (CICD). In addition, an increased generation of reactive oxygen species (ROS) and a strong up-regulation of proteins responsive to oxidative stress suggest that alterations of the cellular redox metabolism likely contribute to the cytotoxicity of the Cu(ii) complex.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

An updated version of NPIDB includes new classifications of DNA–protein complexes and their families

PubMed Central

Zanegina, Olga; Kirsanov, Dmitriy; Baulin, Eugene; Karyagina, Anna; Alexeevski, Andrei; Spirin, Sergey

2016-01-01

The recent upgrade of nucleic acid–protein interaction database (NPIDB, http://npidb.belozersky.msu.ru/) includes a newly elaborated classification of complexes of protein domains with double-stranded DNA and a classification of families of related complexes. Our classifications are based on contacting structural elements of both DNA: the major groove, the minor groove and the backbone; and protein: helices, beta-strands and unstructured segments. We took into account both hydrogen bonds and hydrophobic interaction. The analyzed material contains 1942 structures of protein domains from 748 PDB entries. We have identified 97 interaction modes of individual protein domain–DNA complexes and 17 DNA–protein interaction classes of protein domain families. We analyzed the sources of diversity of DNA–protein interaction modes in different complexes of one protein domain family. The observed interaction mode is sometimes influenced by artifacts of crystallization or diversity in secondary structure assignment. The interaction classes of domain families are more stable and thus possess more biological sense than a classification of single complexes. Integration of the classification into NPIDB allows the user to browse the database according to the interacting structural elements of DNA and protein molecules. For each family, we present average DNA shape parameters in contact zones with domains of the family. PMID:26656949

Surface-Induced Dissociation of Protein Complexes in a Hybrid Fourier Transform Ion Cyclotron Resonance Mass Spectrometer.

PubMed

Yan, Jing; Zhou, Mowei; Gilbert, Joshua D; Wolff, Jeremy J; Somogyi, Árpád; Pedder, Randall E; Quintyn, Royston S; Morrison, Lindsay J; Easterling, Michael L; Paša-Tolić, Ljiljana; Wysocki, Vicki H

2017-01-03

Mass spectrometry continues to develop as a valuable tool in the analysis of proteins and protein complexes. In protein complex mass spectrometry studies, surface-induced dissociation (SID) has been successfully applied in quadrupole time-of-flight (Q-TOF) instruments. SID provides structural information on noncovalent protein complexes that is complementary to other techniques. However, the mass resolution of Q-TOF instruments can limit the information that can be obtained for protein complexes by SID. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides ultrahigh resolution and ultrahigh mass accuracy measurements. In this study, an SID device was designed and successfully installed in a hybrid FT-ICR instrument in place of the standard gas collision cell. The SID-FT-ICR platform has been tested with several protein complex systems (homooligomers, a heterooligomer, and a protein-ligand complex, ranging from 53 to 85 kDa), and the results are consistent with data previously acquired on Q-TOF platforms, matching predictions from known protein interface information. SID fragments with the same m/z but different charge states are well-resolved based on distinct spacing between adjacent isotope peaks, and the addition of metal cations and ligands can also be isotopically resolved with the ultrahigh mass resolution available in FT-ICR.

Generation of GFP Native Protein for Detection of Its Intracellular Uptake by Cell-Penetrating Peptides.

PubMed

Kadkhodayan, S; Sadat, S M; Irani, S; Fotouhi, F; Bolhassani, A

2016-01-01

Different types of lipid- and polymer-based vectors have been developed to deliver proteins into cells, but these methods showed relatively poor efficiency. Recently, a group of short, highly basic peptides known as cell-penetrating peptides (CPPs) were used to carry polypeptides and proteins into cells. In this study, expression and purification of GFP protein was performed using the prokaryotic pET expression system. We used two amphipathic CPPs (Pep-1 and CADY-2) as a novel delivery system to transfer the GFP protein into cells. The morphological features of the CPP/GFP complexes were studied by scanning electron microscopy (SEM), Zetasizer, and SDS-PAGE. The efficiency of GFP transfection using Pep-1 and CADY-2 peptides and TurboFect reagent was compared with FITC-antibody protein control delivered by these transfection vehicles in the HEK-293T cell line. SEM data confirmed formation of discrete nanoparticles with a diameter of below 300 nm. Moreover, formation of the complexes was detected using SDS-PAGE as two individual bands, indicating non-covalent interaction. The size and homogeneity of Pep-1/GFP and CADY-2/GFP complexes were dependent on the ratio of peptide/cargo formulations, and responsible for their biological efficiency. The cells transfected by Pep-1/GFP and CADY-2/GFP complexes at a molar ratio of 20 : 1 demonstrated spreading green regions using fluorescent microscopy. Flow cytometry results showed that the transfection efficiency of Pep-based nanoparticles was similar to CADY-based nanoparticles and comparable with TurboFect-protein complexes. These data open an efficient way for future therapeutic purposes.

Singlet oxygen Triplet Energy Transfer based imaging technology for mapping protein-protein proximity in intact cells

PubMed Central

To, Tsz-Leung; Fadul, Michael J.; Shu, Xiaokun

2014-01-01

Many cellular processes are carried out by large protein complexes that can span several tens of nanometers. Whereas Forster resonance energy transfer has a detection range of <10 nm, here we report the theoretical development and experimental demonstration of a new fluorescence imaging technology with a detection range of up to several tens of nanometers: singlet oxygen triplet energy transfer. We demonstrate that our method confirms the topology of a large protein complex in intact cells, which spans from the endoplasmic reticulum to the outer mitochondrial membrane and the matrix. This new method is thus suited for mapping protein proximity in large protein complexes. PMID:24905026

3D Complex: A Structural Classification of Protein Complexes

PubMed Central

Levy, Emmanuel D; Pereira-Leal, Jose B; Chothia, Cyrus; Teichmann, Sarah A

2006-01-01

Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes. PMID:17112313

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

Binding of small molecules at interface of protein-protein complex - A newer approach to rational drug design.

PubMed

Gurung, A B; Bhattacharjee, A; Ajmal Ali, M; Al-Hemaid, F; Lee, Joongku

2017-02-01

Protein-protein interaction is a vital process which drives many important physiological processes in the cell and has also been implicated in several diseases. Though the protein-protein interaction network is quite complex but understanding its interacting partners using both in silico as well as molecular biology techniques can provide better insights for targeting such interactions. Targeting protein-protein interaction with small molecules is a challenging task because of druggability issues. Nevertheless, several studies on the kinetics as well as thermodynamic properties of protein-protein interactions have immensely contributed toward better understanding of the affinity of these complexes. But, more recent studies on hot spots and interface residues have opened up new avenues in the drug discovery process. This approach has been used in the design of hot spot based modulators targeting protein-protein interaction with the objective of normalizing such interactions.

A tool for calculating binding-site residues on proteins from PDB structures.

PubMed

Hu, Jing; Yan, Changhui

2009-08-03

In the research on protein functional sites, researchers often need to identify binding-site residues on a protein. A commonly used strategy is to find a complex structure from the Protein Data Bank (PDB) that consists of the protein of interest and its interacting partner(s) and calculate binding-site residues based on the complex structure. However, since a protein may participate in multiple interactions, the binding-site residues calculated based on one complex structure usually do not reveal all binding sites on a protein. Thus, this requires researchers to find all PDB complexes that contain the protein of interest and combine the binding-site information gleaned from them. This process is very time-consuming. Especially, combing binding-site information obtained from different PDB structures requires tedious work to align protein sequences. The process becomes overwhelmingly difficult when researchers have a large set of proteins to analyze, which is usually the case in practice. In this study, we have developed a tool for calculating binding-site residues on proteins, TCBRP http://yanbioinformatics.cs.usu.edu:8080/ppbindingsubmit. For an input protein, TCBRP can quickly find all binding-site residues on the protein by automatically combining the information obtained from all PDB structures that consist of the protein of interest. Additionally, TCBRP presents the binding-site residues in different categories according to the interaction type. TCBRP also allows researchers to set the definition of binding-site residues. The developed tool is very useful for the research on protein binding site analysis and prediction.

Text Mining for Protein Docking

PubMed Central

Badal, Varsha D.; Kundrotas, Petras J.; Vakser, Ilya A.

2015-01-01

The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking). Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu). The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features) approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound benchmark set, significantly increasing the docking success rate. PMID:26650466

DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

PubMed Central

Sagendorf, Jared M.

2017-01-01

Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

Modulation of electronic structures of bases through DNA recognition of protein.

PubMed

Hagiwara, Yohsuke; Kino, Hiori; Tateno, Masaru

2010-04-21

The effects of environmental structures on the electronic states of functional regions in a fully solvated DNA·protein complex were investigated using combined ab initio quantum mechanics/molecular mechanics calculations. A complex of a transcriptional factor, PU.1, and the target DNA was used for the calculations. The effects of solvent on the energies of molecular orbitals (MOs) of some DNA bases strongly correlate with the magnitude of masking of the DNA bases from the solvent by the protein. In the complex, PU.1 causes a variation in the magnitude among DNA bases by means of directly recognizing the DNA bases through hydrogen bonds and inducing structural changes of the DNA structure from the canonical one. Thus, the strong correlation found in this study is the first evidence showing the close quantitative relationship between recognition modes of DNA bases and the energy levels of the corresponding MOs. Thus, it has been revealed that the electronic state of each base is highly regulated and organized by the DNA recognition of the protein. Other biological macromolecular systems can be expected to also possess similar modulation mechanisms, suggesting that this finding provides a novel basis for the understanding for the regulation functions of biological macromolecular systems.

Exploiting three kinds of interface propensities to identify protein binding sites.

PubMed

Liu, Bin; Wang, Xiaolong; Lin, Lei; Dong, Qiwen; Wang, Xuan

2009-08-01

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. In this study, we present a building block of proteins called order profiles to use the evolutionary information of the protein sequence frequency profiles and apply this building block to produce a class of propensities called order profile interface propensities. For comparisons, we revisit the usage of residue interface propensities and binary profile interface propensities for protein binding site prediction. Each kind of propensities combined with sequence profiles and accessible surface areas are inputted into SVM. When tested on four types of complexes (hetero-permanent complexes, hetero-transient complexes, homo-permanent complexes and homo-transient complexes), experimental results show that the order profile interface propensities are better than residue interface propensities and binary profile interface propensities. Therefore, order profile is a suitable profile-level building block of the protein sequences and can be widely used in many tasks of computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the protein remote homology detection.

A Polypyrimidine Tract Binding Protein, Pumpkin RBP50, Forms the Basis of a Phloem-Mobile Ribonucleoprotein Complex[W

PubMed Central

Ham, Byung-Kook; Brandom, Jeri L.; Xoconostle-Cázares, Beatriz; Ringgold, Vanessa; Lough, Tony J.; Lucas, William J.

2009-01-01

RNA binding proteins (RBPs) are integral components of ribonucleoprotein (RNP) complexes and play a central role in RNA processing. In plants, some RBPs function in a non-cell-autonomous manner. The angiosperm phloem translocation stream contains a unique population of RBPs, but little is known regarding the nature of the proteins and mRNA species that constitute phloem-mobile RNP complexes. Here, we identified and characterized a 50-kD pumpkin (Cucurbita maxima cv Big Max) phloem RNA binding protein (RBP50) that is evolutionarily related to animal polypyrimidine tract binding proteins. In situ hybridization studies indicated a high level of RBP50 transcripts in companion cells, while immunolocalization experiments detected RBP50 in both companion cells and sieve elements. A comparison of the levels of RBP50 present in vascular bundles and phloem sap indicated that this protein is highly enriched in the phloem sap. Heterografting experiments confirmed that RBP50 is translocated from source to sink tissues. Collectively, these findings established that RBP50 functions as a non-cell-autonomous RBP. Protein overlay, coimmunoprecipitation, and cross-linking experiments identified the phloem proteins and mRNA species that constitute RBP50-based RNP complexes. Gel mobility-shift assays demonstrated that specificity, with respect to the bound mRNA, is established by the polypyrimidine tract binding motifs within such transcripts. We present a model for RBP50-based RNP complexes within the pumpkin phloem translocation stream. PMID:19122103

Theoretical modeling of multiprotein complexes by iSPOT: Integration of small-angle X-ray scattering, hydroxyl radical footprinting, and computational docking.

PubMed

Huang, Wei; Ravikumar, Krishnakumar M; Parisien, Marc; Yang, Sichun

2016-12-01

Structural determination of protein-protein complexes such as multidomain nuclear receptors has been challenging for high-resolution structural techniques. Here, we present a combined use of multiple biophysical methods, termed iSPOT, an integration of shape information from small-angle X-ray scattering (SAXS), protection factors probed by hydroxyl radical footprinting, and a large series of computationally docked conformations from rigid-body or molecular dynamics (MD) simulations. Specifically tested on two model systems, the power of iSPOT is demonstrated to accurately predict the structures of a large protein-protein complex (TGFβ-FKBP12) and a multidomain nuclear receptor homodimer (HNF-4α), based on the structures of individual components of the complexes. Although neither SAXS nor footprinting alone can yield an unambiguous picture for each complex, the combination of both, seamlessly integrated in iSPOT, narrows down the best-fit structures that are about 3.2Å and 4.2Å in RMSD from their corresponding crystal structures, respectively. Furthermore, this proof-of-principle study based on the data synthetically derived from available crystal structures shows that the iSPOT-using either rigid-body or MD-based flexible docking-is capable of overcoming the shortcomings of standalone computational methods, especially for HNF-4α. By taking advantage of the integration of SAXS-based shape information and footprinting-based protection/accessibility as well as computational docking, this iSPOT platform is set to be a powerful approach towards accurate integrated modeling of many challenging multiprotein complexes. Copyright © 2016 Elsevier Inc. All rights reserved.

iATTRACT: simultaneous global and local interface optimization for protein-protein docking refinement.

PubMed

Schindler, Christina E M; de Vries, Sjoerd J; Zacharias, Martin

2015-02-01

Protein-protein interactions are abundant in the cell but to date structural data for a large number of complexes is lacking. Computational docking methods can complement experiments by providing structural models of complexes based on structures of the individual partners. A major caveat for docking success is accounting for protein flexibility. Especially, interface residues undergo significant conformational changes upon binding. This limits the performance of docking methods that keep partner structures rigid or allow limited flexibility. A new docking refinement approach, iATTRACT, has been developed which combines simultaneous full interface flexibility and rigid body optimizations during docking energy minimization. It employs an atomistic molecular mechanics force field for intermolecular interface interactions and a structure-based force field for intramolecular contributions. The approach was systematically evaluated on a large protein-protein docking benchmark, starting from an enriched decoy set of rigidly docked protein-protein complexes deviating by up to 15 Å from the native structure at the interface. Large improvements in sampling and slight but significant improvements in scoring/discrimination of near native docking solutions were observed. Complexes with initial deviations at the interface of up to 5.5 Å were refined to significantly better agreement with the native structure. Improvements in the fraction of native contacts were especially favorable, yielding increases of up to 70%. © 2014 Wiley Periodicals, Inc.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. | Office of Cancer Genomics

Cancer.gov

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity.

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

PubMed

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

2015-03-01

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

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

PubMed

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong; Huang, Sheng-You

2017-07-03

Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein-protein and protein-DNA benchmarks and performed better than template-based modeling on the three protein-RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Intracellular and transdermal protein delivery mediated by non-covalent interactions with a synthetic guanidine-rich molecular carrier.

PubMed

Im, Jungkyun; Das, Sanket; Jeong, Dongjun; Kim, Chang-Jin; Lim, Hyun-Suk; Kim, Ki Hean; Chung, Sung-Kee

2017-08-07

The impermeability of the cell plasma membrane is one of the major barriers for protein transduction into mammalian cells, and it also limits the use of proteins as therapeutic agents. Protein transduction has usually been achieved based on certain invasive processes or cell penetrating peptides (CPP). Herein we report our study in which a synthetic guanidine-rich molecular carrier is used as a delivery vector for intracellular and transdermal delivery of proteins. First a sorbitol-based molecular carrier having 8 guanidine units (Sor-G8) was synthesized, and then was simply mixed with a cargo protein of varying sizes to form the non-covalent complex of carrier-cargo proteins. These ionic complexes were shown to have efficient cellular uptake properties. The optimum conditions including the molar ratio between cargo protein and carrier, and the treatment time have been defined. Several protein cargoes were successfully examined with differing sizes and molecular weights: green fluorescent protein (MW 27kDa), albumin (66kDa), concanavalin A (102kDa), and immunoglobulin G (150kDa). These non-covalent complexes were also found to have excellent transdermal penetration ability into the mouse skin. The skin penetration depth was studied histologically by light microscopy as well as two-photon microscopy thus generating a depth profile. These complexes were largely found in the epidermis and dermis layers, i.e. down to ca. 100μm depth of the mouse skin. Our synthetic Sor-G8 carrier was found to be substantially more efficient that Arg8 in both the intracellular transduction and the transdermal delivery of proteins. The mechanism of the cellular uptake of the complex was briefly studied, and the results suggested macropinocytosis. Copyright © 2017 Elsevier B.V. All rights reserved.

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories

PubMed Central

2014-01-01

Background Molecular Dynamics (MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. Results On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. Conclusions MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes. PMID:25077693

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories.

PubMed

Abdel-Azeim, Safwat; Chermak, Edrisse; Vangone, Anna; Oliva, Romina; Cavallo, Luigi

2014-01-01

Molecular Dynamics (MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes.

A Critical Assessment of the Performance of Protein-ligand Scoring Functions Based on NMR Chemical Shift Perturbations

PubMed Central

Wang, Bing; Westerhoff, Lance M.; Merz, Kenneth M.

2008-01-01

We have generated docking poses for the FKBP-GPI complex using eight docking programs, and compared their scoring functions with scoring based on NMR chemical shift perturbations (NMRScore). Because the chemical shift perturbation (CSP) is exquisitely sensitive on the orientation of ligand inside the binding pocket, NMRScore offers an accurate and straightforward approach to score different poses. All scoring functions were inspected by their abilities to highly rank the native-like structures and separate them from decoy poses generated for a protein-ligand complex. The overall performance of NMRScore is much better than that of energy-based scoring functions associated with docking programs in both aspects. In summary, we find that the combination of docking programs with NMRScore results in an approach that can robustly determine the binding site structure for a protein-ligand complex, thereby, providing a new tool facilitating the structure-based drug discovery process. PMID:17867664

Modeling Structure and Dynamics of Protein Complexes with SAXS Profiles

PubMed Central

Schneidman-Duhovny, Dina; Hammel, Michal

2018-01-01

Small-angle X-ray scattering (SAXS) is an increasingly common and useful technique for structural characterization of molecules in solution. A SAXS experiment determines the scattering intensity of a molecule as a function of spatial frequency, termed SAXS profile. SAXS profiles can be utilized in a variety of molecular modeling applications, such as comparing solution and crystal structures, structural characterization of flexible proteins, assembly of multi-protein complexes, and modeling of missing regions in the high-resolution structure. Here, we describe protocols for modeling atomic structures based on SAXS profiles. The first protocol is for comparing solution and crystal structures including modeling of missing regions and determination of the oligomeric state. The second protocol performs multi-state modeling by finding a set of conformations and their weights that fit the SAXS profile starting from a single-input structure. The third protocol is for protein-protein docking based on the SAXS profile of the complex. We describe the underlying software, followed by demonstrating their application on interleukin 33 (IL33) with its primary receptor ST2 and DNA ligase IV-XRCC4 complex. PMID:29605933

Quantitative Proteomics Reveals Dynamic Interactions of the Minichromosome Maintenance Complex (MCM) in the Cellular Response to Etoposide Induced DNA Damage.

PubMed

Drissi, Romain; Dubois, Marie-Line; Douziech, Mélanie; Boisvert, François-Michel

2015-07-01

The minichromosome maintenance complex (MCM) proteins are required for processive DNA replication and are a target of S-phase checkpoints. The eukaryotic MCM complex consists of six proteins (MCM2-7) that form a heterohexameric ring with DNA helicase activity, which is loaded on chromatin to form the pre-replication complex. Upon entry in S phase, the helicase is activated and opens the DNA duplex to recruit DNA polymerases at the replication fork. The MCM complex thus plays a crucial role during DNA replication, but recent work suggests that MCM proteins could also be involved in DNA repair. Here, we employed a combination of stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics with immunoprecipitation of green fluorescent protein-tagged fusion proteins to identify proteins interacting with the MCM complex, and quantify changes in interactions in response to DNA damage. Interestingly, the MCM complex showed very dynamic changes in interaction with proteins such as Importin7, the histone chaperone ASF1, and the Chromodomain helicase DNA binding protein 3 (CHD3) following DNA damage. These changes in interactions were accompanied by an increase in phosphorylation and ubiquitination on specific sites on the MCM proteins and an increase in the co-localization of the MCM complex with γ-H2AX, confirming the recruitment of these proteins to sites of DNA damage. In summary, our data indicate that the MCM proteins is involved in chromatin remodeling in response to DNA damage. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes

PubMed Central

2012-01-01

Background Precise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification. Results On the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc. Conclusions Our results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information. PMID:22800292

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes.

PubMed

Malhotra, Sony; Sowdhamini, Ramanathan

2012-07-16

Precise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification. On the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc. Our results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information.

Surface-Induced Dissociation of Protein Complexes in a Hybrid Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

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

Yan, Jing; Zhou, Mowei; Gilbert, Joshua D.

Mass spectrometry continues to develop as a valuable tool in the analysis of proteins and protein complexes. In protein complex mass spectrometry studies, surface-induced dissociation (SID) has been successfully applied in quadrupole time-of-flight (Q-TOF) instruments. SID provides structural information on noncovalent protein complexes that is complementary to other techniques. However, the mass resolution of Q-TOF instruments can limit the information that can be obtained for protein complexes by SID. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides ultrahigh resolution and ultrahigh mass accuracy measurements. Here in this study, an SID device was designed and successfully installed in amore » hybrid FT-ICR instrument in place of the standard gas collision cell. The SID-FT-ICR platform has been tested with several protein complex systems (homooligomers, a heterooligomer, and a protein-ligand complex, ranging from 53 to 85 kDa), and the results are consistent with data previously acquired on Q-TOF platforms, matching predictions from known protein interface information. Lastly, SID fragments with the same m/z but different charge states are well-resolved based on distinct spacing between adjacent isotope peaks, and the addition of metal cations and ligands can also be isotopically resolved with the ultrahigh mass resolution available in FT-ICR.« less

Surface-Induced Dissociation of Protein Complexes in a Hybrid Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

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

Yan, Jing; Zhou, Mowei; Gilbert, Joshua D.

Mass spectrometry continues to develop as a valuable tool in the analysis of proteins and protein complexes. In protein complex mass spectrometry studies, surface-induced dissociation (SID) has been successfully applied in quadrupole time-of-flight (Q-TOF) instruments. SID provides structural information on non-covalent protein complexes that is complementary to other techniques. However, the mass resolution of Q-TOF instruments can limit the information that can be obtained for protein complexes by SID. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides ultrahigh resolution and ultrahigh mass accuracy measurements. In this study, an SID device was designed and successfully installed in a hybridmore » FT-ICR instrument in place of the standard gas collision cell. The SID-FT-ICR platform has been tested with several protein complex systems (homooligomers, a heterooligomer, and a protein-ligand complex, ranging from 53 kDa to 85 kDa), and the results are consistent with data previously acquired on Q-TOF platforms, matching predictions from known protein interface information. SID fragments with the same m/z but different charge states are well-resolved based on distinct spacing between adjacent isotope peaks, and the addition of metal cations and ligands can also be isotopically resolved with the ultrahigh mass resolution available in FT-ICR.« less

Surface-Induced Dissociation of Protein Complexes in a Hybrid Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

DOE PAGES

Yan, Jing; Zhou, Mowei; Gilbert, Joshua D.; ...

2016-12-02

Mass spectrometry continues to develop as a valuable tool in the analysis of proteins and protein complexes. In protein complex mass spectrometry studies, surface-induced dissociation (SID) has been successfully applied in quadrupole time-of-flight (Q-TOF) instruments. SID provides structural information on noncovalent protein complexes that is complementary to other techniques. However, the mass resolution of Q-TOF instruments can limit the information that can be obtained for protein complexes by SID. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides ultrahigh resolution and ultrahigh mass accuracy measurements. Here in this study, an SID device was designed and successfully installed in amore » hybrid FT-ICR instrument in place of the standard gas collision cell. The SID-FT-ICR platform has been tested with several protein complex systems (homooligomers, a heterooligomer, and a protein-ligand complex, ranging from 53 to 85 kDa), and the results are consistent with data previously acquired on Q-TOF platforms, matching predictions from known protein interface information. Lastly, SID fragments with the same m/z but different charge states are well-resolved based on distinct spacing between adjacent isotope peaks, and the addition of metal cations and ligands can also be isotopically resolved with the ultrahigh mass resolution available in FT-ICR.« less

A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

PubMed

Mehranfar, Adele; Ghadiri, Nasser; Kouhsar, Morteza; Golshani, Ashkan

2017-09-01

Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions. A data fusion component is used for this step, based on the interval type-2 fuzzy voter that provides an efficient combination of the information sources. This fusion component detects the errors and diminishes their effect on the detection protein complexes. So in the first step, the reliability scores have been assigned for every interaction in the network. In the second step, we have proposed a general protein complex detection algorithm by exploiting and adopting the strong points of other algorithms and existing hypotheses regarding real complexes. Finally, the proposed method has been applied for the yeast interaction datasets for predicting the interactions. The results show that our framework has a better performance regarding precision and F-measure than the existing approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

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

Advantages of Molecular Weight Identification during Native MS Screening.

PubMed

Khan, Ahad; Bresnick, Anne; Cahill, Sean; Girvin, Mark; Almo, Steve; Quinn, Ronald

2018-05-09

Native mass spectrometry detection of ligand-protein complexes allowed rapid detection of natural product binders of apo and calcium-bound S100A4 (a member of the metal binding protein S100 family), T cell/transmembrane, immunoglobulin (Ig), and mucin protein 3, and T cell immunoreceptor with Ig and ITIM (immunoreceptor tyrosine-based inhibitory motif) domains precursor protein from extracts and fractions. Based on molecular weight common hits were detected binding to all four proteins. Seven common hits were identified as apigenin 6- C - β - D -glucoside 8- C - α - L -arabinoside, sweroside, 4',5-dihydroxy-7-methoxyflavanone-6- C -rutinoside, loganin acid, 6- C -glucosylnaringenin, biochanin A 7- O -rutinoside and quercetin 3- O -rutinoside. Mass guided isolation and NMR identification of hits confirmed the mass accuracy of the ligand in the ligand-protein MS complexes. Thus, molecular weight ID from ligand-protein complexes by electrospray ionization Fourier transform mass spectrometry allowed rapid dereplication. Native mass spectrometry using electrospray ionization Fourier transform mass spectrometry is a tool for dereplication and metabolomics analysis. Georg Thieme Verlag KG Stuttgart · New York.

Rhodium complexes as therapeutic agents.

PubMed

Ma, Dik-Lung; Wang, Modi; Mao, Zhifeng; Yang, Chao; Ng, Chan-Tat; Leung, Chung-Hang

2016-02-21

The landscape of inorganic medicinal chemistry has been dominated by the investigation of platinum, and to a lesser extent ruthenium, complexes over the past few decades. Recently, complexes based on other metal centers such as rhodium have attracted attention due to their tunable chemical and biological properties as well as distinct mechanisms of action. This perspective highlights recent examples of rhodium complexes that show diverse biological activities against various targets, including enzymes and protein-protein interactions.

Joining Forces: Integrating Proteomics and Cross-linking with the Mass Spectrometry of Intact Complexes*

PubMed Central

Stengel, Florian; Aebersold, Ruedi; Robinson, Carol V.

2012-01-01

Protein assemblies are critical for cellular function and understanding their physical organization is the key aim of structural biology. However, applying conventional structural biology approaches is challenging for transient, dynamic, or polydisperse assemblies. There is therefore a growing demand for hybrid technologies that are able to complement classical structural biology methods and thereby broaden our arsenal for the study of these important complexes. Exciting new developments in the field of mass spectrometry and proteomics have added a new dimension to the study of protein-protein interactions and protein complex architecture. In this review, we focus on how complementary mass spectrometry-based techniques can greatly facilitate structural understanding of protein assemblies. PMID:22180098

Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes.

PubMed

Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon

2015-09-14

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Binding Direction-Based Two-Dimensional Flattened Contact Area Computing Algorithm for Protein-Protein Interactions.

PubMed

Kang, Beom Sik; Pugalendhi, GaneshKumar; Kim, Ku-Jin

2017-10-13

Interactions between protein molecules are essential for the assembly, function, and regulation of proteins. The contact region between two protein molecules in a protein complex is usually complementary in shape for both molecules and the area of the contact region can be used to estimate the binding strength between two molecules. Although the area is a value calculated from the three-dimensional surface, it cannot represent the three-dimensional shape of the surface. Therefore, we propose an original concept of two-dimensional contact area which provides further information such as the ruggedness of the contact region. We present a novel algorithm for calculating the binding direction between two molecules in a protein complex, and then suggest a method to compute the two-dimensional flattened area of the contact region between two molecules based on the binding direction.

Structure solution of DNA-binding proteins and complexes with ARCIMBOLDO libraries

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

Pröpper, Kevin; Instituto de Biologia Molecular de Barcelona; Meindl, Kathrin

2014-06-01

The structure solution of DNA-binding protein structures and complexes based on the combination of location of DNA-binding protein motif fragments with density modification in a multi-solution frame is described. Protein–DNA interactions play a major role in all aspects of genetic activity within an organism, such as transcription, packaging, rearrangement, replication and repair. The molecular detail of protein–DNA interactions can be best visualized through crystallography, and structures emphasizing insight into the principles of binding and base-sequence recognition are essential to understanding the subtleties of the underlying mechanisms. An increasing number of high-quality DNA-binding protein structure determinations have been witnessed despite themore » fact that the crystallographic particularities of nucleic acids tend to pose specific challenges to methods primarily developed for proteins. Crystallographic structure solution of protein–DNA complexes therefore remains a challenging area that is in need of optimized experimental and computational methods. The potential of the structure-solution program ARCIMBOLDO for the solution of protein–DNA complexes has therefore been assessed. The method is based on the combination of locating small, very accurate fragments using the program Phaser and density modification with the program SHELXE. Whereas for typical proteins main-chain α-helices provide the ideal, almost ubiquitous, small fragments to start searches, in the case of DNA complexes the binding motifs and DNA double helix constitute suitable search fragments. The aim of this work is to provide an effective library of search fragments as well as to determine the optimal ARCIMBOLDO strategy for the solution of this class of structures.« less

Synchrotron Radiation Circular Dichroism (SRCD) Spectroscopy - An Enhanced Method for Examining Protein Conformations and Protein Interactions

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

B Wallace; R Janes

CD (circular dichroism) spectroscopy is a well-established technique in structural biology. SRCD (synchrotron radiation circular dichroism) spectroscopy extends the utility and applications of conventional CD spectroscopy (using laboratory-based instruments) because the high flux of a synchrotron enables collection of data at lower wavelengths (resulting in higher information content), detection of spectra with higher signal-to-noise levels and measurements in the presence of absorbing components (buffers, salts, lipids and detergents). SRCD spectroscopy can provide important static and dynamic structural information on proteins in solution, including secondary structures of intact proteins and their domains, protein stability, the differences between wild-type and mutant proteins,more » the identification of natively disordered regions in proteins, and the dynamic processes of protein folding and membrane insertion and the kinetics of enzyme reactions. It has also been used to effectively study protein interactions, including protein-protein complex formation involving either induced-fit or rigid-body mechanisms, and protein-lipid complexes. A new web-based bioinformatics resource, the Protein Circular Dichroism Data Bank (PCDDB), has been created which enables archiving, access and analyses of CD and SRCD spectra and supporting metadata, now making this information publicly available. To summarize, the developing method of SRCD spectroscopy has the potential for playing an important role in new types of studies of protein conformations and their complexes.« less

Complex lasso: new entangled motifs in proteins

NASA Astrophysics Data System (ADS)

Niemyska, Wanda; Dabrowski-Tumanski, Pawel; Kadlof, Michal; Haglund, Ellinor; Sułkowski, Piotr; Sulkowska, Joanna I.

2016-11-01

We identify new entangled motifs in proteins that we call complex lassos. Lassos arise in proteins with disulfide bridges (or in proteins with amide linkages), when termini of a protein backbone pierce through an auxiliary surface of minimal area, spanned on a covalent loop. We find that as much as 18% of all proteins with disulfide bridges in a non-redundant subset of PDB form complex lassos, and classify them into six distinct geometric classes, one of which resembles supercoiling known from DNA. Based on biological classification of proteins we find that lassos are much more common in viruses, plants and fungi than in other kingdoms of life. We also discuss how changes in the oxidation/reduction potential may affect the function of proteins with lassos. Lassos and associated surfaces of minimal area provide new, interesting and possessing many potential applications geometric characteristics not only of proteins, but also of other biomolecules.

A continuous-exchange cell-free protein synthesis system based on extracts from cultured insect cells.

PubMed

Stech, Marlitt; Quast, Robert B; Sachse, Rita; Schulze, Corina; Wüstenhagen, Doreen A; Kubick, Stefan

2014-01-01

In this study, we present a novel technique for the synthesis of complex prokaryotic and eukaryotic proteins by using a continuous-exchange cell-free (CECF) protein synthesis system based on extracts from cultured insect cells. Our approach consists of two basic elements: First, protein synthesis is performed in insect cell lysates which harbor endogenous microsomal vesicles, enabling a translocation of de novo synthesized target proteins into the lumen of the insect vesicles or, in the case of membrane proteins, their embedding into a natural membrane scaffold. Second, cell-free reactions are performed in a two chamber dialysis device for 48 h. The combination of the eukaryotic cell-free translation system based on insect cell extracts and the CECF translation system results in significantly prolonged reaction life times and increased protein yields compared to conventional batch reactions. In this context, we demonstrate the synthesis of various representative model proteins, among them cytosolic proteins, pharmacological relevant membrane proteins and glycosylated proteins in an endotoxin-free environment. Furthermore, the cell-free system used in this study is well-suited for the synthesis of biologically active tissue-type-plasminogen activator, a complex eukaryotic protein harboring multiple disulfide bonds.

A Continuous-Exchange Cell-Free Protein Synthesis System Based on Extracts from Cultured Insect Cells

PubMed Central

Stech, Marlitt; Quast, Robert B.; Sachse, Rita; Schulze, Corina; Wüstenhagen, Doreen A.; Kubick, Stefan

2014-01-01

In this study, we present a novel technique for the synthesis of complex prokaryotic and eukaryotic proteins by using a continuous-exchange cell-free (CECF) protein synthesis system based on extracts from cultured insect cells. Our approach consists of two basic elements: First, protein synthesis is performed in insect cell lysates which harbor endogenous microsomal vesicles, enabling a translocation of de novo synthesized target proteins into the lumen of the insect vesicles or, in the case of membrane proteins, their embedding into a natural membrane scaffold. Second, cell-free reactions are performed in a two chamber dialysis device for 48 h. The combination of the eukaryotic cell-free translation system based on insect cell extracts and the CECF translation system results in significantly prolonged reaction life times and increased protein yields compared to conventional batch reactions. In this context, we demonstrate the synthesis of various representative model proteins, among them cytosolic proteins, pharmacological relevant membrane proteins and glycosylated proteins in an endotoxin-free environment. Furthermore, the cell-free system used in this study is well-suited for the synthesis of biologically active tissue-type-plasminogen activator, a complex eukaryotic protein harboring multiple disulfide bonds. PMID:24804975

Design of metal cofactors activated by a protein–protein electron transfer system

PubMed Central

Ueno, Takafumi; Yokoi, Norihiko; Unno, Masaki; Matsui, Toshitaka; Tokita, Yuichi; Yamada, Masako; Ikeda-Saito, Masao; Nakajima, Hiroshi; Watanabe, Yoshihito

2006-01-01

Protein-to-protein electron transfer (ET) is a critical process in biological chemistry for which fundamental understanding is expected to provide a wealth of applications in biotechnology. Investigations of protein–protein ET systems in reductive activation of artificial cofactors introduced into proteins remains particularly challenging because of the complexity of interactions between the cofactor and the system contributing to ET. In this work, we construct an artificial protein–protein ET system, using heme oxygenase (HO), which is known to catalyze the conversion of heme to biliverdin. HO uses electrons provided from NADPH/cytochrome P450 reductase (CPR) through protein–protein complex formation during the enzymatic reaction. We report that a FeIII(Schiff-base), in the place of the active-site heme prosthetic group of HO, can be reduced by NADPH/CPR. The crystal structure of the Fe(10-CH2CH2COOH-Schiff-base)·HO composite indicates the presence of a hydrogen bond between the propionic acid carboxyl group and Arg-177 of HO. Furthermore, the ET rate from NADPH/CPR to the composite is 3.5-fold faster than that of Fe(Schiff-base)·HO, although the redox potential of Fe(10-CH2CH2COOH-Schiff-base)·HO (−79 mV vs. NHE) is lower than that of Fe(Schiff-base)·HO (+15 mV vs. NHE), where NHE is normal hydrogen electrode. This work describes a synthetic metal complex activated by means of a protein–protein ET system, which has not previously been reported. Moreover, the result suggests the importance of the hydrogen bond for the ET reaction of HO. Our Fe(Schiff-base)·HO composite model system may provide insights with regard to design of ET biosystems for sensors, catalysts, and electronics devices. PMID:16769893

Protein and gene model inference based on statistical modeling in k-partite graphs.

PubMed

Gerster, Sarah; Qeli, Ermir; Ahrens, Christian H; Bühlmann, Peter

2010-07-06

One of the major goals of proteomics is the comprehensive and accurate description of a proteome. Shotgun proteomics, the method of choice for the analysis of complex protein mixtures, requires that experimentally observed peptides are mapped back to the proteins they were derived from. This process is also known as protein inference. We present Markovian Inference of Proteins and Gene Models (MIPGEM), a statistical model based on clearly stated assumptions to address the problem of protein and gene model inference for shotgun proteomics data. In particular, we are dealing with dependencies among peptides and proteins using a Markovian assumption on k-partite graphs. We are also addressing the problems of shared peptides and ambiguous proteins by scoring the encoding gene models. Empirical results on two control datasets with synthetic mixtures of proteins and on complex protein samples of Saccharomyces cerevisiae, Drosophila melanogaster, and Arabidopsis thaliana suggest that the results with MIPGEM are competitive with existing tools for protein inference.

Efficient delivery of genome-editing proteins using bioreducible lipid nanoparticles.

PubMed

Wang, Ming; Zuris, John A; Meng, Fantao; Rees, Holly; Sun, Shuo; Deng, Pu; Han, Yong; Gao, Xue; Pouli, Dimitra; Wu, Qi; Georgakoudi, Irene; Liu, David R; Xu, Qiaobing

2016-03-15

A central challenge to the development of protein-based therapeutics is the inefficiency of delivery of protein cargo across the mammalian cell membrane, including escape from endosomes. Here we report that combining bioreducible lipid nanoparticles with negatively supercharged Cre recombinase or anionic Cas9:single-guide (sg)RNA complexes drives the electrostatic assembly of nanoparticles that mediate potent protein delivery and genome editing. These bioreducible lipids efficiently deliver protein cargo into cells, facilitate the escape of protein from endosomes in response to the reductive intracellular environment, and direct protein to its intracellular target sites. The delivery of supercharged Cre protein and Cas9:sgRNA complexed with bioreducible lipids into cultured human cells enables gene recombination and genome editing with efficiencies greater than 70%. In addition, we demonstrate that these lipids are effective for functional protein delivery into mouse brain for gene recombination in vivo. Therefore, the integration of this bioreducible lipid platform with protein engineering has the potential to advance the therapeutic relevance of protein-based genome editing.

CryoEM and image sorting for flexible protein/DNA complexes.

PubMed

Villarreal, Seth A; Stewart, Phoebe L

2014-07-01

Intrinsically disordered regions of proteins and conformational flexibility within complexes can be critical for biological function. However, disorder, flexibility, and heterogeneity often hinder structural analyses. CryoEM and single particle image processing techniques offer the possibility of imaging samples with significant flexibility. Division of particle images into more homogenous subsets after data acquisition can help compensate for heterogeneity within the sample. We present the utility of an eigenimage sorting analysis for examining two protein/DNA complexes with significant conformational flexibility and heterogeneity. These complexes are integral to the non-homologous end joining pathway, and are involved in the repair of double strand breaks of DNA. Both complexes include the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) and biotinylated DNA with bound streptavidin, with one complex containing the Ku heterodimer. Initial 3D reconstructions of the two DNA-PKcs complexes resembled a cryoEM structure of uncomplexed DNA-PKcs without additional density clearly attributable to the remaining components. Application of eigenimage sorting allowed division of the DNA-PKcs complex datasets into more homogeneous subsets. This led to visualization of density near the base of the DNA-PKcs that can be attributed to DNA, streptavidin, and Ku. However, comparison of projections of the subset structures with 2D class averages indicated that a significant level of heterogeneity remained within each subset. In summary, image sorting methods allowed visualization of extra density near the base of DNA-PKcs, suggesting that DNA binds in the vicinity of the base of the molecule and potentially to a flexible region of DNA-PKcs. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2011-01-01

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

Conservation of coevolving protein interfaces bridges prokaryote-eukaryote homologies in the twilight zone.

PubMed

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-12-27

Protein-protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein-protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein-protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein-protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach.

The New Kid on the Block: A Specialized Secretion System during Bacterial Sporulation.

PubMed

Morlot, Cécile; Rodrigues, Christopher D A

2018-02-02

The transport of proteins across the bacterial cell envelope is mediated by protein complexes called specialized secretion systems. These nanomachines exist in both Gram-positive and Gram-negative bacteria and have been categorized into different types based on their structural components and function. Interestingly, multiple studies suggest the existence of a protein complex in endospore-forming bacteria that appears to be a new type of specialized secretion system. This protein complex is called the SpoIIIA-SpoIIQ complex and is an exception to the categorical norm since it appears to be a hybrid composed of different parts from well-defined specialized secretion systems. Here we summarize and discuss the current understanding of this complex and its potential role as a specialized secretion system. Copyright © 2018 Elsevier Ltd. All rights reserved.

DNA Origami Scaffolds as Templates for Functional Tetrameric Kir3 K+ Channels.

PubMed

Kurokawa, Tatsuki; Kiyonaka, Shigeki; Nakata, Eiji; Endo, Masayuki; Koyama, Shohei; Mori, Emiko; Tran, Nam Ha; Dinh, Huyen; Suzuki, Yuki; Hidaka, Kumi; Kawata, Masaaki; Sato, Chikara; Sugiyama, Hiroshi; Morii, Takashi; Mori, Yasuo

2018-03-01

In native systems, scaffolding proteins play important roles in assembling proteins into complexes to transduce signals. This concept is yet to be applied to the assembly of functional transmembrane protein complexes in artificial systems. To address this issue, DNA origami has the potential to serve as scaffolds that arrange proteins at specific positions in complexes. Herein, we report that Kir3 K + channel proteins are assembled through zinc-finger protein (ZFP)-adaptors at specific locations on DNA origami scaffolds. Specific binding of the ZFP-fused Kir3 channels and ZFP-based adaptors on DNA origami were confirmed by atomic force microscopy and gel electrophoresis. Furthermore, the DNA origami with ZFP binding sites nearly tripled the K + channel current activity elicited by heterotetrameric Kir3 channels in HEK293T cells. Thus, our method provides a useful template to control the oligomerization states of membrane protein complexes in vitro and in living cells. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma.

PubMed

Haga, Ayako; Ogawara, Yoko; Kubota, Daisuke; Kitabayashi, Issay; Murakami, Yasufumi; Kondo, Tadashi

2013-06-01

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A review of the preparation and application of flavour and essential oils microcapsules based on complex coacervation technology.

PubMed

Xiao, Zuobing; Liu, Wanlong; Zhu, Guangyong; Zhou, Rujun; Niu, Yunwei

2014-06-01

This paper briefly introduces the preparation and application of flavour and essential oils microcapsules based on complex coacervation technology. The conventional encapsulating agents of oppositely charged proteins and polysaccharides that are used for microencapsulation of flavours and essential oils are reviewed along with the recent advances in complex coacervation methods. Proteins extracted from animal-derived products (gelatin, whey proteins, silk fibroin) and from vegetables (soy proteins, pea proteins), and polysaccharides such as gum Arabic, pectin, chitosan, agar, alginate, carrageenan and sodium carboxymethyl cellulose are described in depth. In recent decades, flavour and essential oils microcapsules have found numerous potential practical applications in food, textiles, agriculturals and pharmaceuticals. In this paper, the different coating materials and their application are discussed in detail. Consequently, the information obtained allows criteria to be established for selecting a method for the preparation of microcapsules according to their advantages, limitations and behaviours as carriers of flavours and essential oils. © 2013 Society of Chemical Industry.

Determining absolute protein numbers by quantitative fluorescence microscopy.

PubMed

Verdaasdonk, Jolien Suzanne; Lawrimore, Josh; Bloom, Kerry

2014-01-01

Biological questions are increasingly being addressed using a wide range of quantitative analytical tools to examine protein complex composition. Knowledge of the absolute number of proteins present provides insights into organization, function, and maintenance and is used in mathematical modeling of complex cellular dynamics. In this chapter, we outline and describe three microscopy-based methods for determining absolute protein numbers--fluorescence correlation spectroscopy, stepwise photobleaching, and ratiometric comparison of fluorescence intensity to known standards. In addition, we discuss the various fluorescently labeled proteins that have been used as standards for both stepwise photobleaching and ratiometric comparison analysis. A detailed procedure for determining absolute protein number by ratiometric comparison is outlined in the second half of this chapter. Counting proteins by quantitative microscopy is a relatively simple yet very powerful analytical tool that will increase our understanding of protein complex composition. © 2014 Elsevier Inc. All rights reserved.

Identification of a multi-protein reductive dehalogenase complex in Dehalococcoides mccartyi strain CBDB1 suggests a protein-dependent respiratory electron transport chain obviating quinone involvement.

PubMed

Kublik, Anja; Deobald, Darja; Hartwig, Stefanie; Schiffmann, Christian L; Andrades, Adarelys; von Bergen, Martin; Sawers, R Gary; Adrian, Lorenz

2016-09-01

Dehalococcoides mccartyi strain CBDB1 is an obligate organohalide-respiring bacterium using only hydrogen as electron donor and halogenated organics as electron acceptor. Here, we studied proteins involved in the respiratory chain under non-denaturing conditions. Using blue native gel electrophoresis (BN-PAGE), gel filtration and ultrafiltration an active dehalogenating protein complex with a molecular mass of 250-270 kDa was identified. The active subunit of reductive dehalogenase (RdhA) colocalised with a complex iron-sulfur molybdoenzyme (CISM) subunit (CbdbA195) and an iron-sulfur cluster containing subunit (CbdbA131) of the hydrogen uptake hydrogenase (Hup). No colocalisation between the catalytically active subunits of hydrogenase and reductive dehalogenase was found. By two-dimensional BN/SDS-PAGE the stability of the complex towards detergents was assessed, demonstrating stepwise disintegration with increasing detergent concentrations. Chemical cross-linking confirmed the presence of a higher molecular mass reductive dehalogenase protein complex composed of RdhA, CISM I and Hup hydrogenase and proved to be a potential tool for stabilising protein-protein interactions of the dehalogenating complex prior to membrane solubilisation. Taken together, the identification of the respiratory dehalogenase protein complex and the absence of indications for quinone participation in the respiration suggest a quinone-independent protein-based respiratory electron transfer chain in D. mccartyi. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.

A photo-cleavable biotin affinity tag for the facile release of a photo-crosslinked carbohydrate-binding protein.

PubMed

Chang, Tsung-Che; Adak, Avijit K; Lin, Ting-Wei; Li, Pei-Jhen; Chen, Yi-Ju; Lai, Chain-Hui; Liang, Chien-Fu; Chen, Yu-Ju; Lin, Chun-Cheng

2016-03-15

The use of photo-crosslinking glycoprobes represents a powerful strategy for the covalent capture of labile protein complexes and allows detailed characterization of carbohydrate-mediated interactions. The selective release of target proteins from solid support is a key step in functional proteomics. We envisaged that light activation can be exploited for releasing labeled protein in a dual photo-affinity probe-based strategy. To investigate this possibility, we designed a trifunctional, galactose-based, multivalent glycoprobe for affinity labeling of carbohydrate-binding proteins. The resulting covalent protein-probe adduct is attached to a photo-cleavable biotin affinity tag; the biotin moiety enables specific presentation of the conjugate on streptavidin-coated beads, and the photolabile linker allows the release of the labeled proteins. This dual probe promotes both the labeling and the facile cleavage of the target protein complexes from the solid surfaces and the remainder of the cell lysate in a completely unaltered form, thus eliminating many of the common pitfalls associated with traditional affinity-based purification methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Myocilin, a Component of a Membrane-Associated Protein Complex Driven by a Homologous Q-SNARE Domain

PubMed Central

Dismuke, W. Michael; McKay, Brian S.; Stamer, W. Daniel

2012-01-01

Myocilin is a widely expressed protein with no known function, however, mutations in myocilin appear to manifest uniquely as ocular hypertension and the blinding disease glaucoma. Using the protein homology/analogy recognition engine (PHYRE) we find that the olfactomedin domain of myocilin is similar in sequence motif and structure to a six-bladed, kelch repeat motif based on the known crystal structures of such proteins. Additionally, using sequence analysis we identify a coiled-coil segment of myocilin with homology to human Q-SNARE proteins. Using COS-7 cells expressing full length human myocilin and a version lacking the C-terminal olfactomedin domain, we identified a membrane-associated protein complex containing myocilin by hydrodynamic analysis. The myocilin construct that included the coiled-coil but lacked the olfactomedin domain formed complexes similar to the full-length protein, indicating that the coiled-coil domain of myocilin is sufficient for myocilin to bind to the large detergent resistant complex. In human retina and retinal pigment epithelium, which express myocilin, we detected the protein in a large, SDS-resistant, membrane-associated complex. We characterized the hydrodynamic properties of myocilin in human tissues as either a 15s complex with an Mr=405,000–440,000 yielding a slightly elongated globular shape similar to known SNARE complexes or a dimer of 6.4s and Mr=108,000. By identifying the Q-SNARE homology within the second coil of myocilin and documenting its participation in a SNARE-like complex, we provide evidence of a SNARE domain containing protein associated with a human disease. PMID:22463803

Multicomponent self-assembly as a tool to harness new properties from peptides and proteins in material design.

PubMed

Okesola, Babatunde O; Mata, Alvaro

2018-05-21

Nature is enriched with a wide variety of complex, synergistic, and highly functional protein-based multicomponent assemblies. As such, nature has served as a source of inspiration for using multicomponent self-assembly as a platform to create highly ordered, complex, and dynamic protein and peptide-based nanostructures. Such an assembly system relies on the initial interaction of distinct individual building blocks leading to the formation of a complex that subsequently assembles into supramolecular architectures. This approach not only serves as a powerful platform for gaining insight into how proteins co-assemble in nature but also offers huge opportunities to harness new properties not inherent in the individual building blocks. In the past decades, various multicomponent self-assembly strategies have been used to extract synergistic properties from proteins and peptides. This review highlights the updates in the field of multicomponent self-assembly of proteins and peptides and summarizes various strategies, including covalent conjugation, ligand-receptor interactions, templated/directed assembly and non-specific co-assembly, for driving the self-assembly of multiple proteins and peptide-based building blocks into functional materials. In particular, we focus on peptide- or protein-containing multicomponent systems that, upon self-assembly, enable the emergence of new properties or phenomena. The ultimate goal of this review is to highlight the importance of multicomponent self-assembly in protein and peptide engineering, and to advocate its growth in the fields of materials science and nanotechnology.

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

PubMed

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

A novel Pfs38 protein complex on the surface of Plasmodium falciparum blood-stage merozoites.

PubMed

Paul, Gourab; Deshmukh, Arunaditya; Kaur, Inderjeet; Rathore, Sumit; Dabral, Surbhi; Panda, Ashutosh; Singh, Susheel Kumar; Mohmmed, Asif; Theisen, Michael; Malhotra, Pawan

2017-02-16

The Plasmodium genome encodes for a number of 6-Cys proteins that contain a module of six cysteine residues forming three intramolecular disulphide bonds. These proteins have been well characterized at transmission as well as hepatic stages of the parasite life cycle. In the present study, a large complex of 6-Cys proteins: Pfs41, Pfs38 and Pfs12 and three other merozoite surface proteins: Glutamate-rich protein (GLURP), SERA5 and MSP-1 were identified on the Plasmodium falciparum merozoite surface. Recombinant 6-cys proteins i.e. Pfs38, Pfs12, Pfs41 as well as PfMSP-1 65 were expressed and purified using Escherichia coli expression system and antibodies were raised against each of these proteins. These antibodies were used to immunoprecipitate the native proteins and their associated partners from parasite lysate. ELISA, Far western, surface plasmon resonance and glycerol density gradient fractionation were carried out to confirm the respective interactions. Furthermore, erythrocyte binding assay with 6-cys proteins were undertaken to find out their possible role in host-parasite infection and seropositivity was assessed using Indian and Liberian sera. Immunoprecipitation of parasite-derived polypeptides, followed by LC-MS/MS analysis, identified a large Pfs38 complex comprising of 6-cys proteins: Pfs41, Pfs38, Pfs12 and other merozoite surface proteins: GLURP, SERA5 and MSP-1. The existence of such a complex was further corroborated by several protein-protein interaction tools, co-localization and co-sedimentation analysis. Pfs38 protein of Pfs38 complex binds to host red blood cells (RBCs) directly via glycophorin A as a receptor. Seroprevalence analysis showed that of the six antigens, prevalence varied from 40 to 99%, being generally highest for MSP-1 65 and GLURP proteins. Together the data show the presence of a large Pfs38 protein-associated complex on the parasite surface which is involved in RBC binding. These results highlight the complex molecular interactions among the P. falciparum merozoite surface proteins and advocate the development of a multi-sub-unit malaria vaccine based on some of these protein complexes on merozoite surface.

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

On the Importance of Polar Interactions for Complexes Containing Intrinsically Disordered Proteins

PubMed Central

Wong, Eric T. C.; Na, Dokyun; Gsponer, Jörg

2013-01-01

There is a growing recognition for the importance of proteins with large intrinsically disordered (ID) segments in cell signaling and regulation. ID segments in these proteins often harbor regions that mediate molecular recognition. Coupled folding and binding of the recognition regions has been proposed to confer high specificity to interactions involving ID segments. However, researchers recently questioned the origin of the interaction specificity of ID proteins because of the overrepresentation of hydrophobic residues in their interaction interfaces. Here, we focused on the role of polar and charged residues in interactions mediated by ID segments. Making use of the extended nature of most ID segments when in complex with globular proteins, we first identified large numbers of complexes between globular proteins and ID segments by using radius-of-gyration-based selection criteria. Consistent with previous studies, we found the interfaces of these complexes to be enriched in hydrophobic residues, and that these residues contribute significantly to the stability of the interaction interface. However, our analyses also show that polar interactions play a larger role in these complexes than in structured protein complexes. Computational alanine scanning and salt-bridge analysis indicate that interfaces in ID complexes are highly complementary with respect to electrostatics, more so than interfaces of globular proteins. Follow-up calculations of the electrostatic contributions to the free energy of binding uncovered significantly stronger Coulombic interactions in complexes harbouring ID segments than in structured protein complexes. However, they are counter-balanced by even higher polar-desolvation penalties. We propose that polar interactions are a key contributing factor to the observed high specificity of ID segment-mediated interactions. PMID:23990768

Polyamine binding to proteins in oat and Petunia protoplasts

NASA Technical Reports Server (NTRS)

Mizrahi, Y.; Applewhite, P. B.; Galston, A. W.

1989-01-01

Previous work (A Apelbaum et al. [1988] Plant Physiol 88: 996-998) has demonstrated binding of labeled spermidine (Spd) to a developmentally regulated 18 kilodalton protein in tobacco tissue cultures derived from thin surface layer explants. To assess the general importance of such Spd-protein complexes, we attempted bulk isolation from protoplasts of Petunia and oat (Avena sativa). In Petunia, as in tobacco, fed radioactive Spd is bound to protein, but in oat, Spd is first converted to 1,3,-diaminopropane (DAP), probably by polyamine oxidase action. In oat, binding of DAP to protein depends on age of donor leaf and conditions of illumination and temperature, and the extraction of the DAP-protein complex depends upon buffer and pH. The yield of the DAP-protein complex was maximized by extraction of frozen-thawed protoplasts with a pH 8.8 carbonate buffer containing SDS. Its molecular size, based on Sephacryl column fractionation of ammonium sulfate precipitated material, exceeded 45 kilodaltons. Bound Spd or DAP can be released from their complexes by the action of Pronase, but not DNAse, RNAse, or strong salt solutions, indicating covalent attachment to protein.

Polyamine binding to proteins in oat and Petunia protoplasts.

PubMed

Mizrahi, Y; Applewhite, P B; Galston, A W

1989-01-01

Previous work (A Apelbaum et al. [1988] Plant Physiol 88: 996-998) has demonstrated binding of labeled spermidine (Spd) to a developmentally regulated 18 kilodalton protein in tobacco tissue cultures derived from thin surface layer explants. To assess the general importance of such Spd-protein complexes, we attempted bulk isolation from protoplasts of Petunia and oat (Avena sativa). In Petunia, as in tobacco, fed radioactive Spd is bound to protein, but in oat, Spd is first converted to 1,3,-diaminopropane (DAP), probably by polyamine oxidase action. In oat, binding of DAP to protein depends on age of donor leaf and conditions of illumination and temperature, and the extraction of the DAP-protein complex depends upon buffer and pH. The yield of the DAP-protein complex was maximized by extraction of frozen-thawed protoplasts with a pH 8.8 carbonate buffer containing SDS. Its molecular size, based on Sephacryl column fractionation of ammonium sulfate precipitated material, exceeded 45 kilodaltons. Bound Spd or DAP can be released from their complexes by the action of Pronase, but not DNAse, RNAse, or strong salt solutions, indicating covalent attachment to protein.

Interactions of cullin3/KCTD5 complexes with both cytoplasmic and nuclear proteins: Evidence for a role in protein stabilization

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

Rutz, Natalja; Heilbronn, Regine; Weger, Stefan, E-mail: stefan.weger@charite.de

2015-08-28

Based on its specific interaction with cullin3 mediated by an N-terminal BTB/POZ homologous domain, KCTD5 has been proposed to function as substrate adapter for cullin3 based ubiquitin E3 ligases. In the present study we tried to validate this hypothesis through identification and characterization of additional KCTD5 interaction partners. For the replication protein MCM7, the zinc finger protein ZNF711 and FAM193B, a yet poorly characterized cytoplasmic protein, we could demonstrate specific interaction with KCTD5 both in yeast two-hybrid and co-precipitation studies in mammalian cells. Whereas trimeric complexes of cullin3 and KCTD5 with the respective KCTD5 binding partner were formed, KCTD5/cullin3 inducedmore » polyubiquitylation and/or proteasome-dependent degradation of these binding partners could not be demonstrated. On the contrary, KCTD5 or Cullin3 overexpression increased ZNF711 protein stability. - Highlights: • KCTD5 nuclear translocation depends upon M phase and protein oligomerization. • Identification of MCM7, ZNF711 and FAM193 as KCTD5 interaction partners. • Formation of trimeric complexes of KCTD5/cullin3 with MCM7, ZNF711 and FAM193B. • KCTD5 is not involved in polyubiquitylation of MCM7 replication factor. • The KCTD5/cullin3 complex stabilizes ZNF711 transcription factor.« less

Heat capacity changes in carbohydrates and protein-carbohydrate complexes.

PubMed

Chavelas, Eneas A; García-Hernández, Enrique

2009-05-13

Carbohydrates are crucial for living cells, playing myriads of functional roles that range from being structural or energy-storage devices to molecular labels that, through non-covalent interaction with proteins, impart exquisite selectivity in processes such as molecular trafficking and cellular recognition. The molecular bases that govern the recognition between carbohydrates and proteins have not been fully understood yet. In the present study, we have obtained a surface-area-based model for the formation heat capacity of protein-carbohydrate complexes, which includes separate terms for the contributions of the two molecular types. The carbohydrate model, which was calibrated using carbohydrate dissolution data, indicates that the heat capacity contribution of a given group surface depends on its position in the saccharide molecule, a picture that is consistent with previous experimental and theoretical studies showing that the high abundance of hydroxy groups in carbohydrates yields particular solvation properties. This model was used to estimate the carbohydrate's contribution in the formation of a protein-carbohydrate complex, which in turn was used to obtain the heat capacity change associated with the protein's binding site. The model is able to account for protein-carbohydrate complexes that cannot be explained using a previous model that only considered the overall contribution of polar and apolar groups, while allowing a more detailed dissection of the elementary contributions that give rise to the formation heat capacity effects of these adducts.

Systematic analysis of protein turnover in primary cells.

PubMed

Mathieson, Toby; Franken, Holger; Kosinski, Jan; Kurzawa, Nils; Zinn, Nico; Sweetman, Gavain; Poeckel, Daniel; Ratnu, Vikram S; Schramm, Maike; Becher, Isabelle; Steidel, Michael; Noh, Kyung-Min; Bergamini, Giovanna; Beck, Martin; Bantscheff, Marcus; Savitski, Mikhail M

2018-02-15

A better understanding of proteostasis in health and disease requires robust methods to determine protein half-lives. Here we improve the precision and accuracy of peptide ion intensity-based quantification, enabling more accurate protein turnover determination in non-dividing cells by dynamic SILAC-based proteomics. This approach allows exact determination of protein half-lives ranging from 10 to >1000 h. We identified 4000-6000 proteins in several non-dividing cell types, corresponding to 9699 unique protein identifications over the entire data set. We observed similar protein half-lives in B-cells, natural killer cells and monocytes, whereas hepatocytes and mouse embryonic neurons show substantial differences. Our data set extends and statistically validates the previous observation that subunits of protein complexes tend to have coherent turnover. Moreover, analysis of different proteasome and nuclear pore complex assemblies suggests that their turnover rate is architecture dependent. These results illustrate that our approach allows investigating protein turnover and its implications in various cell types.

Segmental Isotopic Labeling of Proteins for Nuclear Magnetic Resonance

PubMed Central

Dongsheng, Liu; Xu, Rong; Cowburn, David

2009-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as one of the principle techniques of structural biology. It is not only a powerful method for elucidating the 3D structures under near physiological conditions, but also a convenient method for studying protein-ligand interactions and protein dynamics. A major drawback of macromolecular NMR is its size limitation caused by slower tumbling rates and greater complexity of the spectra as size increases. Segmental isotopic labeling allows specific segment(s) within a protein to be selectively examined by NMR thus significantly reducing the spectral complexity for large proteins and allowing a variety of solution-based NMR strategies to be applied. Two related approaches are generally used in the segmental isotopic labeling of proteins: expressed protein ligation and protein trans-splicing. Here we describe the methodology and recent application of expressed protein ligation and protein trans-splicing for NMR structural studies of proteins and protein complexes. We also describe the protocol used in our lab for the segmental isotopic labeling of a 50 kDa protein Csk (C-terminal Src Kinase) using expressed protein ligation methods. PMID:19632474

Increasing Growth Yield and Decreasing Acetylation in Escherichia coli by Optimizing the Carbon-to-Magnesium Ratio in Peptide-Based Media.

PubMed

Christensen, David G; Orr, James S; Rao, Christopher V; Wolfe, Alan J

2017-03-15

Complex media are routinely used to cultivate diverse bacteria. However, this complexity can obscure the factors that govern cell growth. While studying protein acetylation in buffered tryptone broth supplemented with glucose (TB7-glucose), we observed that Escherichia coli did not fully consume glucose prior to stationary phase. However, when we supplemented this medium with magnesium, the glucose was completely consumed during exponential growth, with concomitant increases in cell number and biomass but reduced cell size. Similar results were observed with other sugars and other peptide-based media, including lysogeny broth. Magnesium also limited cell growth for Vibrio fischeri and Bacillus subtilis in TB7-glucose. Finally, magnesium supplementation reduced protein acetylation. Based on these results, we conclude that growth in peptide-based media is magnesium limited. We further conclude that magnesium supplementation can be used to tune protein acetylation without genetic manipulation. These results have the potential to reduce potentially deleterious acetylated isoforms of recombinant proteins without negatively affecting cell growth. IMPORTANCE Bacteria are often grown in complex media. These media are thought to provide the nutrients necessary to grow bacteria to high cell densities. In this work, we found that peptide-based media containing a sugar are magnesium limited for bacterial growth. In particular, magnesium supplementation is necessary for the bacteria to use the sugar for cell growth. Interestingly, in the absence of magnesium supplementation, the bacteria still consume the sugar. However, rather than use it for cell growth, the bacteria instead use the sugar to acetylate lysines on proteins. As lysine acetylation may alter the activity of proteins, this work demonstrates how lysine acetylation can be tuned through magnesium supplementation. These findings may be useful for recombinant protein production, when acetylated isoforms are to be avoided. They also demonstrate how to increase bacterial growth in complex media. Copyright © 2017 American Society for Microbiology.

Increasing Growth Yield and Decreasing Acetylation in Escherichia coli by Optimizing the Carbon-to-Magnesium Ratio in Peptide-Based Media

PubMed Central

Christensen, David G.; Orr, James S.; Rao, Christopher V.

2017-01-01

ABSTRACT Complex media are routinely used to cultivate diverse bacteria. However, this complexity can obscure the factors that govern cell growth. While studying protein acetylation in buffered tryptone broth supplemented with glucose (TB7-glucose), we observed that Escherichia coli did not fully consume glucose prior to stationary phase. However, when we supplemented this medium with magnesium, the glucose was completely consumed during exponential growth, with concomitant increases in cell number and biomass but reduced cell size. Similar results were observed with other sugars and other peptide-based media, including lysogeny broth. Magnesium also limited cell growth for Vibrio fischeri and Bacillus subtilis in TB7-glucose. Finally, magnesium supplementation reduced protein acetylation. Based on these results, we conclude that growth in peptide-based media is magnesium limited. We further conclude that magnesium supplementation can be used to tune protein acetylation without genetic manipulation. These results have the potential to reduce potentially deleterious acetylated isoforms of recombinant proteins without negatively affecting cell growth. IMPORTANCE Bacteria are often grown in complex media. These media are thought to provide the nutrients necessary to grow bacteria to high cell densities. In this work, we found that peptide-based media containing a sugar are magnesium limited for bacterial growth. In particular, magnesium supplementation is necessary for the bacteria to use the sugar for cell growth. Interestingly, in the absence of magnesium supplementation, the bacteria still consume the sugar. However, rather than use it for cell growth, the bacteria instead use the sugar to acetylate lysines on proteins. As lysine acetylation may alter the activity of proteins, this work demonstrates how lysine acetylation can be tuned through magnesium supplementation. These findings may be useful for recombinant protein production, when acetylated isoforms are to be avoided. They also demonstrate how to increase bacterial growth in complex media. PMID:28062462

Cell type-specific recruitment of Drosophila Lin-7 to distinct MAGUK-based protein complexes defines novel roles for Sdt and Dlg-S97.

PubMed

Bachmann, André; Timmer, Marco; Sierralta, Jimena; Pietrini, Grazia; Gundelfinger, Eckart D; Knust, Elisabeth; Thomas, Ulrich

2004-04-15

Stardust (Sdt) and Discs-Large (Dlg) are membrane-associated guanylate kinases (MAGUKs) involved in the organization of supramolecular protein complexes at distinct epithelial membrane compartments in Drosophila. Loss of either Sdt or Dlg affects epithelial development with severe effects on apico-basal polarity. Moreover, Dlg is required for the structural and functional integrity of synaptic junctions. Recent biochemical and cell culture studies have revealed that various mammalian MAGUKs can interact with mLin-7/Veli/MALS, a small PDZ-domain protein. To substantiate these findings for their in vivo significance with regard to Sdt- and Dlg-based protein complexes, we analyzed the subcellular distribution of Drosophila Lin-7 (DLin-7) and performed genetic and biochemical assays to characterize its interaction with either of the two MAGUKs. In epithelia, Sdt mediates the recruitment of DLin-7 to the subapical region, while at larval neuromuscular junctions, a particular isoform of Dlg, Dlg-S97, is required for postsynaptic localization of DLin-7. Ectopic expression of Dlg-S97 in epithelia, however, was not sufficient to induce a redistribution of DLin-7. These results imply that the recruitment of DLin-7 to MAGUK-based protein complexes is defined by cell-type specific mechanisms and that DLin-7 acts downstream of Sdt in epithelia and downstream of Dlg at synapses.

The influence of different cucumariosides on immunogenicity of OmpF porin from Yersinia pseudotuberulosis as a model protein antigen of tubular immunostimulating complex

NASA Astrophysics Data System (ADS)

Sanina, N. M.; Chopenko, N. S.; Davydova, L. A.; Mazeika, A. N.; Portnyagina, O. Yu.; Kim, N. Yu.; Golotin, V. A.; Kostetsky, E. Y.; Shnyrov, V. L.

2017-09-01

Nanoparticulate tubular immunostimulating complex (TI-complex) is a novel promising adjuvant carrier of antigens allowing to create safe and effective vaccines of new generation. The adjuvant activity of TI-complexes based on monogalactosyldyacylglycerol (MGDG) from the sea alga Ulva lactuca and different triterpene glycosides cucumariosides (CDs) from marine invertebrate Cucumaria japonica and their fractions was studied to assess effects of different CDs on the immunogenicity of porin OmpF from Yersinia pseudotuberculosis (YOmpF). TI-complexes with cucumarioside A2-2 (CDA2-2) maximally stimulated anti-porin antibody production. Studies of protein intrinsic fluorescence showed that all CDs had a relaxing effect on the conformation of YOmpF, loosening peripheral region of protein and promoting exposure of the protein antigenic determinants to the water environment. The greatest immunostimulating effect of TI-complexes comprising CDA2-2 was accompanied by mild effect of this CD on the tertiary structure of protein antigen YOmpF, whereas cucumarioside E (CDE) and cucumarioside A2-4 (CDA2-4) caused especially sharp redistribution of spectral form of the YOmpF corresponding to the emission of an intrinsic protein fluorophore tryptophan.

Radiation damage to DNA in DNA-protein complexes.

PubMed

Spotheim-Maurizot, M; Davídková, M

2011-06-03

The most aggressive product of water radiolysis, the hydroxyl (OH) radical, is responsible for the indirect effect of ionizing radiations on DNA in solution and aerobic conditions. According to radiolytic footprinting experiments, the resulting strand breaks and base modifications are inhomogeneously distributed along the DNA molecule irradiated free or bound to ligands (polyamines, thiols, proteins). A Monte-Carlo based model of simulation of the reaction of OH radicals with the macromolecules, called RADACK, allows calculating the relative probability of damage of each nucleotide of DNA irradiated alone or in complexes with proteins. RADACK calculations require the knowledge of the three dimensional structure of DNA and its complexes (determined by X-ray crystallography, NMR spectroscopy or molecular modeling). The confrontation of the calculated values with the results of the radiolytic footprinting experiments together with molecular modeling calculations show that: (1) the extent and location of the lesions are strongly dependent on the structure of DNA, which in turns is modulated by the base sequence and by the binding of proteins and (2) the regions in contact with the protein can be protected against the attack by the hydroxyl radicals via masking of the binding site and by scavenging of the radicals. 2011 Elsevier B.V. All rights reserved.

Searching for microbial protein over-expression in a complex matrix using automated high throughput MS-based proteomics tools.

PubMed

Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob

2013-03-10

In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.

Exploring protein-protein intermolecular recognition between meprin-α and endogenous protease regulator cystatinC coupled with pharmacophore elucidation.

PubMed

Chaudhuri, Ankur; Biswas, Sampa; Chakraborty, Sibani

2018-02-07

Meprins are a group of zinc metalloproteases of the astacin family which play a pivotal role in several physiological and pathologocal diseases. The inhibition of the meprins by various inhibitors, macromolecular and small molecules, is crucial in the control of several diseases. Human cystatinC, an amyloidogenic protein, is reported to be an endogenous inhibitor of meprin-α. In this computational study, we elucidate a rational model for meprinα-cystatinC complex using protein-protein docking. The complex model as well as the unbound form was evaluated by molecular dynamics simulation. A simulation study revealed higher stability of the complex owing to the presence of several interactions. Virtual alanine mutagenesis helps in identifying the hotspots on both proteins. Based on the frequency of occurrence of hotspot amino acids, it was possible to enumerate the important amino acids primarily responsible for protein stability present at the amino-terminal end of cystatin. Finally, pharmacophore elucidation carried out based on the information obtained from a series of small molecular inhibitors against meprin-α can be utilized in future for rational drug design and therapy.

Community of protein complexes impacts disease association

PubMed Central

Wang, Qianghu; Liu, Weisha; Ning, Shangwei; Ye, Jingrun; Huang, Teng; Li, Yan; Wang, Peng; Shi, Hongbo; Li, Xia

2012-01-01

One important challenge in the post-genomic era is uncovering the relationships among distinct pathophenotypes by using molecular signatures. Given the complex functional interdependencies between cellular components, a disease is seldom the consequence of a defect in a single gene product, instead reflecting the perturbations of a group of closely related gene products that carry out specific functions together. Therefore, it is meaningful to explore how the community of protein complexes impacts disease associations. Here, by integrating a large amount of information from protein complexes and the cellular basis of diseases, we built a human disease network in which two diseases are linked if they share common disease-related protein complex. A systemic analysis revealed that linked disease pairs exhibit higher comorbidity than those that have no links, and that the stronger association two diseases have based on protein complexes, the higher comorbidity they are prone to display. Moreover, more connected diseases tend to be malignant, which have high prevalence. We provide novel disease associations that cannot be identified through previous analysis. These findings will potentially provide biologists and clinicians new insights into the etiology, classification and treatment of diseases. PMID:22549411

Current Understanding of Usher Syndrome Type II

PubMed Central

Yang, Jun; Wang, Le; Song, Hongman; Sokolov, Maxim

2012-01-01

Usher syndrome is the most common deafness-blindness caused by genetic mutations. To date, three genes have been identified underlying the most prevalent form of Usher syndrome, the type II form (USH2). The proteins encoded by these genes are demonstrated to form a complex in vivo. This complex is localized mainly at the periciliary membrane complex in photoreceptors and the ankle-link of the stereocilia in hair cells. Many proteins have been found to interact with USH2 proteins in vitro, suggesting that they are potential additional components of this USH2 complex and that the genes encoding these proteins may be the candidate USH2 genes. However, further investigations are critical to establish their existence in the USH2 complex in vivo. Based on the predicted functional domains in USH2 proteins, their cellular localizations in photoreceptors and hair cells, the observed phenotypes in USH2 mutant mice, and the known knowledge about diseases similar to USH2, putative biological functions of the USH2 complex have been proposed. Finally, therapeutic approaches for this group of diseases are now being actively explored. PMID:22201796

The Fibroblast Growth Factor 14·Voltage-gated Sodium Channel Complex Is a New Target of Glycogen Synthase Kinase 3 (GSK3)*

PubMed Central

Shavkunov, Alexander S.; Wildburger, Norelle C.; Nenov, Miroslav N.; James, Thomas F.; Buzhdygan, Tetyana P.; Panova-Elektronova, Neli I.; Green, Thomas A.; Veselenak, Ronald L.; Bourne, Nigel; Laezza, Fernanda

2013-01-01

The FGF14 protein controls biophysical properties and subcellular distribution of neuronal voltage-gated Na+ (Nav) channels through direct binding to the channel C terminus. To gain insights into the dynamic regulation of this protein/protein interaction complex, we employed the split luciferase complementation assay to screen a small molecule library of kinase inhibitors against the FGF14·Nav1.6 channel complex and identified inhibitors of GSK3 as hits. Through a combination of a luminescence-based counter-screening, co-immunoprecipitation, patch clamp electrophysiology, and quantitative confocal immunofluorescence, we demonstrate that inhibition of GSK3 reduces the assembly of the FGF14·Nav channel complex, modifies FGF14-dependent regulation of Na+ currents, and induces dissociation and subcellular redistribution of the native FGF14·Nav channel complex in hippocampal neurons. These results further emphasize the role of FGF14 as a critical component of the Nav channel macromolecular complex, providing evidence for a novel GSK3-dependent signaling pathway that might control excitability through specific protein/protein interactions. PMID:23640885

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

A Light Harvesting Complex-Like Protein in Maintenance of Photosynthetic Components in Chlamydomonas1[OPEN

PubMed Central

Zhao, Lei; Cheng, Dongmei; Huang, Xiahe; Chen, Mei; Xing, Jiale; Gao, Liyan; Li, Lingyu; Wang, Yale; Peng, Lianwei; Wang, Yingchun

2017-01-01

Using a genetic approach, we have identified and characterized a novel protein, named Msf1 (Maintenance factor for photosystem I), that is required for the maintenance of specific components of the photosynthetic apparatus in the green alga Chlamydomonas reinhardtii. Msf1 belongs to the superfamily of light-harvesting complex proteins with three transmembrane domains and consensus chlorophyll-binding sites. Loss of Msf1 leads to reduced accumulation of photosystem I and chlorophyll-binding proteins/complexes. Msf1is a component of a thylakoid complex containing key enzymes of the tetrapyrrole biosynthetic pathway, thus revealing a possible link between Msf1 and chlorophyll biosynthesis. Protein interaction assays and greening experiments demonstrate that Msf1 interacts with Copper target homolog1 (CHL27B) and accumulates concomitantly with chlorophyll in Chlamydomonas, implying that chlorophyll stabilizes Msf1. Contrary to other light-harvesting complex-like genes, the expression of Msf1 is not stimulated by high-light stress, but its protein level increases significantly under heat shock, iron and copper limitation, as well as in stationary cells. Based on these results, we propose that Msf1 is required for the maintenance of photosystem I and specific protein-chlorophyll complexes especially under certain stress conditions. PMID:28637830

Mitochondrial respiratory chain complexes as sources and targets of thiol-based redox-regulation.

PubMed

Dröse, Stefan; Brandt, Ulrich; Wittig, Ilka

2014-08-01

The respiratory chain of the inner mitochondrial membrane is a unique assembly of protein complexes that transfers the electrons of reducing equivalents extracted from foodstuff to molecular oxygen to generate a proton-motive force as the primary energy source for cellular ATP-synthesis. Recent evidence indicates that redox reactions are also involved in regulating mitochondrial function via redox-modification of specific cysteine-thiol groups in subunits of respiratory chain complexes. Vice versa the generation of reactive oxygen species (ROS) by respiratory chain complexes may have an impact on the mitochondrial redox balance through reversible and irreversible thiol-modification of specific target proteins involved in redox signaling, but also pathophysiological processes. Recent evidence indicates that thiol-based redox regulation of the respiratory chain activity and especially S-nitrosylation of complex I could be a strategy to prevent elevated ROS production, oxidative damage and tissue necrosis during ischemia-reperfusion injury. This review focuses on the thiol-based redox processes involving the respiratory chain as a source as well as a target, including a general overview on mitochondria as highly compartmentalized redox organelles and on methods to investigate the redox state of mitochondrial proteins. This article is part of a Special Issue entitled: Thiol-Based Redox Processes. Copyright © 2014 Elsevier B.V. All rights reserved.

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p-coumaric acid and related aromatic acids.

PubMed

Tan, Kemin; Chang, Changsoo; Cuff, Marianne; Osipiuk, Jerzy; Landorf, Elizabeth; Mack, Jamey C; Zerbs, Sarah; Joachimiak, Andrzej; Collart, Frank R

2013-10-01

Lignin comprises 15-25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP-binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p-coumarate, 3-phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X-ray crystal structures of protein-ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin-derived aromatic compounds. The screens and structural data provide new functional assignments for these solute-binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence-based functional annotation methods for this family of proteins. Copyright © 2013 Wiley Periodicals, Inc.

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p-coumaric acid and related aromatic acids

PubMed Central

Tan, Kemin; Chang, Changsoo; Cuff, Marianne; Osipiuk, Jerzy; Landorf, Elizabeth; Mack, Jamey C.; Zerbs, Sarah; Joachimiak, Andrzej; Collart, Frank R.

2013-01-01

Lignin comprises 15.25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP.binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p-coumarate, 3-phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X-ray crystal structures of protein-ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin-derived aromatic compounds. The screens and structural data provide new functional assignments for these solute.binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence-based functional annotation methods for this family of proteins. PMID:23606130

Mass spectrometry–based relative quantification of proteins in precatalytic and catalytically active spliceosomes by metabolic labeling (SILAC), chemical labeling (iTRAQ), and label-free spectral count

PubMed Central

Schmidt, Carla; Grønborg, Mads; Deckert, Jochen; Bessonov, Sergey; Conrad, Thomas; Lührmann, Reinhard; Urlaub, Henning

2014-01-01

The spliceosome undergoes major changes in protein and RNA composition during pre-mRNA splicing. Knowing the proteins—and their respective quantities—at each spliceosomal assembly stage is critical for understanding the molecular mechanisms and regulation of splicing. Here, we applied three independent mass spectrometry (MS)–based approaches for quantification of these proteins: (1) metabolic labeling by SILAC, (2) chemical labeling by iTRAQ, and (3) label-free spectral count for quantification of the protein composition of the human spliceosomal precatalytic B and catalytic C complexes. In total we were able to quantify 157 proteins by at least two of the three approaches. Our quantification shows that only a very small subset of spliceosomal proteins (the U5 and U2 Sm proteins, a subset of U5 snRNP-specific proteins, and the U2 snRNP-specific proteins U2A′ and U2B′′) remains unaltered upon transition from the B to the C complex. The MS-based quantification approaches classify the majority of proteins as dynamically associated specifically with the B or the C complex. In terms of experimental procedure and the methodical aspect of this work, we show that metabolically labeled spliceosomes are functionally active in terms of their assembly and splicing kinetics and can be utilized for quantitative studies. Moreover, we obtain consistent quantification results from all three methods, including the relatively straightforward and inexpensive label-free spectral count technique. PMID:24448447

GPU-enabled molecular dynamics simulations of ankyrin kinase complex

NASA Astrophysics Data System (ADS)

Gautam, Vertika; Chong, Wei Lim; Wisitponchai, Tanchanok; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.; Tayapiwatana, Chatchai; Lee, Vannajan Sanghiran

2014-10-01

The ankyrin repeat (AR) protein can be used as a versatile scaffold for protein-protein interactions. It has been found that the heterotrimeric complex between integrin-linked kinase (ILK), PINCH, and parvin is an essential signaling platform, serving as a convergence point for integrin and growth-factor signaling and regulating cell adhesion, spreading, and migration. Using ILK-AR with high affinity for the PINCH1 as our model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. In this study, the long time scale dynamics simulations with GPU accelerated molecular dynamics (MD) simulations in AMBER12 have been performed to locate the hot spots of protein-protein interaction by the analysis of the Molecular Mechanics-Poisson-Boltzmann Surface Area/Generalized Born Solvent Area (MM-PBSA/GBSA) of the MD trajectories. Our calculations suggest good binding affinity of the complex and also the residues critical in the binding.

Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta

PubMed Central

Zhang, Zhe; Schindler, Christina E. M.; Lange, Oliver F.; Zacharias, Martin

2015-01-01

The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC) was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches. PMID:26053419

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Precision and accuracy in smFRET based structural studies—A benchmark study of the Fast-Nano-Positioning System

NASA Astrophysics Data System (ADS)

Nagy, Julia; Eilert, Tobias; Michaelis, Jens

2018-03-01

Modern hybrid structural analysis methods have opened new possibilities to analyze and resolve flexible protein complexes where conventional crystallographic methods have reached their limits. Here, the Fast-Nano-Positioning System (Fast-NPS), a Bayesian parameter estimation-based analysis method and software, is an interesting method since it allows for the localization of unknown fluorescent dye molecules attached to macromolecular complexes based on single-molecule Förster resonance energy transfer (smFRET) measurements. However, the precision, accuracy, and reliability of structural models derived from results based on such complex calculation schemes are oftentimes difficult to evaluate. Therefore, we present two proof-of-principle benchmark studies where we use smFRET data to localize supposedly unknown positions on a DNA as well as on a protein-nucleic acid complex. Since we use complexes where structural information is available, we can compare Fast-NPS localization to the existing structural data. In particular, we compare different dye models and discuss how both accuracy and precision can be optimized.

Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

PubMed Central

Fiorucci, Sébastien; Zacharias, Martin

2010-01-01

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

Prediction of Ordered Water Molecules in Protein Binding Sites from Molecular Dynamics Simulations: The Impact of Ligand Binding on Hydration Networks.

PubMed

Rudling, Axel; Orro, Adolfo; Carlsson, Jens

2018-02-26

Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein-ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein-ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein-ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein-ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein-ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.

Enrichment of Cross-Linked Peptides Using Charge-Based Fractional Diagonal Chromatography (ChaFRADIC).

PubMed

Tinnefeld, Verena; Venne, A Saskia; Sickmann, Albert; Zahedi, René P

2017-02-03

Chemical cross-linking of proteins is an emerging field with huge potential for the structural investigation of proteins and protein complexes. Owing to the often relatively low yield of cross-linking products, their identification in complex samples benefits from enrichment procedures prior to mass spectrometry analysis. So far, this is mainly accomplished by using biotin moieties in specific cross-linkers or by applying strong cation exchange chromatography (SCX) for a relatively crude enrichment. We present a novel workflow to enrich cross-linked peptides by utilizing charge-based fractional diagonal chromatography (ChaFRADIC). On the basis of two-dimensional diagonal SCX separation, we could increase the number of identified cross-linked peptides for samples of different complexity: pure cross-linked BSA, cross-linked BSA spiked into a simple protein mixture, and cross-linked BSA spiked into a HeLa lysate. We also compared XL-ChaFRADIC with size exclusion chromatography-based enrichment of cross-linked peptides. The XL-ChaFRADIC approach is straightforward, reproducible, and independent of the cross-linking chemistry and cross-linker properties.

Protein docking by the interface structure similarity: how much structure is needed?

PubMed

Sinha, Rohita; Kundrotas, Petras J; Vakser, Ilya A

2012-01-01

The increasing availability of co-crystallized protein-protein complexes provides an opportunity to use template-based modeling for protein-protein docking. Structure alignment techniques are useful in detection of remote target-template similarities. The size of the structure involved in the alignment is important for the success in modeling. This paper describes a systematic large-scale study to find the optimal definition/size of the interfaces for the structure alignment-based docking applications. The results showed that structural areas corresponding to the cutoff values <12 Å across the interface inadequately represent structural details of the interfaces. With the increase of the cutoff beyond 12 Å, the success rate for the benchmark set of 99 protein complexes, did not increase significantly for higher accuracy models, and decreased for lower-accuracy models. The 12 Å cutoff was optimal in our interface alignment-based docking, and a likely best choice for the large-scale (e.g., on the scale of the entire genome) applications to protein interaction networks. The results provide guidelines for the docking approaches, including high-throughput applications to modeled structures.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes.

PubMed

Raschka, Sebastian; Wolf, Alex J; Bemister-Buffington, Joseph; Kuhn, Leslie A

2018-04-01

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes

NASA Astrophysics Data System (ADS)

Raschka, Sebastian; Wolf, Alex J.; Bemister-Buffington, Joseph; Kuhn, Leslie A.

2018-02-01

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

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

PubMed

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.

Novel copper complexes as potential proteasome inhibitors for cancer treatment (Review).

PubMed

Zhang, Zhen; Wang, Huiyun; Yan, Maocai; Wang, Huannan; Zhang, Chunyan

2017-01-01

The use of metal complexes in the pharmaceutical industry has recently increased and as a result, novel metal‑based complexes have initiated an interest as potential anticancer agents. Copper (Cu), which is an essential trace element in all living organisms, is important in maintaining the function of numerous proteins and enzymes. It has recently been demonstrated that Cu complexes may be used as tumor‑specific proteasome inhibitors and apoptosis inducers, by targeting the ubiquitin‑proteasome pathway (UPP). Cu complexes have demonstrated promising results in preclinical studies. The UPP is important in controlling the expression, activity and location of various proteins. Therefore, selective proteasome inhibition and apoptotic induction in cancer cells have been regarded as potential anticancer strategies. The present short review discusses recent progress in the development of Cu complexes, including clioquinol, dithiocarbamates and Schiff bases, as proteasome inhibitors for cancer treatment. A discussion of recent research regarding the understanding of metal inhibitors based on Cu and ligand platforms is presented.

AESOP: A Python Library for Investigating Electrostatics in Protein Interactions.

PubMed

Harrison, Reed E S; Mohan, Rohith R; Gorham, Ronald D; Kieslich, Chris A; Morikis, Dimitrios

2017-05-09

Electric fields often play a role in guiding the association of protein complexes. Such interactions can be further engineered to accelerate complex association, resulting in protein systems with increased productivity. This is especially true for enzymes where reaction rates are typically diffusion limited. To facilitate quantitative comparisons of electrostatics in protein families and to describe electrostatic contributions of individual amino acids, we previously developed a computational framework called AESOP. We now implement this computational tool in Python with increased usability and the capability of performing calculations in parallel. AESOP utilizes PDB2PQR and Adaptive Poisson-Boltzmann Solver to generate grid-based electrostatic potential files for protein structures provided by the end user. There are methods within AESOP for quantitatively comparing sets of grid-based electrostatic potentials in terms of similarity or generating ensembles of electrostatic potential files for a library of mutants to quantify the effects of perturbations in protein structure and protein-protein association. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A Bacillus megaterium System for the Production of Recombinant Proteins and Protein Complexes.

PubMed

Biedendieck, Rebekka

2016-01-01

For many years the Gram-positive bacterium Bacillus megaterium has been used for the production and secretion of recombinant proteins. For this purpose it was systematically optimized. Plasmids with different inducible promoter systems, with different compatible origins, with small tags for protein purification and with various specific signals for protein secretion were combined with genetically improved host strains. Finally, the development of appropriate cultivation conditions for the production strains established this organism as a bacterial cell factory even for large proteins. Along with the overproduction of individual proteins the organism is now also used for the simultaneous coproduction of up to 14 recombinant proteins, multiple subsequently interacting or forming protein complexes. Some of these recombinant strains are successfully used for bioconversion or the biosynthesis of valuable components including vitamins. The titers in the g per liter scale for the intra- and extracellular recombinant protein production prove the high potential of B. megaterium for industrial applications. It is currently further enhanced for the production of recombinant proteins and multi-subunit protein complexes using directed genetic engineering approaches based on transcriptome, proteome, metabolome and fluxome data.

Entropy in molecular recognition by proteins.

PubMed

Caro, José A; Harpole, Kyle W; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G; Sharp, Kim A; Wand, A Joshua

2017-06-20

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein-ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein-ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein-ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or "entropy meter" also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water-protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins.

Protein-protein docking using region-based 3D Zernike descriptors

PubMed Central

2009-01-01

Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235

Protein-protein docking using region-based 3D Zernike descriptors.

PubMed

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Four-color single-molecule fluorescence with noncovalent dye labeling to monitor dynamic multimolecular complexes.

PubMed

DeRocco, Vanessa; Anderson, Trevor; Piehler, Jacob; Erie, Dorothy A; Weninger, Keith

2010-11-01

To enable studies of conformational changes within multimolecular complexes, we present a simultaneous, four-color single molecule fluorescence methodology implemented with total internal reflection illumination and camera-based, wide-field detection. We further demonstrate labeling histidine-tagged proteins noncovalently with Tris-nitrilotriacetic acid (Tris-NTA)-conjugated dyes to achieve single molecule detection. We combine these methods to colocalize the mismatch repair protein MutSα on DNA while monitoring MutSα-induced DNA bending using Förster resonance energy transfer (FRET) and to monitor assembly of membrane-tethered SNARE protein complexes.

Four-color single molecule fluorescence with noncovalent dye labeling to monitor dynamic multimolecular complexes

PubMed Central

DeRocco, Vanessa C.; Anderson, Trevor; Piehler, Jacob; Erie, Dorothy A.; Weninger, Keith

2010-01-01

To allow studies of conformational changes within multi-molecular complexes, we present a simultaneous, 4-color single molecule fluorescence methodology implemented with total internal reflection illumination and camera based, wide-field detection. We further demonstrate labeling histidine-tagged proteins non-covalently with tris-Nitrilotriacetic acid (tris-NTA) conjugated dyes to achieve single molecule detection. We combine these methods to co-localize the mismatch repair protein MutSα on DNA while monitoring MutSα-induced DNA bending using Förster resonance energy transfer (FRET) and to monitor assembly of membrane-tethered SNARE protein complexes. PMID:21091445

Specific and Non-Specific Protein Association in Solution: Computation of Solvent Effects and Prediction of First-Encounter Modes for Efficient Configurational Bias Monte Carlo Simulations

PubMed Central

Cardone, Antonio; Pant, Harish; Hassan, Sergio A.

2013-01-01

Weak and ultra-weak protein-protein association play a role in molecular recognition, and can drive spontaneous self-assembly and aggregation. Such interactions are difficult to detect experimentally, and are a challenge to the force field and sampling technique. A method is proposed to identify low-population protein-protein binding modes in aqueous solution. The method is designed to identify preferential first-encounter complexes from which the final complex(es) at equilibrium evolves. A continuum model is used to represent the effects of the solvent, which accounts for short- and long-range effects of water exclusion and for liquid-structure forces at protein/liquid interfaces. These effects control the behavior of proteins in close proximity and are optimized based on binding enthalpy data and simulations. An algorithm is described to construct a biasing function for self-adaptive configurational-bias Monte Carlo of a set of interacting proteins. The function allows mixing large and local changes in the spatial distribution of proteins, thereby enhancing sampling of relevant microstates. The method is applied to three binary systems. Generalization to multiprotein complexes is discussed. PMID:24044772

Proteomics to study DNA-bound and chromatin-associated gene regulatory complexes

PubMed Central

Wierer, Michael; Mann, Matthias

2016-01-01

High-resolution mass spectrometry (MS)-based proteomics is a powerful method for the identification of soluble protein complexes and large-scale affinity purification screens can decode entire protein interaction networks. In contrast, protein complexes residing on chromatin have been much more challenging, because they are difficult to purify and often of very low abundance. However, this is changing due to recent methodological and technological advances in proteomics. Proteins interacting with chromatin marks can directly be identified by pulldowns with synthesized histone tails containing posttranslational modifications (PTMs). Similarly, pulldowns with DNA baits harbouring single nucleotide polymorphisms or DNA modifications reveal the impact of those DNA alterations on the recruitment of transcription factors. Accurate quantitation – either isotope-based or label free – unambiguously pinpoints proteins that are significantly enriched over control pulldowns. In addition, protocols that combine classical chromatin immunoprecipitation (ChIP) methods with mass spectrometry (ChIP-MS) target gene regulatory complexes in their in-vivo context. Similar to classical ChIP, cells are crosslinked with formaldehyde and chromatin sheared by sonication or nuclease digested. ChIP-MS baits can be proteins in tagged or endogenous form, histone PTMs, or lncRNAs. Locus-specific ChIP-MS methods would allow direct purification of a single genomic locus and the proteins associated with it. There, loci can be targeted either by artificial DNA-binding sites and corresponding binding proteins or via proteins with sequence specificity such as TAL or nuclease deficient Cas9 in combination with a specific guide RNA. We predict that advances in MS technology will soon make such approaches generally applicable tools in epigenetics. PMID:27402878

Small Cofactors May Assist Protein Emergence from RNA World: Clues from RNA-Protein Complexes

PubMed Central

Shen, Liang; Ji, Hong-Fang

2011-01-01

It is now widely accepted that at an early stage in the evolution of life an RNA world arose, in which RNAs both served as the genetic material and catalyzed diverse biochemical reactions. Then, proteins have gradually replaced RNAs because of their superior catalytic properties in catalysis over time. Therefore, it is important to investigate how primitive functional proteins emerged from RNA world, which can shed light on the evolutionary pathway of life from RNA world to the modern world. In this work, we proposed that the emergence of most primitive functional proteins are assisted by the early primitive nucleotide cofactors, while only a minority are induced directly by RNAs based on the analysis of RNA-protein complexes. Furthermore, the present findings have significant implication for exploring the composition of primitive RNA, i.e., adenine base as principal building blocks. PMID:21789260

Inferring drug-disease associations based on known protein complexes.

PubMed

Yu, Liang; Huang, Jianbin; Ma, Zhixin; Zhang, Jing; Zou, Yapeng; Gao, Lin

2015-01-01

Inferring drug-disease associations is critical in unveiling disease mechanisms, as well as discovering novel functions of available drugs, or drug repositioning. Previous work is primarily based on drug-gene-disease relationship, which throws away many important information since genes execute their functions through interacting others. To overcome this issue, we propose a novel methodology that discover the drug-disease association based on protein complexes. Firstly, the integrated heterogeneous network consisting of drugs, protein complexes, and disease are constructed, where we assign weights to the drug-disease association by using probability. Then, from the tripartite network, we get the indirect weighted relationships between drugs and diseases. The larger the weight, the higher the reliability of the correlation. We apply our method to mental disorders and hypertension, and validate the result by using comparative toxicogenomics database. Our ranked results can be directly reinforced by existing biomedical literature, suggesting that our proposed method obtains higher specificity and sensitivity. The proposed method offers new insight into drug-disease discovery. Our method is publicly available at http://1.complexdrug.sinaapp.com/Drug_Complex_Disease/Data_Download.html.

Inferring drug-disease associations based on known protein complexes

PubMed Central

2015-01-01

Inferring drug-disease associations is critical in unveiling disease mechanisms, as well as discovering novel functions of available drugs, or drug repositioning. Previous work is primarily based on drug-gene-disease relationship, which throws away many important information since genes execute their functions through interacting others. To overcome this issue, we propose a novel methodology that discover the drug-disease association based on protein complexes. Firstly, the integrated heterogeneous network consisting of drugs, protein complexes, and disease are constructed, where we assign weights to the drug-disease association by using probability. Then, from the tripartite network, we get the indirect weighted relationships between drugs and diseases. The larger the weight, the higher the reliability of the correlation. We apply our method to mental disorders and hypertension, and validate the result by using comparative toxicogenomics database. Our ranked results can be directly reinforced by existing biomedical literature, suggesting that our proposed method obtains higher specificity and sensitivity. The proposed method offers new insight into drug-disease discovery. Our method is publicly available at http://1.complexdrug.sinaapp.com/Drug_Complex_Disease/Data_Download.html. PMID:26044949

The Human Ligase IIIα-XRCC1 Protein Complex Performs DNA Nick Repair after Transient Unwrapping of Nucleosomal DNA*

PubMed Central

Rashid, Ishtiaque; Tomkinson, Alan E.; Pederson, David S.

2017-01-01

Reactive oxygen species generate potentially cytotoxic and mutagenic lesions in DNA, both between and within the nucleosomes that package DNA in chromatin. The vast majority of these lesions are subject to base excision repair (BER). Enzymes that catalyze the first three steps in BER can act at many sites in nucleosomes without the aid of chromatin-remodeling agents and without irreversibly disrupting the host nucleosome. Here we show that the same is true for a protein complex comprising DNA ligase IIIα and the scaffolding protein X-ray repair cross-complementing protein 1 (XRCC1), which completes the fourth and final step in (short-patch) BER. Using in vitro assembled nucleosomes containing discretely positioned DNA nicks, our evidence indicates that the ligase IIIα-XRCC1 complex binds to DNA nicks in nucleosomes only when they are exposed by periodic, spontaneous partial unwrapping of DNA from the histone octamer; that the scaffolding protein XRCC1 enhances the ligation; that the ligation occurs within a complex that ligase IIIα-XRCC1 forms with the host nucleosome; and that the ligase IIIα-XRCC1-nucleosome complex decays when ligation is complete, allowing the host nucleosome to return to its native configuration. Taken together, our results illustrate ways in which dynamic properties intrinsic to nucleosomes may contribute to the discovery and efficient repair of base damage in chromatin. PMID:28184006

NMR studies of protein-nucleic acid interactions.

PubMed

Varani, Gabriele; Chen, Yu; Leeper, Thomas C

2004-01-01

Protein-DNA and protein-RNA complexes play key functional roles in every living organism. Therefore, the elucidation of their structure and dynamics is an important goal of structural and molecular biology. Nuclear magnetic resonance (NMR) studies of protein and nucleic acid complexes have common features with studies of protein-protein complexes: the interaction surfaces between the molecules must be carefully delineated, the relative orientation of the two species needs to be accurately and precisely determined, and close intermolecular contacts defined by nuclear Overhauser effects (NOEs) must be obtained. However, differences in NMR properties (e.g., chemical shifts) and biosynthetic pathways for sample productions generate important differences. Chemical shift differences between the protein and nucleic acid resonances can aid the NMR structure determination process; however, the relatively limited dispersion of the RNA ribose resonances makes the process of assigning intermolecular NOEs more difficult. The analysis of the resulting structures requires computational tools unique to nucleic acid interactions. This chapter summarizes the most important elements of the structure determination by NMR of protein-nucleic acid complexes and their analysis. The main emphasis is on recent developments (e.g., residual dipolar couplings and new Web-based analysis tools) that have facilitated NMR studies of these complexes and expanded the type of biological problems to which NMR techniques of structural elucidation can now be applied.

Chemical synthesis and X-ray structure of a heterochiral {D-protein antagonist plus vascular endothelial growth factor} protein complex by racemic crystallography.

PubMed

Mandal, Kalyaneswar; Uppalapati, Maruti; Ault-Riché, Dana; Kenney, John; Lowitz, Joshua; Sidhu, Sachdev S; Kent, Stephen B H

2012-09-11

Total chemical synthesis was used to prepare the mirror image (D-protein) form of the angiogenic protein vascular endothelial growth factor (VEGF-A). Phage display against D-VEGF-A was used to screen designed libraries based on a unique small protein scaffold in order to identify a high affinity ligand. Chemically synthesized D- and L- forms of the protein ligand showed reciprocal chiral specificity in surface plasmon resonance binding experiments: The L-protein ligand bound only to D-VEGF-A, whereas the D-protein ligand bound only to L-VEGF-A. The D-protein ligand, but not the L-protein ligand, inhibited the binding of natural VEGF(165) to the VEGFR1 receptor. Racemic protein crystallography was used to determine the high resolution X-ray structure of the heterochiral complex consisting of {D-protein antagonist + L-protein form of VEGF-A}. Crystallization of a racemic mixture of these synthetic proteins in appropriate stoichiometry gave a racemic protein complex of more than 73 kDa containing six synthetic protein molecules. The structure of the complex was determined to a resolution of 1.6 Å. Detailed analysis of the interaction between the D-protein antagonist and the VEGF-A protein molecule showed that the binding interface comprised a contact surface area of approximately 800 Å(2) in accord with our design objectives, and that the D-protein antagonist binds to the same region of VEGF-A that interacts with VEGFR1-domain 2.

Definition and characterization of a "trypsinosome" from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures.

PubMed

Le Bihan, Thierry; Robinson, Mark D; Stewart, Ian I; Figeys, Daniel

2004-01-01

Although HPLC-ESI-MS/MS is rapidly becoming an indispensable tool for the analysis of peptides in complex mixtures, the sequence coverage it affords is often quite poor. Low protein expression resulting in peptide signal intensities that fall below the limit of detection of the MS system in combination with differences in peptide ionization efficiency plays a significant role in this. A second important factor stems from differences in physicochemical properties of each peptide and how these properties relate to chromatographic retention and ultimate detection. To identify and understand those properties, we compared data from experimentally identified peptides with data from peptides predicted by in silico digest of all corresponding proteins in the experimental set. Three different complex protein mixtures extracted were used to define a training set to evaluate the amino acid retention coefficients based on linear regression analysis. The retention coefficients were also compared with other previous hydrophobic and retention scale. From this, we have constructed an empirical model that can be readily used to predict peptides that are likely to be observed on our HPLC-ESI-MS/MS system based on their physicochemical properties. Finally, we demonstrated that in silico prediction of peptides and their retention coefficients can be used to generate an inclusion list for a targeted mass spectrometric identification of low abundance proteins in complex protein samples. This approach is based on experimentally derived data to calibrate the method and therefore may theoretically be applied to any HPLC-MS/MS system on which data are being generated.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

The emergence of top-down proteomics in clinical research

PubMed Central

2013-01-01

Proteomic technology has advanced steadily since the development of 'soft-ionization' techniques for mass-spectrometry-based molecular identification more than two decades ago. Now, the large-scale analysis of proteins (proteomics) is a mainstay of biological research and clinical translation, with researchers seeking molecular diagnostics, as well as protein-based markers for personalized medicine. Proteomic strategies using the protease trypsin (known as bottom-up proteomics) were the first to be developed and optimized and form the dominant approach at present. However, researchers are now beginning to understand the limitations of bottom-up techniques, namely the inability to characterize and quantify intact protein molecules from a complex mixture of digested peptides. To overcome these limitations, several laboratories are taking a whole-protein-based approach, in which intact protein molecules are the analytical targets for characterization and quantification. We discuss these top-down techniques and how they have been applied to clinical research and are likely to be applied in the near future. Given the recent improvements in mass-spectrometry-based proteomics and stronger cooperation between researchers, clinicians and statisticians, both peptide-based (bottom-up) strategies and whole-protein-based (top-down) strategies are set to complement each other and help researchers and clinicians better understand and detect complex disease phenotypes. PMID:23806018

Visualizing ligand molecules in Twilight electron density.

PubMed

Weichenberger, Christian X; Pozharski, Edwin; Rupp, Bernhard

2013-02-01

Three-dimensional models of protein structures determined by X-ray crystallography are based on the interpretation of experimentally derived electron-density maps. The real-space correlation coefficient (RSCC) provides an easily comprehensible, objective measure of the residue-based fit of atom coordinates to electron density. Among protein structure models, protein-ligand complexes are of special interest, given their contribution to understanding the molecular underpinnings of biological activity and to drug design. For consumers of such models, it is not trivial to determine the degree to which ligand-structure modelling is biased by subjective electron-density interpretation. A standalone script, Twilight, is presented for the analysis, visualization and annotation of a pre-filtered set of 2815 protein-ligand complexes deposited with the PDB as of 15 January 2012 with ligand RSCC values that are below a threshold of 0.6. It also provides simplified access to the visualization of any protein-ligand complex available from the PDB and annotated by the Uppsala Electron Density Server. The script runs on various platforms and is available for download at http://www.ruppweb.org/twilight/.

Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone

PubMed Central

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-01-01

Protein–protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein–protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein–protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein–protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach. PMID:27965389

Macroscopic modeling and simulations of supercoiled DNA with bound proteins

NASA Astrophysics Data System (ADS)

Huang, Jing; Schlick, Tamar

2002-11-01

General methods are presented for modeling and simulating DNA molecules with bound proteins on the macromolecular level. These new approaches are motivated by the need for accurate and affordable methods to simulate slow processes (on the millisecond time scale) in DNA/protein systems, such as the large-scale motions involved in the Hin-mediated inversion process. Our approaches, based on the wormlike chain model of long DNA molecules, introduce inhomogeneous potentials for DNA/protein complexes based on available atomic-level structures. Electrostatically, treat those DNA/protein complexes as sets of effective charges, optimized by our discrete surface charge optimization package, in which the charges are distributed on an excluded-volume surface that represents the macromolecular complex. We also introduce directional bending potentials as well as non-identical bead hydrodynamics algorithm to further mimic the inhomogeneous effects caused by protein binding. These models thus account for basic elements of protein binding effects on DNA local structure but remain computational tractable. To validate these models and methods, we reproduce various properties measured by both Monte Carlo methods and experiments. We then apply the developed models to study the Hin-mediated inversion system in long DNA. By simulating supercoiled, circular DNA with or without bound proteins, we observe significant effects of protein binding on global conformations and long-time dynamics of the DNA on the kilo basepair length.

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

PubMed Central

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

2016-01-01

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

Forage polyphenol oxidase and ruminant livestock nutrition

PubMed Central

Lee, Michael R. F.

2014-01-01

Polyphenol oxidase (PPO) is predominately associated with the detrimental effect of browning fruit and vegetables, however, interest within PPO containing forage crops (crops to be fed to animals) has grown since the browning reaction was associated with reduced nitrogen (N) losses in silo and the rumen. The reduction in protein breakdown in silo of red clover (high PPO forage) increased the quality of protein, improving N-use efficiency [feed N into product N (e.g., Milk): NUE] when fed to ruminants. A further benefit of red clover silage feeding is a significant reduction in lipolysis (cleaving of glycerol-based lipid) in silo and an increase in the deposition of beneficial C18 polyunsaturated fatty acid (PUFA) in animal products, which has also been linked to PPO activity. PPOs protection of plant protein and glycerol based-PUFA in silo is related to the deactivation of plant proteases and lipases. This deactivation occurs through PPO catalyzing the conversion of diphenols to quinones which bind with cellular nucleophiles such as protein reforming a protein-bound phenol (PBP). If the protein is an enzyme (e.g., protease or lipase) the complexing denatures the enzyme. However, PPO is inactive in the anaerobic rumen and therefore any subsequent protection of plant protein and glycerol based-PUFA in the rumen must be as a result of events that occurred to the forage pre-ingestion. Reduced activity of plant proteases and lipases would have little effect on NUE and glycerol based-PUFA in the rumen due to the greater concentration of rumen microbial proteases and lipases. The mechanism for PPOs protection of plant protein in the rumen is a consequence of complexing plant protein, rather than protease deactivation per se. These complexed proteins reduce protein digestibility in the rumen and subsequently increase undegraded dietary protein flow to the small intestine. The mechanism for protecting glycerol-based PUFA has yet to be fully elucidated but may be associated with entrapment within PBP reducing access to microbial lipases or differences in rumen digestion kinetics of the forage and therefore not related to PPO activity. PMID:25538724

New strategies to inhibit KEAP1 and the Cul3-based E3 ubiquitin ligases

PubMed Central

Canning, Peter; Bullock, Alex N.

2014-01-01

E3 ubiquitin ligases that direct substrate proteins to the ubiquitin–proteasome system are promising, though largely unexplored drug targets both because of their function and their remarkable specificity. CRLs [Cullin–RING (really interesting new gene) ligases] are the largest group of E3 ligases and function as modular multisubunit complexes constructed around a Cullin-family scaffold protein. The Cul3-based CRLs uniquely assemble with BTB (broad complex/tramtrack/bric-à-brac) proteins that also homodimerize and perform the role of both the Cullin adapter and the substrate-recognition component of the E3. The most prominent member is the BTB–BACK (BTB and C-terminal Kelch)–Kelch protein KEAP1 (Kelch-like ECH-associated protein 1), a master regulator of the oxidative stress response and a potential drug target for common conditions such as diabetes, Alzheimer's disease and Parkinson's disease. Structural characterization of BTB–Cul3 complexes has revealed a number of critical assembly mechanisms, including the binding of an N-terminal Cullin extension to a bihelical ‘3-box’ at the C-terminus of the BTB domain. Improved understanding of the structure of these complexes should contribute significantly to the effort to develop novel therapeutics targeted to CRL3-regulated pathways. PMID:24450635

Identification of continuous interaction sites in PLA(2)-based protein complexes by peptide arrays.

PubMed

Fortes-Dias, Consuelo Latorre; Santos, Roberta Márcia Marques dos; Magro, Angelo José; Fontes, Marcos Roberto de Mattos; Chávez-Olórtegui, Carlos; Granier, Claude

2009-01-01

Crotoxin (CA.CB) is a beta-neurotoxin from Crotalus durissus terrificus snake venom that is responsible for main envenomation effects upon biting by this snake. It is a heterodimer of an acidic protein (CA) devoid of any biological activity per se and a basic, enzymatically active, PLA(2) counterpart (CB). Both lethal and enzymatic activities of crotoxin have been shown to be inhibited by CNF, a protein from the blood of C. d. terrificus snakes. CNF replaces CA in the CA.CB complex, forming a stable, non-toxic complex CNF.CB. The molecular sites involved in the tight interfacial protein-protein interactions in these PLA(2)-based complexes have not been clearly determined. To help address this question, we used the peptide arrays approach to map possible interfacial interaction sites in CA.CB and CNF.CB. Amino acid stretches putatively involved in these interactions were firstly identified in the primary structure of CB. Further analysis of the interfacial availability of these stretches in the presumed biologically active structure of CB, suggested two interaction main sites, located at the amino-terminus and beta-wing regions. Peptide segments at the carboxyl-terminus of CB were also suggested to play a secondary role in the binding of both CA and CNF.

Structure of homeodomain-leucine zipper/DNA complexes studied using hydroxyl radical cleavage of DNA and methylation interference.

PubMed

Tron, Adriana E; Comelli, Raúl N; Gonzalez, Daniel H

2005-12-27

Homeodomain-leucine zipper (HD-Zip) proteins, unlike most homeodomain proteins, bind a pseudopalindromic DNA sequence as dimers. We have investigated the structure of the DNA complexes formed by two HD-Zip proteins with different nucleotide preferences at the central position of the binding site using footprinting and interference methods. The results indicate that the respective complexes are not symmetric, with the strand bearing a central purine (top strand) showing higher protection around the central region and the bottom strand protected toward the 3' end. Binding to a sequence with a nonpreferred central base pair produces a decrease in protection in either the top or the bottom strand, depending upon the protein. Modeling studies derived from the complex formed by the monomeric Antennapedia homeodomain with DNA indicate that in the HD-Zip/DNA complex the recognition helix of one of the monomers is displaced within the major groove respective to the other one. This monomer seems to lose contacts with a part of the recognition sequence upon binding to the nonpreferred site. The results show that the structure of the complex formed by HD-Zip proteins with DNA is dependent upon both protein intrinsic characteristics and the nucleotides present at the central position of the recognition sequence.

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Slow histidine H/D exchange protocol for thermodynamic analysis of protein folding and stability using mass spectrometry.

PubMed

Tran, Duc T; Banerjee, Sambuddha; Alayash, Abdu I; Crumbliss, Alvin L; Fitzgerald, Michael C

2012-02-07

Described here is a mass spectrometry-based protocol to study the thermodynamic stability of proteins and protein-ligand complexes using the chemical denaturant dependence of the slow H/D exchange reaction of the imidazole C(2) proton in histidine side chains. The protocol is developed using several model protein systems including: ribonuclease (Rnase) A, myoglobin, bovine carbonic anhydrase (BCA) II, hemoglobin (Hb), and the hemoglobin-haptoglobin (Hb-Hp) protein complex. Folding free energies consistent with those previously determined by other more conventional techniques were obtained for the two-state folding proteins, Rnase A and myoglobin. The protocol successfully detected a previously observed partially unfolded intermediate stabilized in the BCA II folding/unfolding reaction, and it could be used to generate a K(d) value of 0.24 nM for the Hb-Hp complex. The compatibility of the protocol with conventional mass spectrometry-based proteomic sample preparation and analysis methods was also demonstrated in an experiment in which the protocol was used to detect the binding of zinc to superoxide dismutase in the yeast cell lysate sample. The yeast cell sample analyses also helped define the scope of the technique, which requires the presence of globally protected histidine residues in a protein's three-dimensional structure for successful application. © 2011 American Chemical Society

F2Dock: Fast Fourier Protein-Protein Docking

PubMed Central

Bajaj, Chandrajit; Chowdhury, Rezaul; Siddavanahalli, Vinay

2009-01-01

The functions of proteins is often realized through their mutual interactions. Determining a relative transformation for a pair of proteins and their conformations which form a stable complex, reproducible in nature, is known as docking. It is an important step in drug design, structure determination and understanding function and structure relationships. In this paper we extend our non-uniform fast Fourier transform docking algorithm to include an adaptive search phase (both translational and rotational) and thereby speed up its execution. We have also implemented a multithreaded version of the adaptive docking algorithm for even faster execution on multicore machines. We call this protein-protein docking code F2Dock (F2 = Fast Fourier). We have calibrated F2Dock based on an extensive experimental study on a list of benchmark complexes and conclude that F2Dock works very well in practice. Though all docking results reported in this paper use shape complementarity and Coulombic potential based scores only, F2Dock is structured to incorporate Lennard-Jones potential and re-ranking docking solutions based on desolvation energy. PMID:21071796

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

PubMed

Fiorucci, Sébastien; Zacharias, Martin

2010-05-19

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

Live Cell Visualization of Multiple Protein-Protein Interactions with BiFC Rainbow.

PubMed

Wang, Sheng; Ding, Miao; Xue, Boxin; Hou, Yingping; Sun, Yujie

2018-05-18

As one of the most powerful tools to visualize PPIs in living cells, bimolecular fluorescence complementation (BiFC) has gained great advancement during recent years, including deep tissue imaging with far-red or near-infrared fluorescent proteins or super-resolution imaging with photochromic fluorescent proteins. However, little progress has been made toward simultaneous detection and visualization of multiple PPIs in the same cell, mainly due to the spectral crosstalk. In this report, we developed novel BiFC assays based on large-Stokes-shift fluorescent proteins (LSS-FPs) to detect and visualize multiple PPIs in living cells. With the large excitation/emission spectral separation, LSS-FPs can be imaged together with normal Stokes shift fluorescent proteins to realize multicolor BiFC imaging using a simple illumination scheme. We also further demonstrated BiFC rainbow combining newly developed BiFC assays with previously established mCerulean/mVenus-based BiFC assays to achieve detection and visualization of four PPI pairs in the same cell. Additionally, we prove that with the complete spectral separation of mT-Sapphire and CyOFP1, LSS-FP-based BiFC assays can be readily combined with intensity-based FRET measurement to detect ternary protein complex formation with minimal spectral crosstalk. Thus, our newly developed LSS-FP-based BiFC assays not only expand the fluorescent protein toolbox available for BiFC but also facilitate the detection and visualization of multiple protein complex interactions in living cells.

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

PubMed Central

Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

2017-01-01

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

Investigating the binding behaviour of two avidin-based testosterone binders using molecular recognition force spectroscopy.

PubMed

Rangl, Martina; Leitner, Michael; Riihimäki, Tiina; Lehtonen, Soili; Hytönen, Vesa P; Gruber, Hermann J; Kulomaa, Markku; Hinterdorfer, Peter; Ebner, Andreas

2014-02-01

Molecular recognition force spectroscopy, a biosensing atomic force microscopy technique allows to characterise the dissociation of ligand-receptor complexes at the molecular level. Here, we used molecular recognition force spectroscopy to study the binding capability of recently developed testosterone binders. The two avidin-based proteins called sbAvd-1 and sbAvd-2 are expected to bind both testosterone and biotin but differ in their binding behaviour towards these ligands. To explore the ligand binding and dissociation energy landscape of these proteins, we tethered biotin or testosterone to the atomic force microscopy probe while the testosterone-binding protein was immobilized on the surface. Repeated formation and rupture of the ligand-receptor complex at different pulling velocities allowed determination of the loading rate dependence of the complex-rupturing force. In this way, we obtained the molecular dissociation rate (k(off)) and energy landscape distances (x(β)) of the four possible complexes: sbAvd-1-biotin, sbAvd-1-testosterone, sbAvd-2-biotin and sbAvd-2-testosterone. It was found that the kinetic off-rates for both proteins and both ligands are similar. In contrast, the x(β) values, as well as the probability of complex formations, varied considerably. In addition, competitive binding experiments with biotin and testosterone in solution differ significantly for the two testosterone-binding proteins, implying a decreased cross-reactivity of sbAvd-2. Unravelling the binding behaviour of the investigated testosterone-binding proteins is expected to improve their usability for possible sensing applications. Copyright © 2014 John Wiley & Sons, Ltd.

Probing the modulated formation of gold nanoparticles-beta-lactoglobulin corona complexes and their applications.

PubMed

Yang, Jiang; Wang, Bo; You, Youngsang; Chang, Woo-Jin; Tang, Ke; Wang, Yi-Cheng; Zhang, Wenzhao; Ding, Feng; Gunasekaran, Sundaram

2017-11-23

Understanding the interactions between proteins and nanoparticles (NPs) along with the underlying structural and dynamic information is of utmost importance to exploit nanotechnology for biomedical applications. Upon adsorption onto a NP surface, proteins form a well-organized layer, termed the corona, that dictates the identity of the NP-protein complex and governs its biological pathways. Given its high biological relevance, in-depth molecular investigations and applications of NPs-protein corona complexes are still scarce, especially since different proteins form unique corona patterns, making identification of the biomolecular motifs at the interface critical. In this work, we provide molecular insights and structural characterizations of the bio-nano interface of a popular food-based protein, namely bovine beta-lactoglobulin (β-LG), with gold nanoparticles (AuNPs) and report on our investigations of the formation of corona complexes by combined molecular simulations and complementary experiments. Two major binding sites in β-LG were identified as being driven by citrate-mediated electrostatic interactions, while the associated binding kinetics and conformational changes in the secondary structures were also characterized. More importantly, the superior stability of the corona led us to further explore its biomedical applications, such as in the smartphone-based point-of-care biosensing of Escherichia coli (E. coli) and in the computed tomography (CT) of the gastrointestinal (GI) tract through oral administration to probe GI tolerance and functions. Considering their biocompatibility, edible nature, and efficient excretion through defecation, AuNPs-β-LG corona complexes have shown promising perspectives for future in vitro and in vivo clinical settings.

Exploring the Molecular Design of Protein Interaction Sites with Molecular Dynamics Simulations and Free Energy Calculations†

PubMed Central

Liang, Shide; Li, Liwei; Hsu, Wei-Lun; Pilcher, Meaghan N.; Uversky, Vladimir; Zhou, Yaoqi; Dunker, A. Keith; Meroueh, Samy O.

2009-01-01

The significant work that has been invested toward understanding protein–protein interaction has not translated into significant advances in structure-based predictions. In particular redesigning protein surfaces to bind to unrelated receptors remains a challenge, partly due to receptor flexibility, which is often neglected in these efforts. In this work, we computationally graft the binding epitope of various small proteins obtained from the RCSB database to bind to barnase, lysozyme, and trypsin using a previously derived and validated algorithm. In an effort to probe the protein complexes in a realistic environment, all native and designer complexes were subjected to a total of nearly 400 ns of explicit-solvent molecular dynamics (MD) simulation. The MD data led to an unexpected observation: some of the designer complexes were highly unstable and decomposed during the trajectories. In contrast, the native and a number of designer complexes remained consistently stable. The unstable conformers provided us with a unique opportunity to define the structural and energetic factors that lead to unproductive protein–protein complexes. To that end we used free energy calculations following the MM-PBSA approach to determine the role of nonpolar effects, electrostatics and entropy in binding. Remarkably, we found that a majority of unstable complexes exhibited more favorable electrostatics than native or stable designer complexes, suggesting that favorable electrostatic interactions are not prerequisite for complex formation between proteins. However, nonpolar effects remained consistently more favorable in native and stable designer complexes reinforcing the importance of hydrophobic effects in protein–protein binding. While entropy systematically opposed binding in all cases, there was no observed trend in the entropy difference between native and designer complexes. A series of alanine scanning mutations of hot-spot residues at the interface of native and designer complexes showed less than optimal contacts of hot-spot residues with their surroundings in the unstable conformers, resulting in more favorable entropy for these complexes. Finally, disorder predictions revealed that secondary structures at the interface of unstable complexes exhibited greater disorder than the stable complexes. PMID:19113835

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

Comparative Evaluation of Recombinant Protein Production in Different Biofactories: The Green Perspective

PubMed Central

Capaldi, Stefano

2014-01-01

In recent years, the production of recombinant pharmaceutical proteins in heterologous systems has increased significantly. Most applications involve complex proteins and glycoproteins that are difficult to produce, thus promoting the development and improvement of a wide range of production platforms. No individual system is optimal for the production of all recombinant proteins, so the diversity of platforms based on plants offers a significant advantage. Here, we discuss the production of four recombinant pharmaceutical proteins using different platforms, highlighting from these examples the unique advantages of plant-based systems over traditional fermenter-based expression platforms. PMID:24745008

Chemical synthesis and X-ray structure of a heterochiral {D-protein antagonist plus vascular endothelial growth factor} protein complex by racemic crystallography

PubMed Central

Mandal, Kalyaneswar; Uppalapati, Maruti; Ault-Riché, Dana; Kenney, John; Lowitz, Joshua; Sidhu, Sachdev S.; Kent, Stephen B.H.

2012-01-01

Total chemical synthesis was used to prepare the mirror image (D-protein) form of the angiogenic protein vascular endothelial growth factor (VEGF-A). Phage display against D-VEGF-A was used to screen designed libraries based on a unique small protein scaffold in order to identify a high affinity ligand. Chemically synthesized D- and L- forms of the protein ligand showed reciprocal chiral specificity in surface plasmon resonance binding experiments: The L-protein ligand bound only to D-VEGF-A, whereas the D-protein ligand bound only to L-VEGF-A. The D-protein ligand, but not the L-protein ligand, inhibited the binding of natural VEGF165 to the VEGFR1 receptor. Racemic protein crystallography was used to determine the high resolution X-ray structure of the heterochiral complex consisting of {D-protein antagonist + L-protein form ofVEGF-A}. Crystallization of a racemic mixture of these synthetic proteins in appropriate stoichiometry gave a racemic protein complex of more than 73 kDa containing six synthetic protein molecules. The structure of the complex was determined to a resolution of 1.6 Å. Detailed analysis of the interaction between the D-protein antagonist and the VEGF-A protein molecule showed that the binding interface comprised a contact surface area of approximately 800 Å2 in accord with our design objectives, and that the D-protein antagonist binds to the same region of VEGF-A that interacts with VEGFR1-domain 2. PMID:22927390

MURC/Cavin-4 and cavin family members form tissue-specific caveolar complexes.

PubMed

Bastiani, Michele; Liu, Libin; Hill, Michelle M; Jedrychowski, Mark P; Nixon, Susan J; Lo, Harriet P; Abankwa, Daniel; Luetterforst, Robert; Fernandez-Rojo, Manuel; Breen, Michael R; Gygi, Steven P; Vinten, Jorgen; Walser, Piers J; North, Kathryn N; Hancock, John F; Pilch, Paul F; Parton, Robert G

2009-06-29

Polymerase I and transcript release factor (PTRF)/Cavin is a cytoplasmic protein whose expression is obligatory for caveola formation. Using biochemistry and fluorescence resonance energy transfer-based approaches, we now show that a family of related proteins, PTRF/Cavin-1, serum deprivation response (SDR)/Cavin-2, SDR-related gene product that binds to C kinase (SRBC)/Cavin-3, and muscle-restricted coiled-coil protein (MURC)/Cavin-4, forms a multiprotein complex that associates with caveolae. This complex can constitutively assemble in the cytosol and associate with caveolin at plasma membrane caveolae. Cavin-1, but not other cavins, can induce caveola formation in a heterologous system and is required for the recruitment of the cavin complex to caveolae. The tissue-restricted expression of cavins suggests that caveolae may perform tissue-specific functions regulated by the composition of the cavin complex. Cavin-4 is expressed predominantly in muscle, and its distribution is perturbed in human muscle disease associated with Caveolin-3 dysfunction, identifying Cavin-4 as a novel muscle disease candidate caveolar protein.

Structural interaction fingerprints: a new approach to organizing, mining, analyzing, and designing protein-small molecule complexes.

PubMed

Singh, Juswinder; Deng, Zhan; Narale, Gaurav; Chuaqui, Claudio

2006-01-01

The combination of advances in structure-based drug design efforts in the pharmaceutical industry in parallel with structural genomics initiatives in the public domain has led to an explosion in the number of structures of protein-small molecule complexes structures. This information has critical importance to both the understanding of the structural basis for molecular recognition in biological systems and the design of better drugs. A significant challenge exists in managing this vast amount of data and fully leveraging it. Here, we review our work to develop a simple, fast way to store, organize, mine, and analyze large numbers of protein-small molecule complexes. We illustrate the utility of the approach to the management of inhibitor complexes from the protein kinase family. Finally, we describe our recent efforts in applying this method to the design of target-focused chemical libraries.

Cas5d Protein Processes Pre-crRNA and Assembles into a Cascade-like Interference Complex in Subtype I-C/Dvulg CRISPR-Cas System

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

Nam, Ki Hyun; Haitjema, Charles; Liu, Xueqi

Clustered regularly interspaced short palindromic repeats (CRISPRs), together with an operon of CRISPR-associated (Cas) proteins, form an RNA-based prokaryotic immune system against exogenous genetic elements. Cas5 family proteins are found in several type I CRISPR-Cas systems. Here, we report the molecular function of subtype I-C/Dvulg Cas5d from Bacillus halodurans. We show that Cas5d cleaves pre-crRNA into unit length by recognizing both the hairpin structure and the 3 single stranded sequence in the CRISPR repeat region. Cas5d structure reveals a ferredoxin domain-based architecture and a catalytic triad formed by Y46, K116, and H117 residues. We further show that after pre-crRNA processing,more » Cas5d assembles with crRNA, Csd1, and Csd2 proteins to form a multi-sub-unit interference complex similar to Escherichia coli Cascade (CRISPR-associated complex for antiviral defense) in architecture. Our results suggest that formation of a crRNA-presenting Cascade-like complex is likely a common theme among type I CRISPR subtypes.« less

Design and implementation of bimolecular fluorescence complementation (BiFC) assays for the visualization of protein interactions in living cells.

PubMed

Kerppola, Tom K

2006-01-01

Bimolecular fluorescence complementation (BiFC) analysis enables direct visualization of protein interactions in living cells. The BiFC assay is based on the discoveries that two non-fluorescent fragments of a fluorescent protein can form a fluorescent complex and that the association of the fragments can be facilitated when they are fused to two proteins that interact with each other. BiFC must be confirmed by parallel analysis of proteins in which the interaction interface has been mutated. It is not necessary for the interaction partners to juxtapose the fragments within a specific distance of each other because they can associate when they are tethered to a complex with flexible linkers. It is also not necessary for the interaction partners to form a complex with a long half-life or a high occupancy since the fragments can associate in a transient complex and un-associated fusion proteins do not interfere with detection of the complex. Many interactions can be visualized when the fusion proteins are expressed at levels comparable to their endogenous counterparts. The BiFC assay has been used for the visualization of interactions between many types of proteins in different subcellular locations and in different cell types and organisms. It is technically straightforward and can be performed using a regular fluorescence microscope and standard molecular biology and cell culture reagents.

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

PubMed

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

2009-04-01

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

Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions†

PubMed Central

Naegle, Kristen M.; White, Forest M.; Lauffenburger, Douglas A.; Yaffe, Michael B.

2012-01-01

Cell signaling networks propagate information from extracellular cues via dynamic modulation of protein–protein interactions in a context-dependent manner. Networks based on receptor tyrosine kinases (RTKs), for example, phosphorylate intracellular proteins in response to extracellular ligands, resulting in dynamic protein–protein interactions that drive phenotypic changes. Most commonly used methods for discovering these protein–protein interactions, however, are optimized for detecting stable, longer-lived complexes, rather than the type of transient interactions that are essential components of dynamic signaling networks such as those mediated by RTKs. Substrate phosphorylation downstream of RTK activation modifies substrate activity and induces phospho-specific binding interactions, resulting in the formation of large transient macromolecular signaling complexes. Since protein complex formation should follow the trajectory of events that drive it, we reasoned that mining phosphoproteomic datasets for highly similar dynamic behavior of measured phosphorylation sites on different proteins could be used to predict novel, transient protein–protein interactions that had not been previously identified. We applied this method to explore signaling events downstream of EGFR stimulation. Our computational analysis of robustly co-regulated phosphorylation sites, based on multiple clustering analysis of quantitative time-resolved mass-spectrometry phosphoproteomic data, not only identified known sitewise-specific recruitment of proteins to EGFR, but also predicted novel, a priori interactions. A particularly intriguing prediction of EGFR interaction with the cytoskeleton-associated protein PDLIM1 was verified within cells using co-immunoprecipitation and in situ proximity ligation assays. Our approach thus offers a new way to discover protein–protein interactions in a dynamic context- and phosphorylation site-specific manner. PMID:22851037

Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry.

PubMed

Planatscher, Hannes; Supper, Jochen; Poetz, Oliver; Stoll, Dieter; Joos, Thomas; Templin, Markus F; Zell, Andreas

2010-06-25

Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency. We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties. For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics.

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

Creating Knock-outs of Conserved Oligomeric Golgi complex subunits using CRISPR-mediated gene editing paired with a selection strategy based on glycosylation defects associated with impaired COG complex function

PubMed Central

Blackburn, Jessica Bailey; Lupashin, Vladimir V.

2017-01-01

Summary The Conserved Oligomeric Golgi (COG) complex is a key evolutionally conserved multisubunit protein machinery that regulates tethering and fusion of intra-Golgi transport vesicles. The Golgi apparatus specifically promotes sorting and complex glycosylation of glycoconjugates. Without proper glycosylation and processing, proteins and lipids will be mislocalized and/or have impaired function. The Golgi glycosylation machinery is kept in homeostasis by a careful balance of anterograde and retrograde trafficking to ensure proper localization of the glycosylation enzymes and their substrates. This balance, like other steps of membrane trafficking, is maintained by vesicle trafficking machinery that includes COPI vesicular coat proteins, SNAREs, Rabs, and both coiled-coil and multi-subunit vesicular tethers. COG complex interacts with other membrane trafficking components and is essential for proper localization of Golgi glycosylation machinery. Here we describe using CRISPR-mediated gene editing coupled with a phenotype-based selection strategy directly linked to the COG complex’s role in glycosylation homeostasis to obtain COG complex subunit knock-outs (KOs). This has resulted in clonal KOs for each COG subunit in HEK293T cells and gives the ability to further probe the role of the COG complex in Golgi homeostasis. PMID:27632008

Deoxycholate-Based Glycosides (DCGs) for Membrane Protein Stabilisation.

PubMed

Bae, Hyoung Eun; Gotfryd, Kamil; Thomas, Jennifer; Hussain, Hazrat; Ehsan, Muhammad; Go, Juyeon; Loland, Claus J; Byrne, Bernadette; Chae, Pil Seok

2015-07-06

Detergents are an absolute requirement for studying the structure of membrane proteins. However, many conventional detergents fail to stabilise denaturation-sensitive membrane proteins, such as eukaryotic proteins and membrane protein complexes. New amphipathic agents with enhanced efficacy in stabilising membrane proteins will be helpful in overcoming the barriers to studying membrane protein structures. We have prepared a number of deoxycholate-based amphiphiles with carbohydrate head groups, designated deoxycholate-based glycosides (DCGs). These DCGs are the hydrophilic variants of previously reported deoxycholate-based N-oxides (DCAOs). Membrane proteins in these agents, particularly the branched diglucoside-bearing amphiphiles DCG-1 and DCG-2, displayed favourable behaviour compared to previously reported parent compounds (DCAOs) and conventional detergents (LDAO and DDM). Given their excellent properties, these agents should have significant potential for membrane protein studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping mechanical force propagation through biomolecular complexes

DOE PAGES

Schoeler, Constantin; Bernardi, Rafael C.; Malinowska, Klara H.; ...

2015-08-11

In this paper, we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. Finally, the results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.

Dramatically stabilizing multiprotein complex structure in the absence of bulk water using tuned Hofmeister salts.

PubMed

Han, Linjie; Hyung, Suk-Joon; Ruotolo, Brandon T

2013-01-01

The role that water plays in the salt-based stabilization of proteins is central to our understanding of protein biophysics. Ion hydration and the ability of ions to alter water surface tension are typically invoked, along with direct ion-protein binding, to describe Hofmeister stabilization phenomena observed for proteins experimentally, but the relative influence of these forces has been extraordinarily difficult to measure directly. Recently, we have used gas-phase measurements of proteins and large multiprotein complexes, using a combination of innovative ion mobility (IM) and mass spectrometry (MS) techniques, to assess the ability of bound cations and anions to stabilize protein ions in the absence of the solvation forces described above. Our previous work has studied a broad set of 12 anions bound to a range of proteins and protein complexes, and while primarily motivated by the analytical challenges surrounding the gas-phase measurement of solution-phase relevant protein structures, our work has also lead to a detailed physical mechanism of anion-protein complex stabilization in the absence of bulk solvent. Our more-recent work has screened a similarly-broad set of cations for their ability to stabilize gas-phase protein structure, and we have discovered surprising differences between the operative mechanisms for cations and anions in gas-phase protein stabilization. In both cases, cations and anions affect protein stabilization in the absence of solvent in a manner that is generally reversed relative to their ability to stabilize the same proteins in solution. In addition, our evidence suggests that the relative solution-phase binding affinity of the anions and cations studied here is preserved in our gas-phase measurements, allowing us to study the influence of such interactions in detail. In this report, we collect and summarize such gas-phase measurements to distill a generalized picture of salt-based protein stabilization in the absence of bulk water. Further, we communicate our most recent efforts to study the combined effects of stabilizing cations and anions on gas-phase proteins, and identify those salts that bear anion/cation pairs having the strongest stabilizing influence on protein structures

Study of base pair mutations in proline-rich homeodomain (PRH)-DNA complexes using molecular dynamics.

PubMed

Jalili, Seifollah; Karami, Leila; Schofield, Jeremy

2013-06-01

Proline-rich homeodomain (PRH) is a regulatory protein controlling transcription and gene expression processes by binding to the specific sequence of DNA, especially to the sequence 5'-TAATNN-3'. The impact of base pair mutations on the binding between the PRH protein and DNA is investigated using molecular dynamics and free energy simulations to identify DNA sequences that form stable complexes with PRH. Three 20-ns molecular dynamics simulations (PRH-TAATTG, PRH-TAATTA and PRH-TAATGG complexes) in explicit solvent water were performed to investigate three complexes structurally. Structural analysis shows that the native TAATTG sequence forms a complex that is more stable than complexes with base pair mutations. It is also observed that upon mutation, the number and occupancy of the direct and water-mediated hydrogen bonds decrease. Free energy calculations performed with the thermodynamic integration method predict relative binding free energies of 0.64 and 2 kcal/mol for GC to AT and TA to GC mutations, respectively, suggesting that among the three DNA sequences, the PRH-TAATTG complex is more stable than the two mutated complexes. In addition, it is demonstrated that the stability of the PRH-TAATTA complex is greater than that of the PRH-TAATGG complex.

Mathematics, Thermodynamics, and Modeling to Address Ten Common Misconceptions about Protein Structure, Folding, and Stability

ERIC Educational Resources Information Center

Robic, Srebrenka

2010-01-01

To fully understand the roles proteins play in cellular processes, students need to grasp complex ideas about protein structure, folding, and stability. Our current understanding of these topics is based on mathematical models and experimental data. However, protein structure, folding, and stability are often introduced as descriptive, qualitative…

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

PubMed

Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

Developing a Multiplexed Quantitative Cross-Linking Mass Spectrometry Platform for Comparative Structural Analysis of Protein Complexes.

PubMed

Yu, Clinton; Huszagh, Alexander; Viner, Rosa; Novitsky, Eric J; Rychnovsky, Scott D; Huang, Lan

2016-10-18

Cross-linking mass spectrometry (XL-MS) represents a recently popularized hybrid methodology for defining protein-protein interactions (PPIs) and analyzing structures of large protein assemblies. In particular, XL-MS strategies have been demonstrated to be effective in elucidating molecular details of PPIs at the peptide resolution, providing a complementary set of structural data that can be utilized to refine existing complex structures or direct de novo modeling of unknown protein structures. To study structural and interaction dynamics of protein complexes, quantitative cross-linking mass spectrometry (QXL-MS) strategies based on isotope-labeled cross-linkers have been developed. Although successful, these approaches are mostly limited to pairwise comparisons. In order to establish a robust workflow enabling comparative analysis of multiple cross-linked samples simultaneously, we have developed a multiplexed QXL-MS strategy, namely, QMIX (Quantitation of Multiplexed, Isobaric-labeled cross (X)-linked peptides) by integrating MS-cleavable cross-linkers with isobaric labeling reagents. This study has established a new analytical platform for quantitative analysis of cross-linked peptides, which can be directly applied for multiplexed comparisons of the conformational dynamics of protein complexes and PPIs at the proteome scale in future studies.

Dual Role of Protein Phosphorylation in DNA Activator/Coactivator Binding

PubMed Central

Dadarlat, Voichita M.; Skeel, Robert D.

2011-01-01

Binding free energies are calculated for the phosphorylated and unphosphorylated complexes between the kinase inducible domain (KID) of the DNA transcriptional activator cAMP response element binding (CREB) protein and the KIX domain of its coactivator, CREB-binding protein (CBP). To our knowledge, this is the first application of a method based on a potential of mean force (PMF) with restraining potentials to compute the binding free energy of protein-protein complexes. The KID:KIX complexes are chosen here because of their biological relevance to the DNA transcription process and their relatively small size (81 residues for the KIX domain of CBP, and 28 residues for KID). The results for pKID:KIX and KID:KIX are −9.55 and −4.96 kcal/mol, respectively, in good agreement with experimental estimates (−8.8 and −5.8 kcal/mol, respectively). A comparison between specific contributions to protein-protein binding for the phosphorylated and unphosphorylated complexes reveals a dual role for the phosphorylation of KID at Ser-133 in effecting a more favorable free energy of the bound system: 1), stabilization of the unbound conformation of phosphorylated KID due to favorable intramolecular interactions of the phosphate group of Ser-133 with the charged groups of an arginine-rich region spanning both α-helices, which lowers the configurational entropy; and 2), more favorable intermolecular electrostatic interactions between pSer-133 and Arg-131 of KID, and Lys-662, Tyr-658, and Glu-666 of KIX. Charge reduction through ligand phosphorylation emerges as a possible mechanism for controlling the unbound state conformation of KID and, ultimately, gene expression. This work also demonstrates that the PMF-based method with restraining potentials provides an added benefit in that important elements of the binding pathway are evidenced. Furthermore, the practicality of the PMF-based method for larger systems is validated by agreement with experiment. In addition, we provide a somewhat differently structured exposition of the PMF-based method with restraining potentials and outline its generalization to systems in which both protein and ligand may adopt unbound conformations that are different from those of the bound state. PMID:21244843

New insights into potential functions for the protein 4.1superfamily of proteins in kidney epithelium

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

Calinisan, Venice; Gravem, Dana; Chen, Ray Ping-Hsu

2005-06-17

Members of the protein 4.1 family of adapter proteins are expressed in a broad panel of tissues including various epithelia where they likely play an important role in maintenance of cell architecture and polarity and in control of cell proliferation. We have recently characterized the structure and distribution of three members of the protein 4.1 family, 4.1B, 4.1R and 4.1N, in mouse kidney. We describe here binding partners for renal 4.1 proteins, identified through the screening of a rat kidney yeast two-hybrid system cDNA library. The identification of putative protein 4.1-based complexes enables us to envision potential functions for 4.1more » proteins in kidney: organization of signaling complexes, response to osmotic stress, protein trafficking, and control of cell proliferation. We discuss the relevance of these protein 4.1-based interactions in kidney physio-pathology in the context of their previously identified functions in other cells and tissues. Specifically, we will focus on renal 4.1 protein interactions with beta amyloid precursor protein (beta-APP), 14-3-3 proteins, and the cell swelling-activated chloride channel pICln. We also discuss the functional relevance of another member of the protein 4.1 superfamily, ezrin, in kidney physiopathology.« less

Detection of in situ protein-protein complexes at the Drosophila larval neuromuscular junction using proximity ligation assay.

PubMed

Wang, Simon; Yoo, SooHyun; Kim, Hae-Yoon; Wang, Mannan; Zheng, Clare; Parkhouse, Wade; Krieger, Charles; Harden, Nicholas

2015-01-20

Discs large (Dlg) is a conserved member of the membrane-associated guanylate kinase family, and serves as a major scaffolding protein at the larval neuromuscular junction (NMJ) in Drosophila. Previous studies have shown that the postsynaptic distribution of Dlg at the larval NMJ overlaps with that of Hu-li tai shao (Hts), a homologue to the mammalian adducins. In addition, Dlg and Hts are observed to form a complex with each other based on co-immunoprecipitation experiments involving whole adult fly lysates. Due to the nature of these experiments, however, it was unknown whether this complex exists specifically at the NMJ during larval development. Proximity Ligation Assay (PLA) is a recently developed technique used mostly in cell and tissue culture that can detect protein-protein interactions in situ. In this assay, samples are incubated with primary antibodies against the two proteins of interest using standard immunohistochemical procedures. The primary antibodies are then detected with a specially designed pair of oligonucleotide-conjugated secondary antibodies, termed PLA probes, which can be used to generate a signal only when the two probes have bound in close proximity to each other. Thus, proteins that are in a complex can be visualized. Here, it is demonstrated how PLA can be used to detect in situ protein-protein interactions at the Drosophila larval NMJ. The technique is performed on larval body wall muscle preparations to show that a complex between Dlg and Hts does indeed exist at the postsynaptic region of NMJs.

Painting proteins with covalent labels: what's in the picture?

PubMed

Fitzgerald, Michael C; West, Graham M

2009-06-01

Knowledge about the structural and biophysical properties of proteins when they are free in solution and/or in complexes with other molecules is essential for understanding the biological processes that proteins regulate. Such knowledge is also important to drug discovery efforts, particularly those focused on the development of therapeutic agents with protein targets. In the last decade a variety of different covalent labeling techniques have been used in combination with mass spectrometry to probe the solution-phase structures and biophysical properties of proteins and protein-ligand complexes. Highlighted here are five different mass spectrometry-based covalent labeling strategies including: continuous hydrogen/deuterium (H/D) exchange labeling, hydroxyl radical-mediated footprinting, SUPREX (stability of unpurified proteins from rates of H/D exchange), PLIMSTEX (protein-ligand interaction by mass spectrometry, titration, and H/D exchange), and SPROX (stability of proteins from rates of oxidation). The basic experimental protocols used in each of the above-cited methods are summarized along with the kind of biophysical information they generate. Also discussed are the relative strengths and weaknesses of the different methods for probing the wide range of conformational states that proteins and protein-ligand complexes can adopt when they are in solution.

A Three-Hybrid System to Probe In Vivo Protein-Protein Interactions: Application to the Essential Proteins of the RD1 Complex of M. tuberculosis

PubMed Central

Bhalla, Kuhulika; Ghosh, Anamika; Kumar, Krishan; Kumar, Sushil; Ranganathan, Anand

2011-01-01

Background Protein-protein interactions play a crucial role in enabling a pathogen to survive within a host. In many cases the interactions involve a complex of proteins rather than just two given proteins. This is especially true for pathogens like M. tuberculosis that are able to successfully survive the inhospitable environment of the macrophage. Studying such interactions in detail may help in developing small molecules that either disrupt or augment the interactions. Here, we describe the development of an E. coli based bacterial three-hybrid system that can be used effectively to study ternary protein complexes. Methodology/Principal Findings The protein-protein interactions involved in M. tuberculosis pathogenesis have been used as a model for the validation of the three-hybrid system. Using the M. tuberculosis RD1 encoded proteins CFP10, ESAT6 and Rv3871 for our proof-of-concept studies, we show that the interaction between the proteins CFP10 and Rv3871 is strengthened and stabilized in the presence of ESAT6, the known heterodimeric partner of CFP10. Isolating peptide candidates that can disrupt crucial protein-protein interactions is another application that the system offers. We demonstrate this by using CFP10 protein as a disruptor of a previously established interaction between ESAT6 and a small peptide HCL1; at the same time we also show that CFP10 is not able to disrupt the strong interaction between ESAT6 and another peptide SL3. Conclusions/Significance The validation of the three-hybrid system paves the way for finding new peptides that are stronger binders of ESAT6 compared even to its natural partner CFP10. Additionally, we believe that the system offers an opportunity to study tri-protein complexes and also perform a screening of protein/peptide binders to known interacting proteins so as to elucidate novel tri-protein complexes. PMID:22087330

MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

PubMed Central

2010-01-01

Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw. PMID:20939868

Monolayers of derivatized poly(l-lysine)-grafted poly(ethylene glycol) on metal oxides as a class of biomolecular interfaces

PubMed Central

Ruiz-Taylor, L. A.; Martin, T. L.; Zaugg, F. G.; Witte, K.; Indermuhle, P.; Nock, S.; Wagner, P.

2001-01-01

We report on the design and characterization of a class of biomolecular interfaces based on derivatized poly(l-lysine)-grafted poly(ethylene glycol) copolymers adsorbed on negatively charged surfaces. As a model system, we synthesized biotin-derivatized poly(l-lysine)-grafted poly(ethylene glycol) copolymers, PLL-g-[(PEGm)(1−x) (PEG-biotin)x], where x varies from 0 to 1. Monolayers were produced on titanium dioxide substrates and characterized by x-ray photoelectron spectroscopy. The specific biorecognition properties of these biotinylated surfaces were investigated with the use of radiolabeled streptavidin alone and within complex protein mixtures. The PLL-g-PEG-biotin monolayers specifically capture streptavidin, even from a complex protein mixture, while still preventing nonspecific adsorption of other proteins. This streptavidin layer can subsequently capture biotinylated proteins. Finally, with the use of microfluidic networks and protein arraying, we demonstrate the potential of this class of biomolecular interfaces for applications based on protein patterning. PMID:11158560

Nuclear magnetic resonance-based model of a TF1/HmU-DNA complex.

PubMed

Silva, M V; Pasternack, L B; Kearns, D R

1997-12-15

Transcription factor 1 (TF1), a type II DNA-binding protein encoded by the Bacillus subtilis bacteriophage SPO1, has the capacity for sequence-selective DNA binding and a preference for 5-hydroxymethyl-2'-deoxyuridine (HmU)-containing DNA. In NMR studies of the TF1/HmU-DNA complex, intermolecular NOEs indicate that the flexible beta-ribbon and C-terminal alpha-helix are involved in the DNA-binding site of TF1, placing it in the beta-sheet category of DNA-binding proteins proposed to bind by wrapping two beta-ribbon "arms" around the DNA. Intermolecular and intramolecular NOEs were used to generate an energy-minimized model of the protein-DNA complex in which both DNA bending and protein structure changes are evident.

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins.

PubMed

Akbal-Delibas, Bahar; Haspel, Nurit

2013-01-01

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units. Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures. Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

Recent progress in biopolymer nanoparticle and microparticle formation by heat-treating electrostatic protein-polysaccharide complexes.

PubMed

Jones, Owen G; McClements, David Julian

2011-09-14

Functional biopolymer nanoparticles or microparticles can be formed by heat treatment of globular protein-ionic polysaccharide electrostatic complexes under appropriate solution conditions. These biopolymer particles can be used as encapsulation and delivery systems, fat mimetics, lightening agents, or texture modifiers. This review highlights recent progress in the design and fabrication of biopolymer particles based on heating globular protein-ionic polysaccharide complexes above the thermal denaturation temperature of the proteins. The influence of biopolymer type, protein-polysaccharide ratio, pH, ionic strength, and thermal history on the characteristics of the biopolymer particles formed is reviewed. Our current understanding of the underlying physicochemical mechanisms of particle formation and properties is given. The information provided in this review should facilitate the rational design of biopolymer particles with specific physicochemical and functional attributes, as well as stimulate further research in identifying the physicochemical origin of particle formation. Copyright © 2010 Elsevier B.V. All rights reserved.

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

Horowitz, Scott; Salmon, Loïc; Koldewey, Philipp

We present that challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone–substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a new structural biology approach based on X-ray crystallography, termed residual electron and anomalous density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the Escherichia coli chaperonemore » Spy, and to capture a series of snapshots depicting the various folding states of Im7 bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded to native-like states and reveals how a substrate can explore its folding landscape while being bound to a chaperone.« less

A plant virus movement protein forms ringlike complexes with the major nucleolar protein, fibrillarin, in vitro.

PubMed

Canetta, Elisabetta; Kim, Sang Hyon; Kalinina, Natalia O; Shaw, Jane; Adya, Ashok K; Gillespie, Trudi; Brown, John W S; Taliansky, Michael

2008-02-29

Fibrillarin, one of the major proteins of the nucleolus, has methyltransferase activity directing 2'-O-ribose methylation of rRNA and snRNAs and is required for rRNA processing. The ability of the plant umbravirus, groundnut rosette virus, to move long distances through the phloem, the specialized plant vascular system, has been shown to strictly depend on the interaction of one of its proteins, the ORF3 protein (protein encoded by open reading frame 3), with fibrillarin. This interaction is essential for several stages in the groundnut rosette virus life cycle such as nucleolar import of the ORF3 protein via Cajal bodies, relocalization of some fibrillarin from the nucleolus to cytoplasm, and assembly of cytoplasmic umbraviral ribonucleoprotein particles that are themselves required for the long-distance spread of the virus and systemic infection. Here, using atomic force microscopy, we determine the architecture of these complexes as single-layered ringlike structures with a diameter of 18-22 nm and a height of 2.0+/-0.4 nm, which consist of several (n=6-8) distinct protein granules. We also estimate the molar ratio of fibrillarin to ORF3 protein in the complexes as approximately 1:1. Based on these data, we propose a model of the structural organization of fibrillarin-ORF3 protein complexes and discuss potential mechanistic and functional implications that may also apply to other viruses.

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Evidence for a Posttranscriptional Role of a TFIIICα-like Protein in Chironomus tentans

PubMed Central

Sabri, Nafiseh; Farrants, Ann-Kristin Östlund; Hellman, Ulf; Visa, Neus

2002-01-01

We have cloned and sequenced a cDNA that encodes for a nuclear protein of 238 kDa in the dipteran Chironomus tentans. This protein, that we call p2D10, is structurally similar to the α subunit of the general transcription factor TFIIIC. Using immunoelectron microscopy we have shown that a fraction of p2D10 is located at sites of transcription, which is consistent with a possible role of this protein in transcription initiation. We have also found that a large fraction of p2D10 is located in the nucleoplasm and in the nuclear pore complexes. Using gel filtration chromatography and coimmunoprecipitation methods, we have identified and characterized two p2D10-containing complexes that differ in molecular mass and composition. The heavy p2D10-containing complex contains at least one other component of the TFIIIC complex, TFIIIC-ε. Based on its molecular mass and composition, the heavy p2D10-containing complex may be the Pol III holoenzyme. The light p2D10-containing complex contains RNA together with at least two proteins that are thought to be involved in mRNA trafficking, RAE1 and hrp65. The observations reported here suggest that this new TFIIIC-α-like protein is involved in posttranscriptional steps of premRNA metabolism in Chironomus tentans. PMID:12006668

Probing the role of intercalating protein sidechains for kink formation in DNA

PubMed Central

Sandmann, Achim

2018-01-01

Protein binding can induce DNA kinks, which are for example important to enhance the specificity of the interaction and to facilitate the assembly of multi protein complexes. The respective proteins frequently exhibit amino acid sidechains that intercalate between the DNA base steps at the site of the kink. However, on a molecular level there is only little information available about the role of individual sidechains for kink formation. To unravel structural principles of protein-induced DNA kinking we have performed molecular dynamics (MD) simulations of five complexes that varied in their architecture, function, and identity of intercalated residues. Simulations were performed for the DNA complexes of wildtype proteins (Sac7d, Sox-4, CcpA, TFAM, TBP) and for mutants, in which the intercalating residues were individually or combined replaced by alanine. The work revealed that for systems with multiple intercalated residues, not all of them are necessarily required for kink formation. In some complexes (Sox-4, TBP), one of the residues proved to be essential for kink formation, whereas the second residue has only a very small effect on the magnitude of the kink. In other systems (e.g. Sac7d) each of the intercalated residues proved to be individually capable of conferring a strong kink suggesting a partially redundant role of the intercalating residues. Mutation of the key residues responsible for kinking either resulted in stable complexes with reduced kink angles or caused conformational instability as evidenced by a shift of the kink to an adjacent base step. Thus, MD simulations can help to identify the role of individual inserted residues for kinking, which is not readily apparent from an inspection of the static structures. This information might be helpful for understanding protein-DNA interactions in more detail and for designing proteins with altered DNA binding properties in the future. PMID:29432448

Probing the role of intercalating protein sidechains for kink formation in DNA.

PubMed

Sandmann, Achim; Sticht, Heinrich

2018-01-01

Protein binding can induce DNA kinks, which are for example important to enhance the specificity of the interaction and to facilitate the assembly of multi protein complexes. The respective proteins frequently exhibit amino acid sidechains that intercalate between the DNA base steps at the site of the kink. However, on a molecular level there is only little information available about the role of individual sidechains for kink formation. To unravel structural principles of protein-induced DNA kinking we have performed molecular dynamics (MD) simulations of five complexes that varied in their architecture, function, and identity of intercalated residues. Simulations were performed for the DNA complexes of wildtype proteins (Sac7d, Sox-4, CcpA, TFAM, TBP) and for mutants, in which the intercalating residues were individually or combined replaced by alanine. The work revealed that for systems with multiple intercalated residues, not all of them are necessarily required for kink formation. In some complexes (Sox-4, TBP), one of the residues proved to be essential for kink formation, whereas the second residue has only a very small effect on the magnitude of the kink. In other systems (e.g. Sac7d) each of the intercalated residues proved to be individually capable of conferring a strong kink suggesting a partially redundant role of the intercalating residues. Mutation of the key residues responsible for kinking either resulted in stable complexes with reduced kink angles or caused conformational instability as evidenced by a shift of the kink to an adjacent base step. Thus, MD simulations can help to identify the role of individual inserted residues for kinking, which is not readily apparent from an inspection of the static structures. This information might be helpful for understanding protein-DNA interactions in more detail and for designing proteins with altered DNA binding properties in the future.

Web application for studying the free energy of binding and protonation states of protein-ligand complexes based on HINT

PubMed Central

Bayden, Alexander S.; Fornabaio, Micaela; Scarsdale, J. Neel

2009-01-01

A public web server performing computational titration at the active site in a protein-ligand complex has been implemented. This calculation is based on the Hydropathic INTeraction (HINT) noncovalent force field. From 3D coordinate data for the protein, ligand and bridging waters (if available), the server predicts the best combination of protonation states for each ionizable residue and/or ligand functional group as well as the Gibbs free energy of binding for the ionization-optimized protein-ligand complex. The 3D structure for the modified molecules is available as output. In addition, a graph depicting how this energy changes with acidity, i.e., as a function of added protons, can be obtained. This data may prove to be of use in preparing models for virtual screening and molecular docking. A few illustrative examples are presented. In β secretase (2va7) computational titration flipped the amide groups of Gln12 and Asn37 and protonated a ligand amine yielding an improvement of 6.37 kcal mol−1 in the protein-ligand binding score. Protonation of Glu139 in mutant HIV-1 reverse transcriptase (2opq) allows a water bridge between the protein and inhibitor that increases the protein-ligand interaction score by 0.16 kcal mol−1. In human sialidase NEU2 complexed with an isobutyl ether mimetic inhibitor (2f11) computational titration suggested that protonating Glu218, deprotonating Arg237, flipping the amide bond on Tyr334, and optimizing the positions of several other polar protons would increase the protein-ligand interaction score by 0.71 kcal mol−1. PMID:19554265

The Molybdenum Cofactor Biosynthesis Network: In vivo Protein-Protein Interactions of an Actin Associated Multi-Protein Complex.

PubMed

Kaufholdt, David; Baillie, Christin-Kirsty; Meinen, Rieke; Mendel, Ralf R; Hänsch, Robert

2017-01-01

Survival of plants and nearly all organisms depends on the pterin based molybdenum cofactor (Moco) as well as its effective biosynthesis and insertion into apo-enzymes. To this end, both the central Moco biosynthesis enzymes are characterized and the conserved four-step reaction pathway for Moco biosynthesis is well-understood. However, protection mechanisms to prevent degradation during biosynthesis as well as transfer of the highly oxygen sensitive Moco and its intermediates are not fully enlightened. The formation of protein complexes involving transient protein-protein interactions is an efficient strategy for protected metabolic channelling of sensitive molecules. In this review, Moco biosynthesis and allocation network is presented and discussed. This network was intensively studied based on two in vivo interaction methods: bimolecular fluorescence complementation (BiFC) and split-luciferase. Whereas BiFC allows localisation of interacting partners, split-luciferase assay determines interaction strengths in vivo . Results demonstrate (i) interaction of Cnx2 and Cnx3 within the mitochondria and (ii) assembly of a biosynthesis complex including the cytosolic enzymes Cnx5, Cnx6, Cnx7, and Cnx1, which enables a protected transfer of intermediates. The whole complex is associated with actin filaments via Cnx1 as anchor protein. After biosynthesis, Moco needs to be handed over to the specific apo-enzymes. A potential pathway was discovered. Molybdenum-containing enzymes of the sulphite oxidase family interact directly with Cnx1. In contrast, the xanthine oxidoreductase family acquires Moco indirectly via a Moco binding protein (MoBP2) and Moco sulphurase ABA3. In summary, the uncovered interaction matrix enables an efficient transfer for intermediate and product protection via micro-compartmentation.

3dRPC: a web server for 3D RNA-protein structure prediction.

PubMed

Huang, Yangyu; Li, Haotian; Xiao, Yi

2018-04-01

RNA-protein interactions occur in many biological processes. To understand the mechanism of these interactions one needs to know three-dimensional (3D) structures of RNA-protein complexes. 3dRPC is an algorithm for prediction of 3D RNA-protein complex structures and consists of a docking algorithm RPDOCK and a scoring function 3dRPC-Score. RPDOCK is used to sample possible complex conformations of an RNA and a protein by calculating the geometric and electrostatic complementarities and stacking interactions at the RNA-protein interface according to the features of atom packing of the interface. 3dRPC-Score is a knowledge-based potential that uses the conformations of nucleotide-amino-acid pairs as statistical variables and that is used to choose the near-native complex-conformations obtained from the docking method above. Recently, we built a web server for 3dRPC. The users can easily use 3dRPC without installing it locally. RNA and protein structures in PDB (Protein Data Bank) format are the only needed input files. It can also incorporate the information of interface residues or residue-pairs obtained from experiments or theoretical predictions to improve the prediction. The address of 3dRPC web server is http://biophy.hust.edu.cn/3dRPC. yxiao@hust.edu.cn.

Recruitment of Fanconi Anemia and Breast Cancer Proteins to DNA Damage Sites is differentially Governed by Replication

PubMed Central

Shen, Xi; Do, Huong; Li, Yongjian; Chung, Woo-Hyun; Tomasz, Maria; de Winter, Johan P.; Xia, Bing; Elledge, Stephen J.; Wang, Weidong; Li, Lei

2009-01-01

Summary Fanconi anemia (FA) is characterized by cellular hypersensivity to DNA crosslinking agents, but how the Fanconi pathway protects cells from DNA crosslinks and whether FA proteins act directly on crosslinks remains unclear. We developed a chromatin-IP-based strategy termed eChIP and detected association of multiple FA proteins with DNA crosslinks in vivo. Inter-dependence analyses revealed that crosslink-specific enrichment of various FA proteins is controlled by distinct mechanisms. BRCA-related FA proteins (BRCA2, FANCJ/BACH1, and FANCN/PALB2), but not FA core and I/D2 complexes, require replication for their crosslink association. FANCD2, but not FANCJ and FANCN, requires the FA core complex for its recruitment. FA core complex requires nucleotide excision repair proteins XPA and XPC for its association. Consistent with the distinct recruitment mechanism, recombination-independent crosslink repair was inversely affected in cells deficient of FANC-core versus BRCA-related FA proteins. Thus, FA proteins participate in distinct DNA damage response mechanisms governed by DNA replication status. PMID:19748364

The spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β

PubMed Central

Koag, Myong-Chul; Nam, Kwangho; Lee, Seongmin

2014-01-01

To provide molecular-level insights into the spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β (polβ), we report four crystal structures of polβ complexed with dG•dTTP and dA•dCTP mismatches in the presence of Mg2+ or Mn2+. The Mg2+-bound ground-state structures show that the dA•dCTP-Mg2+ complex adopts an ‘intermediate’ protein conformation while the dG•dTTP-Mg2+ complex adopts an open protein conformation. The Mn2+-bound ‘pre-chemistry-state’ structures show that the dA•dCTP-Mn2+ complex is structurally very similar to the dA•dCTP-Mg2+ complex, whereas the dG•dTTP-Mn2+ complex undergoes a large-scale conformational change to adopt a Watson–Crick-like dG•dTTP base pair and a closed protein conformation. These structural differences, together with our molecular dynamics simulation studies, suggest that polβ increases replication fidelity via a two-stage mismatch discrimination mechanism, where one is in the ground state and the other in the closed conformation state. In the closed conformation state, polβ appears to allow only a Watson–Crick-like conformation for purine•pyrimidine base pairs, thereby discriminating the mismatched base pairs based on their ability to form the Watson–Crick-like conformation. Overall, the present studies provide new insights into the spontaneous replication error and the replication fidelity mechanisms of polβ. PMID:25200079

Synthesis and Evaluation of a Novel Adenosine-Ribose Probe for Global-Scale Profiling of Nucleoside and Nucleotide-Binding Proteins

PubMed Central

Mahajan, Shikha; Manetsch, Roman; Merkler, David J.; Stevens Jr., Stanley M.

2015-01-01

Proteomics is a powerful approach used for investigating the complex molecular mechanisms of disease pathogenesis and progression. An important challenge in modern protein profiling approaches involves targeting of specific protein activities in order to identify altered molecular processes associated with disease pathophysiology. Adenosine-binding proteins represent an important subset of the proteome where aberrant expression or activity changes of these proteins have been implicated in numerous human diseases. Herein, we describe an affinity-based approach for the enrichment of adenosine-binding proteins from a complex cell proteome. A novel N 6-biotinylated-8-azido-adenosine probe (AdoR probe) was synthesized, which contains a reactive group that forms a covalent bond with the target proteins, as well as a biotin tag for affinity enrichment using avidin chromatography. Probe specificity was confirmed with protein standards prior to further evaluation in a complex protein mixture consisting of a lysate derived from mouse neuroblastoma N18TG2 cells. Protein identification and relative quantitation using mass spectrometry allowed for the identification of small variations in abundance of nucleoside- and nucleotide-binding proteins in these samples where a significant enrichment of AdoR-binding proteins in the labeled proteome from the neuroblastoma cells was observed. The results from this study demonstrate the utility of this method to enrich for nucleoside- and nucleotide-binding proteins in a complex protein mixture, pointing towards a unique set of proteins that can be examined in the context of further understanding mechanisms of disease, or fundamental biological processes in general. PMID:25671571

Computational Methods to Predict Protein Interaction Partners

NASA Astrophysics Data System (ADS)

Valencia, Alfonso; Pazos, Florencio

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

Distinct functions for IFT140 and IFT20 in opsin transport.

PubMed Central

Crouse, Jacquelin A.; Lopes, Vanda S.; SanAgustin, Jovenal T.; Keady, Brian T.; Williams, David S.; Pazour, Gregory J.

2014-01-01

In the vertebrate retina, light is detected by the outer segments of photoreceptor rods and cones, which are highly modified cilia. Like other cilia, outer segments have no protein synthetic capacity and depend on proteins made in the cell body for their formation and maintenance. The mechanism of transport into the outer segment is not fully understood but intraflagellar transport (IFT) is thought to be a major mechanism for moving protein from the cell body into the cilium. In the case of photoreceptor cells, the high density of receptors and the disk turnover that occurs daily necessitates much higher rates of transport than would be required in other cilia. In this work, we show that the IFT complex A protein IFT140 is required for development and maintenance of outer segments. In earlier work we found that acute deletion of Ift20 caused opsin to accumulate at the Golgi complex. In this work we find that acute deletion of Ift140 does not cause opsin to accumulate at the Golgi complex but rather it accumulates in the plasma membrane of the inner segments. This work is strong support of a model of opsin transport where IFT20 is involved in the movement from the Golgi complex to the base of the cilium. Then, once at the base, the opsin is carried through the connecting cilium by an IFT complex that includes IFT140. PMID:24619649

Computational modeling of carbohydrate recognition in protein complex

NASA Astrophysics Data System (ADS)

Ishida, Toyokazu

2017-11-01

To understand the mechanistic principle of carbohydrate recognition in proteins, we propose a systematic computational modeling strategy to identify complex carbohydrate chain onto the reduced 2D free energy surface (2D-FES), determined by MD sampling combined with QM/MM energy corrections. In this article, we first report a detailed atomistic simulation study of the norovirus capsid proteins with carbohydrate antigens based on ab initio QM/MM combined with MD-FEP simulations. The present result clearly shows that the binding geometries of complex carbohydrate antigen are determined not by one single, rigid carbohydrate structure, but rather by the sum of averaged conformations mapped onto the minimum free energy region of QM/MM 2D-FES.

Macrocyclic metal complexes for metalloenzyme mimicry and sensor development.

PubMed

Joshi, Tanmaya; Graham, Bim; Spiccia, Leone

2015-08-18

Examples of proteins that incorporate one or more metal ions within their structure are found within a broad range of classes, including oxidases, oxidoreductases, reductases, proteases, proton transport proteins, electron transfer/transport proteins, storage proteins, lyases, rusticyanins, metallochaperones, sporulation proteins, hydrolases, endopeptidases, luminescent proteins, iron transport proteins, oxygen storage/transport proteins, calcium binding proteins, and monooxygenases. The metal coordination environment therein is often generated from residues inherent to the protein, small exogenous molecules (e.g., aqua ligands) and/or macrocyclic porphyrin units found, for example, in hemoglobin, myoglobin, cytochrome C, cytochrome C oxidase, and vitamin B12. Thus, there continues to be considerable interest in employing macrocyclic metal complexes to construct low-molecular weight models for metallobiosites that mirror essential features of the coordination environment of a bound metal ion without inclusion of the surrounding protein framework. Herein, we review and appraise our research exploring the application of the metal complexes formed by two macrocyclic ligands, 1,4,7-triazacyclononane (tacn) and 1,4,7,10-tetraazacyclododecane (cyclen), and their derivatives in biological inorganic chemistry. Taking advantage of the kinetic inertness and thermodynamic stability of their metal complexes, these macrocyclic scaffolds have been employed in the development of models that aid the understanding of metal ion-binding natural systems, and complexes with potential applications in biomolecule sensing, diagnosis, and therapy. In particular, the focus has been on "coordinatively unsaturated" metal complexes that incorporate a kinetically inert and stable metal-ligand moiety, but which also contain one or more weakly bound ligands, allowing for the reversible binding of guest molecules via the formation and dissociation of coordinate bonds. With regards to mimicking metallobiosites, examples are presented from our work on tacn-based complexes developed as simplified structural models for multimetallic enzyme sites. In particular, structural comparisons are made between multinuclear copper(II) complexes formed by such ligands and multicopper enzymes featuring type-2 and type-3 copper centers, such as ascorbate oxidase (AO) and laccase (Lc). Likewise, with the aid of relevant examples, we highlight the importance of cooperativity between either multiple metal centers or a metal center and a proximal auxiliary unit appended to the macrocyclic ligand in achieving efficient phosphate ester cleavage. Finally, the critical importance of the Zn(II)-imido and Zn(II)-phosphate interactions in Zn-cyclen-based systems for delivering highly sensitive electrochemical and fluorescent chemosensors is also showcased. The Account additionally highlights some of the factors that limit the performance of these synthetic nucleases and the practical application of the biosensors, and then identifies some avenues for the development of more effective macrocyclic constructs in the future.

Oligomeric protein complexes of apolipoproteins stabilize the internal fluid environment of organism in redfins of the Tribolodon genus [Pisces; Cypriniformes, Cyprinidae].

PubMed

Andreeva, Alla M; Serebryakova, Marina V; Lamash, Nina E

2017-06-01

One of the most important functions of plasma proteins in vertebrates is their participation in osmotic homeostasis in the organism. Modern concepts about plasma proteins and their capillary filtration are based on a model of large monomeric proteins that are able to penetrate the interstitial space. At the same time, it was revealed that a considerable amount of oligomeric complexes are present in the low-molecular-weight (LM) protein fraction in the extracellular fluids of fishes. The functions of these complexes are unknown. In the present study, we investigated the LM-fraction proteins in the plasma and interstitial fluid (IF) of redfins of the genus Tribolodon. This fish alternatively spends parts of its life cycle in saline and fresh waters. We identified the protein Wap65, serpins and apolipoproteins in this fraction. By combining the methods of 2D-E under native and denaturing conditions with MALDI, we demonstrated that only apolipoproteins formed complexes. We showed that serum apolipoproteins (АроА-I, Аро-14) were present in the form of homooligomeric complexes that were dissociated with the release of monomeric forms of proteins in the course of capillary filtration to IF. Dissociation of homooligomers is not directly correlated with the change in salinity but is correlated with seasonal dynamics. We found that there was a significant decrease in the total protein concentration in IF relative to plasma. Therefore, we suggested that dissociation of homooligomeric complexes from various apolipoproteins supports the isoosmoticity of extracellular fluids relative to capillary wall stabilization through a fluid medium in fish. Copyright © 2017 Elsevier Inc. All rights reserved.

Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex.

PubMed

Mishra, Vinita; Pathak, Chandramani

2018-05-29

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

PLASS: Protein-ligand affinity statistical score a knowledge-based force-field model of interaction derived from the PDB

NASA Astrophysics Data System (ADS)

Ozrin, V. D.; Subbotin, M. V.; Nikitin, S. M.

2004-04-01

We have developed PLASS (Protein-Ligand Affinity Statistical Score), a pair-wise potential of mean-force for rapid estimation of the binding affinity of a ligand molecule to a protein active site. This scoring function is derived from the frequency of occurrence of atom-type pairs in crystallographic complexes taken from the Protein Data Bank (PDB). Statistical distributions are converted into distance-dependent contributions to the Gibbs free interaction energy for 10 atomic types using the Boltzmann hypothesis, with only one adjustable parameter. For a representative set of 72 protein-ligand structures, PLASS scores correlate well with the experimentally measured dissociation constants: a correlation coefficient R of 0.82 and RMS error of 2.0 kcal/mol. Such high accuracy results from our novel treatment of the volume correction term, which takes into account the inhomogeneous properties of the protein-ligand complexes. PLASS is able to rank reliably the affinity of complexes which have as much diversity as in the PDB.

Visualizing chaperone-assisted protein folding

DOE PAGES

Horowitz, Scott; Salmon, Loïc; Koldewey, Philipp; ...

2016-05-30

We present that challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone–substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a new structural biology approach based on X-ray crystallography, termed residual electron and anomalous density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the Escherichia coli chaperonemore » Spy, and to capture a series of snapshots depicting the various folding states of Im7 bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded to native-like states and reveals how a substrate can explore its folding landscape while being bound to a chaperone.« less

Structural basis for specific recognition of multiple mRNA targets by a PUF regulatory protein

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

Wang, Yeming; Opperman, Laura; Wickens, Marvin

2011-11-02

Caenorhabditis elegans fem-3 binding factor (FBF) is a founding member of the PUMILIO/FBF (PUF) family of mRNA regulatory proteins. It regulates multiple mRNAs critical for stem cell maintenance and germline development. Here, we report crystal structures of FBF in complex with 6 different 9-nt RNA sequences, including elements from 4 natural mRNAs. These structures reveal that FBF binds to conserved bases at positions 1-3 and 7-8. The key specificity determinant of FBF vs. other PUF proteins lies in positions 4-6. In FBF/RNA complexes, these bases stack directly with one another and turn away from the RNA-binding surface. A short regionmore » of FBF is sufficient to impart its unique specificity and lies directly opposite the flipped bases. We suggest that this region imposes a flattened curvature on the protein; hence, the requirement for the additional nucleotide. The principles of FBF/RNA recognition suggest a general mechanism by which PUF proteins recognize distinct families of RNAs yet exploit very nearly identical atomic contacts in doing so.« less

Structural basis for specific recognition of multiple mRNA targets by a PUF regulatory protein

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

Wang, Yeming; Opperman, Laura; Wickens, Marvin

2010-08-19

Caenorhabditis elegans fem-3 binding factor (FBF) is a founding member of the PUMILIO/FBF (PUF) family of mRNA regulatory proteins. It regulates multiple mRNAs critical for stem cell maintenance and germline development. Here, we report crystal structures of FBF in complex with 6 different 9-nt RNA sequences, including elements from 4 natural mRNAs. These structures reveal that FBF binds to conserved bases at positions 1-3 and 7-8. The key specificity determinant of FBF vs. other PUF proteins lies in positions 4-6. In FBF/RNA complexes, these bases stack directly with one another and turn away from the RNA-binding surface. A short regionmore » of FBF is sufficient to impart its unique specificity and lies directly opposite the flipped bases. We suggest that this region imposes a flattened curvature on the protein; hence, the requirement for the additional nucleotide. The principles of FBF/RNA recognition suggest a general mechanism by which PUF proteins recognize distinct families of RNAs yet exploit very nearly identical atomic contacts in doing so.« less

Aspartate aminotransferase is potently inhibited by copper complexes: Exploring copper complex-binding proteome.

PubMed

Jia, Yuqi; Lu, Liping; Yuan, Caixia; Feng, Sisi; Zhu, Miaoli

2017-05-01

Recent researches indicated that a copper complex-binding proteome that potently interacted with copper complexes and then influenced cellular metabolism might exist in organism. In order to explore the copper complex-binding proteome, a copper chelating ion-immobilized affinity chromatography (Cu-IMAC) column and mass spectrometry were used to separate and identify putative Cu-binding proteins in primary rat hepatocytes. A total of 97 putative Cu-binding proteins were isolated and identified. Five higher abundance proteins, aspartate aminotransferase (AST), malate dehydrogenase (MDH), catalase (CAT), calreticulin (CRT) and albumin (Alb) were further purified using a SP-, and (or) Q-Sepharose Fast Flow column. The interaction between the purified proteins and selected 11 copper complexes and CuCl 2 was investigated. The enzymes inhibition tests demonstrated that AST was potently inhibited by copper complexes while MDH and CAT were weakly inhibited. Schiff-based copper complexes 6 and 7 potently inhibited AST with the IC 50 value of 3.6 and 7.2μM, respectively and exhibited better selectivity over MDH and CAT. Fluorescence titration results showed the two complexes tightly bound to AST with binding constant of 3.89×10 6 and 3.73×10 6 M -1 , respectively and a stoichiometry ratio of 1:1. Copper complex 6 was able to enter into HepG2 cells and further inhibit intracellular AST activity. Copyright © 2017 Elsevier Inc. All rights reserved.

An SH2 domain-based tyrosine kinase assay using biotin ligase modified with a terbium(III) complex.

PubMed

Sueda, Shinji; Shinboku, Yuki; Kusaba, Takeshi

2013-01-01

Src homology 2 (SH2) domains are modules of approximately 100 amino acids and are known to bind phosphotyrosine-containing sequences with high affinity and specificity. In the present work, we developed an SH2 domain-based assay for Src tyrosine kinase using a unique biotinylation reaction from archaeon Sulfolobus tokodaii. S. tokodaii biotinylation has a unique property that biotin protein ligase (BPL) forms a stable complex with its biotinylated substrate protein (BCCP). Here, an SH2 domain from lymphocyte-specific tyrosine kinase was genetically fused to a truncated BCCP, and the resulting fusion protein was labeled through biotinylation with BPL carrying multiple copies of a luminescent Tb(3+) complex. The labeled SH2 fusion proteins were employed to detect a phosphorylated peptide immobilized on the surface of the microtiter plate, where the phosphorylated peptide was produced by phosphorylation to the substrate peptide by Src tyrosine kinase. Our assay allows for a reliable determination of the activity of Src kinase lower than 10 pg/μL by a simple procedure.

The impact of CRISPR repeat sequence on structures of a Cas6 protein-RNA complex

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

Wang, Ruiying; Zheng, Han; Preamplume, Gan

The repeat-associated mysterious proteins (RAMPs) comprise the most abundant family of proteins involved in prokaryotic immunity against invading genetic elements conferred by the clustered regularly interspaced short palindromic repeat (CRISPR) system. Cas6 is one of the first characterized RAMP proteins and is a key enzyme required for CRISPR RNA maturation. Despite a strong structural homology with other RAMP proteins that bind hairpin RNA, Cas6 distinctly recognizes single-stranded RNA. Previous structural and biochemical studies show that Cas6 captures the 5' end while cleaving the 3' end of the CRISPR RNA. Here, we describe three structures and complementary biochemical analysis of amore » noncatalytic Cas6 homolog from Pyrococcus horikoshii bound to CRISPR repeat RNA of different sequences. Our study confirms the specificity of the Cas6 protein for single-stranded RNA and further reveals the importance of the bases at Positions 5-7 in Cas6-RNA interactions. Substitutions of these bases result in structural changes in the protein-RNA complex including its oligomerization state.« less

Correlation between the Stereochemistry and Bioactivity in Octahedral Rhodium Prolinato Complexes.

PubMed

Rajaratnam, Rajathees; Martin, Elisabeth K; Dörr, Markus; Harms, Klaus; Casini, Angela; Meggers, Eric

2015-08-17

Controlling the relative and absolute configuration of octahedral metal complexes constitutes a key challenge that needs to be overcome in order to fully exploit the structural properties of octahedral metal complexes for applications in the fields of catalysis, materials sciences, and life sciences. Herein, we describe the application of a proline-based chiral tridentate ligand to decisively control the coordination mode of an octahedral rhodium(III) complex. We demonstrate the mirror-like relationship of synthesized enantiomers and differences between diastereomers. Further, we demonstrate, using the established pyridocarbazole pharmacophore ligand as part of the organometallic complexes, the importance of the relative and absolute stereochemistry at the metal toward chiral environments like protein kinases. Protein kinase profiling and inhibition data confirm that the proline-based enantiopure rhodium(III) complexes, despite having all of the same constitution, differ strongly in their selectivity properties despite their unmistakably mutual origin. Moreover, two exemplary compounds have been shown to induce different toxic effects in an ex vivo rat liver model.

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

PubMed

Yang, Lei; Zhao, Xudong; Tang, Xianglong

2014-01-01

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

Molecular interactions of orthologues of floral homeotic proteins from the gymnosperm Gnetum gnemon provide a clue to the evolutionary origin of 'floral quartets'.

PubMed

Wang, Yong-Qiang; Melzer, Rainer; Theissen, Günter

2010-10-01

Several lines of evidence suggest that the identity of floral organs in angiosperms is specified by multimeric transcription factor complexes composed of MADS-domain proteins. These bind to specific cis-regulatory elements ('CArG-boxes') of their target genes involving DNA-loop formation, thus constituting 'floral quartets'. Gymnosperms, angiosperms' closest relatives, contain orthologues of floral homeotic genes, but when and how the interactions constituting floral quartets were established during evolution has remained unknown. We have comprehensively studied the dimerization and DNA-binding of several classes of MADS-domain proteins from the gymnosperm Gnetum gnemon. Determination of protein-protein and protein-DNA interactions by yeast two-hybrid, in vitro pull-down and electrophoretic mobility shift assays revealed complex patterns of homo- and heterodimerization among orthologues of floral homeotic class B, class C and class E proteins and B(sister) proteins. Using DNase I footprint assays we demonstrate that both orthologues of class B with C proteins, and orthologues of class C proteins alone, but not orthologues of class B proteins alone can loop DNA in floral quartet-like complexes. This is in contrast to class B and class C proteins from angiosperms, which require other factors such as class E floral homeotic proteins to 'glue' them together in multimeric complexes. Our findings suggest that the evolutionary origin of floral quartet formation is based on the interaction of different DNA-bound homodimers, does not depend on class E proteins, and predates the origin of angiosperms. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

Preprotein import into chloroplasts via the Toc and Tic complexes is regulated by redox signals in Pisum sativum.

PubMed

Stengel, Anna; Benz, J Philipp; Buchanan, Bob B; Soll, Jürgen; Bölter, Bettina

2009-11-01

The import of nuclear-encoded preproteins is necessary to maintain chloroplast function. The recognition and transfer of most precursor proteins across the chloroplast envelopes are facilitated by two membrane-inserted protein complexes, the translocons of the chloroplast outer and inner envelope (Toc and Tic complexes, respectively). Several signals have been invoked to regulate the import of preproteins. In our study, we were interested in redox-based import regulation mediated by two signals: regulation based on thiols and on the metabolic NADP+/NADPH ratio. We sought to identify the proteins participating in the regulation of these transport pathways and to characterize the preprotein subgroups whose import is redox-dependent. Our results provide evidence that the formation and reduction of disulfide bridges in the Toc receptors and Toc translocation channel have a strong influence on import yield of all tested preproteins that depend on the Toc complex for translocation. Furthermore, the metabolic NADP+/NADPH ratio influences not only the composition of the Tic complex, but also the import efficiency of most, but not all, preproteins tested. Thus, several Tic subcomplexes appear to participate in the translocation of different preprotein subgroups, and the redox-active components of these complexes likely play a role in regulating transport.

Classification of pseudo pairs between nucleotide bases and amino acids by analysis of nucleotide-protein complexes.

PubMed

Kondo, Jiro; Westhof, Eric

2011-10-01

Nucleotide bases are recognized by amino acid residues in a variety of DNA/RNA binding and nucleotide binding proteins. In this study, a total of 446 crystal structures of nucleotide-protein complexes are analyzed manually and pseudo pairs together with single and bifurcated hydrogen bonds observed between bases and amino acids are classified and annotated. Only 5 of the 20 usual amino acid residues, Asn, Gln, Asp, Glu and Arg, are able to orient in a coplanar fashion in order to form pseudo pairs with nucleotide bases through two hydrogen bonds. The peptide backbone can also form pseudo pairs with nucleotide bases and presents a strong bias for binding to the adenine base. The Watson-Crick side of the nucleotide bases is the major interaction edge participating in such pseudo pairs. Pseudo pairs between the Watson-Crick edge of guanine and Asp are frequently observed. The Hoogsteen edge of the purine bases is a good discriminatory element in recognition of nucleotide bases by protein side chains through the pseudo pairing: the Hoogsteen edge of adenine is recognized by various amino acids while the Hoogsteen edge of guanine is only recognized by Arg. The sugar edge is rarely recognized by either the side-chain or peptide backbone of amino acid residues.

Classification of pseudo pairs between nucleotide bases and amino acids by analysis of nucleotide–protein complexes

PubMed Central

Kondo, Jiro; Westhof, Eric

2011-01-01

Nucleotide bases are recognized by amino acid residues in a variety of DNA/RNA binding and nucleotide binding proteins. In this study, a total of 446 crystal structures of nucleotide–protein complexes are analyzed manually and pseudo pairs together with single and bifurcated hydrogen bonds observed between bases and amino acids are classified and annotated. Only 5 of the 20 usual amino acid residues, Asn, Gln, Asp, Glu and Arg, are able to orient in a coplanar fashion in order to form pseudo pairs with nucleotide bases through two hydrogen bonds. The peptide backbone can also form pseudo pairs with nucleotide bases and presents a strong bias for binding to the adenine base. The Watson–Crick side of the nucleotide bases is the major interaction edge participating in such pseudo pairs. Pseudo pairs between the Watson–Crick edge of guanine and Asp are frequently observed. The Hoogsteen edge of the purine bases is a good discriminatory element in recognition of nucleotide bases by protein side chains through the pseudo pairing: the Hoogsteen edge of adenine is recognized by various amino acids while the Hoogsteen edge of guanine is only recognized by Arg. The sugar edge is rarely recognized by either the side-chain or peptide backbone of amino acid residues. PMID:21737431

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

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

PubMed

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 docking calculations with biochemical pathways and enables users to easily and quickly assess PPI feasibilities by archiving PPI predictions. MEGADOCK-Web also promotes the discovery of new PPIs and protein functions and is freely available for use at http://www.bi.cs.titech.ac.jp/megadock-web/ .

Inhibition of herpesvirus and influenza virus replication by blocking polymerase subunit interactions.

PubMed

Palù, Giorgio; Loregian, Arianna

2013-09-01

Protein-protein interactions (PPIs) play a key role in many biological processes, including virus replication in the host cell. Since most of the PPIs are functionally essential, a possible strategy to inhibit virus replication is based on the disruption of viral protein complexes by peptides or small molecules that interfere with subunit interactions. In particular, an attractive target for antiviral drugs is the binding between the subunits of essential viral enzymes. This review describes the development of new antiviral compounds that inhibit herpesvirus and influenza virus replication by blocking interactions between subunit proteins of their polymerase complexes. Copyright © 2013 Elsevier B.V. All rights reserved.

Plant protein and animal proteins: do they differentially affect cardiovascular disease risk?

PubMed

Richter, Chesney K; Skulas-Ray, Ann C; Champagne, Catherine M; Kris-Etherton, Penny M

2015-11-01

Proteins from plant-based compared with animal-based food sources may have different effects on cardiovascular disease (CVD) risk factors. Numerous epidemiologic and intervention studies have evaluated their respective health benefits; however, it is difficult to isolate the role of plant or animal protein on CVD risk. This review evaluates the current evidence from observational and intervention studies, focusing on the specific protein-providing foods and populations studied. Dietary protein is derived from many food sources, and each provides a different composite of nonprotein compounds that can also affect CVD risk factors. Increasing the consumption of protein-rich foods also typically results in lower intakes of other nutrients, which may simultaneously influence outcomes. Given these complexities, blanket statements about plant or animal protein may be too general, and greater consideration of the specific protein food sources and the background diet is required. The potential mechanisms responsible for any specific effects of plant and animal protein are similarly multifaceted and include the amino acid content of particular foods, contributions from other nonprotein compounds provided concomitantly by the whole food, and interactions with the gut microbiome. Evidence to date is inconclusive, and additional studies are needed to further advance our understanding of the complexity of plant protein vs. animal protein comparisons. Nonetheless, current evidence supports the idea that CVD risk can be reduced by a dietary pattern that provides more plant sources of protein compared with the typical American diet and also includes animal-based protein foods that are unprocessed and low in saturated fat. © 2015 American Society for Nutrition.

Plant Protein and Animal Proteins: Do They Differentially Affect Cardiovascular Disease Risk?12

PubMed Central

Richter, Chesney K; Skulas-Ray, Ann C; Champagne, Catherine M; Kris-Etherton, Penny M

2015-01-01

Proteins from plant-based compared with animal-based food sources may have different effects on cardiovascular disease (CVD) risk factors. Numerous epidemiologic and intervention studies have evaluated their respective health benefits; however, it is difficult to isolate the role of plant or animal protein on CVD risk. This review evaluates the current evidence from observational and intervention studies, focusing on the specific protein-providing foods and populations studied. Dietary protein is derived from many food sources, and each provides a different composite of nonprotein compounds that can also affect CVD risk factors. Increasing the consumption of protein-rich foods also typically results in lower intakes of other nutrients, which may simultaneously influence outcomes. Given these complexities, blanket statements about plant or animal protein may be too general, and greater consideration of the specific protein food sources and the background diet is required. The potential mechanisms responsible for any specific effects of plant and animal protein are similarly multifaceted and include the amino acid content of particular foods, contributions from other nonprotein compounds provided concomitantly by the whole food, and interactions with the gut microbiome. Evidence to date is inconclusive, and additional studies are needed to further advance our understanding of the complexity of plant protein vs. animal protein comparisons. Nonetheless, current evidence supports the idea that CVD risk can be reduced by a dietary pattern that provides more plant sources of protein compared with the typical American diet and also includes animal-based protein foods that are unprocessed and low in saturated fat. PMID:26567196

The neuronal porosome complex in health and disease

PubMed Central

Naik, Akshata R; Lewis, Kenneth T

2015-01-01

Cup-shaped secretory portals at the cell plasma membrane called porosomes mediate the precision release of intravesicular material from cells. Membrane-bound secretory vesicles transiently dock and fuse at the base of porosomes facing the cytosol to expel pressurized intravesicular contents from the cell during secretion. The structure, isolation, composition, and functional reconstitution of the neuronal porosome complex have greatly progressed, providing a molecular understanding of its function in health and disease. Neuronal porosomes are 15 nm cup-shaped lipoprotein structures composed of nearly 40 proteins, compared to the 120 nm nuclear pore complex composed of >500 protein molecules. Membrane proteins compose the porosome complex, making it practically impossible to solve its atomic structure. However, atomic force microscopy and small-angle X-ray solution scattering studies have provided three-dimensional structural details of the native neuronal porosome at sub-nanometer resolution, providing insights into the molecular mechanism of its function. The participation of several porosome proteins previously implicated in neurotransmission and neurological disorders, further attest to the crosstalk between porosome proteins and their coordinated involvement in release of neurotransmitter at the synapse. PMID:26264442

Characterization of known protein complexes using k-connectivity and other topological measures

PubMed Central

Gallagher, Suzanne R; Goldberg, Debra S

2015-01-01

Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the complex decrease within protein-protein interaction networks. However, k-connectivity, the number of vertices or edges that need to be removed in order to disconnect a graph, may be consistently high for protein complexes. The property of k-connectivity has been little used previously in the investigation of protein-protein interactions. To understand the discriminative power of k-connectivity and other topological measures for identifying unknown protein complexes, we characterized these properties in known Saccharomyces cerevisiae protein complexes in networks generated both from highly accurate X-ray crystallography experiments which give an accurate model of each complex, and also as the complexes appear in high-throughput yeast 2-hybrid studies in which new complexes may be discovered. We also computed these properties for appropriate random subgraphs.We found that clustering coefficient, mutual clustering coefficient, and k-connectivity are better indicators of known protein complexes than edge density, degree, or betweenness. This suggests new directions for future protein complex-finding algorithms. PMID:26913183

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

NASA Astrophysics Data System (ADS)

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-01

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

PubMed

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-18

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

MURC/Cavin-4 and cavin family members form tissue-specific caveolar complexes

PubMed Central

Bastiani, Michele; Liu, Libin; Hill, Michelle M.; Jedrychowski, Mark P.; Nixon, Susan J.; Lo, Harriet P.; Abankwa, Daniel; Luetterforst, Robert; Fernandez-Rojo, Manuel; Breen, Michael R.; Gygi, Steven P.; Vinten, Jorgen; Walser, Piers J.; North, Kathryn N.; Hancock, John F.; Pilch, Paul F.

2009-01-01

Polymerase I and transcript release factor (PTRF)/Cavin is a cytoplasmic protein whose expression is obligatory for caveola formation. Using biochemistry and fluorescence resonance energy transfer–based approaches, we now show that a family of related proteins, PTRF/Cavin-1, serum deprivation response (SDR)/Cavin-2, SDR-related gene product that binds to C kinase (SRBC)/Cavin-3, and muscle-restricted coiled-coil protein (MURC)/Cavin-4, forms a multiprotein complex that associates with caveolae. This complex can constitutively assemble in the cytosol and associate with caveolin at plasma membrane caveolae. Cavin-1, but not other cavins, can induce caveola formation in a heterologous system and is required for the recruitment of the cavin complex to caveolae. The tissue-restricted expression of cavins suggests that caveolae may perform tissue-specific functions regulated by the composition of the cavin complex. Cavin-4 is expressed predominantly in muscle, and its distribution is perturbed in human muscle disease associated with Caveolin-3 dysfunction, identifying Cavin-4 as a novel muscle disease candidate caveolar protein. PMID:19546242

A water-soluble conjugated polymer for protein identification and denaturation detection.

PubMed

Xu, Qingling; Wu, Chunxian; Zhu, Chunlei; Duan, Xinrui; Liu, Libing; Han, Yuchun; Wang, Yilin; Wang, Shu

2010-12-03

Rapid and sensitive methods to detect proteins and protein denaturation have become increasingly needful in the field of proteomics, medical diagnostics, and biology. In this paper, we have reported the synthesis of a new cationic water-soluble conjugated polymer that contains fluorene and diene moieties in the backbone (PFDE) for protein identification by sensing an array of PFDE solutions in different ionic strengths using the linear discriminant analysis technique (LDA). The PFDE can form complexes with proteins by electrostatic and/or hydrophobic interactions and exhibits different fluorescence response. Three main factors contribute to the fluorescence response of PFDE, namely, the net charge density on the protein surface, the hydrophobic nature of the protein, and the metalloprotein characteristics. The denaturation of proteins can also be detected using PFDE as a fluorescent probe. The interactions between PFDE and proteins were also studied by dynamic light scattering (DLS) and isothermal titration microcalorimetry (ITC) techniques. In contrast to other methods based on conjugated polymers, the synthesis of a series of quencher or dye-labeled acceptors or protein substrates has been avoided in our method, which significantly reduces the cost and the synthetic complexity. Our method provides promising applications on protein identification and denaturation detection in a simple, fast, and label-free manner based on non-specific interaction-induced perturbation of PFDE fluorescence response.

iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize

PubMed Central

Dong, Yongbin; Wang, Qilei; Du, Chunguang; Xiong, Wenwei; Li, Xinyu; Zhu, Sailan; Li, Yuling

2017-01-01

Grain weight is one of the most important yield components and a developmentally complex structure comprised of two major compartments (endosperm and pericarp) in maize (Zea mays L.), however, very little is known concerning the coordinated accumulation of the numerous proteins involved. Herein, we used isobaric tags for relative and absolute quantitation (iTRAQ)-based comparative proteomic method to analyze the characteristics of dynamic proteomics for endosperm and pericarp during grain development. Totally, 9539 proteins were identified for both components at four development stages, among which 1401 proteins were non-redundant, 232 proteins were specific in pericarp and 153 proteins were specific in endosperm. A functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the tissue development. Three and 76 proteins involved in 49 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were integrated for the specific endosperm and pericarp proteins, respectively, reflecting their complex metabolic interactions. In addition, four proteins with important functions and different expression levels were chosen for gene cloning and expression analysis. Different concordance between mRNA level and the protein abundance was observed across different proteins, stages, and tissues as in previous research. These results could provide useful message for understanding the developmental mechanisms in grain development in maize. PMID:28837076

Prions, prionoid complexes and amyloids: the bad, the good and something in between.

PubMed

Hafner Bratkovič, Iva

2017-04-19

Prions are infectious agents causing transmissible spongiform encephalopathies in humans and animals. These protein-based particles template conformational changes in a host-encoded prion protein to an insoluble self-like conformation. Prions are also present in yeast, where they support protein-based epigenetic inheritance. There is emerging evidence that prion-like (prionoid) particles can support a variety of pathological and beneficial functions. The recent data on the prionoid spread of other pathological amyloids are discussed in light of differences between prions and prion-like aggregates. On the other hand, prion-like action has also been found to support important functions such as memory, and amyloids were shown to have a variety of physiological roles from storage to scaffolding in simple organisms and in humans. Higher-order protein complexes play important roles in signalling. Many death-fold domains can polymerise upon nucleation to enhance sensitivity and induce a robust response. Although these polymers are structurally different from amyloids, some of them are characterised by prionoid activities, such as intercellular spread. The initial activation of these complexes is vital for organismal health, whereas prolonged activation leading to unresolved inflammation underlies autoinflammatory and other diseases. Prionoid complexes play important roles far beyond prion diseases and neurodegeneration.

NMR approaches in structure-based lead discovery: Recent developments and new frontiers for targeting multi-protein complexes

PubMed Central

Dias, David M.; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. PMID:25175337

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

PubMed Central

2018-01-01

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 allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles. PMID:29518071

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

PubMed

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 allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles.

RHIM-based protein:protein interactions in anti-microbial defence against programmed cell death by necroptosis.

PubMed

Baker, Max O D G; Shanmugam, Nirukshan; Pham, Chi L L; Strange, Merryn; Steain, Megan; Sunde, Margaret

2018-05-05

The Receptor-interacting protein kinase Homotypic Interaction Motif (RHIM) is an amino acid sequence that mediates multiple protein:protein interactions in the mammalian programmed cell death pathway known as necroptosis. At least one key RHIM-based complex has been shown to have a functional amyloid fibril structure, which provides a stable hetero-oligomeric platform for downstream signaling. RHIMs and related motifs are present in immunity-related proteins across nature, from viruses to fungi to metazoans. Necroptosis is a hallmark feature of cellular clearance of infection. For this reason, numerous pathogens, including viruses and bacteria, have developed varied methods to modulate necroptosis, focusing on inhibiting RHIM:RHIM interactions, and thus their downstream cell death effects. This review will discuss current understanding of RHIM:RHIM interactions in normal cellular activation of necroptosis, from a structural and cell biology perspective. It will compare the mechanisms by which pathogens subvert these interactions in order to maintain their replicative and infective cycles and consider the similarities between RHIMs and other functional amyloid-forming proteins associated with cell death and innate immunity. It will discuss the implications of the heteromeric nature and structure of RHIM-based amyloid complexes in the context of other functional amyloids. Copyright © 2018. Published by Elsevier Ltd.

Prioritisation of associations between protein domains and complex diseases using domain-domain interaction networks.

PubMed

Wang, W; Zhang, W; Jiang, R; Luan, Y

2010-05-01

It is of vital importance to find genetic variants that underlie human complex diseases and locate genes that are responsible for these diseases. Since proteins are typically composed of several structural domains, it is reasonable to assume that harmful genetic variants may alter structures of protein domains, affect functions of proteins and eventually cause disorders. With this understanding, the authors explore the possibility of recovering associations between protein domains and complex diseases. The authors define associations between protein domains and disease families on the basis of associations between non-synonymous single nucleotide polymorphisms (nsSNPs) and complex diseases, similarities between diseases, and relations between proteins and domains. Based on a domain-domain interaction network, the authors propose a 'guilt-by-proximity' principle to rank candidate domains according to their average distance to a set of seed domains in the domain-domain interaction network. The authors validate the method through large-scale cross-validation experiments on simulated linkage intervals, random controls and the whole genome. Results show that areas under receiver operating characteristic curves (AUC scores) can be as high as 77.90%, and the mean rank ratios can be as low as 21.82%. The authors further offer a freely accessible web interface for a genome-wide landscape of associations between domains and disease families.

Experimental Methods for Protein Interaction Identification and Characterization

NASA Astrophysics Data System (ADS)

Uetz, Peter; Titz, Björn; Cagney, Gerard

There are dozens of methods for the detection of protein-protein interactions but they fall into a few broad categories. Fragment complementation assays such as the yeast two-hybrid (Y2H) system are based on split proteins that are functionally reconstituted by fusions of interacting proteins. Biophysical methods include structure determination and mass spectrometric (MS) identification of proteins in complexes. Biochemical methods include methods such as far western blotting and peptide arrays. Only the Y2H and protein complex purification combined with MS have been used on a larger scale. Due to the lack of data it is still difficult to compare these methods with respect to their efficiency and error rates. Current data does not favor any particular method and thus multiple experimental approaches are necessary to maximally cover the interactome of any target cell or organism.

Protein-protein interaction predictions using text mining methods.

PubMed

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

2015-03-01

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

Exploring the free-energy landscape of carbohydrate-protein complexes: development and validation of scoring functions considering the binding-site topology

NASA Astrophysics Data System (ADS)

Eid, Sameh; Saleh, Noureldin; Zalewski, Adam; Vedani, Angelo

2014-12-01

Carbohydrates play a key role in a variety of physiological and pathological processes and, hence, represent a rich source for the development of novel therapeutic agents. Being able to predict binding mode and binding affinity is an essential, yet lacking, aspect of the structure-based design of carbohydrate-based ligands. We assembled a diverse data set comprising 273 carbohydrate-protein crystal structures with known binding affinity and evaluated the prediction accuracy of a large collection of well-established scoring and free-energy functions, as well as combinations thereof. Unfortunately, the tested functions were not capable of reproducing binding affinities in the studied complexes. To simplify the complex free-energy surface of carbohydrate-protein systems, we classified the studied proteins according to the topology and solvent exposure of the carbohydrate-binding site into five distinct categories. A free-energy model based on the proposed classification scheme reproduced binding affinities in the carbohydrate data set with an r 2 of 0.71 and root-mean-squared-error of 1.25 kcal/mol ( N = 236). The improvement in model performance underlines the significance of the differences in the local micro-environments of carbohydrate-binding sites and demonstrates the usefulness of calibrating free-energy functions individually according to binding-site topology and solvent exposure.

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

PubMed

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 computational time significantly while keeping high prediction accuracy.

Alchemical Free Energy Calculations for Nucleotide Mutations in Protein-DNA Complexes.

PubMed

Gapsys, Vytautas; de Groot, Bert L

2017-12-12

Nucleotide-sequence-dependent interactions between proteins and DNA are responsible for a wide range of gene regulatory functions. Accurate and generalizable methods to evaluate the strength of protein-DNA binding have long been sought. While numerous computational approaches have been developed, most of them require fitting parameters to experimental data to a certain degree, e.g., machine learning algorithms or knowledge-based statistical potentials. Molecular-dynamics-based free energy calculations offer a robust, system-independent, first-principles-based method to calculate free energy differences upon nucleotide mutation. We present an automated procedure to set up alchemical MD-based calculations to evaluate free energy changes occurring as the result of a nucleotide mutation in DNA. We used these methods to perform a large-scale mutation scan comprising 397 nucleotide mutation cases in 16 protein-DNA complexes. The obtained prediction accuracy reaches 5.6 kJ/mol average unsigned deviation from experiment with a correlation coefficient of 0.57 with respect to the experimentally measured free energies. Overall, the first-principles-based approach performed on par with the molecular modeling approaches Rosetta and FoldX. Subsequently, we utilized the MD-based free energy calculations to construct protein-DNA binding profiles for the zinc finger protein Zif268. The calculation results compare remarkably well with the experimentally determined binding profiles. The software automating the structure and topology setup for alchemical calculations is a part of the pmx package; the utilities have also been made available online at http://pmx.mpibpc.mpg.de/dna_webserver.html .

Sulfonyl 3-alkynyl pantetheinamides as mechanism-based crosslinkers of ACP dehydratase

PubMed Central

Ishikawa, Fumihiro; Haushalter, Robert W.; Lee, D. John; Finzel, Kara; Burkart, Michael D.

2013-01-01

The acyl carrier protein (ACP) plays a central function in acetate biosynthetic pathways, serving as a tether for substrates and growing intermediates. Activity and structural studies have highlighted the complexities of this role, and its protein-protein interactions have recently come under scrutiny as a regulator of catalysis. As existing methods to interrogate these interactions have fallen short, we have sought to develop new tools to aid their study. Here we describe the design, synthesis, and application of pantetheinamides capable of crosslinking ACPs with catalytic β-hydroxyacyl carrier protein dehydratase (DH) domains based upon a 3-alkynyl sulfone warhead. We demonstrate this process by application to the Escherichia coli fatty acid synthase and apply it to probe protein-protein interactions with non-cognate carrier proteins. Finally, we use solution phase protein NMR to demonstrate that sulfonyl-3-alkynyl pantetheinamide is fully sequestered by the ACP, indicating that the crypto-ACP closely mimics the natural DH substrate. This crosslinking technology offers immediate potential to lock these biosynthetic enzymes in their native binding states by providing access to mechanistically-crosslinked enzyme complexes, presenting a solution to ongoing structural challenges. PMID:23718183

Parallel Force Assay for Protein-Protein Interactions

PubMed Central

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

2014-01-01

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

Parallel force assay for protein-protein interactions.

PubMed

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

2014-01-01

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

A combination of spin diffusion methods for the determination of protein-ligand complex structural ensembles.

PubMed

Pilger, Jens; Mazur, Adam; Monecke, Peter; Schreuder, Herman; Elshorst, Bettina; Bartoschek, Stefan; Langer, Thomas; Schiffer, Alexander; Krimm, Isabelle; Wegstroth, Melanie; Lee, Donghan; Hessler, Gerhard; Wendt, K-Ulrich; Becker, Stefan; Griesinger, Christian

2015-05-26

Structure-based drug design (SBDD) is a powerful and widely used approach to optimize affinity of drug candidates. With the recently introduced INPHARMA method, the binding mode of small molecules to their protein target can be characterized even if no spectroscopic information about the protein is known. Here, we show that the combination of the spin-diffusion-based NMR methods INPHARMA, trNOE, and STD results in an accurate scoring function for docking modes and therefore determination of protein-ligand complex structures. Applications are shown on the model system protein kinase A and the drug targets glycogen phosphorylase and soluble epoxide hydrolase (sEH). Multiplexing of several ligands improves the reliability of the scoring function further. The new score allows in the case of sEH detecting two binding modes of the ligand in its binding site, which was corroborated by X-ray analysis. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electrostatically Accelerated Encounter and Folding for Facile Recognition of Intrinsically Disordered Proteins

PubMed Central

Ganguly, Debabani; Zhang, Weihong; Chen, Jianhan

2013-01-01

Achieving facile specific recognition is essential for intrinsically disordered proteins (IDPs) that are involved in cellular signaling and regulation. Consideration of the physical time scales of protein folding and diffusion-limited protein-protein encounter has suggested that the frequent requirement of protein folding for specific IDP recognition could lead to kinetic bottlenecks. How IDPs overcome such potential kinetic bottlenecks to viably function in signaling and regulation in general is poorly understood. Our recent computational and experimental study of cell-cycle regulator p27 (Ganguly et al., J. Mol. Biol. (2012)) demonstrated that long-range electrostatic forces exerted on enriched charges of IDPs could accelerate protein-protein encounter via “electrostatic steering” and at the same time promote “folding-competent” encounter topologies to enhance the efficiency of IDP folding upon encounter. Here, we further investigated the coupled binding and folding mechanisms and the roles of electrostatic forces in the formation of three IDP complexes with more complex folded topologies. The surface electrostatic potentials of these complexes lack prominent features like those observed for the p27/Cdk2/cyclin A complex to directly suggest the ability of electrostatic forces to facilitate folding upon encounter. Nonetheless, similar electrostatically accelerated encounter and folding mechanisms were consistently predicted for all three complexes using topology-based coarse-grained simulations. Together with our previous analysis of charge distributions in known IDP complexes, our results support a prevalent role of electrostatic interactions in promoting efficient coupled binding and folding for facile specific recognition. These results also suggest that there is likely a co-evolution of IDP folded topology, charge characteristics, and coupled binding and folding mechanisms, driven at least partially by the need to achieve fast association kinetics for cellular signaling and regulation. PMID:24278008

A model of the complex between human {beta}-microseminoprotein and CRISP-3 based on NMR data

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

Ghasriani, Houman; Fernlund, Per; Udby, Lene

2009-01-09

{beta}-Microseminoprotein (MSP), a 10 kDa seminal plasma protein, forms a tight complex with cysteine-rich secretory protein 3 (CRISP-3) from granulocytes. The 3D structure of human MSP has been determined but there is as yet no 3D structure for CRISP-3. We have now studied the complex between human MSP and CRISP-3 with multidimensional NMR. {sup 15}N-HSQC spectra show substantial differences between free and complexed hMSP. Using several 3D-NMR spectra of triply labeled hMSP in complex with a recombinant N-terminal domain of CRISP-3, most of the backbone of hMSP could be assigned. The data show that only one side of hMSP, comprisingmore » {beta}-strands 1, 4, 5, and 8 are affected by the complex formation, indicating that {beta}-strands 1 and 8 form the main binding surface. Based on this we present a tentative structure for the hMSP-CRISP-3 complex using the known crystal structure of triflin as a model of CRISP-3.« less

Protein-ligand docking using FFT based sampling: D3R case study.

PubMed

Padhorny, Dzmitry; Hall, David R; Mirzaei, Hanieh; Mamonov, Artem B; Moghadasi, Mohammad; Alekseenko, Andrey; Beglov, Dmitri; Kozakov, Dima

2018-01-01

Fast Fourier transform (FFT) based approaches have been successful in application to modeling of relatively rigid protein-protein complexes. Recently, we have been able to adapt the FFT methodology to treatment of flexible protein-peptide interactions. Here, we report our latest attempt to expand the capabilities of the FFT approach to treatment of flexible protein-ligand interactions in application to the D3R PL-2016-1 challenge. Based on the D3R assessment, our FFT approach in conjunction with Monte Carlo minimization off-grid refinement was among the top performing methods in the challenge. The potential advantage of our method is its ability to globally sample the protein-ligand interaction landscape, which will be explored in further applications.

Protein-Protein Docking with F2Dock 2.0 and GB-Rerank

PubMed Central

Chowdhury, Rezaul; Rasheed, Muhibur; Keidel, Donald; Moussalem, Maysam; Olson, Arthur; Sanner, Michel; Bajaj, Chandrajit

2013-01-01

Motivation Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F2 Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error. Results The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F2 Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F2 Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F2 Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F2 Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other. Availability The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dockclient.shtml. PMID:23483883

Comparison of sample preparation techniques and data analysis for the LC-MS/MS-based identification of proteins in human follicular fluid.

PubMed

Lehmann, Roland; Schmidt, André; Pastuschek, Jana; Müller, Mario M; Fritzsche, Andreas; Dieterle, Stefan; Greb, Robert R; Markert, Udo R; Slevogt, Hortense

2018-06-25

The proteomic analysis of complex body fluids by liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis requires the selection of suitable sample preparation techniques and optimal parameter settings in data analysis software packages to obtain reliable results. Proteomic analysis of follicular fluid, as a representative of a complex body fluid similar to serum or plasma, is difficult as it contains a vast amount of high abundant proteins and a variety of proteins with different concentrations. However, the accessibility of this complex body fluid for LC-MS/MS analysis is an opportunity to gain insights into the status, the composition of fertility-relevant proteins including immunological factors or for the discovery of new diagnostic and prognostic markers for, for example, the treatment of infertility. In this study, we compared different sample preparation methods (FASP, eFASP and in-solution digestion) and three different data analysis software packages (Proteome Discoverer with SEQUEST, Mascot and MaxQuant with Andromeda) combined with semi- and full-tryptic databank search options to obtain a maximum coverage of the follicular fluid proteome. We found that the most comprehensive proteome coverage is achieved by the eFASP sample preparation method using SDS in the initial denaturing step and the SEQUEST-based semi-tryptic data analysis. In conclusion, we have developed a fractionation-free methodical workflow for in depth LC-MS/MS-based analysis for the standardized investigation of human follicle fluid as an important representative of a complex body fluid. Taken together, we were able to identify a total of 1392 proteins in follicular fluid. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

Fabrication of an ionic-liquid-based polymer monolithic column and its application in the fractionation of proteins from complex biosamples.

PubMed

Zhang, Doudou; Zhang, Qian; Bai, Ligai; Han, Dandan; Liu, Haiyan; Yan, Hongyuan

2018-05-01

An ionic-liquid-based polymer monolithic column was synthesized by free radical polymerization within the confines of a stainless-steel column (50 mm × 4.6 mm id). In the processes, ionic liquid and stearyl methacrylate were used as dual monomers, ethylene glycol dimethacrylate as the cross-linking agent, and polyethylene glycol 200 and isopropanol as co-porogens. Effects of the prepolymerization solution components on the properties of the resulting monoliths were studied in detail. Scanning electron microscopy, nitrogen adsorption-desorption measurements, and mercury intrusion porosimetry were used to investigate the morphology and pore size distribution of the prepared monoliths, which showed that the homemade ionic-liquid-based monolith column possessed a relatively uniform macropore structure with a total macropore specific surface area of 44.72 m 2 /g. Compared to a non-ionic-liquid-based monolith prepared under the same conditions, the ionic-liquid-based monolith exhibited excellent selectivity and high performance for separating proteins from complex biosamples, such as egg white, snailase, bovine serum albumin digest solution, human plasma, etc., indicating promising applications in the fractionation and analysis of proteins from the complex biosamples in proteomics research. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A non-heme iron-mediated chemical demethylation in DNA and RNA.

PubMed

Yi, Chengqi; Yang, Cai-Guang; He, Chuan

2009-04-21

DNA methylation is arguably one of the most important chemical signals in biology. However, aberrant DNA methylation can lead to cytotoxic or mutagenic consequences. A DNA repair protein in Escherichia coli, AlkB, corrects some of the unwanted methylations of DNA bases by a unique oxidative demethylation in which the methyl carbon is liberated as formaldehyde. The enzyme also repairs exocyclic DNA lesions--that is, derivatives in which the base is augmented with an additional heterocyclic subunit--by a similar mechanism. Two proteins in humans that are homologous to AlkB, ABH2 and ABH3, repair the same spectrum of lesions; another human homologue of AlkB, FTO, is linked to obesity. In this Account, we describe our studies of AlkB, ABH2, and ABH3, including our development of a general strategy to trap homogeneous protein-DNA complexes through active-site disulfide cross-linking. AlkB uses a non-heme mononuclear iron(II) and the cofactors 2-ketoglutarate (2KG) and dioxygen to effect oxidative demethylation of the DNA base lesions 1-methyladenine (1-meA), 3-methylcytosine (3-meC), 1-methylguanine (1-meG), and 3-methylthymine (3-meT). ABH3, like AlkB, works better on single-stranded DNA (ssDNA) and is capable of repairing damaged bases in RNA. Conversely, ABH2 primarily repairs lesions in double-stranded DNA (dsDNA); it is the main housekeeping enzyme that protects the mammalian genome from 1-meA base damage. The AlkB-family proteins have moderate affinities for their substrates and bind DNA in a non-sequence-specific manner. Knowing that these proteins flip the damaged base out from the duplex DNA and insert it into the active site for further processing, we first engineered a disulfide cross-link in the active site to stabilize the Michaelis complex. Based on the detailed structural information afforded by the active-site cross-linked structures, we can readily install a cross-link away from the active site to obtain the native-like structures of these complexes. The crystal structures show a distinct base-flipping feature in AlkB and establish ABH2 as a dsDNA repair protein. They also provide a molecular framework for understanding the demethylation reaction catalyzed by these proteins and help to explain their substrate preferences. The chemical cross-linking method demonstrated here can be applied to trap other labile protein-DNA interactions and can serve as a general strategy for exploring the structural and functional aspects of base-flipping proteins.

Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

PubMed

Sasse, Alexander; de Vries, Sjoerd J; Schindler, Christina E M; de Beauchêne, Isaure Chauvot; Zacharias, Martin

2017-01-01

Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scoring step is one of the bottlenecks in the performance of many state-of-the-art protocols. The performance of scoring functions depends on the quality of the generated structures and its coupling to the sampling algorithm. A tool kit, GRADSCOPT (GRid Accelerated Directly SCoring OPTimizing), was designed to allow rapid development and optimization of different knowledge-based scoring potentials for specific objectives in protein-protein docking. Different atomistic and coarse-grained potentials can be created by a grid-accelerated directly scoring dependent Monte-Carlo annealing or by a linear regression optimization. We demonstrate that the scoring functions generated by our approach are similar to or even outperform state-of-the-art scoring functions for predicting near-native solutions. Of additional importance, we find that potentials specifically trained to identify the native bound complex perform rather poorly on identifying acceptable or medium quality (near-native) solutions. In contrast, atomistic long-range contact potentials can increase the average fraction of near-native poses by up to a factor 2.5 in the best scored 1% decoys (compared to existing scoring), emphasizing the need of specific docking potentials for different steps in the docking protocol.

Growth and recombinant protein expression with Escherichia coli in different batch cultivation media.

PubMed

Hortsch, Ralf; Weuster-Botz, Dirk

2011-04-01

Parallel operated milliliter-scale stirred tank bioreactors were applied for recombinant protein expression studies in simple batch experiments without pH titration. An enzymatic glucose release system (EnBase), a complex medium, and the frequently used LB and TB media were compared with regard to growth of Escherichia coli and recombinant protein expression (alcohol dehydrogenase (ADH) from Lactobacillus brevis and formate dehydrogenase (FDH) from Candida boidinii). Dissolved oxygen and pH were recorded online, optical densities were measured at-line, and the activities of ADH and FDH were analyzed offline. Best growth was observed in a complex medium with maximum dry cell weight concentrations of 14 g L(-1). EnBase cultivations enabled final dry cell weight concentrations between 6 and 8 g L(-1). The pH remained nearly constant in EnBase cultivations due to the continuous glucose release, showing the usefulness of this glucose release system especially for pH-sensitive bioprocesses. Cell-specific enzyme activities varied considerably depending on the different media used. Maximum specific ADH activities were measured with the complex medium, 6 h after induction with IPTG, whereas the highest specific FDH activities were achieved with the EnBase medium at low glucose release profiles 24 h after induction. Hence, depending on the recombinant protein, different medium compositions, times for induction, and times for cell harvest have to be evaluated to achieve efficient expression of recombinant proteins in E. coli. A rapid experimental evaluation can easily be performed with parallel batch operated small-scale stirred tank bioreactors.

HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy

PubMed Central

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong

2017-01-01

Abstract Protein–protein and protein–DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein–protein and protein–DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10–20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein–protein and protein–DNA benchmarks and performed better than template-based modeling on the three protein–RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. PMID:28521030

Inhibition of the checkpoint protein PD-1 by the therapeutic antibody pembrolizumab outlined by quantum chemistry.

PubMed

Tavares, Ana Beatriz M L A; Lima Neto, José X; Fulco, Umberto L; Albuquerque, Eudenilson L

2018-01-30

Much of the recent excitement in the cancer immunotherapy approach has been generated by the recognition that immune checkpoint proteins, like the receptor PD-1, can be blocked by antibody-based drugs with profound effects. Promising clinical data have already been released pointing to the efficiency of the drug pembrolizumab to block the PD-1 pathway, triggering the T-lymphocytes to destroy the cancer cells. Thus, a deep understanding of this drug/receptor complex is essential for the improvement of new drugs targeting the protein PD-1. In this context, by employing quantum chemistry methods based on the Density Functional Theory (DFT), we investigate in silico the binding energy features of the receptor PD-1 in complex with its drug inhibitor. Our computational results give a better understanding of the binding mechanisms, being also an efficient alternative towards the development of antibody-based drugs, pointing to new treatments for cancer therapy.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Toroidal surface complexes of bacteriophage {phi}12 are responsible for host-cell attachment

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

Leo-Macias, Alejandra; Katz, Garrett; Wei Hui

2011-06-05

Cryo-electron tomography and subtomogram averaging are utilized to determine that the bacteriophage {phi}12, a member of the Cystoviridae family, contains surface complexes that are toroidal in shape, are composed of six globular domains with six-fold symmetry, and have a discrete density connecting them to the virus membrane-envelope surface. The lack of this kind of spike in a reassortant of {phi}12 demonstrates that the gene for the hexameric spike is located in {phi}12's medium length genome segment, likely to the P3 open reading frames which are the proteins involved in viral-host cell attachment. Based on this and on protein mass estimatesmore » derived from the obtained averaged structure, it is suggested that each of the globular domains is most likely composed of a total of four copies of P3a and/or P3c proteins. Our findings may have implications in the study of the evolution of the cystovirus species in regard to their host specificity. - Research Highlights: > Subtomogram averaging reveals enhanced detail of a {phi}12 cystovirus surface protein complex. > The surface protein complex has a toroidal shape and six-fold symmetry. > It is encoded by the medium-size genome segment. > The proteins of the surface complex most likely are one copy of P3a and three copies of P3c.« less

Bioengineered protein-based nanocage for drug delivery.

PubMed

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigation of the effects of dietary protein source on copper and zinc bioavailability in rainbow trout

USDA-ARS?s Scientific Manuscript database

Limited research has examined the effects that dietary protein sources have on copper (Cu) and Zinc (Zn) absorption, interactions and utilization in rainbow trout. Therefore, the objective of the first trial was to determine what effect protein source (plant vs. animal based), Cu source (complex vs....

Purification and partial characterization of a lectin protein complex, the clathrilectin, from the calcareous sponge Clathrina clathrus.

PubMed

Gardères, Johan; Domart-Coulon, Isabelle; Marie, Arul; Hamer, Bojan; Batel, Renato; Müller, Werner E G; Bourguet-Kondracki, Marie-Lise

2016-10-01

Carbohydrate-binding proteins were purified from the marine calcareous sponge Clathrina clathrus via affinity chromatography on lactose and N-acetyl glucosamine-agarose resins. Proteomic analysis of acrylamide gel separated protein subunits obtained in reducing conditions pointed out several candidates for lectins. Based on amino-acid sequence similarity, two peptides displayed homology with the jack bean lectin Concanavalin A, including a conserved domain shared by proteins in the L-type lectin superfamily. An N-acetyl glucosamine - binding protein complex, named clathrilectin, was further purified via gel filtration chromatography, bioguided with a diagnostic rabbit erythrocyte haemagglutination assay, and its activity was found to be calcium dependent. Clathrilectin, a protein complex of 3200kDa estimated by gel filtration, is composed of monomers with apparent molecular masses of 208 and 180kDa estimated on 10% SDS-PAGE. Nine internal peptides were identified using proteomic analyses, and compared to protein libraries from the demosponge Amphimedon queenslandica and a calcareous sponge Sycon sp. from the Adriatic Sea. The clathrilectin is the first lectin isolated from a calcareous sponge and displays homologies with predicted sponge proteins potentially involved in cell aggregation and interaction with bacteria. Copyright © 2016 Elsevier Inc. All rights reserved.

Gold(III) complexes with hydroxyquinoline, aminoquinoline and quinoline ligands: Synthesis, cytotoxicity, DNA and protein binding studies.

PubMed

Martín-Santos, Cecilia; Michelucci, Elena; Marzo, Tiziano; Messori, Luigi; Szumlas, Piotr; Bednarski, Patrick J; Mas-Ballesté, Rubén; Navarro-Ranninger, Carmen; Cabrera, Silvia; Alemán, José

2015-12-01

In this article, we report on the synthesis and the chemical and biological characterization of novel gold(III) complexes based on hydroxyl- or amino-quinoline ligands that are evaluated as prospective anticancer agents. To gain further insight into their reactivity and possible mode of action, their interactions with model proteins and standard nucleic acid molecules were investigated. Copyright © 2015 Elsevier Inc. All rights reserved.

Accurate characterization of weak macromolecular interactions by titration of NMR residual dipolar couplings: application to the CD2AP SH3-C:ubiquitin complex.

PubMed

Ortega-Roldan, Jose Luis; Jensen, Malene Ringkjøbing; Brutscher, Bernhard; Azuaga, Ana I; Blackledge, Martin; van Nuland, Nico A J

2009-05-01

The description of the interactome represents one of key challenges remaining for structural biology. Physiologically important weak interactions, with dissociation constants above 100 muM, are remarkably common, but remain beyond the reach of most of structural biology. NMR spectroscopy, and in particular, residual dipolar couplings (RDCs) provide crucial conformational constraints on intermolecular orientation in molecular complexes, but the combination of free and bound contributions to the measured RDC seriously complicates their exploitation for weakly interacting partners. We develop a robust approach for the determination of weak complexes based on: (i) differential isotopic labeling of the partner proteins facilitating RDC measurement in both partners; (ii) measurement of RDC changes upon titration into different equilibrium mixtures of partially aligned free and complex forms of the proteins; (iii) novel analytical approaches to determine the effective alignment in all equilibrium mixtures; and (iv) extraction of precise RDCs for bound forms of both partner proteins. The approach is demonstrated for the determination of the three-dimensional structure of the weakly interacting CD2AP SH3-C:Ubiquitin complex (K(d) = 132 +/- 13 muM) and is shown, using cross-validation, to be highly precise. We expect this methodology to extend the remarkable and unique ability of NMR to study weak protein-protein complexes.

9-Fluorenylmethyloxycarbonyl/ tbutyl-based convergent protein synthesis.

PubMed

Barlos, K; Gatos, D

1999-01-01

Besides linear solid phase peptide synthesis, segment condensation in solution and chemical ligation, convergent peptide synthesis (CPS) was developed in order to enable the efficient preparation of complex peptides and small proteins. According to this synthetic strategy, solid phase synthesized and suitably protected peptide fragments corresponding to the entire peptide/protein-sequence are condensed on a solid support or in solution, to the target protein. This review summarizes CPS performed utilizing the mild 9-fluorenylmethyloxycarbonyl/tbutyloxycarbonyl-based protecting scheme for the amino acids. Copyright 1999 John Wiley & Sons, Inc.

Entropy in molecular recognition by proteins

PubMed Central

Caro, José A.; Harpole, Kyle W.; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G.; Sharp, Kim A.

2017-01-01

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein–ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein–ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein–ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or “entropy meter” also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water–protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins. PMID:28584100

A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

PubMed

Mobilio, Dominick; Walker, Gary; Brooijmans, Natasja; Nilakantan, Ramaswamy; Denny, R Aldrin; Dejoannis, Jason; Feyfant, Eric; Kowticwar, Rupesh K; Mankala, Jyoti; Palli, Satish; Punyamantula, Sairam; Tatipally, Maneesh; John, Reji K; Humblet, Christine

2010-08-01

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

Predicting Protein–protein Association Rates using Coarse-grained Simulation and Machine Learning

PubMed Central

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-01-01

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate. PMID:28418043

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

PubMed

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.

Study of intermolecular contacts in the proline-rich homeodomain (PRH)-DNA complex using molecular dynamics simulations.

PubMed

Jalili, Seifollah; Karami, Leila

2012-03-01

The proline-rich homeodomain (PRH)-DNA complex consists of a protein with 60 residues and a 13-base-pair DNA. The PRH protein is a transcription factor that plays a key role in the regulation of gene expression. PRH is a significant member of the Q50 class of homeodomain proteins. The homeodomain section of PRH is essential for binding to DNA and mediates sequence-specific DNA binding. Three 20-ns molecular dynamics (MD) simulations (free protein, free DNA and protein-DNA complex) in explicit solvent water were performed to elucidate the intermolecular contacts in the PRH-DNA complex and the role of dynamics of water molecules forming water-mediated contacts. The simulation provides a detailed explanation of the trajectory of hydration water molecules. The simulations show that some water molecules in the protein-DNA interface exchange with bulk waters. The simulation identifies that most of the contacts consisted of direct interactions between the protein and DNA including specific and non-specific contacts, but several water-mediated polar contacts were also observed. The specific interaction between Gln50 and C18 and water-mediated hydrogen bond between Gln50 and T7 were found to be present during almost the entire time of the simulation. These results show good consistency with experimental and previous computational studies. Structural properties such as root-mean-square deviations (RMSD), root-mean-square fluctuations (RMSF) and secondary structure were also analyzed as a function of time. Analyses of the trajectories showed that the dynamic fluctuations of both the protein and the DNA were lowered by the complex formation.

Ceruloplasmin: Macromolecular Assemblies with Iron-Containing Acute Phase Proteins

PubMed Central

Samygina, Valeriya R.; Sokolov, Alexey V.; Bourenkov, Gleb; Petoukhov, Maxim V.; Pulina, Maria O.; Zakharova, Elena T.; Vasilyev, Vadim B.; Bartunik, Hans; Svergun, Dmitri I.

2013-01-01

Copper-containing ferroxidase ceruloplasmin (Cp) forms binary and ternary complexes with cationic proteins lactoferrin (Lf) and myeloperoxidase (Mpo) during inflammation. We present an X-ray crystal structure of a 2Cp-Mpo complex at 4.7 Å resolution. This structure allows one to identify major protein–protein interaction areas and provides an explanation for a competitive inhibition of Mpo by Cp and for the activation of p-phenylenediamine oxidation by Mpo. Small angle X-ray scattering was employed to construct low-resolution models of the Cp-Lf complex and, for the first time, of the ternary 2Cp-2Lf-Mpo complex in solution. The SAXS-based model of Cp-Lf supports the predicted 1∶1 stoichiometry of the complex and demonstrates that both lobes of Lf contact domains 1 and 6 of Cp. The 2Cp-2Lf-Mpo SAXS model reveals the absence of interaction between Mpo and Lf in the ternary complex, so Cp can serve as a mediator of protein interactions in complex architecture. Mpo protects antioxidant properties of Cp by isolating its sensitive loop from proteases. The latter is important for incorporation of Fe3+ into Lf, which activates ferroxidase activity of Cp and precludes oxidation of Cp substrates. Our models provide the structural basis for possible regulatory role of these complexes in preventing iron-induced oxidative damage. PMID:23843990

Architecture of the human interactome defines protein communities and disease networks

PubMed Central

Huttlin, Edward L.; Bruckner, Raphael J.; Paulo, Joao A.; Cannon, Joe R.; Ting, Lily; Baltier, Kurt; Colby, Greg; Gebreab, Fana; Gygi, Melanie P.; Parzen, Hannah; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Pontano-Vaites, Laura; Swarup, Sharan; White, Anne E.; Schweppe, Devin K.; Rad, Ramin; Erickson, Brian K.; Obar, Robert A.; Guruharsha, K.G.; Li, Kejie; Artavanis-Tsakonas, Spyros; Gygi, Steven P.; Harper, J. Wade

2017-01-01

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidation of how genome variation contributes to disease1–3. Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering (MCL)5 of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization. PMID:28514442

Rapid self-assembly of complex biomolecular architectures during mussel byssus biofabrication

PubMed Central

Priemel, Tobias; Degtyar, Elena; Dean, Mason N.; Harrington, Matthew J.

2017-01-01

Protein-based biogenic materials provide important inspiration for the development of high-performance polymers. The fibrous mussel byssus, for instance, exhibits exceptional wet adhesion, abrasion resistance, toughness and self-healing capacity–properties that arise from an intricate hierarchical organization formed in minutes from a fluid secretion of over 10 different protein precursors. However, a poor understanding of this dynamic biofabrication process has hindered effective translation of byssus design principles into synthetic materials. Here, we explore mussel byssus assembly in Mytilus edulis using a synergistic combination of histological staining and confocal Raman microspectroscopy, enabling in situ tracking of specific proteins during induced thread formation from soluble precursors to solid fibres. Our findings reveal critical insights into this complex biological manufacturing process, showing that protein precursors spontaneously self-assemble into complex architectures, while maturation proceeds in subsequent regulated steps. Beyond their biological importance, these findings may guide development of advanced materials with biomedical and industrial relevance. PMID:28262668

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

PubMed

Ashtawy, Hossam M; Mahapatra, Nihar R

2015-01-01

Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex.

Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins

PubMed Central

2015-01-01

Background Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when bound to a receptor protein, from among a large set of candidate poses. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited docking power (or ability to successfully identify the correct pose) has been a major impediment to cost-effective drug discovery. Therefore, in this work, we explore a range of novel SFs employing different machine-learning (ML) approaches in conjunction with physicochemical and geometrical features characterizing protein-ligand complexes to predict the native or near-native pose of a ligand docked to a receptor protein's binding site. We assess the docking accuracies of these new ML SFs as well as those of conventional SFs in the context of the 2007 PDBbind benchmark dataset on both diverse and homogeneous (protein-family-specific) test sets. Further, we perform a systematic analysis of the performance of the proposed SFs in identifying native poses of ligands that are docked to novel protein targets. Results and conclusion We find that the best performing ML SF has a success rate of 80% in identifying poses that are within 1 Å root-mean-square deviation from the native poses of 65 different protein families. This is in comparison to a success rate of only 70% achieved by the best conventional SF, ASP, employed in the commercial docking software GOLD. In addition, the proposed ML SFs perform better on novel proteins that they were never trained on before. We also observed steady gains in the performance of these scoring functions as the training set size and number of features were increased by considering more protein-ligand complexes and/or more computationally-generated poses for each complex. PMID:25916860

Modeling and simulating networks of interdependent protein interactions.

PubMed

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

2018-05-21

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

Recent mass spectrometry-based techniques and considerations for disulfide bond characterization in proteins.

PubMed

Lakbub, Jude C; Shipman, Joshua T; Desaire, Heather

2018-04-01

Disulfide bonds are important structural moieties of proteins: they ensure proper folding, provide stability, and ensure proper function. With the increasing use of proteins for biotherapeutics, particularly monoclonal antibodies, which are highly disulfide bonded, it is now important to confirm the correct disulfide bond connectivity and to verify the presence, or absence, of disulfide bond variants in the protein therapeutics. These studies help to ensure safety and efficacy. Hence, disulfide bonds are among the critical quality attributes of proteins that have to be monitored closely during the development of biotherapeutics. However, disulfide bond analysis is challenging because of the complexity of the biomolecules. Mass spectrometry (MS) has been the go-to analytical tool for the characterization of such complex biomolecules, and several methods have been reported to meet the challenging task of mapping disulfide bonds in proteins. In this review, we describe the relevant, recent MS-based techniques and provide important considerations needed for efficient disulfide bond analysis in proteins. The review focuses on methods for proper sample preparation, fragmentation techniques for disulfide bond analysis, recent disulfide bond mapping methods based on the fragmentation techniques, and automated algorithms designed for rapid analysis of disulfide bonds from liquid chromatography-MS/MS data. Researchers involved in method development for protein characterization can use the information herein to facilitate development of new MS-based methods for protein disulfide bond analysis. In addition, individuals characterizing biotherapeutics, especially by disulfide bond mapping in antibodies, can use this review to choose the best strategies for disulfide bond assignment of their biologic products. Graphical Abstract This review, describing characterization methods for disulfide bonds in proteins, focuses on three critical components: sample preparation, mass spectrometry data, and software tools.

Large-scale inference of protein tissue origin in gram-positive sepsis plasma using quantitative targeted proteomics

PubMed Central

Malmström, Erik; Kilsgård, Ola; Hauri, Simon; Smeds, Emanuel; Herwald, Heiko; Malmström, Lars; Malmström, Johan

2016-01-01

The plasma proteome is highly dynamic and variable, composed of proteins derived from surrounding tissues and cells. To investigate the complex processes that control the composition of the plasma proteome, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in murine plasma. The strategy relies on the construction of a comprehensive protein tissue atlas from cells and highly vascularized organs using shotgun mass spectrometry. The protein tissue atlas was transformed to a spectral library for highly reproducible quantification of tissue-specific proteins directly in plasma using SWATH-like data-independent mass spectrometry analysis. We show that the method can determine drastic changes of tissue-specific protein profiles in blood plasma from mouse animal models with sepsis. The strategy can be extended to several other species advancing our understanding of the complex processes that contribute to the plasma proteome dynamics. PMID:26732734

Activity-Based Protein Profiling of Microbes

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

Sadler, Natalie C.; Wright, Aaron T.

Activity-Based Protein Profiling (ABPP) in conjunction with multimodal characterization techniques has yielded impactful findings in microbiology, particularly in pathogen, bioenergy, drug discovery, and environmental research. Using small molecule chemical probes that react irreversibly with specific proteins or protein families in complex systems has provided insights in enzyme functions in central metabolic pathways, drug-protein interactions, and regulatory protein redox, for systems ranging from photoautotrophic cyanobacteria to mycobacteria, and combining live cell or cell extract ABPP with proteomics, molecular biology, modeling, and other techniques has greatly expanded our understanding of these systems. New opportunities for application of ABPP to microbial systems include:more » enhancing protein annotation, characterizing protein activities in myriad environments, and reveal signal transduction and regulatory mechanisms in microbial systems.« less

Not all transmembrane helices are born equal: Towards the extension of the sequence homology concept to membrane proteins

PubMed Central

2011-01-01

Background Sequence homology considerations widely used to transfer functional annotation to uncharacterized protein sequences require special precautions in the case of non-globular sequence segments including membrane-spanning stretches composed of non-polar residues. Simple, quantitative criteria are desirable for identifying transmembrane helices (TMs) that must be included into or should be excluded from start sequence segments in similarity searches aimed at finding distant homologues. Results We found that there are two types of TMs in membrane-associated proteins. On the one hand, there are so-called simple TMs with elevated hydrophobicity, low sequence complexity and extraordinary enrichment in long aliphatic residues. They merely serve as membrane-anchoring device. In contrast, so-called complex TMs have lower hydrophobicity, higher sequence complexity and some functional residues. These TMs have additional roles besides membrane anchoring such as intra-membrane complex formation, ligand binding or a catalytic role. Simple and complex TMs can occur both in single- and multi-membrane-spanning proteins essentially in any type of topology. Whereas simple TMs have the potential to confuse searches for sequence homologues and to generate unrelated hits with seemingly convincing statistical significance, complex TMs contain essential evolutionary information. Conclusion For extending the homology concept onto membrane proteins, we provide a necessary quantitative criterion to distinguish simple TMs (and a sufficient criterion for complex TMs) in query sequences prior to their usage in homology searches based on assessment of hydrophobicity and sequence complexity of the TM sequence segments. Reviewers This article was reviewed by Shamil Sunyaev, L. Aravind and Arcady Mushegian. PMID:22024092

Blind predictions of protein interfaces by docking calculations in CAPRI.

PubMed

Lensink, Marc F; Wodak, Shoshana J

2010-11-15

Reliable prediction of the amino acid residues involved in protein-protein interfaces can provide valuable insight into protein function, and inform mutagenesis studies, and drug design applications. A fast-growing number of methods are being proposed for predicting protein interfaces, using structural information, energetic criteria, or sequence conservation or by integrating multiple criteria and approaches. Overall however, their performance remains limited, especially when applied to nonobligate protein complexes, where the individual components are also stable on their own. Here, we evaluate interface predictions derived from protein-protein docking calculations. To this end we measure the overlap between the interfaces in models of protein complexes submitted by 76 participants in CAPRI (Critical Assessment of Predicted Interactions) and those of 46 observed interfaces in 20 CAPRI targets corresponding to nonobligate complexes. Our evaluation considers multiple models for each target interface, submitted by different participants, using a variety of docking methods. Although this results in a substantial variability in the prediction performance across participants and targets, clear trends emerge. Docking methods that perform best in our evaluation predict interfaces with average recall and precision levels of about 60%, for a small majority (60%) of the analyzed interfaces. These levels are significantly higher than those obtained for nonobligate complexes by most extant interface prediction methods. We find furthermore that a sizable fraction (24%) of the interfaces in models ranked as incorrect in the CAPRI assessment are actually correctly predicted (recall and precision ≥50%), and that these models contribute to 70% of the correct docking-based interface predictions overall. Our analysis proves that docking methods are much more successful in identifying interfaces than in predicting complexes, and suggests that these methods have an excellent potential of addressing the interface prediction challenge. © 2010 Wiley-Liss, Inc.

Comparative genome analysis reveals a conserved family of actin-like proteins in apicomplexan parasites

PubMed Central

Gordon, Jennifer L; Sibley, L David

2005-01-01

Background The phylum Apicomplexa is an early-branching eukaryotic lineage that contains a number of important human and animal pathogens. Their complex life cycles and unique cytoskeletal features distinguish them from other model eukaryotes. Apicomplexans rely on actin-based motility for cell invasion, yet the regulation of this system remains largely unknown. Consequently, we focused our efforts on identifying actin-related proteins in the recently completed genomes of Toxoplasma gondii, Plasmodium spp., Cryptosporidium spp., and Theileria spp. Results Comparative genomic and phylogenetic studies of apicomplexan genomes reveals that most contain only a single conventional actin and yet they each have 8–10 additional actin-related proteins. Among these are a highly conserved Arp1 protein (likely part of a conserved dynactin complex), and Arp4 and Arp6 homologues (subunits of the chromatin-remodeling machinery). In contrast, apicomplexans lack canonical Arp2 or Arp3 proteins, suggesting they lost the Arp2/3 actin polymerization complex on their evolutionary path towards intracellular parasitism. Seven of these actin-like proteins (ALPs) are novel to apicomplexans. They show no phylogenetic associations to the known Arp groups and likely serve functions specific to this important group of intracellular parasites. Conclusion The large diversity of actin-like proteins in apicomplexans suggests that the actin protein family has diverged to fulfill various roles in the unique biology of intracellular parasites. Conserved Arps likely participate in vesicular transport and gene expression, while apicomplexan-specific ALPs may control unique biological traits such as actin-based gliding motility. PMID:16343347

Structural Confirmation of a Bent and Open Model for the Initiation Complex of T7 RNA Polymerase

PubMed Central

Turingan, Rosemary S.; Liu, Cuihua; Hawkins, Mary E.; Martin, Craig T.

2008-01-01

T7 RNA polymerase is known to induce bending of its promoter DNA upon binding, as evidenced by gel-shift assays and by recent end-to-end fluorescence energy transfer distance measurements. Crystal structures of promoter-bound and initially transcribing complexes, however, lack downstream DNA, providing no information on the overall path of the DNA through the protein. Crystal structures of the elongation complex do include downstream DNA and provide valuable guidance in the design of models for the complete melted bubble structure at initiation. In the current study, we test a specific structural model for the initiation complex, obtained by alignment of the C-terminal regions of the protein structures from both initiation and elongation and then simple transferal of the downstream DNA from the elongation complex onto the initiation complex. FRET measurement of distances from a point upstream on the promoter DNA to various points along the downstream helix reproduce the expected helical periodicity in the distances and support the model’s orientation and phasing of the downstream DNA. The model also makes predictions about the extent of melting downstream of the active site. By monitoring fluorescent base analogs incorporated at various positions in the DNA we have mapped the downstream edge of the bubble, confirming the model. The initially melted bubble, in the absence of substrate, encompasses 7–8 bases and is sufficient to allow synthesis of a 3 base transcript before further melting is required. The results demonstrate that despite massive changes in the N-terminal portion of the protein and in the DNA upstream of the active site, the DNA downstream of the active site is virtually identical in both initiation and elongation complexes. PMID:17253774

Conformational co-dependence between Plasmodium berghei LCCL proteins promotes complex formation and stability.

PubMed

Saeed, Sadia; Tremp, Annie Z; Dessens, Johannes T

2012-10-01

Malaria parasites express a conserved family of LCCL-lectin adhesive-like domain proteins (LAPs) that have essential functions in sporozoite transmission. In Plasmodium falciparum all six family members are expressed in gametocytes and form a multi-protein complex. Intriguingly, knockout of P. falciparum LCCL proteins adversely affects expression of other family members at protein, but not at mRNA level, a phenomenon termed co-dependent expression. Here, we investigate this in Plasmodium berghei by crossing a PbLAP1 null mutant parasite with a parasite line expressing GFP-tagged PbLAP3 that displays strong fluorescence in gametocytes. Selected and validated double mutants show normal synthesis and subcellular localization of PbLAP3::GFP. However, GFP-based fluorescence is dramatically reduced without PbLAP1 present, indicating that PbLAP1 and PbLAP3 interact. Moreover, absence of PbLAP1 markedly reduces the half-life of PbLAP3, consistent with a scenario of misfolding. These findings unveil a potential mechanism of conformational interdependence that facilitates assembly and stability of the functional LCCL protein complex. Copyright © 2012 Elsevier B.V. All rights reserved.

Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

PubMed

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.

[Atomic force microscopy fishing of gp120 on immobilized aptamer and its mass spectrometry identification].

PubMed

Bukharina, N S; Ivanov, Yu D; Pleshakova, T O; Frantsuzov, P A; Andreeva, E Yu; Kaysheva, A L; Izotov, A A; Pavlova, T I; Ziborov, V S; Radko, S P; Archakov, A I

2015-01-01

A method of atomic force microscopy-based fishing (AFM fishing) has been developed for protein detection in the analyte solution using a chip with an immobilized aptamer. This method is based on the biospecific fishing of a target protein from a bulk solution onto the small AFM chip area with the immobilized aptamer to this protein used as the molecular probe. Such aptamer-based approach allows to increase an AFM image contrast compared to the antibody-based approach. Mass spectrometry analysis used after the biospecific fishing to identify the target protein on the AFM chip has proved complex formation. Use of the AFM chip with the immobilized aptamer avoids interference of the antibody and target protein peaks in a mass spectrum.

Mussel-Inspired Protein Nanoparticles Containing Iron(III)-DOPA Complexes for pH-Responsive Drug Delivery.

PubMed

Kim, Bum Jin; Cheong, Hogyun; Hwang, Byeong Hee; Cha, Hyung Joon

2015-06-15

A novel bioinspired strategy for protein nanoparticle (NP) synthesis to achieve pH-responsive drug release exploits the pH-dependent changes in the coordination stoichiometry of iron(III)-3,4-dihydroxyphenylalanine (DOPA) complexes, which play a major cross-linking role in mussel byssal threads. Doxorubicin-loaded polymeric NPs that are based on Fe(III)-DOPA complexation were thus synthesized with a DOPA-modified recombinant mussel adhesive protein through a co-electrospraying process. The release of doxorubicin was found to be predominantly governed by a change in the structure of the Fe(III)-DOPA complexes induced by an acidic pH value. It was also demonstrated that the fabricated NPs exhibited effective cytotoxicity towards cancer cells through efficient cellular uptake and cytosolic release. Therefore, it is anticipated that Fe(III)-DOPA complexation can be successfully utilized as a new design principle for pH-responsive NPs for diverse controlled drug-delivery applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crystal structures of ASK1-inhibtor complexes provide a platform for structure-based drug design

PubMed Central

Singh, Onkar; Shillings, Anthony; Craggs, Peter; Wall, Ian; Rowland, Paul; Skarzynski, Tadeusz; Hobbs, Clare I; Hardwick, Phil; Tanner, Rob; Blunt, Michelle; Witty, David R; Smith, Kathrine J

2013-01-01

ASK1, a member of the MAPK Kinase Kinase family of proteins has been shown to play a key role in cancer, neurodegeneration and cardiovascular diseases and is emerging as a possible drug target. Here we describe a ‘replacement-soaking’ method that has enabled the high-throughput X-ray structure determination of ASK1/ligand complexes. Comparison of the X-ray structures of five ASK1/ligand complexes from 3 different chemotypes illustrates that the ASK1 ATP binding site is able to accommodate a range of chemical diversity and different binding modes. The replacement-soaking system is also able to tolerate some protein flexibility. This crystal system provides a robust platform for ASK1/ligand structure determination and future structure based drug design. PMID:23776076

Ubiquitin C-terminal electrophiles are activity-based probes for identification and mechanistic study of ubiquitin conjugating machinery.

PubMed

Love, Kerry Routenberg; Pandya, Renuka K; Spooner, Eric; Ploegh, Hidde L

2009-04-17

Protein modification by ubiquitin (Ub) and ubiquitin-like modifiers (Ubl) requires the action of activating (E1), conjugating (E2), and ligating (E3) enzymes and is a key step in the specific destruction of proteins. Deubiquitinating enzymes (DUBs) deconjugate substrates modified with Ub/Ubl's and recycle Ub inside the cell. Genome mining based on sequence homology to proteins with known function has assigned many enzymes to this pathway without confirmation of either conjugating or DUB activity. Function-dependent methodologies are still the most useful for rapid identification or assessment of biological activity of expressed proteins from cells. Activity-based protein profiling uses chemical probes that are active-site-directed for the classification of protein activities in complex mixtures. Here we show that the design and use of an expanded set of Ub-based electrophilic probes allowed us to recover and identify members of each enzyme class in the ubiquitin-proteasome system, including E3 ligases and DUBs with previously unverified activity. We show that epitope-tagged Ub-electrophilic probes can be used as activity-based probes for E3 ligase identification by in vitro labeling and activity studies of purified enzymes identified from complex mixtures in cell lysate. Furthermore, the reactivity of our probe with the HECT domain of the E3 Ub ligase ARF-BP1 suggests that multiple cysteines may be in the vicinity of the E2-binding site and are capable of the transfer of Ub to self or to a substrate protein.

In silico work flow for scaffold hopping in Leishmania.

PubMed

Waugh, Barnali; Ghosh, Ambarnil; Bhattacharyya, Dhananjay; Ghoshal, Nanda; Banerjee, Rahul

2014-11-17

Leishmaniasis,a broad spectrum of diseases caused by several sister species of protozoa belonging to family trypanosomatidae and genus leishmania , generally affects poorer sections of the populace in third world countries. With the emergence of strains resistant to traditional therapies and the high cost of second line drugs which generally have severe side effects, it becomes imperative to continue the search for alternative drugs to combat the disease. In this work, the leishmanial genomes and the human genome have been compared to identify proteins unique to the parasite and whose structures (or those of close homologues) are available in the Protein Data Bank. Subsequent to the prioritization of these proteins (based on their essentiality, virulence factor etc.), inhibitors have been identified for a subset of these prospective drug targets by means of an exhaustive literature survey. A set of three dimensional protein-ligand complexes have been assembled from the list of leishmanial drug targets by culling structures from the Protein Data Bank or by means of template based homology modeling followed by ligand docking with the GOLD software. Based on these complexes several structure based pharmacophores have been designed and used to search for alternative inhibitors in the ZINC database. This process led to a list of prospective compounds which could serve as potential antileishmanials. These small molecules were also used to search the Drug Bank to identify prospective lead compounds already in use as approved drugs. Interestingly, paromomycin which is currently being used as an antileishmanial drug spontaneously appeared in the list, probably giving added confidence to the 'scaffold hopping' computational procedures adopted in this work. The report thus provides the basis to experimentally verify several lead compounds for their predicted antileishmanial activity and includes several useful data bases of prospective drug targets in leishmania, their inhibitors and protein--inhibitor three dimensional complexes.

Consistent prediction of GO protein localization.

PubMed

Spetale, Flavio E; Arce, Debora; Krsticevic, Flavia; Bulacio, Pilar; Tapia, Elizabeth

2018-05-17

The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automated GO-CC annotation of proteins suffer from the inconsistency of individual GO-CC term predictions. Here, we present FGGA-CC + , a class of hierarchical graph-based classifiers for the consistent GO-CC annotation of protein coding genes at the subcellular compartment or macromolecular complex levels. Aiming to boost the accuracy of GO-CC predictions, we make use of the protein localization knowledge in the GO-Biological Process (GO-BP) annotations to boost the accuracy of GO-CC prediction. As a result, FGGA-CC + classifiers are built from annotation data in both the GO-CC and GO-BP ontologies. Due to their graph-based design, FGGA-CC + classifiers are fully interpretable and their predictions amenable to expert analysis. Promising results on protein annotation data from five model organisms were obtained. Additionally, successful validation results in the annotation of a challenging subset of tandem duplicated genes in the tomato non-model organism were accomplished. Overall, these results suggest that FGGA-CC + classifiers can indeed be useful for satisfying the huge demand of GO-CC annotation arising from ubiquitous high throughout sequencing and proteomic projects.

Experimental design based 3-D QSAR analysis of steroid-protein interactions: Application to human CBG complexes

NASA Astrophysics Data System (ADS)

Norinder, Ulf

1990-12-01

An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.

A Novel Protein Interaction between Nucleotide Binding Domain of Hsp70 and p53 Motif

PubMed Central

Elengoe, Asita; Naser, Mohammed Abu; Hamdan, Salehhuddin

2015-01-01

Currently, protein interaction of Homo sapiens nucleotide binding domain (NBD) of heat shock 70 kDa protein (PDB: 1HJO) with p53 motif remains to be elucidated. The NBD-p53 motif complex enhances the p53 stabilization, thereby increasing the tumor suppression activity in cancer treatment. Therefore, we identified the interaction between NBD and p53 using STRING version 9.1 program. Then, we modeled the three-dimensional structure of p53 motif through homology modeling and determined the binding affinity and stability of NBD-p53 motif complex structure via molecular docking and dynamics (MD) simulation. Human DNA binding domain of p53 motif (SCMGGMNR) retrieved from UniProt (UniProtKB: P04637) was docked with the NBD protein, using the Autodock version 4.2 program. The binding energy and intermolecular energy for the NBD-p53 motif complex were −0.44 Kcal/mol and −9.90 Kcal/mol, respectively. Moreover, RMSD, RMSF, hydrogen bonds, salt bridge, and secondary structure analyses revealed that the NBD protein had a strong bond with p53 motif and the protein-ligand complex was stable. Thus, the current data would be highly encouraging for designing Hsp70 structure based drug in cancer therapy. PMID:26098630

A Novel Protein Interaction between Nucleotide Binding Domain of Hsp70 and p53 Motif.

PubMed

Elengoe, Asita; Naser, Mohammed Abu; Hamdan, Salehhuddin

2015-01-01

Currently, protein interaction of Homo sapiens nucleotide binding domain (NBD) of heat shock 70 kDa protein (PDB: 1HJO) with p53 motif remains to be elucidated. The NBD-p53 motif complex enhances the p53 stabilization, thereby increasing the tumor suppression activity in cancer treatment. Therefore, we identified the interaction between NBD and p53 using STRING version 9.1 program. Then, we modeled the three-dimensional structure of p53 motif through homology modeling and determined the binding affinity and stability of NBD-p53 motif complex structure via molecular docking and dynamics (MD) simulation. Human DNA binding domain of p53 motif (SCMGGMNR) retrieved from UniProt (UniProtKB: P04637) was docked with the NBD protein, using the Autodock version 4.2 program. The binding energy and intermolecular energy for the NBD-p53 motif complex were -0.44 Kcal/mol and -9.90 Kcal/mol, respectively. Moreover, RMSD, RMSF, hydrogen bonds, salt bridge, and secondary structure analyses revealed that the NBD protein had a strong bond with p53 motif and the protein-ligand complex was stable. Thus, the current data would be highly encouraging for designing Hsp70 structure based drug in cancer therapy.

The GARP Complex Is Involved in Intracellular Cholesterol Transport via Targeting NPC2 to Lysosomes.

PubMed

Wei, Jian; Zhang, Ying-Yu; Luo, Jie; Wang, Ju-Qiong; Zhou, Yu-Xia; Miao, Hong-Hua; Shi, Xiong-Jie; Qu, Yu-Xiu; Xu, Jie; Li, Bo-Liang; Song, Bao-Liang

2017-06-27

Proper intracellular cholesterol trafficking is critical for cellular function. Two lysosome-resident proteins, NPC1 and NPC2, mediate the egress of low-density lipoprotein-derived cholesterol from lysosomes. However, other proteins involved in this process remain largely unknown. Through amphotericin B-based selection, we isolated two cholesterol transport-defective cell lines. Subsequent whole-transcriptome-sequencing analysis revealed two cell lines bearing the same mutation in the vacuolar protein sorting 53 (Vps53) gene. Depletion of VPS53 or other subunits of the Golgi-associated retrograde protein (GARP) complex impaired NPC2 sorting to lysosomes and caused cholesterol accumulation. GARP deficiency blocked the retrieval of the cation-independent mannose 6-phosphate receptor (CI-MPR) to the trans-Golgi network. Further, Vps54 mutant mice displayed reduced cellular NPC2 protein levels and increased cholesterol accumulation, underscoring the physiological role of the GARP complex in cholesterol transport. We conclude that the GARP complex contributes to intracellular cholesterol transport by targeting NPC2 to lysosomes in a CI-MPR-dependent manner. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Rescore protein-protein docked ensembles with an interface contact statistics.

PubMed

Mezei, Mihaly

2017-02-01

The recently developed statistical measure for the type of residue-residue contact at protein complex interfaces, based on a parameter-free definition of contact, has been used to define a contact score that is correlated with the likelihood of correctness of a proposed complex structure. Comparing the proposed contact scores on the native structure and on a set of model structures the proposed measure was shown to generally favor the native structure but in itself was not able to reliably score the native structure to be the best. Adjusting the scores of redocking experiments with the contact score showed that the adjusted score was able to move up the ranking of the native-like structure among the proposed complexes when the native-like was not ranked the best by the respective program. Tests on docking of unbound proteins compared the contact scores of the complexes with the contact score of the crystal structure again showing the tendency of the contact score to favor native-like conformations. The possibility of using the contact score to improve the determination of biological dimers in a crystal structure was also explored. Proteins 2017; 85:235-241. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Functional Assembly of Soluble and Membrane Recombinant Proteins of Mammalian NADPH Oxidase Complex.

PubMed

Souabni, Hajer; Ezzine, Aymen; Bizouarn, Tania; Baciou, Laura

2017-01-01

Activation of phagocyte cells from an innate immune system is associated with a massive consumption of molecular oxygen to generate highly reactive oxygen species (ROS) as microbial weapons. This is achieved by a multiprotein complex, the so-called NADPH oxidase. The activity of phagocyte NADPH oxidase relies on an assembly of more than five proteins, among them the membrane heterodimer named flavocytochrome b 558 (Cytb 558 ), constituted by the tight association of the gp91 phox (also named Nox2) and p22 phox proteins. The Cytb 558 is the membrane catalytic core of the NADPH oxidase complex, through which the reducing equivalent provided by NADPH is transferred via the associated prosthetic groups (one flavin and two hemes) to reduce dioxygen into superoxide anion. The other major proteins (p47 phox , p67 phox , p40 phox , Rac) requisite for the complex activity are cytosolic proteins. Thus, the NADPH oxidase functioning relies on a synergic multi-partner assembly that in vivo can be hardly studied at the molecular level due to the cell complexity. Thus, a cell-free assay method has been developed to study the NADPH oxidase activity that allows measuring and eventually quantifying the ROS generation based on optical techniques following reduction of cytochrome c. This setup is a valuable tool for the identification of protein interactions, of crucial components and additives for a functional enzyme. Recently, this method was improved by the engineering and the production of a complete recombinant NADPH oxidase complex using the combination of purified proteins expressed in bacterial and yeast host cells. The reconstitution into artificial membrane leads to a fully controllable system that permits fine functional studies.

The DnaJ-Like Zinc-Finger Protein HCF222 Is Required for Thylakoid Membrane Biogenesis in Plants1[OPEN

PubMed Central

Hartings, Stephanie; Paradies, Susanne; Karnuth, Bianca; Eisfeld, Sabrina; Mehsing, Jasmin; Wolff, Christian; Levey, Tatjana

2017-01-01

To understand the biogenesis of the thylakoid membrane in higher plants and to identify auxiliary proteins required to build up this highly complex membrane system, we have characterized the allelic nuclear mutants high chlorophyll fluorescence222-1 (hcf222-1) and hcf222-2 and isolated the causal gene by map-based cloning. In the ethyl methanesulfonate-induced mutant hcf222-1, the accumulation of the cytochrome b6f (Cytb6f) complex was reduced to 30% compared with the wild type. Other thylakoid membrane complexes accumulated to normal levels. The T-DNA knockout mutant hcf222-2 showed a more severe defect with respect to thylakoid membrane proteins and accumulated only 10% of the Cytb6f complex, accompanied by a reduction in photosystem II, the photosystem II light-harvesting complex, and photosystem I. HCF222 encodes a protein of 99 amino acids in Arabidopsis (Arabidopsis thaliana) that has similarities to the cysteine-rich zinc-binding domain of DnaJ chaperones. The insulin precipitation assay demonstrated that HCF222 has disulfide reductase activity in vitro. The protein is conserved in higher plants and bryophytes but absent in algae and cyanobacteria. Confocal fluorescence microscopy showed that a fraction of HCF222-green fluorescent protein was detectable in the endoplasmic reticulum but that it also could be recognized in chloroplasts. A fusion construct of HCF222 containing a plastid transit peptide targets the protein into chloroplasts and was able to complement the mutational defect. These findings indicate that the chloroplast-targeted HCF222 is indispensable for the maturation and/or assembly of the Cytb6f complex and is very likely involved in thiol-disulfide biochemistry at the thylakoid membrane. PMID:28572458

The DnaJ-Like Zinc-Finger Protein HCF222 Is Required for Thylakoid Membrane Biogenesis in Plants.

PubMed

Hartings, Stephanie; Paradies, Susanne; Karnuth, Bianca; Eisfeld, Sabrina; Mehsing, Jasmin; Wolff, Christian; Levey, Tatjana; Westhoff, Peter; Meierhoff, Karin

2017-07-01

To understand the biogenesis of the thylakoid membrane in higher plants and to identify auxiliary proteins required to build up this highly complex membrane system, we have characterized the allelic nuclear mutants high chlorophyll fluorescence222-1 ( hcf222-1 ) and hcf222-2 and isolated the causal gene by map-based cloning. In the ethyl methanesulfonate-induced mutant hcf222-1 , the accumulation of the cytochrome b 6 f (Cytb6f) complex was reduced to 30% compared with the wild type. Other thylakoid membrane complexes accumulated to normal levels. The T-DNA knockout mutant hcf222-2 showed a more severe defect with respect to thylakoid membrane proteins and accumulated only 10% of the Cytb6f complex, accompanied by a reduction in photosystem II, the photosystem II light-harvesting complex, and photosystem I. HCF222 encodes a protein of 99 amino acids in Arabidopsis ( Arabidopsis thaliana ) that has similarities to the cysteine-rich zinc-binding domain of DnaJ chaperones. The insulin precipitation assay demonstrated that HCF222 has disulfide reductase activity in vitro. The protein is conserved in higher plants and bryophytes but absent in algae and cyanobacteria. Confocal fluorescence microscopy showed that a fraction of HCF222-green fluorescent protein was detectable in the endoplasmic reticulum but that it also could be recognized in chloroplasts. A fusion construct of HCF222 containing a plastid transit peptide targets the protein into chloroplasts and was able to complement the mutational defect. These findings indicate that the chloroplast-targeted HCF222 is indispensable for the maturation and/or assembly of the Cytb6f complex and is very likely involved in thiol-disulfide biochemistry at the thylakoid membrane. © 2017 American Society of Plant Biologists. All Rights Reserved.

How much do we know about the coupling of G-proteins to serotonin receptors?

PubMed Central

2014-01-01

Serotonin receptors are G-protein-coupled receptors (GPCRs) involved in a variety of psychiatric disorders. G-proteins, heterotrimeric complexes that couple to multiple receptors, are activated when their receptor is bound by the appropriate ligand. Activation triggers a cascade of further signalling events that ultimately result in cell function changes. Each of the several known G-protein types can activate multiple pathways. Interestingly, since several G-proteins can couple to the same serotonin receptor type, receptor activation can result in induction of different pathways. To reach a better understanding of the role, interactions and expression of G-proteins a literature search was performed in order to list all the known heterotrimeric combinations and serotonin receptor complexes. Public databases were analysed to collect transcript and protein expression data relating to G-proteins in neural tissues. Only a very small number of heterotrimeric combinations and G-protein-receptor complexes out of the possible thousands suggested by expression data analysis have been examined experimentally. In addition this has mostly been obtained using insect, hamster, rat and, to a lesser extent, human cell lines. Besides highlighting which interactions have not been explored, our findings suggest additional possible interactions that should be examined based on our expression data analysis. PMID:25011628

How much do we know about the coupling of G-proteins to serotonin receptors?

PubMed

Giulietti, Matteo; Vivenzio, Viviana; Piva, Francesco; Principato, Giovanni; Bellantuono, Cesario; Nardi, Bernardo

2014-07-10

Serotonin receptors are G-protein-coupled receptors (GPCRs) involved in a variety of psychiatric disorders. G-proteins, heterotrimeric complexes that couple to multiple receptors, are activated when their receptor is bound by the appropriate ligand. Activation triggers a cascade of further signalling events that ultimately result in cell function changes. Each of the several known G-protein types can activate multiple pathways. Interestingly, since several G-proteins can couple to the same serotonin receptor type, receptor activation can result in induction of different pathways. To reach a better understanding of the role, interactions and expression of G-proteins a literature search was performed in order to list all the known heterotrimeric combinations and serotonin receptor complexes. Public databases were analysed to collect transcript and protein expression data relating to G-proteins in neural tissues. Only a very small number of heterotrimeric combinations and G-protein-receptor complexes out of the possible thousands suggested by expression data analysis have been examined experimentally. In addition this has mostly been obtained using insect, hamster, rat and, to a lesser extent, human cell lines. Besides highlighting which interactions have not been explored, our findings suggest additional possible interactions that should be examined based on our expression data analysis.

Hydrodynamic size-based separation and characterization of protein aggregates from total cell lysates

PubMed Central

Tanase, Maya; Zolla, Valerio; Clement, Cristina C; Borghi, Francesco; Urbanska, Aleksandra M; Rodriguez-Navarro, Jose Antonio; Roda, Barbara; Zattoni, Andrea; Reschiglian, Pierluigi; Cuervo, Ana Maria; Santambrogio, Laura

2016-01-01

Herein we describe a protocol that uses hollow-fiber flow field-flow fractionation (FFF) coupled with multiangle light scattering (MALS) for hydrodynamic size-based separation and characterization of complex protein aggregates. The fractionation method, which requires 1.5 h to run, was successfully modified from the analysis of protein aggregates, as found in simple protein mixtures, to complex aggregates, as found in total cell lysates. In contrast to other related methods (filter assay, analytical ultracentrifugation, gel electrophoresis and size-exclusion chromatography), hollow-fiber flow FFF coupled with MALS allows a flow-based fractionation of highly purified protein aggregates and simultaneous measurement of their molecular weight, r.m.s. radius and molecular conformation (e.g., round, rod-shaped, compact or relaxed). The polyethersulfone hollow fibers used, which have a 0.8-mm inner diameter, allow separation of as little as 20 μg of total cell lysates. In addition, the ability to run the samples in different denaturing and nondenaturing buffer allows defining true aggregates from artifacts, which can form during sample preparation. The protocol was set up using Paraquat-induced carbonylation, a model that induces protein aggregation in cultured cells. This technique will advance the biochemical, proteomic and biophysical characterization of molecular-weight aggregates associated with protein mutations, as found in many CNS degenerative diseases, or chronic oxidative stress, as found in aging, and chronic metabolic and inflammatory conditions. PMID:25521790

Analysis of Structural Features Contributing to Weak Affinities of Ubiquitin/Protein Interactions.

PubMed

Cohen, Ariel; Rosenthal, Eran; Shifman, Julia M

2017-11-10

Ubiquitin is a small protein that enables one of the most common post-translational modifications, where the whole ubiquitin molecule is attached to various target proteins, forming mono- or polyubiquitin conjugations. As a prototypical multispecific protein, ubiquitin interacts non-covalently with a variety of proteins in the cell, including ubiquitin-modifying enzymes and ubiquitin receptors that recognize signals from ubiquitin-conjugated substrates. To enable recognition of multiple targets and to support fast dissociation from the ubiquitin modifying enzymes, ubiquitin/protein interactions are characterized with low affinities, frequently in the higher μM and lower mM range. To determine how structure encodes low binding affinity of ubiquitin/protein complexes, we analyzed structures of more than a hundred such complexes compiled in the Ubiquitin Structural Relational Database. We calculated various structure-based features of ubiquitin/protein binding interfaces and compared them to the same features of general protein-protein interactions (PPIs) with various functions and generally higher affinities. Our analysis shows that ubiquitin/protein binding interfaces on average do not differ in size and shape complementarity from interfaces of higher-affinity PPIs. However, they contain fewer favorable hydrogen bonds and more unfavorable hydrophobic/charge interactions. We further analyzed how binding interfaces change upon affinity maturation of ubiquitin toward its target proteins. We demonstrate that while different features are improved in different experiments, the majority of the evolved complexes exhibit better shape complementarity and hydrogen bond pattern compared to wild-type complexes. Our analysis helps to understand how low-affinity PPIs have evolved and how they could be converted into high-affinity PPIs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Binding Free Energy Change Caused by Point Mutations with Knowledge-Modified MM/PBSA Method.

PubMed

Petukh, Marharyta; Li, Minghui; Alexov, Emil

2015-07-01

A new methodology termed Single Amino Acid Mutation based change in Binding free Energy (SAAMBE) was developed to predict the changes of the binding free energy caused by mutations. The method utilizes 3D structures of the corresponding protein-protein complexes and takes advantage of both approaches: sequence- and structure-based methods. The method has two components: a MM/PBSA-based component, and an additional set of statistical terms delivered from statistical investigation of physico-chemical properties of protein complexes. While the approach is rigid body approach and does not explicitly consider plausible conformational changes caused by the binding, the effect of conformational changes, including changes away from binding interface, on electrostatics are mimicked with amino acid specific dielectric constants. This provides significant improvement of SAAMBE predictions as indicated by better match against experimentally determined binding free energy changes over 1300 mutations in 43 proteins. The final benchmarking resulted in a very good agreement with experimental data (correlation coefficient 0.624) while the algorithm being fast enough to allow for large-scale calculations (the average time is less than a minute per mutation).

Clustering biomolecular complexes by residue contacts similarity.

PubMed

Rodrigues, João P G L M; Trellet, Mikaël; Schmitz, Christophe; Kastritis, Panagiotis; Karaca, Ezgi; Melquiond, Adrien S J; Bonvin, Alexandre M J J

2012-07-01

Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions. Albeit widely used, these measures suffer from several theoretical and technical limitations (e.g., choice of regions for fitting) that impair their application in multicomponent systems (N > 2), large-scale studies (e.g., interactomes), and other time-critical scenarios. We present here a simple similarity measure for structural clustering based on atomic contacts--the fraction of common contacts--and compare it with the most used similarity measure of the protein docking community--interface backbone RMSD. We show that this method produces very compact clusters in remarkably short time when applied to a collection of binary and multicomponent protein-protein and protein-DNA complexes. Furthermore, it allows easy clustering of similar conformations of multicomponent symmetrical assemblies in which chain permutations can occur. Simple contact-based metrics should be applicable to other structural biology clustering problems, in particular for time-critical or large-scale endeavors. Copyright © 2012 Wiley Periodicals, Inc.

The NESH/Abi-3-based WAVE2 complex is functionally distinct from the Abi-1-based WAVE2 complex.

PubMed

Sekino, Saki; Kashiwagi, Yuriko; Kanazawa, Hitoshi; Takada, Kazuki; Baba, Takashi; Sato, Seiichi; Inoue, Hiroki; Kojima, Masaki; Tani, Katsuko

2015-10-01

Abl interactor (Abi) family proteins play significant roles in actin cytoskeleton organization through participation in the WAVE complex. Mammals possess three Abi proteins: Abi-1, Abi-2, and NESH/Abi-3. Abi-1 and Abi-2 were originally identified as Abl tyrosine kinase-binding proteins. It has been disclosed that Abi-1 acts as a bridge between c-Abl and WAVE2, and c-Abl-mediated WAVE2 phosphorylation promotes actin remodeling. We showed previously that NESH/Abi-3 is present in the WAVE2 complex, but neither binds to c-Abl nor promotes c-Abl-mediated phosphorylation of WAVE2. In this study, we characterized NESH/Abi-3 in more detail, and compared its properties with those of Abi-1 and Abi-2. NESH/Abi-3 was ectopically expressed in NIH3T3 cells, in which Abi-1, but not NESH/Abi-3, is expressed. The expression of NESH/Abi-3 caused degradation of endogenous Abi-1, which led to the formation of a NESH/Abi-3-based WAVE2 complex. When these cells were plated on fibronectin-coated dishes, the translocation of WAVE2 to the plasma membrane was significantly reduced and the formation of peripheral lamellipodial structures was disturbed, suggesting that the NESH/Abi-3-based WAVE2 complex was unable to help produce lamellipodial protrusions. Next, Abi-1, Abi-2, or NESH/Abi-3 was expressed in v-src-transformed NIH3T3 cells. Only in NESH/Abi-3-expressed cells did treatment with an Abl kinase inhibitor, imatinib mesylate, or siRNA-mediated knockdown of c-Abl promote the formation of invadopodia, which are ventral membrane protrusions with extracellular matrix degradation activity. Structural studies showed that a linker region between the proline-rich regions and the Src homology 3 (SH3) domain of Abi-1 is crucial for its interaction with c-Abl and c-Abl-mediated phosphorylation of WAVE2. The NESH/Abi-3-based WAVE2 complex is functionally distinct from the Abi-1-based one, and NESH/Abi-3 may be involved in the formation of ventral protrusions under certain conditions.

Photoelectrochemical Complexes of Fucoxanthin-Chlorophyll Protein for Bio-Photovoltaic Conversion with a High Open-Circuit Photovoltage.

PubMed

Zhang, Tianning; Liu, Cheng; Dong, Wenjing; Wang, Wenda; Sun, Yan; Chen, Xin; Yang, Chunhong; Dai, Ning

2017-12-05

Open-circuit photovoltage (V oc ) is among the critical parameters for achieving an efficient light-to-charge conversion in existing solar photovoltaic devices. Natural photosynthesis exploits light-harvesting chlorophyll (Chl) protein complexes to transfer sunlight energy efficiently. We describe the exploitation of photosynthetic fucoxanthin-chlorophyll protein (FCP) complexes for realizing photoelectrochemical cells with a high V oc . An antenna-dependent photocurrent response and a V oc up to 0.72 V are observed and demonstrated in the bio-photovoltaic devices fabricated with photosynthetic FCP complexes and TiO 2 nanostructures. Such high V oc is determined by fucoxanthin in FCP complexes, and is rarely found in photoelectrochemical cells with other natural light-harvesting antenna. We think that the FCP-based bio-photovoltaic conversion will provide an opportunity to fabricate environmental benign photoelectrochemical cells with high V oc , and also help improve the understanding of the essential physics behind the light-to-charge conversion in photosynthetic complexes. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Survey of large protein complexes D. vulgaris reveals great structural diversity

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

Han, B.-G.; Dong, M.; Liu, H.

2009-08-15

An unbiased survey has been made of the stable, most abundant multi-protein complexes in Desulfovibrio vulgaris Hildenborough (DvH) that are larger than Mr {approx} 400 k. The quaternary structures for 8 of the 16 complexes purified during this work were determined by single-particle reconstruction of negatively stained specimens, a success rate {approx}10 times greater than that of previous 'proteomic' screens. In addition, the subunit compositions and stoichiometries of the remaining complexes were determined by biochemical methods. Our data show that the structures of only two of these large complexes, out of the 13 in this set that have recognizable functions,more » can be modeled with confidence based on the structures of known homologs. These results indicate that there is significantly greater variability in the way that homologous prokaryotic macromolecular complexes are assembled than has generally been appreciated. As a consequence, we suggest that relying solely on previously determined quaternary structures for homologous proteins may not be sufficient to properly understand their role in another cell of interest.« less

Mass spectrometric identification of proteins in complex post-genomic projects. Soluble proteins of the metabolically versatile, denitrifying 'Aromatoleum' sp. strain EbN1.

PubMed

Hufnagel, Peter; Rabus, Ralf

2006-01-01

The rapidly developing proteomics technologies help to advance the global understanding of physiological and cellular processes. The lifestyle of a study organism determines the type and complexity of a given proteomic project. The complexity of this study is characterized by a broad collection of pathway-specific subproteomes, reflecting the metabolic versatility as well as the regulatory potential of the aromatic-degrading, denitrifying bacterium 'Aromatoleum' sp. strain EbN1. Differences in protein profiles were determined using a gel-based approach. Protein identification was based on a progressive application of MALDI-TOF-MS, MALDI-TOF-MS/MS and LC-ESI-MS/MS. This progression was result-driven and automated by software control. The identification rate was increased by the assembly of a project-specific list of background signals that was used for internal calibration of the MS spectra, and by the combination of two search engines using a dedicated MetaScoring algorithm. In total, intelligent bioinformatics could increase the identification yield from 53 to 70% of the analyzed 5,050 gel spots; a total of 556 different proteins were identified. MS identification was highly reproducible: most proteins were identified more than twice from parallel 2DE gels with an average sequence coverage of >50% and rather restrictive score thresholds (Mascot >or=95, ProFound >or=2.2, MetaScore >or=97). The MS technologies and bioinformatics tools that were implemented and integrated to handle this complex proteomic project are presented. In addition, we describe the basic principles and current developments of the applied technologies and provide an overview over the current state of microbial proteome research. Copyright (c) 2006 S. Karger AG, Basel.

Local Geometry and Evolutionary Conservation of Protein Surfaces Reveal the Multiple Recognition Patches in Protein-Protein Interactions

PubMed Central

Laine, Elodie; Carbone, Alessandra

2015-01-01

Protein-protein interactions (PPIs) are essential to all biological processes and they represent increasingly important therapeutic targets. Here, we present a new method for accurately predicting protein-protein interfaces, understanding their properties, origins and binding to multiple partners. Contrary to machine learning approaches, our method combines in a rational and very straightforward way three sequence- and structure-based descriptors of protein residues: evolutionary conservation, physico-chemical properties and local geometry. The implemented strategy yields very precise predictions for a wide range of protein-protein interfaces and discriminates them from small-molecule binding sites. Beyond its predictive power, the approach permits to dissect interaction surfaces and unravel their complexity. We show how the analysis of the predicted patches can foster new strategies for PPIs modulation and interaction surface redesign. The approach is implemented in JET2, an automated tool based on the Joint Evolutionary Trees (JET) method for sequence-based protein interface prediction. JET2 is freely available at www.lcqb.upmc.fr/JET2. PMID:26690684

Energy design for protein-protein interactions

PubMed Central

Ravikant, D. V. S.; Elber, Ron

2011-01-01

Proteins bind to other proteins efficiently and specifically to carry on many cell functions such as signaling, activation, transport, enzymatic reactions, and more. To determine the geometry and strength of binding of a protein pair, an energy function is required. An algorithm to design an optimal energy function, based on empirical data of protein complexes, is proposed and applied. Emphasis is made on negative design in which incorrect geometries are presented to the algorithm that learns to avoid them. For the docking problem the search for plausible geometries can be performed exhaustively. The possible geometries of the complex are generated on a grid with the help of a fast Fourier transform algorithm. A novel formulation of negative design makes it possible to investigate iteratively hundreds of millions of negative examples while monotonically improving the quality of the potential. Experimental structures for 640 protein complexes are used to generate positive and negative examples for learning parameters. The algorithm designed in this work finds the correct binding structure as the lowest energy minimum in 318 cases of the 640 examples. Further benchmarks on independent sets confirm the significant capacity of the scoring function to recognize correct modes of interactions. PMID:21842951

Quantitative interaction analysis permits molecular insights into functional NOX4 NADPH oxidase heterodimer assembly.

PubMed

O'Neill, Sharon; Mathis, Magalie; Kovačič, Lidija; Zhang, Suisheng; Reinhardt, Jürgen; Scholz, Dimitri; Schopfer, Ulrich; Bouhelal, Rochdi; Knaus, Ulla G

2018-06-08

Protein-protein interactions critically regulate many biological systems, but quantifying functional assembly of multipass membrane complexes in their native context is still challenging. Here, we combined modeling-assisted protein modification and information from human disease variants with a minimal-size fusion tag, split-luciferase-based approach to probe assembly of the NADPH oxidase 4 (NOX4)-p22 phox enzyme, an integral membrane complex with unresolved structure, which is required for electron transfer and generation of reactive oxygen species (ROS). Integrated analyses of heterodimerization, trafficking, and catalytic activity identified determinants for the NOX4-p22 phox interaction, such as heme incorporation into NOX4 and hot spot residues in transmembrane domains 1 and 4 in p22 phox Moreover, their effect on NOX4 maturation and ROS generation was analyzed. We propose that this reversible and quantitative protein-protein interaction technique with its small split-fragment approach will provide a protein engineering and discovery tool not only for NOX research, but also for other intricate membrane protein complexes, and may thereby facilitate new drug discovery strategies for managing NOX-associated diseases. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Placental Proteomics: A Shortcut to Biological Insight

PubMed Central

Robinson, John M.; Vandré, Dale D.; Ackerman, William E.

2012-01-01

Proteomics analysis of biological samples has the potential to identify novel protein expression patterns and/or changes in protein expression patterns in different developmental or disease states. An important component of successful proteomics research, at least in its present form, is to reduce the complexity of the sample if it is derived from cells or tissues. One method to simplify complex tissues is to focus on a specific, highly purified sub-proteome. Using this approach we have developed methods to prepare highly enriched fractions of the apical plasma membrane of the syncytiotrophoblast. Through proteomics analysis of this fraction we have identified over five hundred proteins several of which were previously not known to reside in the syncytiotrophoblast. Herein, we focus on two of these, dysferlin and myoferlin. These proteins, largely known from studies of skeletal muscle, may not have been found in the human placenta were it not for discovery-based proteomics analysis. This new knowledge, acquired through a discovery-driven approach, can now be applied for the generation of hypothesis-based experimentation. Thus discovery-based and hypothesis-based research are complimentary approaches that when coupled together can hasten scientific discoveries. PMID:19070895

Simulating evolution of protein complexes through gene duplication and co-option.

PubMed

Haarsma, Loren; Nelesen, Serita; VanAndel, Ethan; Lamine, James; VandeHaar, Peter

2016-06-21

We present a model of the evolution of protein complexes with novel functions through gene duplication, mutation, and co-option. Under a wide variety of input parameters, digital organisms evolve complexes of 2-5 bound proteins which have novel functions but whose component proteins are not independently functional. Evolution of complexes with novel functions happens more quickly as gene duplication rates increase, point mutation rates increase, protein complex functional probability increases, protein complex functional strength increases, and protein family size decreases. Evolution of complexity is inhibited when the metabolic costs of making proteins exceeds the fitness gain of having functional proteins, or when point mutation rates get so large the functional proteins undergo deleterious mutations faster than new functional complexes can evolve. Copyright © 2016 Elsevier Ltd. All rights reserved.

3D-SURFER 2.0: web platform for real-time search and characterization of protein surfaces.

PubMed

Xiong, Yi; Esquivel-Rodriguez, Juan; Sael, Lee; Kihara, Daisuke

2014-01-01

The increasing number of uncharacterized protein structures necessitates the development of computational approaches for function annotation using the protein tertiary structures. Protein structure database search is the basis of any structure-based functional elucidation of proteins. 3D-SURFER is a web platform for real-time protein surface comparison of a given protein structure against the entire PDB using 3D Zernike descriptors. It can smoothly navigate the protein structure space in real-time from one query structure to another. A major new feature of Release 2.0 is the ability to compare the protein surface of a single chain, a single domain, or a single complex against databases of protein chains, domains, complexes, or a combination of all three in the latest PDB. Additionally, two types of protein structures can now be compared: all-atom-surface and backbone-atom-surface. The server can also accept a batch job for a large number of database searches. Pockets in protein surfaces can be identified by VisGrid and LIGSITE (csc) . The server is available at http://kiharalab.org/3d-surfer/.

Protein docking prediction using predicted protein-protein interface.

PubMed

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles

PubMed Central

Brender, Jeffrey R.; Zhang, Yang

2015-01-01

The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies. PMID:26506533

Performance of MDockPP in CAPRI rounds 28-29 and 31-35 including the prediction of water-mediated interactions.

PubMed

Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Ma, Zhiwei; Grinter, Sam Z; Zou, Xiaoqin

2017-03-01

Protein-protein interactions are either through direct contacts between two binding partners or mediated by structural waters. Both direct contacts and water-mediated interactions are crucial to the formation of a protein-protein complex. During the recent CAPRI rounds, a novel parallel searching strategy for predicting water-mediated interactions is introduced into our protein-protein docking method, MDockPP. Briefly, a FFT-based docking algorithm is employed in generating putative binding modes, and an iteratively derived statistical potential-based scoring function, ITScorePP, in conjunction with biological information is used to assess and rank the binding modes. Up to 10 binding modes are selected as the initial protein-protein complex structures for MD simulations in explicit solvent. Water molecules near the interface are clustered based on the snapshots extracted from independent equilibrated trajectories. Then, protein-ligand docking is employed for a parallel search for water molecules near the protein-protein interface. The water molecules generated by ligand docking and the clustered water molecules generated by MD simulations are merged, referred to as the predicted structural water molecules. Here, we report the performance of this protocol for CAPRI rounds 28-29 and 31-35 containing 20 valid docking targets and 11 scoring targets. In the docking experiments, we predicted correct binding modes for nine targets, including one high-accuracy, two medium-accuracy, and six acceptable predictions. Regarding the two targets for the prediction of water-mediated interactions, we achieved models ranked as "excellent" in accordance with the CAPRI evaluation criteria; one of these two targets is considered as a difficult target for structural water prediction. Proteins 2017; 85:424-434. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

NMR approaches in structure-based lead discovery: recent developments and new frontiers for targeting multi-protein complexes.

PubMed

Dias, David M; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Origin and Evolutionary Alteration of the Mitochondrial Import System in Eukaryotic Lineages

PubMed Central

Fukasawa, Yoshinori; Oda, Toshiyuki; Tomii, Kentaro

2017-01-01

Abstract Protein transport systems are fundamentally important for maintaining mitochondrial function. Nevertheless, mitochondrial protein translocases such as the kinetoplastid ATOM complex have recently been shown to vary in eukaryotic lineages. Various evolutionary hypotheses have been formulated to explain this diversity. To resolve any contradiction, estimating the primitive state and clarifying changes from that state are necessary. Here, we present more likely primitive models of mitochondrial translocases, specifically the translocase of the outer membrane (TOM) and translocase of the inner membrane (TIM) complexes, using scrutinized phylogenetic profiles. We then analyzed the translocases’ evolution in eukaryotic lineages. Based on those results, we propose a novel evolutionary scenario for diversification of the mitochondrial transport system. Our results indicate that presequence transport machinery was mostly established in the last eukaryotic common ancestor, and that primitive translocases already had a pathway for transporting presequence-containing proteins. Moreover, secondary changes including convergent and migrational gains of a presequence receptor in TOM and TIM complexes, respectively, likely resulted from constrained evolution. The nature of a targeting signal can constrain alteration to the protein transport complex. PMID:28369657

Quantitative interaction proteomics using mass spectrometry.

PubMed

Wepf, Alexander; Glatter, Timo; Schmidt, Alexander; Aebersold, Ruedi; Gstaiger, Matthias

2009-03-01

We present a mass spectrometry-based strategy for the absolute quantification of protein complex components isolated through affinity purification. We quantified bait proteins via isotope-labeled reference peptides corresponding to an affinity tag sequence and prey proteins by label-free correlational quantification using the precursor ion signal intensities of proteotypic peptides generated in reciprocal purifications. We used this method to quantitatively analyze interaction stoichiometries in the human protein phosphatase 2A network.

A rapid and accurate approach for prediction of interactomes from co-elution data (PrInCE).

PubMed

Stacey, R Greg; Skinnider, Michael A; Scott, Nichollas E; Foster, Leonard J

2017-10-23

An organism's protein interactome, or complete network of protein-protein interactions, defines the protein complexes that drive cellular processes. Techniques for studying protein complexes have traditionally applied targeted strategies such as yeast two-hybrid or affinity purification-mass spectrometry to assess protein interactions. However, given the vast number of protein complexes, more scalable methods are necessary to accelerate interaction discovery and to construct whole interactomes. We recently developed a complementary technique based on the use of protein correlation profiling (PCP) and stable isotope labeling in amino acids in cell culture (SILAC) to assess chromatographic co-elution as evidence of interacting proteins. Importantly, PCP-SILAC is also capable of measuring protein interactions simultaneously under multiple biological conditions, allowing the detection of treatment-specific changes to an interactome. Given the uniqueness and high dimensionality of co-elution data, new tools are needed to compare protein elution profiles, control false discovery rates, and construct an accurate interactome. Here we describe a freely available bioinformatics pipeline, PrInCE, for the analysis of co-elution data. PrInCE is a modular, open-source library that is computationally inexpensive, able to use label and label-free data, and capable of detecting tens of thousands of protein-protein interactions. Using a machine learning approach, PrInCE offers greatly reduced run time, more predicted interactions at the same stringency, prediction of protein complexes, and greater ease of use over previous bioinformatics tools for co-elution data. PrInCE is implemented in Matlab (version R2017a). Source code and standalone executable programs for Windows and Mac OSX are available at https://github.com/fosterlab/PrInCE , where usage instructions can be found. An example dataset and output are also provided for testing purposes. PrInCE is the first fast and easy-to-use data analysis pipeline that predicts interactomes and protein complexes from co-elution data. PrInCE allows researchers without bioinformatics expertise to analyze high-throughput co-elution datasets.

Analysis of the interface variability in NMR structure ensembles of protein-protein complexes.

PubMed

Calvanese, Luisa; D'Auria, Gabriella; Vangone, Anna; Falcigno, Lucia; Oliva, Romina

2016-06-01

NMR structures consist in ensembles of conformers, all satisfying the experimental restraints, which exhibit a certain degree of structural variability. We analyzed here the interface in NMR ensembles of protein-protein heterodimeric complexes and found it to span a wide range of different conservations. The different exhibited conservations do not simply correlate with the size of the systems/interfaces, and are most probably the result of an interplay between different factors, including the quality of experimental data and the intrinsic complex flexibility. In any case, this information is not to be missed when NMR structures of protein-protein complexes are analyzed; especially considering that, as we also show here, the first NMR conformer is usually not the one which best reflects the overall interface. To quantify the interface conservation and to analyze it, we used an approach originally conceived for the analysis and ranking of ensembles of docking models, which has now been extended to directly deal with NMR ensembles. We propose this approach, based on the conservation of the inter-residue contacts at the interface, both for the analysis of the interface in whole ensembles of NMR complexes and for the possible selection of a single conformer as the best representative of the overall interface. In order to make the analyses automatic and fast, we made the protocol available as a web tool at: https://www.molnac.unisa.it/BioTools/consrank/consrank-nmr.html. Copyright © 2016 Elsevier Inc. All rights reserved.

Imaging protein complex formation in the autophagy pathway: analysis of the interaction of LC3 and Atg4BC74A in live cells using Förster resonance energy transfer and fluorescence recovery after photobleaching

NASA Astrophysics Data System (ADS)

Kraft, Lewis J.; Kenworthy, Anne K.

2012-01-01

The protein microtubule-associated protein 1, light chain 3 (LC3) functions in autophagosome formation and plays a central role in the autophagy pathway. Previously, we found LC3 diffuses more slowly in cells than is expected for a freely diffusing monomer, suggesting it may constitutively associate with a macromolecular complex containing other protein components of the pathway. In the current study, we used Förster resonance energy transfer (FRET) microscopy and fluorescence recovery after photobleaching (FRAP) to investigate the interactions of LC3 with Atg4BC74A, a catalytically inactive mutant of the cysteine protease involved in lipidation and de-lipidation of LC3, as a model system to probe protein complex formation in the autophagy pathway. We show Atg4BC74A is in FRET proximity with LC3 in both the cytoplasm and nucleus of living cells, consistent with previous biochemical evidence that suggests these proteins directly interact. In addition, overexpressed Atg4BC74A diffuses significantly more slowly than predicted based on its molecular weight, and its translational diffusion coefficient is significantly slowed upon coexpression with LC3 to match that of LC3 itself. Taken together, these results suggest Atg4BC74A and LC3 are contained within the same multiprotein complex and that this complex exists in both the cytoplasm and nucleoplasm of living cells.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Analysis of DNA interactions using single-molecule force spectroscopy.

PubMed

Ritzefeld, Markus; Walhorn, Volker; Anselmetti, Dario; Sewald, Norbert

2013-06-01

Protein-DNA interactions are involved in many biochemical pathways and determine the fate of the corresponding cell. Qualitative and quantitative investigations on these recognition and binding processes are of key importance for an improved understanding of biochemical processes and also for systems biology. This review article focusses on atomic force microscopy (AFM)-based single-molecule force spectroscopy and its application to the quantification of forces and binding mechanisms that lead to the formation of protein-DNA complexes. AFM and dynamic force spectroscopy are exciting tools that allow for quantitative analysis of biomolecular interactions. Besides an overview on the method and the most important immobilization approaches, the physical basics of the data evaluation is described. Recent applications of AFM-based force spectroscopy to investigate DNA intercalation, complexes involving DNA aptamers and peptide- and protein-DNA interactions are given.

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

PubMed

Meckes, David G

2014-01-01

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

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

PubMed

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

2016-06-16

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

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

PubMed

Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong

2016-07-01

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

Dual-Color Click Beetle Luciferase Heteroprotein Fragment Complementation Assays

PubMed Central

Villalobos, Victor; Naik, Snehal; Bruinsma, Monique; Dothager, Robin S.; Pan, Mei-Hsiu; Samrakandi, Mustapha; Moss, Britney; Elhammali, Adnan; Piwnica-Worms, David

2010-01-01

Summary Understanding the functional complexity of protein interactions requires mapping biomolecular complexes within the cellular environment over biologically-relevant time scales. Herein we describe a novel set of reversible, multicolored heteroprotein complementation fragments based on various firefly and click beetle luciferases that utilize the same substrate, D-luciferin. Luciferase heteroprotein fragment complementation systems enabled dual-color quantification of two discreet pairs of interacting proteins simultaneously or two distinct proteins interacting with a third shared protein in live cells. Using real-time analysis of click beetle green and click beetle red luciferase heteroprotein fragment complementation applied to β-TrCP, an E3-ligase common to the regulation of both β-catenin and IκBα, GSK3β was identified as a novel candidate kinase regulating IκBα processing. These dual-color protein interaction switches may enable directed dynamic analysis of a variety of protein interactions in living cells. PMID:20851351

Isolation and Preparation of Extracellular Proteins from Lignocellulose Degrading Fungi for Comparative Proteomic Studies Using Mass Spectrometry.

PubMed

Gruninger, Robert J; Tsang, Adrian; McAllister, Tim A

2017-01-01

Fungi utilize a unique mechanism of nutrient acquisition involving extracellular digestion. To understand the biology of these microbes, it is important to identify and characterize the function of proteins that are secreted and involved in this process. Mass spectrometry-based proteomics is a powerful tool to study complex mixtures of proteins and understand how the proteins produced by an organism change in response to different conditions. Many fungi are efficient decomposers of plant cell wall, and anaerobic fungi are well recognized for their ability to digest lignocellulose. Here, we outline a protocol for the enrichment and isolation of proteins secreted by anaerobic fungi after growth on simple (glucose) and complex (straw and alfalfa hay) carbon sources. We provide detailed instruction on generating protein fragments and preparing these for proteomic analysis using reversed phase chromatography and mass spectrometry.

Protein Aggregates Are Recruited to Aggresome by Histone Deacetylase 6 via Unanchored Ubiquitin C Termini*

PubMed Central

Ouyang, Hui; Ali, Yousuf O.; Ravichandran, Mani; Dong, Aiping; Qiu, Wei; MacKenzie, Farrell; Dhe-Paganon, Sirano; Arrowsmith, Cheryl H.; Zhai, R. Grace

2012-01-01

The aggresome pathway is activated when proteasomal clearance of misfolded proteins is hindered. Misfolded polyubiquitinated protein aggregates are recruited and transported to the aggresome via the microtubule network by a protein complex consisting of histone deacetylase 6 (HDAC6) and the dynein motor complex. The current model suggests that HDAC6 recognizes protein aggregates by binding directly to polyubiquitinated proteins. Here, we show that there are substantial amounts of unanchored ubiquitin in protein aggregates with solvent-accessible C termini. The ubiquitin-binding domain (ZnF-UBP) of HDAC6 binds exclusively to the unanchored C-terminal diglycine motif of ubiquitin instead of conjugated polyubiquitin. The unanchored ubiquitin C termini in the aggregates are generated in situ by aggregate-associated deubiquitinase ataxin-3. These results provide structural and mechanistic bases for the role of HDAC6 in aggresome formation and further suggest a novel ubiquitin-mediated signaling pathway, where the exposure of ubiquitin C termini within protein aggregates enables HDAC6 recognition and transport to the aggresome. PMID:22069321

Encounter complexes and dimensionality reduction in protein-protein association.

PubMed

Kozakov, Dima; Li, Keyong; Hall, David R; Beglov, Dmitri; Zheng, Jiefu; Vakili, Pirooz; Schueler-Furman, Ora; Paschalidis, Ioannis Ch; Clore, G Marius; Vajda, Sandor

2014-04-08

An outstanding challenge has been to understand the mechanism whereby proteins associate. We report here the results of exhaustively sampling the conformational space in protein-protein association using a physics-based energy function. The agreement between experimental intermolecular paramagnetic relaxation enhancement (PRE) data and the PRE profiles calculated from the docked structures shows that the method captures both specific and non-specific encounter complexes. To explore the energy landscape in the vicinity of the native structure, the nonlinear manifold describing the relative orientation of two solid bodies is projected onto a Euclidean space in which the shape of low energy regions is studied by principal component analysis. Results show that the energy surface is canyon-like, with a smooth funnel within a two dimensional subspace capturing over 75% of the total motion. Thus, proteins tend to associate along preferred pathways, similar to sliding of a protein along DNA in the process of protein-DNA recognition. DOI: http://dx.doi.org/10.7554/eLife.01370.001.

sc-PDB: a database for identifying variations and multiplicity of 'druggable' binding sites in proteins.

PubMed

Meslamani, Jamel; Rognan, Didier; Kellenberger, Esther

2011-05-01

The sc-PDB database is an annotated archive of druggable binding sites extracted from the Protein Data Bank. It contains all-atoms coordinates for 8166 protein-ligand complexes, chosen for their geometrical and physico-chemical properties. The sc-PDB provides a functional annotation for proteins, a chemical description for ligands and the detailed intermolecular interactions for complexes. The sc-PDB now includes a hierarchical classification of all the binding sites within a functional class. The sc-PDB entries were first clustered according to the protein name indifferent of the species. For each cluster, we identified dissimilar sites (e.g. catalytic and allosteric sites of an enzyme). SCOPE AND APPLICATIONS: The classification of sc-PDB targets by binding site diversity was intended to facilitate chemogenomics approaches to drug design. In ligand-based approaches, it avoids comparing ligands that do not share the same binding site. In structure-based approaches, it permits to quantitatively evaluate the diversity of the binding site definition (variations in size, sequence and/or structure). The sc-PDB database is freely available at: http://bioinfo-pharma.u-strasbg.fr/scPDB.

TRF1 and TRF2 use different mechanisms to find telomeric DNA but share a novel mechanism to search for protein partners at telomeres.

PubMed

Lin, Jiangguo; Countryman, Preston; Buncher, Noah; Kaur, Parminder; E, Longjiang; Zhang, Yiyun; Gibson, Greg; You, Changjiang; Watkins, Simon C; Piehler, Jacob; Opresko, Patricia L; Kad, Neil M; Wang, Hong

2014-02-01

Human telomeres are maintained by the shelterin protein complex in which TRF1 and TRF2 bind directly to duplex telomeric DNA. How these proteins find telomeric sequences among a genome of billions of base pairs and how they find protein partners to form the shelterin complex remains uncertain. Using single-molecule fluorescence imaging of quantum dot-labeled TRF1 and TRF2, we study how these proteins locate TTAGGG repeats on DNA tightropes. By virtue of its basic domain TRF2 performs an extensive 1D search on nontelomeric DNA, whereas TRF1's 1D search is limited. Unlike the stable and static associations observed for other proteins at specific binding sites, TRF proteins possess reduced binding stability marked by transient binding (∼ 9-17 s) and slow 1D diffusion on specific telomeric regions. These slow diffusion constants yield activation energy barriers to sliding ∼ 2.8-3.6 κ(B)T greater than those for nontelomeric DNA. We propose that the TRF proteins use 1D sliding to find protein partners and assemble the shelterin complex, which in turn stabilizes the interaction with specific telomeric DNA. This 'tag-team proofreading' represents a more general mechanism to ensure a specific set of proteins interact with each other on long repetitive specific DNA sequences without requiring external energy sources.

Purification and characterization of a cellulolytic multienzyme complex produced by Neocallimastix patriciarum J11.

PubMed

Wang, Hui-Chang; Chen, Yo-Chia; Hseu, Ruey-Shyang

2014-08-22

Understanding the roles of the components of the multienzyme complex of the anaerobial cellulase system, acting on complex substrates, is crucial to the development of efficient cellulase systems for industrial applications such as converting lignocellulose to sugars for bioethanol production. In this study, we purified the multienzyme complex of Neocallimastix patriciarum J11 from a broth through cellulose affinity purification. The multienzyme complex is composed of at least 12 comprised proteins, based on sodium dodecyl sulfate polyacrylamide gel electrophoresis. Eight of these constituents have demonstrated β-glucanase activity on zymogram analysis. The multienzyme complex contained scaffoldings that respond to the gathering of the cellulolytic components. The levels and subunit ratio of the multienzyme complex from N. patriciarum J11 might have been affected by their utilized carbon sources, whereas the components of the complexes were consistent. The trypsin-digested peptides of six proteins were matched to the sequences of cellulases originating from rumen fungi, based on identification through liquid chromatography/mass spectrometry, revealing that at least three types of cellulase, including one endoglucanase and two exoglucanases, could be found in the multienzyme complex of N. patriciarum J11. The cellulolytic subunits could hydrolyze synergistically on both the internal bonds and the reducing and nonreducing ends of cellulose. Based on our research, our findings are the first to depict the composition of the multienzyme complex produced by N. patriciarum J11, and this complex is composed of scaffoldin and three types of cellulase. Copyright © 2014 Elsevier Inc. All rights reserved.

Hemolymph proteins of Anopheles gambiae larvae infected by Escherichia coli.

PubMed

He, Xuesong; Cao, Xiaolong; He, Yan; Bhattarai, Krishna; Rogers, Janet; Hartson, Steve; Jiang, Haobo

2017-09-01

Anopheles gambiae is a major vector of human malaria and its immune system in part determines the fate of ingested parasites. Proteins, hemocytes and fat body in hemolymph are critical components of this system, mediating both humoral and cellular defenses. Here we assessed differences in the hemolymph proteomes of water- and E. coli-pricked mosquito larvae by a gel-LC-MS approach. Among the 1756 proteins identified, 603 contained a signal peptide but accounted for two-third of the total protein amount on the quantitative basis. The sequence homology search indicated that 233 of the 1756 may be related to defense. In general, we did not detect substantial differences between the control and induced plasma samples in terms of protein numbers or levels. Protein distributions in the gel slices suggested post-translational modifications (e.g. proteolysis) and formation of serpin-protease complexes and high Mr immune complexes. Based on the twenty-five most abundant proteins, we further suggest that major functions of the larval hemolymph are storage, transport, and immunity. In summary, this study provided first data on constitution, levels, and possible functions of hemolymph proteins in the mosquito larvae, reflecting complex changes occurring in the fight against E. coli infection. Copyright © 2017 Elsevier Ltd. All rights reserved.

The FACT Complex Promotes Avian Leukosis Virus DNA Integration.

PubMed

Winans, Shelby; Larue, Ross C; Abraham, Carly M; Shkriabai, Nikolozi; Skopp, Amelie; Winkler, Duane; Kvaratskhelia, Mamuka; Beemon, Karen L

2017-04-01

All retroviruses need to integrate a DNA copy of their genome into the host chromatin. Cellular proteins regulating and targeting lentiviral and gammaretroviral integration in infected cells have been discovered, but the factors that mediate alpharetroviral avian leukosis virus (ALV) integration are unknown. In this study, we have identified the FACT protein complex, which consists of SSRP1 and Spt16, as a principal cellular binding partner of ALV integrase (IN). Biochemical experiments with purified recombinant proteins show that SSRP1 and Spt16 are able to individually bind ALV IN, but only the FACT complex effectively stimulates ALV integration activity in vitro Likewise, in infected cells, the FACT complex promotes ALV integration activity, with proviral integration frequency varying directly with cellular expression levels of the FACT complex. An increase in 2-long-terminal-repeat (2-LTR) circles in the depleted FACT complex cell line indicates that this complex regulates the ALV life cycle at the level of integration. This regulation is shown to be specific to ALV, as disruption of the FACT complex did not inhibit either lentiviral or gammaretroviral integration in infected cells. IMPORTANCE The majority of human gene therapy approaches utilize HIV-1- or murine leukemia virus (MLV)-based vectors, which preferentially integrate near genes and regulatory regions; thus, insertional mutagenesis is a substantial risk. In contrast, ALV integrates more randomly throughout the genome, which decreases the risks of deleterious integration. Understanding how ALV integration is regulated could facilitate the development of ALV-based vectors for use in human gene therapy. Here we show that the FACT complex directly binds and regulates ALV integration efficiency in vitro and in infected cells. Copyright © 2017 American Society for Microbiology.

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.

PubMed

Audain, Enrique; Uszkoreit, Julian; Sachsenberg, Timo; Pfeuffer, Julianus; Liang, Xiao; Hermjakob, Henning; Sanchez, Aniel; Eisenacher, Martin; Reinert, Knut; Tabb, David L; Kohlbacher, Oliver; Perez-Riverol, Yasset

2017-01-06

In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF+. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended. Protein inference is one of the major challenges in MS-based proteomics nowadays. Currently, there are a vast number of protein inference algorithms and implementations available for the proteomics community. Protein assembly impacts in the final results of the research, the quantitation values and the final claims in the research manuscript. Even though protein inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF+ and combinations thereof were evaluated for every protein inference tool. In total >186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could, concerning the question behind the study, compensate for slightly shorter reports using the parsimonious reports. 4) The current workflow can be easily extended to support new algorithms and search engine combinations. Copyright © 2016. Published by Elsevier B.V.

Mechanistic Insights Into Catalytic RNA-Protein Complexes Involved in Translation of the Genetic Code.

PubMed

Routh, Satya B; Sankaranarayanan, Rajan

2017-01-01

The contemporary world is an "RNA-protein world" rather than a "protein world" and tracing its evolutionary origins is of great interest and importance. The different RNAs that function in close collaboration with proteins are involved in several key physiological processes, including catalysis. Ribosome-the complex megadalton cellular machinery that translates genetic information encoded in nucleotide sequence to amino acid sequence-epitomizes such an association between RNA and protein. RNAs that can catalyze biochemical reactions are known as ribozymes. They usually employ general acid-base catalytic mechanism, often involving the 2'-OH of RNA that activates and/or stabilizes a nucleophile during the reaction pathway. The protein component of such RNA-protein complexes (RNPCs) mostly serves as a scaffold which provides an environment conducive for the RNA to function, or as a mediator for other interacting partners. In this review, we describe those RNPCs that are involved at different stages of protein biosynthesis and in which RNA performs the catalytic function; the focus of the account is on highlighting mechanistic aspects of these complexes. We also provide a perspective on such associations in the context of proofreading during translation of the genetic code. The latter aspect is not much appreciated and recent works suggest that this is an avenue worth exploring, since an understanding of the subject can provide useful insights into how RNAs collaborate with proteins to ensure fidelity during these essential cellular processes. It may also aid in comprehending evolutionary aspects of such associations. © 2017 Elsevier Inc. All rights reserved.

GeLC-MRM quantitation of mutant KRAS oncoprotein in complex biological samples.

PubMed

Halvey, Patrick J; Ferrone, Cristina R; Liebler, Daniel C

2012-07-06

Tumor-derived mutant KRAS (v-Ki-ras-2 Kirsten rat sarcoma viral oncogene) oncoprotein is a critical driver of cancer phenotypes and a potential biomarker for many epithelial cancers. Targeted mass spectrometry analysis by multiple reaction monitoring (MRM) enables selective detection and quantitation of wild-type and mutant KRAS proteins in complex biological samples. A recently described immunoprecipitation approach (Proc. Nat. Acad. Sci.2011, 108, 2444-2449) can be used to enrich KRAS for MRM analysis, but requires large protein inputs (2-4 mg). Here, we describe sodium dodecyl sulfate-polyacrylamide gel electrophoresis-based enrichment of KRAS in a low molecular weight (20-25 kDa) protein fraction prior to MRM analysis (GeLC-MRM). This approach reduces background proteome complexity, thus, allowing mutant KRAS to be reliably quantified in low protein inputs (5-50 μg). GeLC-MRM detected KRAS mutant variants (G12D, G13D, G12V, G12S) in a panel of cancer cell lines. GeLC-MRM analysis of wild-type and mutant was linear with respect to protein input and showed low variability across process replicates (CV = 14%). Concomitant analysis of a peptide from the highly similar HRAS and NRAS proteins enabled correction of KRAS-targeted measurements for contributions from these other proteins. KRAS peptides were also quantified in fluid from benign pancreatic cysts and pancreatic cancers at concentrations from 0.08 to 1.1 fmol/μg protein. GeLC-MRM provides a robust, sensitive approach to quantitation of mutant proteins in complex biological samples.

Visual Reading Method for Detection of Bacterial Tannase

PubMed Central

Osawa, R.; Walsh, T. P.

1993-01-01

Tannase activity of bacteria capable of degrading tannin-protein complexes was determined by a newly developed visual reading method. The method is based on two phenomena: (i) the ability of tannase to hydrolyze methyl gallate to release free gallic acid and (ii) the green to brown coloration of gallic acid after prolonged exposure to oxygen in an alkaline condition. The method has been successfully used to detect the presence of tannase in the cultures of bacteria capable of degrading tannin-protein complexes. PMID:16348918

The application of quantum mechanics in structure-based drug design.

PubMed

Mucs, Daniel; Bryce, Richard A

2013-03-01

Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein-ligand recognition. In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein-ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein-ligand docking, protein-ligand binding affinities and ligand strain on binding. Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.

Technical aspects of gel-based proteomics designed for elucidating an aryl hydrocarbon receptor complex.

PubMed

Wada, Yoshinao; Nakano, Norihiko

2004-01-01

The identification of proteins by mass spectrometry has revolutionalized the basic method of identifying proteins constituting an intracellular unit or network for certain biological functions. The gel-based strategy following immunoprecipitation was applied to elucidating proteins associated with the aryl hydrocarbon receptor (AhR). Two hundred femtomoles of AhR was recovered from approximately 2 x 10(7) HepG2 cells by immunoprecipitation and was sufficient for identification by peptide mass fingerprinting. Possible candidates for the AhR-associated proteins were also identified. Improvements of the current strategy to increase the overall sensitivity tenfold are required to clarify the AhR complex in full detail. For example, a combination of trypsin and Achromobacter protease I for in-gel digestion allows the number of missed cleavage sites to be set at zero for database searching, thereby reducing random matches and facilitating identification. There is also room for improvement in each step of sample preparation prior to mass spectrometry.

The diversity and specificity of the extracellular proteome in the cellulolytic bacterium Caldicellulosiruptor bescii is driven by the nature of the cellulosic growth substrate

DOE PAGES

Poudel, Suresh; Giannone, Richard J.; Basen, Mirko; ...

2018-03-23

Background: Caldicellulosiruptor bescii is a thermophilic cellulolytic bacterium that efficiently deconstructs lignocellulosic biomass into sugars, which subsequently can be fermented into alcohols, such as ethanol, and other products. Deconstruction of complex substrates by C. bescii involves a myriad of highly abundant, substrate-specific extracellular solute binding proteins (ESBPs) and carbohydrate-active enzymes (CAZymes) containing carbohydrate-binding modules (CBMs). Mass spectrometry-based proteomics was employed to investigate how these substrate recognition proteins and enzymes vary as a function of lignocellulosic substrates.Results:Proteomic analysis revealed several key extracellular proteins that respond specifically to either C5 or C6 mono- and polysaccharides. These include proteins of unknown functions (PUFs),more » ESBPs, and CAZymes. ESBPs that were previously shown to interact more efficiently with hemicellulose and pectin were detected in high abundance during growth on complex C5 substrates, such as switchgrass and xylan. Some proteins, such as Athe_0614 and Athe_2368, whose functions are not well defined were predicted to be involved in xylan utilization and ABC transport and were significantly more abundant in complex and C5 substrates, respectively. The proteins encoded by the entire glucan degradation locus (GDL; Athe_1857, 1859, 1860, 1865, 1867, and 1866) were highly abundant under all growth conditions, particularly when C. bescii was grown on cellobiose, switchgrass, or xylan. In contrast, the glycoside hydrolases Athe_0609 (Pullulanase) and 0610, which both possess CBM20 and a starch binding domain, appear preferential to C5/complex substrate deconstruction. Some PUFs, such as Athe_2463 and 2464, were detected as highly abundant when grown on C5 substrates (xylan and xylose), also suggesting C5-substrate specificity. In conclusion, this study reveals the protein membership of the C. bescii secretome and demonstrates its plasticity based on the complexity (mono-/disaccharides vs. polysaccharides) and type of carbon (C5 vs. C6) available to the microorganism. The presence or increased abundance of extracellular proteins as a response to specific substrates helps to further elucidate C. bescii’s utilization and conversion of lignocellulosic biomass to biofuel and other valuable products. This includes improved characterization of extracellular proteins that lack discrete functional roles and are poorly/not annotated.« less

The diversity and specificity of the extracellular proteome in the cellulolytic bacterium Caldicellulosiruptor bescii is driven by the nature of the cellulosic growth substrate

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

Poudel, Suresh; Giannone, Richard J.; Basen, Mirko

Background: Caldicellulosiruptor bescii is a thermophilic cellulolytic bacterium that efficiently deconstructs lignocellulosic biomass into sugars, which subsequently can be fermented into alcohols, such as ethanol, and other products. Deconstruction of complex substrates by C. bescii involves a myriad of highly abundant, substrate-specific extracellular solute binding proteins (ESBPs) and carbohydrate-active enzymes (CAZymes) containing carbohydrate-binding modules (CBMs). Mass spectrometry-based proteomics was employed to investigate how these substrate recognition proteins and enzymes vary as a function of lignocellulosic substrates.Results:Proteomic analysis revealed several key extracellular proteins that respond specifically to either C5 or C6 mono- and polysaccharides. These include proteins of unknown functions (PUFs),more » ESBPs, and CAZymes. ESBPs that were previously shown to interact more efficiently with hemicellulose and pectin were detected in high abundance during growth on complex C5 substrates, such as switchgrass and xylan. Some proteins, such as Athe_0614 and Athe_2368, whose functions are not well defined were predicted to be involved in xylan utilization and ABC transport and were significantly more abundant in complex and C5 substrates, respectively. The proteins encoded by the entire glucan degradation locus (GDL; Athe_1857, 1859, 1860, 1865, 1867, and 1866) were highly abundant under all growth conditions, particularly when C. bescii was grown on cellobiose, switchgrass, or xylan. In contrast, the glycoside hydrolases Athe_0609 (Pullulanase) and 0610, which both possess CBM20 and a starch binding domain, appear preferential to C5/complex substrate deconstruction. Some PUFs, such as Athe_2463 and 2464, were detected as highly abundant when grown on C5 substrates (xylan and xylose), also suggesting C5-substrate specificity. In conclusion, this study reveals the protein membership of the C. bescii secretome and demonstrates its plasticity based on the complexity (mono-/disaccharides vs. polysaccharides) and type of carbon (C5 vs. C6) available to the microorganism. The presence or increased abundance of extracellular proteins as a response to specific substrates helps to further elucidate C. bescii’s utilization and conversion of lignocellulosic biomass to biofuel and other valuable products. This includes improved characterization of extracellular proteins that lack discrete functional roles and are poorly/not annotated.« less

The diversity and specificity of the extracellular proteome in the cellulolytic bacterium Caldicellulosiruptor bescii is driven by the nature of the cellulosic growth substrate.

PubMed

Poudel, Suresh; Giannone, Richard J; Basen, Mirko; Nookaew, Intawat; Poole, Farris L; Kelly, Robert M; Adams, Michael W W; Hettich, Robert L

2018-01-01

Caldicellulosiruptor bescii is a thermophilic cellulolytic bacterium that efficiently deconstructs lignocellulosic biomass into sugars, which subsequently can be fermented into alcohols, such as ethanol, and other products. Deconstruction of complex substrates by C. bescii involves a myriad of highly abundant, substrate-specific extracellular solute binding proteins (ESBPs) and carbohydrate-active enzymes (CAZymes) containing carbohydrate-binding modules (CBMs). Mass spectrometry-based proteomics was employed to investigate how these substrate recognition proteins and enzymes vary as a function of lignocellulosic substrates. Proteomic analysis revealed several key extracellular proteins that respond specifically to either C5 or C6 mono- and polysaccharides. These include proteins of unknown functions (PUFs), ESBPs, and CAZymes. ESBPs that were previously shown to interact more efficiently with hemicellulose and pectin were detected in high abundance during growth on complex C5 substrates, such as switchgrass and xylan. Some proteins, such as Athe_0614 and Athe_2368, whose functions are not well defined were predicted to be involved in xylan utilization and ABC transport and were significantly more abundant in complex and C5 substrates, respectively. The proteins encoded by the entire glucan degradation locus (GDL; Athe_1857, 1859, 1860, 1865, 1867, and 1866) were highly abundant under all growth conditions, particularly when C. bescii was grown on cellobiose, switchgrass, or xylan. In contrast, the glycoside hydrolases Athe_0609 (Pullulanase) and 0610, which both possess CBM20 and a starch binding domain, appear preferential to C5/complex substrate deconstruction. Some PUFs, such as Athe_2463 and 2464, were detected as highly abundant when grown on C5 substrates (xylan and xylose), also suggesting C5-substrate specificity. This study reveals the protein membership of the C. bescii secretome and demonstrates its plasticity based on the complexity (mono-/disaccharides vs. polysaccharides) and type of carbon (C5 vs. C6) available to the microorganism. The presence or increased abundance of extracellular proteins as a response to specific substrates helps to further elucidate C. bescii 's utilization and conversion of lignocellulosic biomass to biofuel and other valuable products. This includes improved characterization of extracellular proteins that lack discrete functional roles and are poorly/not annotated.

SDS-binding assay based on tyrosine fluorescence as a tool to determine binding properties of human serum albumin in blood plasma

NASA Astrophysics Data System (ADS)

Zhdanova, Nadezda; Shirshin, Evgeny; Fadeev, Victor; Priezzhev, Alexander

2016-04-01

Among all plasma proteins human serum albumin (HSA) is the most studied one as it is the main transport protein and can bind a wide variety of ligands especially fatty acids (FAs). The concentration of FAs bound to HSA in human blood plasma differs by three times under abnormal conditions (fasting, physical exercises or in case of social important diseases). In the present study a surfactant sodium dodecyl sulfate (SDS) was used to simulate FAs binding to HSA. It was shown that the increase of Tyr fluorescence of human blood plasma due to SDS addition can be completely explained by HSA-SDS complex formation. Binding parameters of SDS-HSA complex (average number of sites and apparent constant of complex formation) were determined from titration curves based on tyrosine (Tyr) fluorescence.

In-vivo detection of binary PKA network interactions upon activation of endogenous GPCRs

PubMed Central

Röck, Ruth; Bachmann, Verena; Bhang, Hyo-eun C; Malleshaiah, Mohan; Raffeiner, Philipp; Mayrhofer, Johanna E; Tschaikner, Philipp M; Bister, Klaus; Aanstad, Pia; Pomper, Martin G; Michnick, Stephen W; Stefan, Eduard

2015-01-01

Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems. PMID:26099953

Delivery of Therapeutic Proteins Using Electrospun Fibers-Recent Developments and Current Challenges.

PubMed

Seif, Salem; Planz, Viktoria; Windbergs, Maike

2017-10-01

Proteins play a vital role within the human body by regulating various functions and even serving as structural constituent of many body parts. In this context, protein-based therapeutics have attracted a lot of attention in the last few decades as potential treatment of different diseases. Due to the steadily increasing interest in protein-based therapeutics, different dosage forms were investigated for delivering such complex macromolecules to the human body. Here, electrospun fibers hold a great potential for embedding proteins without structural damage and for controlled release of the protein for therapeutic applications. This review provides a comprehensive overview of the current state of protein-based carrier systems using electrospun fibers, with special emphasis on discussing their potential and key challenges in developing such therapeutic strategies, along with a prospective view of anticipated future directions. © 2017 Deutsche Pharmazeutische Gesellschaft.

Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

PubMed

Wang, Rui-Sheng; Loscalzo, Joseph

2018-05-20

Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunctional mechanistic pathways. Identifying such disease modules will provide insights into a systems-level understanding of molecular mechanisms of diseases. Owing to the incompleteness of our knowledge of disease proteins and limited information on the biological mediators of pathobiological processes, the key proteins (seed proteins) for many diseases appear scattered over the human protein-protein interactome and form a few small branches, rather than coherent network modules. In this paper, we develop a network-based algorithm, called the Seed Connector algorithm (SCA), to pinpoint disease modules by adding as few additional linking proteins (seed connectors) to the seed protein pool as possible. Such seed connectors are hidden disease module elements that are critical for interpreting the functional context of disease proteins. The SCA aims to connect seed disease proteins so that disease mechanisms and pathways can be decoded based on predicted coherent network modules. We validate the algorithm using a large corpus of 70 complex diseases and binding targets of over 200 drugs, and demonstrate the biological relevance of the seed connectors. Lastly, as a specific proof of concept, we apply the SCA to a set of seed proteins for coronary artery disease derived from a meta-analysis of large-scale genome-wide association studies and obtain a coronary artery disease module enriched with important disease-related signaling pathways and drug targets not previously recognized. Copyright © 2018 Elsevier Ltd. All rights reserved.

Supramolecular Architectures and Mimics of Complex Natural Folds Derived from Rationally Designed alpha-Helical Protein Structures

NASA Astrophysics Data System (ADS)

Tavenor, Nathan Albert

Protein-based supramolecular polymers (SMPs) are a class of biomaterials which draw inspiration from and expand upon the many examples of complex protein quaternary structures observed in nature: collagen, microtubules, viral capsids, etc. Designing synthetic supramolecular protein scaffolds both increases our understanding of natural superstructures and allows for the creation of novel materials. Similar to small-molecule SMPs, protein-based SMPs form due to self-assembly driven by intermolecular interactions between monomers, and monomer structure determines the properties of the overall material. Using protein-based monomers takes advantage of the self-assembly and highly specific molecular recognition properties encodable in polypeptide sequences to rationally design SMP architectures. The central hypothesis underlying our work is that alpha-helical coiled coils, a well-studied protein quaternary folding motif, are well-suited to SMP design through the addition of synthetic linkers at solvent-exposed sites. Through small changes in the structures of the cross-links and/or peptide sequence, we have been able to control both the nanoscale organization and the macroscopic properties of the SMPs. Changes to the linker and hydrophobic core of the peptide can be used to control polymer rigidity, stability, and dimensionality. The gaps in knowledge that this thesis sought to fill on this project were 1) the relationship between the molecular structure of the cross-linked polypeptides and the macroscopic properties of the SMPs and 2) a means of creating materials exhibiting multi-dimensional net or framework topologies. Separate from the above efforts on supramolecular architectures was work on improving backbone modification strategies for an alpha-helix in the context of a complex protein tertiary fold. Earlier work in our lab had successfully incorporated unnatural building blocks into every major secondary structure (beta-sheet, alpha-helix, loops and beta-turns) of a small protein with a tertiary fold. Although the tertiary fold of the native sequence was mimicked by the resulting artificial protein, the thermodynamic stability was greatly compromised. Most of this energetic penalty derived from the modifications present in the alpha-helix. The contribution within this thesis was direct comparison of several alpha-helical design strategies and establishment of the thermodynamic consequences of each.

Analysis of the complex formation, interaction and electron transfer pathway between the "open" conformation of NADPH-cytochrome P450 reductase and aromatase.

PubMed

Dai, Yuejie; Zhen, Jing; Zhang, Xiuli; Zhong, Yonghui; Liu, Shaodan; Sun, Ziyue; Guo, Yue; Wu, Qingli

2015-09-01

The complex structure of human aromatase (CYP19) and the open form of ΔTGEE mutant NADPH-cytochrome P450 reductase (mCPR) was constructed using template-based protein alignment method. Dynamic simulation of formed complex was performed on NAMD 2.9, in which CHARMm all 27_prot_lipid_na force field and an explicit TIP3P water solvent model were applied. The result showed mCPR in its open conformation could steadily combine with aromatase from the proximal face. Data analysis indicates hydrogen bonds and four salt bridges on the binding surface enhance the interaction between the two protein molecules. Amino acid, Lys108 plays a key role in aromatase activity through the formation of a salt bridge with Asp147 and two hydrogen bonds with Asp147 and Gln150 in mCPR. The optimal pathway for the first electron transfer from CPR to aromatase was revealed and calculated using HARLEM software. The rates for solvent mediated and non-solvent mediated electron transfer from FMNH2 to heme were determined as 1.04×10(6)s(-)(1) and 4.86×10(5)s(-)(1) respectively, which indicates the solvent water can facilitate the electron transfer from FMNH2 to heme. This study presents a novel strategy for the study of the protein-protein interactions based on the template-based protein alignment, which may help new aromtase development targeting the electron transfer between mCPR and aromatase. Copyright © 2015 Elsevier Inc. All rights reserved.

Predicting Physical Interactions between Protein Complexes*

PubMed Central

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

2013-01-01

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

Complex I-complex II ratio strongly differs in various organs of Arabidopsis thaliana.

PubMed

Peters, Katrin; Niessen, Markus; Peterhänsel, Christoph; Späth, Bettina; Hölzle, Angela; Binder, Stefan; Marchfelder, Anita; Braun, Hans-Peter

2012-06-01

In most studies, amounts of protein complexes of the oxidative phosphorylation (OXPHOS) system in different organs or tissues are quantified on the basis of isolated mitochondrial fractions. However, yield of mitochondrial isolations might differ with respect to tissue type due to varying efficiencies of cell disruption during organelle isolation procedures or due to tissue-specific properties of organelles. Here we report an immunological investigation on the ratio of the OXPHOS complexes in different tissues of Arabidopsis thaliana which is based on total protein fractions isolated from five Arabidopsis organs (leaves, stems, flowers, roots and seeds) and from callus. Antibodies were generated against one surface exposed subunit of each of the five OXPHOS complexes and used for systematic immunoblotting experiments. Amounts of all complexes are highest in flowers (likewise with respect to organ fresh weight or total protein content of the flower fraction). Relative amounts of protein complexes in all other fractions were determined with respect to their amounts in flowers. Our investigation reveals high relative amounts of complex I in green organs (leaves and stems) but much lower amounts in non-green organs (roots, callus tissue). In contrast, complex II only is represented by low relative amounts in green organs but by significantly higher amounts in non-green organs, especially in seeds. In fact, the complex I-complex II ratio differs by factor 37 between callus and leaf, indicating drastic differences in electron entry into the respiratory chain in these two fractions. Variation in amounts concerning complexes III, IV and V was less pronounced in different Arabidopsis tissues (quantification of complex V in leaves was not meaningful due to a cross-reaction of the antibody with the chloroplast form of this enzyme). Analyses were complemented by in gel activity measurements for the protein complexes of the OXPHOS system and comparative 2D blue native/SDS PAGE analyses using isolated mitochondria. We suggest that complex I has an especially important role in the context of photosynthesis which might be due to its indirect involvement in photorespiration and its numerous enzymatic side activities in plants.

An ultrastable conjugate of silver nanoparticles and protein formed through weak interactions

NASA Astrophysics Data System (ADS)

Brahmkhatri, Varsha P.; Chandra, Kousik; Dubey, Abhinav; Atreya, Hanudatta S.

2015-07-01

In recent years, silver nanoparticles (AgNPs) have attracted significant attention owing to their unique physicochemical, optical, conductive and antimicrobial properties. One of the properties of AgNPs which is crucial for all applications is their stability. In the present study we unravel a mechanism through which silver nanoparticles are rendered ultrastable in an aqueous solution in complex with the protein ubiquitin (Ubq). This involves a dynamic and reversible association and dissociation of ubiquitin from the surface of AgNP. The exchange occurs at a rate much greater than 25 s-1 implying a residence time of <40 ms for the protein. The AgNP-Ubq complex remains stable for months due to steric stabilization over a wide pH range compared to unconjugated AgNPs. NMR studies reveal that the protein molecules bind reversibly to AgNP with an approximate dissociation constant of 55 μM and undergo fast exchange. At pH > 4 the positively charged surface of the protein comes in contact with the citrate capped AgNP surface. Further, NMR relaxation-based experiments suggest that in addition to the dynamic exchange, a conformational rearrangement of the protein takes place upon binding to AgNP. The ultrastability of the AgNP-Ubq complex was found to be useful for its anti-microbial activity, which allowed the recycling of this complex multiple times without the loss of stability. Altogether, the study provides new insights into the mechanism of protein-silver nanoparticle interactions and opens up new avenues for its application in a wide range of systems.In recent years, silver nanoparticles (AgNPs) have attracted significant attention owing to their unique physicochemical, optical, conductive and antimicrobial properties. One of the properties of AgNPs which is crucial for all applications is their stability. In the present study we unravel a mechanism through which silver nanoparticles are rendered ultrastable in an aqueous solution in complex with the protein ubiquitin (Ubq). This involves a dynamic and reversible association and dissociation of ubiquitin from the surface of AgNP. The exchange occurs at a rate much greater than 25 s-1 implying a residence time of <40 ms for the protein. The AgNP-Ubq complex remains stable for months due to steric stabilization over a wide pH range compared to unconjugated AgNPs. NMR studies reveal that the protein molecules bind reversibly to AgNP with an approximate dissociation constant of 55 μM and undergo fast exchange. At pH > 4 the positively charged surface of the protein comes in contact with the citrate capped AgNP surface. Further, NMR relaxation-based experiments suggest that in addition to the dynamic exchange, a conformational rearrangement of the protein takes place upon binding to AgNP. The ultrastability of the AgNP-Ubq complex was found to be useful for its anti-microbial activity, which allowed the recycling of this complex multiple times without the loss of stability. Altogether, the study provides new insights into the mechanism of protein-silver nanoparticle interactions and opens up new avenues for its application in a wide range of systems. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03047a

Cell polarity, cell adhesion, and spermatogenesis: role of cytoskeletons

PubMed Central

Li, Linxi; Gao, Ying; Chen, Haiqi; Jesus, Tito; Tang, Elizabeth; Li, Nan; Lian, Qingquan; Ge, Ren-shan; Cheng, C. Yan

2017-01-01

In the rat testis, studies have shown that cell polarity, in particular spermatid polarity, to support spermatogenesis is conferred by the coordinated efforts of the Par-, Crumbs-, and Scribble-based polarity complexes in the seminiferous epithelium. Furthermore, planar cell polarity (PCP) is conferred by PCP proteins such as Van Gogh-like 2 (Vangl2) in the testis. On the other hand, cell junctions at the Sertoli cell–spermatid (steps 8–19) interface are exclusively supported by adhesion protein complexes (for example, α6β1-integrin-laminin-α3,β3,γ3 and nectin-3-afadin) at the actin-rich apical ectoplasmic specialization (ES) since the apical ES is the only anchoring device in step 8–19 spermatids. For cell junctions at the Sertoli cell–cell interface, they are supported by adhesion complexes at the actin-based basal ES (for example, N-cadherin-β-catenin and nectin-2-afadin), tight junction (occludin-ZO-1 and claudin 11-ZO-1), and gap junction (connexin 43-plakophilin-2) and also intermediate filament-based desmosome (for example, desmoglein-2-desmocollin-2). In short, the testis-specific actin-rich anchoring device known as ES is crucial to support spermatid and Sertoli cell adhesion. Accumulating evidence has shown that the Par-, Crumbs-, and Scribble-based polarity complexes and the PCP Vangl2 are working in concert with actin- or microtubule-based cytoskeletons (or both) and these polarity (or PCP) protein complexes exert their effects through changes in the organization of the cytoskeletal elements across the seminiferous epithelium of adult rat testes. As such, there is an intimate relationship between cell polarity, cell adhesion, and cytoskeletal function in the testis. Herein, we critically evaluate these recent findings based on studies on different animal models. We also suggest some crucial future studies to be performed. PMID:28928959

Protein-protein docking on hardware accelerators: comparison of GPU and MIC architectures

PubMed Central

2015-01-01

Background The hardware accelerators will provide solutions to computationally complex problems in bioinformatics fields. However, the effect of acceleration depends on the nature of the application, thus selection of an appropriate accelerator requires some consideration. Results In the present study, we compared the effects of acceleration using graphics processing unit (GPU) and many integrated core (MIC) on the speed of fast Fourier transform (FFT)-based protein-protein docking calculation. The GPU implementation performed the protein-protein docking calculations approximately five times faster than the MIC offload mode implementation. The MIC native mode implementation has the advantage in the implementation costs. However, the performance was worse with larger protein pairs because of memory limitations. Conclusion The results suggest that GPU is more suitable than MIC for accelerating FFT-based protein-protein docking applications. PMID:25707855

Binding regularities in complexes of transcription factors with operator DNA: homeodomain family.

PubMed

Chirgadze, Yu N; Zheltukhin, E I; Polozov, R V; Sivozhelezov, V S; Ivanov, V V

2009-06-01

In order to disclose general regularities of binding in homeodomain-DNA complexes we considered five of them and extended the observed regularities over the entire homeodomain family. The five complexes have been selected by similarity of protein structures and patterns of contacting residues. Their long range interactions and interfaces were compared. The long-range stage of the recognition process was characterized by electrostatic potentials about 5 Angstrom away from molecular surfaces of protein or DNA. For proteins, clear positive potential is displayed only at the side contacting the DNA. The double-chained DNA molecule displays a rather strong negative potential, especially in their grooves. Thus, a functional role of electrostatics is a guiding of the protein into the DNA major groove, so the protein and DNA could form a loose non-specific complex. At the close-range stage, neutralization of the phosphate charges by positively charged residues is necessary for decreasing the strong electrostatic potential of DNA, allowing nucleotide bases to participate in the formation of protein-DNA atomic contacts in the interface. The recognizing alpha-helix of protein was shown to form both invariant and variable groups of contacts with DNA by means of certain specific side groups. The invariant contacts included highly specific protein-DNA hydrogen bonds between asparagine and adenine, nonpolar contacts of hydrophobic amino acids serving as a stereochemical barrier for fixing the protein factor on DNA, and an interface cluster of water molecules providing local conformational mobility necessary for the dissociation process. There is a unique water molecule within the interface that is conservative and located at the interface center. Invariant contacts of the proteins are mostly formed with the TAAT motif of the promoter DNA forward strand. While the invariant contacts specify the family of homeodomains, the variable contacts that are formed with the reverse strand of DNA provide specificity of individual complexes within the homeodomain family.

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

PubMed

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

2011-05-20

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

A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra

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

Kou, Qiang; Wu, Si; Tolić, Nikola

Motivation: Although proteomics has rapidly developed in the past decade, researchers are still in the early stage of exploring the world of complex proteoforms, which are protein products with various primary structure alterations resulting from gene mutations, alternative splicing, post-translational modifications, and other biological processes. Proteoform identification is essential to mapping proteoforms to their biological functions as well as discovering novel proteoforms and new protein functions. Top-down mass spectrometry is the method of choice for identifying complex proteoforms because it provides a “bird’s eye view” of intact proteoforms. The combinatorial explosion of various alterations on a protein may result inmore » billions of possible proteoforms, making proteoform identification a challenging computational problem. Results: We propose a new data structure, called the mass graph, for efficient representation of proteoforms and design mass graph alignment algorithms. We developed TopMG, a mass graph-based software tool for proteoform identification by top-down mass spectrometry. Experiments on top-down mass spectrometry data sets showed that TopMG outperformed existing methods in identifying complex proteoforms.« less

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures.

PubMed

Chundawat, Shishir P S; Lipton, Mary S; Purvine, Samuel O; Uppugundla, Nirmal; Gao, Dahai; Balan, Venkatesh; Dale, Bruce E

2011-10-07

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

A chloroplast "wake up" mechanism: Illumination with weak light activates the photosynthetic antenna function in dark-adapted plants.

PubMed

Janik, Ewa; Bednarska, Joanna; Zubik, Monika; Luchowski, Rafal; Mazur, Radoslaw; Sowinski, Karol; Grudzinski, Wojciech; Garstka, Maciej; Gruszecki, Wieslaw I

2017-03-01

The efficient and fluent operation of photosynthesis in plants relies on activity of pigment-protein complexes called antenna, absorbing light and transferring excitations toward the reaction centers. Here we show, based on the results of the fluorescence lifetime imaging analyses of single chloroplasts, that pigment-protein complexes, in dark-adapted plants, are not able to act effectively as photosynthetic antennas, due to pronounced, adverse excitation quenching. It appeared that the antenna function could be activated by a short (on a minute timescale) illumination with light of relatively low intensity, substantially below the photosynthesis saturation threshold. The low-light-induced activation of the antenna function was attributed to phosphorylation of the major accessory light-harvesting complex LHCII, based on the fact that such a mechanism was not observed in the stn7 Arabidopsis thaliana mutant, with impaired LHCII phosphorylation. It is proposed that the protein phosphorylation-controlled change in the LHCII clustering ability provides mechanistic background for this regulatory process. Copyright © 2016 Elsevier GmbH. All rights reserved.

Highly selective BSA imprinted polyacrylamide hydrogels facilitated by a metal-coding MIP approach.

PubMed

El-Sharif, H F; Yapati, H; Kalluru, S; Reddy, S M

2015-12-01

We report the fabrication of metal-coded molecularly imprinted polymers (MIPs) using hydrogel-based protein imprinting techniques. A Co(II) complex was prepared using (E)-2-((2 hydrazide-(4-vinylbenzyl)hydrazono)methyl)phenol; along with iron(III) chloroprotoporphyrin (Hemin), vinylferrocene (VFc), zinc(II) protoporphyrin (ZnPP) and protoporphyrin (PP), these complexes were introduced into the MIPs as co-monomers for metal-coding of non-metalloprotein imprints. Results indicate a 66% enhancement for bovine serum albumin (BSA) protein binding capacities (Q, mg/g) via metal-ion/ligand exchange properties within the metal-coded MIPs. Specifically, Co(II)-complex-based MIPs exhibited 92 ± 1% specific binding with Q values of 5.7 ± 0.45 mg BSA/g polymer and imprinting factors (IF) of 14.8 ± 1.9 (MIP/non-imprinted (NIP) control). The selectivity of our Co(II)-coded BSA MIPs were also tested using bovine haemoglobin (BHb), lysozyme (Lyz), and trypsin (Tryp). By evaluating imprinting factors (K), each of the latter proteins was found to have lower affinities in comparison to cognate BSA template. The hydrogels were further characterised by thermal analysis and differential scanning calorimetry (DSC) to assess optimum polymer composition. The development of hydrogel-based molecularly imprinted polymer (HydroMIPs) technology for the memory imprinting of proteins and for protein biosensor development presents many possibilities, including uses in bio-sample clean-up or selective extraction, replacement of biological antibodies in immunoassays and biosensors for medicine and the environment. Biosensors for proteins and viruses are currently expensive to develop because they require the use of expensive antibodies. Because of their biomimicry capabilities (and their potential to act as synthetic antibodies), HydroMIPs potentially offer a route to the development of new low-cost biosensors. Herein, a metal ion-mediated imprinting approach was employed to metal-code our hydrogel-based MIPs for the selective recognition of bovine serum albumin (BSA). Specifically, Co(II)-complex based MIPs exhibited a 66% enhancement (in comparison to our normal MIPs) exhibiting 92 ± 1% specific binding with Q values of 5.7 ± 0.45 mg BSA/g polymer and imprinting factors (IF) of 14.8 ± 1.9 (MIP/ non-imprinted (NIP) control). The proposed metal-coded MIPs for protein recognition are intended to lead to unprecedented improvement in MIP selectivity and for future biosensor development that rely on an electrochemical redox processes. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.

PubMed

Wu, Min; Kwoh, Chee-Keong; Li, Xiaoli; Zheng, Jie

2014-09-11

The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired. In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks. The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with recombination hotspots. The trans-regulators predicted by our pipeline are enriched with epigenetic functions (e.g., histone modifications), demonstrating the epigenetic regulatory mechanisms of recombination hotspots. The identified protein complexes also provide us with candidates to further investigate the molecular machineries for recombination hotspots. Moreover, the experimental data and results are available on our web site http://www.ntu.edu.sg/home/zhengjie/data/RecombinationHotspot/NetPipe/.

An analytical platform for mass spectrometry-based identification and chemical analysis of RNA in ribonucleoprotein complexes.

PubMed

Taoka, Masato; Yamauchi, Yoshio; Nobe, Yuko; Masaki, Shunpei; Nakayama, Hiroshi; Ishikawa, Hideaki; Takahashi, Nobuhiro; Isobe, Toshiaki

2009-11-01

We describe here a mass spectrometry (MS)-based analytical platform of RNA, which combines direct nano-flow reversed-phase liquid chromatography (RPLC) on a spray tip column and a high-resolution LTQ-Orbitrap mass spectrometer. Operating RPLC under a very low flow rate with volatile solvents and MS in the negative mode, we could estimate highly accurate mass values sufficient to predict the nucleotide composition of a approximately 21-nucleotide small interfering RNA, detect post-transcriptional modifications in yeast tRNA, and perform collision-induced dissociation/tandem MS-based structural analysis of nucleolytic fragments of RNA at a sub-femtomole level. Importantly, the method allowed the identification and chemical analysis of small RNAs in ribonucleoprotein (RNP) complex, such as the pre-spliceosomal RNP complex, which was pulled down from cultured cells with a tagged protein cofactor as bait. We have recently developed a unique genome-oriented database search engine, Ariadne, which allows tandem MS-based identification of RNAs in biological samples. Thus, the method presented here has broad potential for automated analysis of RNA; it complements conventional molecular biology-based techniques and is particularly suited for simultaneous analysis of the composition, structure, interaction, and dynamics of RNA and protein components in various cellular RNP complexes.

Simulation-Based Validation of the p53 Transcriptional Activity with Hybrid Functional Petri Net.

PubMed

Doi, Atsushi; Nagasaki, Masao; Matsuno, Hiroshi; Miyano, Satoru

2011-01-01

MDM2 and p19ARF are essential proteins in cancer pathways forming a complex with protein p53 to control the transcriptional activity of protein p53. It is confirmed that protein p53 loses its transcriptional activity by forming the functional dimer with protein MDM2. However, it is still unclear that protein p53 keeps its transcriptional activity when it forms the trimer with proteins MDM2 and p19ARF. We have observed mutual behaviors among genes p53, MDM2, p19ARF and their products on a computational model with hybrid functional Petri net (HFPN) which is constructed based on information described in the literature. The simulation results suggested that protein p53 should have the transcriptional activity in the forms of the trimer of proteins p53, MDM2, and p19ARF. This paper also discusses the advantages of HFPN based modeling method in terms of pathway description for simulations.

iview: an interactive WebGL visualizer for protein-ligand complex.

PubMed

Li, Hongjian; Leung, Kwong-Sak; Nakane, Takanori; Wong, Man-Hon

2014-02-25

Visualization of protein-ligand complex plays an important role in elaborating protein-ligand interactions and aiding novel drug design. Most existing web visualizers either rely on slow software rendering, or lack virtual reality support. The vital feature of macromolecular surface construction is also unavailable. We have developed iview, an easy-to-use interactive WebGL visualizer of protein-ligand complex. It exploits hardware acceleration rather than software rendering. It features three special effects in virtual reality settings, namely anaglyph, parallax barrier and oculus rift, resulting in visually appealing identification of intermolecular interactions. It supports four surface representations including Van der Waals surface, solvent excluded surface, solvent accessible surface and molecular surface. Moreover, based on the feature-rich version of iview, we have also developed a neat and tailor-made version specifically for our istar web platform for protein-ligand docking purpose. This demonstrates the excellent portability of iview. Using innovative 3D techniques, we provide a user friendly visualizer that is not intended to compete with professional visualizers, but to enable easy accessibility and platform independence.

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

PubMed

Puckett, Mary C

2015-01-01

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

Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

NASA Astrophysics Data System (ADS)

Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

2016-05-01

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

Peptide nucleic acid probe for protein affinity purification based on biotin-streptavidin interaction and peptide nucleic acid strand hybridization.

PubMed

Tse, Jenny; Wang, Yuanyuan; Zengeya, Thomas; Rozners, Eriks; Tan-Wilson, Anna

2015-02-01

We describe a new method for protein affinity purification that capitalizes on the high affinity of streptavidin for biotin but does not require dissociation of the biotin-streptavidin complex for protein retrieval. Conventional reagents place both the selectively reacting group (the "warhead") and the biotin on the same molecule. We place the warhead and the biotin on separate molecules, each linked to a short strand of peptide nucleic acid (PNA), synthetic polymers that use the same bases as DNA but attached to a backbone that is resistant to attack by proteases and nucleases. As in DNA, PNA strands with complementary base sequences hybridize. In conditions that favor PNA duplex formation, the warhead strand (carrying the tagged protein) and the biotin strand form a complex that is held onto immobilized streptavidin. As in DNA, the PNA duplex dissociates at moderately elevated temperature; therefore, retrieval of the tagged protein is accomplished by a brief exposure to heat. Using iodoacetate as the warhead, 8-base PNA strands, biotin, and streptavidin-coated magnetic beads, we demonstrate retrieval of the cysteine protease papain. We were also able to use our iodoacetyl-PNA:PNA-biotin probe for retrieval and identification of a thiol reductase and a glutathione transferase from soybean seedling cotyledons. Copyright © 2014 Elsevier Inc. All rights reserved.

WAVE binds Ena/VASP for enhanced Arp2/3 complex–based actin assembly

PubMed Central

Havrylenko, Svitlana; Noguera, Philippe; Abou-Ghali, Majdouline; Manzi, John; Faqir, Fahima; Lamora, Audrey; Guérin, Christophe; Blanchoin, Laurent; Plastino, Julie

2015-01-01

The WAVE complex is the main activator of the Arp2/3 complex for actin filament nucleation and assembly in the lamellipodia of moving cells. Other important players in lamellipodial protrusion are Ena/VASP proteins, which enhance actin filament elongation. Here we examine the molecular coordination between the nucleating activity of the Arp2/3 complex and the elongating activity of Ena/VASP proteins for the formation of actin networks. Using an in vitro bead motility assay, we show that WAVE directly binds VASP, resulting in an increase in Arp2/3 complex–based actin assembly. We show that this interaction is important in vivo as well, for the formation of lamellipodia during the ventral enclosure event of Caenorhabditis elegans embryogenesis. Ena/VASP's ability to bind F-actin and profilin-complexed G-actin are important for its effect, whereas Ena/VASP tetramerization is not necessary. Our data are consistent with the idea that binding of Ena/VASP to WAVE potentiates Arp2/3 complex activity and lamellipodial actin assembly. PMID:25355952

The solution structure of the pentatricopeptide repeat protein PPR10 upon binding atpH RNA

PubMed Central

Gully, Benjamin S.; Cowieson, Nathan; Stanley, Will A.; Shearston, Kate; Small, Ian D.; Barkan, Alice; Bond, Charles S.

2015-01-01

The pentatricopeptide repeat (PPR) protein family is a large family of RNA-binding proteins that is characterized by tandem arrays of a degenerate 35-amino-acid motif which form an α-solenoid structure. PPR proteins influence the editing, splicing, translation and stability of specific RNAs in mitochondria and chloroplasts. Zea mays PPR10 is amongst the best studied PPR proteins, where sequence-specific binding to two RNA transcripts, atpH and psaJ, has been demonstrated to follow a recognition code where the identity of two amino acids per repeat determines the base-specificity. A recently solved ZmPPR10:psaJ complex crystal structure suggested a homodimeric complex with considerably fewer sequence-specific protein–RNA contacts than inferred previously. Here we describe the solution structure of the ZmPPR10:atpH complex using size-exclusion chromatography-coupled synchrotron small-angle X-ray scattering (SEC-SY-SAXS). Our results support prior evidence that PPR10 binds RNA as a monomer, and that it does so in a manner that is commensurate with a canonical and predictable RNA-binding mode across much of the RNA–protein interface. PMID:25609698

A combinatorial approach to protein docking with flexible side chains.

PubMed

Althaus, Ernst; Kohlbacher, Oliver; Lenhof, Hans-Peter; Müller, Peter

2002-01-01

Rigid-body docking approaches are not sufficient to predict the structure of a protein complex from the unbound (native) structures of the two proteins. Accounting for side chain flexibility is an important step towards fully flexible protein docking. This work describes an approach that allows conformational flexibility for the side chains while keeping the protein backbone rigid. Starting from candidates created by a rigid-docking algorithm, we demangle the side chains of the docking site, thus creating reasonable approximations of the true complex structure. These structures are ranked with respect to the binding free energy. We present two new techniques for side chain demangling. Both approaches are based on a discrete representation of the side chain conformational space by the use of a rotamer library. This leads to a combinatorial optimization problem. For the solution of this problem, we propose a fast heuristic approach and an exact, albeit slower, method that uses branch-and-cut techniques. As a test set, we use the unbound structures of three proteases and the corresponding protein inhibitors. For each of the examples, the highest-ranking conformation produced was a good approximation of the true complex structure.

All-Atom Four-Body Knowledge-Based Statistical Potentials to Distinguish Native Protein Structures from Nonnative Folds

PubMed Central

2017-01-01

Recent advances in understanding protein folding have benefitted from coarse-grained representations of protein structures. Empirical energy functions derived from these techniques occasionally succeed in distinguishing native structures from their corresponding ensembles of nonnative folds or decoys which display varying degrees of structural dissimilarity to the native proteins. Here we utilized atomic coordinates of single protein chains, comprising a large diverse training set, to develop and evaluate twelve all-atom four-body statistical potentials obtained by exploring alternative values for a pair of inherent parameters. Delaunay tessellation was performed on the atomic coordinates of each protein to objectively identify all quadruplets of interacting atoms, and atomic potentials were generated via statistical analysis of the data and implementation of the inverted Boltzmann principle. Our potentials were evaluated using benchmarking datasets from Decoys-‘R'-Us, and comparisons were made with twelve other physics- and knowledge-based potentials. Ranking 3rd, our best potential tied CHARMM19 and surpassed AMBER force field potentials. We illustrate how a generalized version of our potential can be used to empirically calculate binding energies for target-ligand complexes, using HIV-1 protease-inhibitor complexes for a practical application. The combined results suggest an accurate and efficient atomic four-body statistical potential for protein structure prediction and assessment. PMID:29119109

Blocking the RecA activity and SOS-response in bacteria with a short α-helical peptide.

PubMed

Yakimov, Alexander; Pobegalov, Georgii; Bakhlanova, Irina; Khodorkovskii, Mikhail; Petukhov, Michael; Baitin, Dmitry

2017-09-19

The RecX protein, a very active natural RecA protein inhibitor, can completely disassemble RecA filaments at nanomolar concentrations that are two to three orders of magnitude lower than that of RecA protein. Based on the structure of RecX protein complex with the presynaptic RecA filament, we designed a short first in class α-helical peptide that both inhibits RecA protein activities in vitro and blocks the bacterial SOS-response in vivo. The peptide was designed using SEQOPT, a novel method for global sequence optimization of protein α-helices. SEQOPT produces artificial peptide sequences containing only 20 natural amino acids with the maximum possible conformational stability at a given pH, ionic strength, temperature, peptide solubility. It also accounts for restrictions due to known amino acid residues involved in stabilization of protein complexes under consideration. The results indicate that a few key intermolecular interactions inside the RecA protein presynaptic complex are enough to reproduce the main features of the RecX protein mechanism of action. Since the SOS-response provides a major mechanism of bacterial adaptation to antibiotics, these results open new ways for the development of antibiotic co-therapy that would not cause bacterial resistance. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Locating overlapping dense subgraphs in gene (protein) association networks and predicting novel protein functional groups among these subgraphs

NASA Astrophysics Data System (ADS)

Palla, Gergely; Derenyi, Imre; Farkas, Illes J.; Vicsek, Tamas

2006-03-01

Most tasks in a cell are performed not by individual proteins, but by functional groups of proteins (either physically interacting with each other or associated in other ways). In gene (protein) association networks these groups show up as sets of densely connected nodes. In the yeast, Saccharomyces cerevisiae, known physically interacting groups of proteins (called protein complexes) strongly overlap: the total number of proteins contained by these complexes by far underestimates the sum of their sizes (2750 vs. 8932). Thus, most functional groups of proteins, both physically interacting and other, are likely to share many of their members with other groups. However, current algorithms searching for dense groups of nodes in networks usually exclude overlaps. With the aim to discover both novel functions of individual proteins and novel protein functional groups we combine in protein association networks (i) a search for overlapping dense subgraphs based on the Clique Percolation Method (CPM) (Palla, G., et.al. Nature 435, 814-818 (2005), http://angel.elte.hu/clustering), which explicitly allows for overlaps among the groups, and (ii) a verification and characterization of the identified groups of nodes (proteins) with the help of standard annotation databases listing known functions.

Network pharmacology-based strategy for predicting active ingredients and potential targets of Yangxinshi tablet for treating heart failure.

PubMed

Chen, Langdong; Cao, Yan; Zhang, Hai; Lv, Diya; Zhao, Yahong; Liu, Yanjun; Ye, Guan; Chai, Yifeng

2018-01-31

Yangxinshi tablet (YXST) is an effective treatment for heart failure and myocardial infarction; it consists of 13 herbal medicines formulated according to traditional Chinese Medicine (TCM) practices. It has been used for the treatment of cardiovascular disease for many years in China. In this study, a network pharmacology-based strategy was used to elucidate the mechanism of action of YXST for the treatment of heart failure. Cardiovascular disease-related protein target and compound databases were constructed for YXST. A molecular docking platform was used to predict the protein targets of YXST. The affinity between proteins and ingredients was determined using surface plasmon resonance (SPR) assays. The action modes between targets and representative ingredients were calculated using Glide docking, and the related pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A protein target database containing 924 proteins was constructed; 179 compounds in YXST were identified, and 48 compounds with high relevance to the proteins were defined as representative ingredients. Thirty-four protein targets of the 48 representative ingredients were analyzed and classified into two categories: immune and cardiovascular systems. The SPR assay and molecular docking partly validated the interplay between protein targets and representative ingredients. Moreover, 28 pathways related to heart failure were identified, which provided directions for further research on YXST. This study demonstrated that the cardiovascular protective effect of YXST mainly involved the immune and cardiovascular systems. Through the research strategy based on network pharmacology, we analysis the complex system of YXST and found 48 representative compounds, 34 proteins and 28 related pathways of YXST, which could help us understand the underlying mechanism of YSXT's anti-heart failure effect. The network-based investigation could help researchers simplify the complex system of YXSY. It may also offer a feasible approach to decipher the chemical and pharmacological bases of other TCM formulas. Copyright © 2018 Elsevier B.V. All rights reserved.

Small-volume potentiometric titrations: EPR investigations of Fe-S cluster N2 in mitochondrial complex I.

PubMed

Wright, John J; Salvadori, Enrico; Bridges, Hannah R; Hirst, Judy; Roessler, Maxie M

2016-09-01

EPR-based potentiometric titrations are a well-established method for determining the reduction potentials of cofactors in large and complex proteins with at least one EPR-active state. However, such titrations require large amounts of protein. Here, we report a new method that requires an order of magnitude less protein than previously described methods, and that provides EPR samples suitable for measurements at both X- and Q-band microwave frequencies. We demonstrate our method by determining the reduction potential of the terminal [4Fe-4S] cluster (N2) in the intramolecular electron-transfer relay in mammalian respiratory complex I. The value determined by our method, E m7 =-158mV, is precise, reproducible, and consistent with previously reported values. Our small-volume potentiometric titration method will facilitate detailed investigations of EPR-active centres in non-abundant and refractory proteins that can only be prepared in small quantities. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Following DNA chain extension and protein conformational changes in crystals of a Y-family DNA polymerase via Raman crystallography.

PubMed

Espinoza-Herrera, Shirly J; Gaur, Vineet; Suo, Zucai; Carey, Paul R

2013-07-23

Y-Family DNA polymerases are known to bypass DNA lesions in vitro and in vivo. Sulfolobus solfataricus DNA polymerase (Dpo4) was chosen as a model Y-family enzyme for investigating the mechanism of DNA synthesis in single crystals. Crystals of Dpo4 in complexes with DNA (the binary complex) in the presence or absence of an incoming nucleotide were analyzed by Raman microscopy. (13)C- and (15)N-labeled d*CTP, or unlabeled dCTP, were soaked into the binary crystals with G as the templating base. In the presence of the catalytic metal ions, Mg(2+) and Mn(2+), nucleotide incorporation was detected by the disappearance of the triphosphate band of dCTP and the retention of *C modes in the crystal following soaking out of noncovalently bound C(or *C)TP. The addition of the second coded base, thymine, was observed by adding cognate dTTP to the crystal following a single d*CTP addition. Adding these two bases caused visible damage to the crystal that was possibly caused by protein and/or DNA conformational change within the crystal. When d*CTP is soaked into the Dpo4 crystal in the absence of Mn(2+) or Mg(2+), the primer extension reaction did not occur; instead, a ternary protein·template·d*CTP complex was formed. In the Raman difference spectra of both binary and ternary complexes, in addition to the modes of d(*C)CTP, features caused by ring modes from the template/primer bases being perturbed and from the DNA backbone appear, as well as features from perturbed peptide and amino acid side chain modes. These effects are more pronounced in the ternary complex than in the binary complex. Using standardized Raman intensities followed as a function of time, the C(*C)TP population in the crystal was maximal at ∼20 min. These remained unchanged in the ternary complex but declined in the binary complexes as chain incorporation occurred.

Interaction of the Human Respiratory Syncytial Virus matrix protein with cellular adaptor protein complex 3 plays a critical role in trafficking.

PubMed

Ward, Casey; Maselko, Maciej; Lupfer, Christopher; Prescott, Meagan; Pastey, Manoj K

2017-01-01

Human Respiratory Syncytial Virus (HRSV) is a leading cause of bronchopneumonia in infants and the elderly. To date, knowledge of viral and host protein interactions within HRSV is limited and are critical areas of research. Here, we show that HRSV Matrix (M) protein interacts with the cellular adaptor protein complex 3 specifically via its medium subunit (AP-3Mu3A). This novel protein-protein interaction was first detected via yeast-two hybrid screen and was further confirmed in a mammalian system by immunofluorescence colocalization and co-immunoprecipitation. This novel interaction is further substantiated by the presence of a known tyrosine-based adaptor protein MU subunit sorting signal sequence, YXXФ: where Ф is a bulky hydrophobic residue, which is conserved across the related RSV M proteins. Analysis of point-mutated HRSV M derivatives indicated that AP-3Mu3A- mediated trafficking is contingent on the presence of the tyrosine residue within the YXXL sorting sequence at amino acids 197-200 of the M protein. AP-3Mu3A is up regulated at 24 hours post-infection in infected cells versus mock-infected HEp2 cells. Together, our data suggests that the AP-3 complex plays a critical role in the trafficking of HRSV proteins specifically matrix in epithelial cells. The results of this study add new insights and targets that may lead to the development of potential antivirals and attenuating mutations suitable for candidate vaccines in the future.

FRODOCK 2.0: fast protein-protein docking server.

PubMed

Ramírez-Aportela, Erney; López-Blanco, José Ramón; Chacón, Pablo

2016-08-01

The prediction of protein-protein complexes from the structures of unbound components is a challenging and powerful strategy to decipher the mechanism of many essential biological processes. We present a user-friendly protein-protein docking server based on an improved version of FRODOCK that includes a complementary knowledge-based potential. The web interface provides a very effective tool to explore and select protein-protein models and interactively screen them against experimental distance constraints. The competitive success rates and efficiency achieved allow the retrieval of reliable potential protein-protein binding conformations that can be further refined with more computationally demanding strategies. The server is free and open to all users with no login requirement at http://frodock.chaconlab.org pablo@chaconlab.org Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Tandem Affinity Purification of Protein Complexes from Eukaryotic Cells.

PubMed

Ma, Zheng; Fung, Victor; D'Orso, Iván

2017-01-26

The purification of active protein-protein and protein-nucleic acid complexes is crucial for the characterization of enzymatic activities and de novo identification of novel subunits and post-translational modifications. Bacterial systems allow for the expression and purification of a wide variety of single polypeptides and protein complexes. However, this system does not enable the purification of protein subunits that contain post-translational modifications (e.g., phosphorylation and acetylation), and the identification of novel regulatory subunits that are only present/expressed in the eukaryotic system. Here, we provide a detailed description of a novel, robust, and efficient tandem affinity purification (TAP) method using STREP- and FLAG-tagged proteins that facilitates the purification of protein complexes with transiently or stably expressed epitope-tagged proteins from eukaryotic cells. This protocol can be applied to characterize protein complex functionality, to discover post-translational modifications on complex subunits, and to identify novel regulatory complex components by mass spectrometry. Notably, this TAP method can be applied to study protein complexes formed by eukaryotic or pathogenic (viral and bacterial) components, thus yielding a wide array of downstream experimental opportunities. We propose that researchers working with protein complexes could utilize this approach in many different ways.

Molecular Signatures of Membrane Protein Complexes Underlying Muscular Dystrophy*

PubMed Central

Turk, Rolf; Hsiao, Jordy J.; Smits, Melinda M.; Ng, Brandon H.; Pospisil, Tyler C.; Jones, Kayla S.; Campbell, Kevin P.; Wright, Michael E.

2016-01-01

Mutations in genes encoding components of the sarcolemmal dystrophin-glycoprotein complex (DGC) are responsible for a large number of muscular dystrophies. As such, molecular dissection of the DGC is expected to both reveal pathological mechanisms, and provides a biological framework for validating new DGC components. Establishment of the molecular composition of plasma-membrane protein complexes has been hampered by a lack of suitable biochemical approaches. Here we present an analytical workflow based upon the principles of protein correlation profiling that has enabled us to model the molecular composition of the DGC in mouse skeletal muscle. We also report our analysis of protein complexes in mice harboring mutations in DGC components. Bioinformatic analyses suggested that cell-adhesion pathways were under the transcriptional control of NFκB in DGC mutant mice, which is a finding that is supported by previous studies that showed NFκB-regulated pathways underlie the pathophysiology of DGC-related muscular dystrophies. Moreover, the bioinformatic analyses suggested that inflammatory and compensatory mechanisms were activated in skeletal muscle of DGC mutant mice. Additionally, this proteomic study provides a molecular framework to refine our understanding of the DGC, identification of protein biomarkers of neuromuscular disease, and pharmacological interrogation of the DGC in adult skeletal muscle https://www.mda.org/disease/congenital-muscular-dystrophy/research. PMID:27099343

Protein Identification Using Top-Down Spectra*

PubMed Central

Liu, Xiaowen; Sirotkin, Yakov; Shen, Yufeng; Anderson, Gordon; Tsai, Yihsuan S.; Ting, Ying S.; Goodlett, David R.; Smith, Richard D.; Bafna, Vineet; Pevzner, Pavel A.

2012-01-01

In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set. PMID:22027200

Stabilization of non-productive conformations underpins rapid electron transfer to electron-transferring flavoprotein.

PubMed

Toogood, Helen S; van Thiel, Adam; Scrutton, Nigel S; Leys, David

2005-08-26

Crystal structures of protein complexes with electron-transferring flavoprotein (ETF) have revealed a dual protein-protein interface with one region serving as anchor while the ETF FAD domain samples available space within the complex. We show that mutation of the conserved Glu-165beta in human ETF leads to drastically modulated rates of interprotein electron transfer with both medium chain acyl-CoA dehydrogenase and dimethylglycine dehydrogenase. The crystal structure of free E165betaA ETF is essentially identical to that of wild-type ETF, but the crystal structure of the E165betaA ETF.medium chain acyl-CoA dehydrogenase complex reveals clear electron density for the FAD domain in a position optimal for fast interprotein electron transfer. Based on our observations, we present a dynamic multistate model for conformational sampling that for the wild-type ETF. medium chain acyl-CoA dehydrogenase complex involves random motion between three distinct positions for the ETF FAD domain. ETF Glu-165beta plays a key role in stabilizing positions incompatible with fast interprotein electron transfer, thus ensuring high rates of complex dissociation.

Illuminating cellular structure and function in the early secretory pathway by multispectral 3D imaging in living cells

NASA Astrophysics Data System (ADS)

Rietdorf, Jens; Stephens, David J.; Squire, Anthony; Simpson, Jeremy; Shima, David T.; Paccaud, Jean-Pierre; Bastiaens, Philippe I.; Pepperkok, Rainer

2000-04-01

Membrane traffic between the endoplasmic reticulum (ER) and the Golgi complex is regulated by two vesicular coat complexes, COPII and COPI. COPII has been implicated in selective packaging of anterograde cargo into coated transport vesicles budding from the ER. COPI-coated vesicles are proposed to mediate recycling of proteins from the Golgi complex to the ER. We have used multi spectral 3D imaging to visualize COPI and COPII behavior simultaneously with various GFP-tagged secretory markers in living cells. This shows that COPII and COPI act sequentially whereby COPI association with anterograde transport complexes is involved in microtubule-based transport and the en route segregation of ER recycling molecules from secretory cargo within TCS in transit to the Golgi complex. We have also investigated the possibility to discriminate spectrally GFP fusion proteins by fluorescence lifetime imaging. This shows that at least two, and possibly up to three GFP fusion proteins can be discriminated and localized in living cells using a single excitation wavelength and a single broad band emission filter.

Replication-mediated disassociation of replication protein A-XPA complex upon DNA damage: implications for RPA handing off.

PubMed

Jiang, Gaofeng; Zou, Yue; Wu, Xiaoming

2012-08-01

RPA (replication protein A), the eukaryotic ssDNA (single-stranded DNA)-binding protein, participates in most cellular processes in response to genotoxic insults, such as NER (nucleotide excision repair), DNA, DSB (double-strand break) repair and activation of cell cycle checkpoint signalling. RPA interacts with XPA (xeroderma pigmentosum A) and functions in early stage of NER. We have shown that in cells the RPA-XPA complex disassociated upon exposure of cells to high dose of UV irradiation. The dissociation required replication stress and was partially attributed to tRPA hyperphosphorylation. Treatment of cells with CPT (camptothecin) and HU (hydroxyurea), which cause DSB DNA damage and replication fork collapse respectively and also leads to the disruption of RPA-XPA complex. Purified RPA and XPA were unable to form complex in vitro in the presence of ssDNA. We propose that the competition-based RPA switch among different DNA metabolic pathways regulates the dissociation of RPA with XPA in cells after DNA damage. The biological significances of RPA-XPA complex disruption in relation with checkpoint activation, DSB repair and RPA hyperphosphorylation are discussed.

Light-fuelled transport of large dendrimers and proteins.

PubMed

Koskela, Jenni E; Liljeström, Ville; Lim, Jongdoo; Simanek, Eric E; Ras, Robin H A; Priimagi, Arri; Kostiainen, Mauri A

2014-05-14

This work presents a facile water-based supramolecular approach for light-induced surface patterning. The method is based upon azobenzene-functionalized high-molecular weight triazine dendrimers up to generation 9, demonstrating that even very large globular supramolecular complexes can be made to move in response to light. We also demonstrate light-fuelled macroscopic movements in native biomolecules, showing that complexes of apoferritin protein and azobenzene can effectively form light-induced surface patterns. Fundamentally, the results establish that thin films comprising both flexible and rigid globular particles of large diameter can be moved with light, whereas the presented material concepts offer new possibilities for the yet marginally explored biological applications of azobenzene surface patterning.

A knowledge-based decision support system in bioinformatics: an application to protein complex extraction

PubMed Central

2013-01-01

Background We introduce a Knowledge-based Decision Support System (KDSS) in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB) coding the expertise about the proposed scenario, our KDSS is able to suggest both strategies and tools, according to the features of input dataset. Our system provides a navigable workflow for the current experiment and furthermore it offers support in the configuration and running of every processing component of that workflow. This last feature makes our system a crossover between classical DSS and Workflow Management Systems. Results We briefly present the KDSS' architecture and basic concepts used in the design of the knowledge base and the reasoning component. The system is then tested using a subset of Saccharomyces cerevisiae Protein-Protein interaction dataset. We used this subset because it has been well studied in literature by several research groups in the field of complex extraction: in this way we could easily compare the results obtained through our KDSS with theirs. Our system suggests both a preprocessing and a clustering strategy, and for each of them it proposes and eventually runs suited algorithms. Our system's final results are then composed of a workflow of tasks, that can be reused for other experiments, and the specific numerical results for that particular trial. Conclusions The proposed approach, using the KDSS' knowledge base, provides a novel workflow that gives the best results with regard to the other workflows produced by the system. This workflow and its numeric results have been compared with other approaches about PPI network analysis found in literature, offering similar results. PMID:23368995

Accurate characterization of weak macromolecular interactions by titration of NMR residual dipolar couplings: application to the CD2AP SH3-C:ubiquitin complex

PubMed Central

Ortega-Roldan, Jose Luis; Jensen, Malene Ringkjøbing; Brutscher, Bernhard; Azuaga, Ana I.; Blackledge, Martin; van Nuland, Nico A. J.

2009-01-01

The description of the interactome represents one of key challenges remaining for structural biology. Physiologically important weak interactions, with dissociation constants above 100 μM, are remarkably common, but remain beyond the reach of most of structural biology. NMR spectroscopy, and in particular, residual dipolar couplings (RDCs) provide crucial conformational constraints on intermolecular orientation in molecular complexes, but the combination of free and bound contributions to the measured RDC seriously complicates their exploitation for weakly interacting partners. We develop a robust approach for the determination of weak complexes based on: (i) differential isotopic labeling of the partner proteins facilitating RDC measurement in both partners; (ii) measurement of RDC changes upon titration into different equilibrium mixtures of partially aligned free and complex forms of the proteins; (iii) novel analytical approaches to determine the effective alignment in all equilibrium mixtures; and (iv) extraction of precise RDCs for bound forms of both partner proteins. The approach is demonstrated for the determination of the three-dimensional structure of the weakly interacting CD2AP SH3-C:Ubiquitin complex (Kd = 132 ± 13 μM) and is shown, using cross-validation, to be highly precise. We expect this methodology to extend the remarkable and unique ability of NMR to study weak protein–protein complexes. PMID:19359362

Analysis of Immune Complex Structure by Statistical Mechanics and Light Scattering Techniques.

NASA Astrophysics Data System (ADS)

Busch, Nathan Adams

1995-01-01

The size and structure of immune complexes determine their behavior in the immune system. The chemical physics of the complex formation is not well understood; this is due in part to inadequate characterization of the proteins involved, and in part by lack of sufficiently well developed theoretical techniques. Understanding the complex formation will permit rational design of strategies for inhibiting tissue deposition of the complexes. A statistical mechanical model of the proteins based upon the theory of associating fluids was developed. The multipole electrostatic potential for each protein used in this study was characterized for net protein charge, dipole moment magnitude, and dipole moment direction. The binding sites, between the model antigen and antibodies, were characterized for their net surface area, energy, and position relative to the dipole moment of the protein. The equilibrium binding graphs generated with the protein statistical mechanical model compares favorably with experimental data obtained from radioimmunoassay results. The isothermal compressibility predicted by the model agrees with results obtained from dynamic light scattering. The statistical mechanics model was used to investigate association between the model antigen and selected pairs of antibodies. It was found that, in accordance to expectations from thermodynamic arguments, the highest total binding energy yielded complex distributions which were skewed to higher complex size. From examination of the simulated formation of ring structures from linear chain complexes, and from the joint shape probability surfaces, it was found that ring configurations were formed by the "folding" of linear chains until the ends are within binding distance. By comparing the single antigen/two antibody system which differ only in their respective binding site locations, it was found that binding site location influences complex size and shape distributions only when ring formation occurs. The internal potential energy of a ring complex is considerably less than that of the non-associating system; therefore the ring complexes are quite stable and show no evidence of breaking, and collapsing into smaller complexes. The ring formation will occur only in systems where the total free energy of each complex may be minimized. Thus, ring formation will occur even though entropically unfavorable conformations result if the total free energy can be minimized by doing so.

A New Ligand-Based Method for Purifying Active Human Plasma-Derived Ficolin-3 Complexes Supports the Phenomenon of Crosstalk between Pattern-Recognition Molecules and Immunoglobulins

PubMed Central

Man-Kupisinska, Aleksandra; Michalski, Mateusz; Maciejewska, Anna; Swierzko, Anna S.; Cedzynski, Maciej; Lugowski, Czeslaw; Lukasiewicz, Jolanta

2016-01-01

Despite recombinant protein technology development, proteins isolated from natural sources remain important for structure and activity determination. Ficolins represent a class of proteins that are difficult to isolate. To date, three methods for purifying ficolin-3 from plasma/serum have been proposed, defined by most critical step: (i) hydroxyapatite absorption chromatography (ii) N-acetylated human serum albumin affinity chromatography and (iii) anti-ficolin-3 monoclonal antibody-based affinity chromatography. We present a new protocol for purifying ficolin-3 complexes from human plasma that is based on an exclusive ligand: the O-specific polysaccharide of Hafnia alvei PCM 1200 LPS (O-PS 1200). The protocol includes (i) poly(ethylene glycol) precipitation; (ii) yeast and l-fucose incubation, for depletion of mannose-binding lectin; (iii) affinity chromatography using O-PS 1200-Sepharose; (iv) size-exclusion chromatography. Application of this protocol yielded average 2.2 mg of ficolin-3 preparation free of mannose-binding lectin (MBL), ficolin-1 and -2 from 500 ml of plasma. The protein was complexed with MBL-associated serine proteases (MASPs) and was able to activate the complement in vitro. In-process monitoring of MBL, ficolins, and total protein content revealed the presence of difficult-to-remove immunoglobulin G, M and A, in some extent in agreement with recent findings suggesting crosstalk between IgG and ficolin-3. We demonstrated that recombinant ficolin-3 interacts with IgG and IgM in a concentration-dependent manner. Although this association does not appear to influence ficolin-3-ligand interactions in vitro, it may have numerous consequences in vivo. Thus our purification procedure provides Ig-ficolin-3/MASP complexes that might be useful for gaining further insight into the crosstalk and biological activity of ficolin-3. PMID:27232184

Structural Basis for the Interaction of the Golgi-Associated Retrograde Protein (GARP) Complex with the t-SNARE Syntaxin 6

PubMed Central

Abascal-Palacios, Guillermo; Schindler, Christina; Rojas, Adriana L; Bonifacino, Juan S.; Hierro, Aitor

2016-01-01

Summary The Golgi-Associated Retrograde Protein (GARP) is a tethering complex involved in the fusion of endosome-derived transport vesicles to the trans-Golgi network through interaction with components of the Syntaxin 6/Syntaxin 16/Vti1a/VAMP4 SNARE complex. The mechanisms by which GARP and other tethering factors engage the SNARE fusion machinery are poorly understood. Herein we report the structural basis for the interaction of the human Ang2 subunit of GARP with Syntaxin 6 and the closely related Syntaxin 10. The crystal structure of Syntaxin 6 Habc domain in complex with a peptide from the N terminus of Ang2 shows a novel binding mode in which a di-tyrosine motif of Ang2 interacts with a highly conserved groove in Syntaxin 6. Structure-based mutational analyses validate the crystal structure and support the phylogenetic conservation of this interaction. The same binding determinants are found in other tethering proteins and syntaxins, suggesting a general interaction mechanism. PMID:23932592

PRISM-EM: template interface-based modelling of multi-protein complexes guided by cryo-electron microscopy density maps.

PubMed

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

2016-10-01

The structures of protein assemblies are important for elucidating cellular processes at the molecular level. Three-dimensional electron microscopy (3DEM) is a powerful method to identify the structures of assemblies, especially those that are challenging to study by crystallography. Here, a new approach, PRISM-EM, is reported to computationally generate plausible structural models using a procedure that combines crystallographic structures and density maps obtained from 3DEM. The predictions are validated against seven available structurally different crystallographic complexes. The models display mean deviations in the backbone of <5 Å. PRISM-EM was further tested on different benchmark sets; the accuracy was evaluated with respect to the structure of the complex, and the correlation with EM density maps and interface predictions were evaluated and compared with those obtained using other methods. PRISM-EM was then used to predict the structure of the ternary complex of the HIV-1 envelope glycoprotein trimer, the ligand CD4 and the neutralizing protein m36.

TelAP1 links telomere complexes with developmental expression site silencing in African trypanosomes

PubMed Central

Reis, Helena; Schwebs, Marie; Dietz, Sabrina; Janzen, Christian J; Butter, Falk

2018-01-01

Abstract During its life cycle, Trypanosoma brucei shuttles between a mammalian host and the tsetse fly vector. In the mammalian host, immune evasion of T. brucei bloodstream form (BSF) cells relies on antigenic variation, which includes monoallelic expression and periodic switching of variant surface glycoprotein (VSG) genes. The active VSG is transcribed from only 1 of the 15 subtelomeric expression sites (ESs). During differentiation from BSF to the insect-resident procyclic form (PCF), the active ES is transcriptionally silenced. We used mass spectrometry-based interactomics to determine the composition of telomere protein complexes in T. brucei BSF and PCF stages to learn more about the structure and functions of telomeres in trypanosomes. Our data suggest a different telomere complex composition in the two forms of the parasite. One of the novel telomere-associated proteins, TelAP1, forms a complex with telomeric proteins TbTRF, TbRAP1 and TbTIF2 and influences ES silencing kinetics during developmental differentiation. PMID:29385523

Nucleoprotein Complexes Containing Replicating Simian Virus 40 DNA: Comparison with Polyoma Nucleoprotein Complexes

PubMed Central

Hall, Mark R.; Meinke, William; Goldstein, David A.

1973-01-01

Procedures for isolating nucleoprotein complexes containing replicating polyoma DNA from infected mouse cells were used to prepare short-lived nucleoprotein complexes (r-SV40 complexes) containing replicating simian virus 40 (SV40) DNA from infected monkey cells. Like the polyoma complexes, r-SV40 complexes were only partially released from nuclei by cell lysis but could be extracted from nuclei by prolonged treatment with solutions containing Triton X-100. r-SV40 complexes sedimented faster than complexes containing SV40 supercoiled DNA (SV40 complex) in sucrose gradients, and both types of SV40 nucleoprotein complexes sedimented ahead of polyoma complexes containing supercoiled polyoma DNA (py complex). The sedimentation rates of py complex and SV40 complex were 56 and 61S, respectively, based on the sedimentation rate of the mouse large ribosomal subunit as a marker. r-SV40 complexes sedimented as multiple peaks between 56 and 75S. Sedimentation and buoyant density measurements indicated that protein is bound to all forms of SV40 DNA at about the same ratio of protein to DNA (1-2/1) as was reported for polyoma nucleoproteins. PMID:4359958

Crystal structures of the apo and ATP bound Mycobacterium tuberculosis nitrogen regulatory PII protein

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

Shetty, Nishant D.; Reddy, Manchi C.M.; Palaninathan, Satheesh K.

2010-10-11

PII constitutes a family of signal transduction proteins that act as nitrogen sensors in microorganisms and plants. Mycobacterium tuberculosis (Mtb) has a single homologue of PII whose precise role has as yet not been explored. We have solved the crystal structures of the Mtb PII protein in its apo and ATP bound forms to 1.4 and 2.4 {angstrom} resolutions, respectively. The protein forms a trimeric assembly in the crystal lattice and folds similarly to the other PII family proteins. The Mtb PII:ATP binary complex structure reveals three ATP molecules per trimer, each bound between the base of the T-loop ofmore » one subunit and the C-loop of the neighboring subunit. In contrast to the apo structure, at least one subunit of the binary complex structure contains a completely ordered T-loop indicating that ATP binding plays a role in orienting this loop region towards target proteins like the ammonium transporter, AmtB. Arg38 of the T-loop makes direct contact with the {gamma}-phosphate of the ATP molecule replacing the Mg{sup 2+} position seen in the Methanococcus jannaschii GlnK1 structure. The C-loop of a neighboring subunit encloses the other side of the ATP molecule, placing the GlnK specific C-terminal 3{sub 10} helix in the vicinity. Homology modeling studies with the E. coli GlnK:AmtB complex reveal that Mtb PII could form a complex similar to the complex in E. coli. The structural conservation and operon organization suggests that the Mtb PII gene encodes for a GlnK protein and might play a key role in the nitrogen regulatory pathway.« less

Protein-ligand complex structure from serial femtosecond crystallography using soaked thermolysin microcrystals and comparison with structures from synchrotron radiation.

PubMed

Naitow, Hisashi; Matsuura, Yoshinori; Tono, Kensuke; Joti, Yasumasa; Kameshima, Takashi; Hatsui, Takaki; Yabashi, Makina; Tanaka, Rie; Tanaka, Tomoyuki; Sugahara, Michihiro; Kobayashi, Jun; Nango, Eriko; Iwata, So; Kunishima, Naoki

2017-08-01

Serial femtosecond crystallography (SFX) with an X-ray free-electron laser is used for the structural determination of proteins from a large number of microcrystals at room temperature. To examine the feasibility of pharmaceutical applications of SFX, a ligand-soaking experiment using thermolysin microcrystals has been performed using SFX. The results were compared with those from a conventional experiment with synchrotron radiation (SR) at 100 K. A protein-ligand complex structure was successfully obtained from an SFX experiment using microcrystals soaked with a small-molecule ligand; both oil-based and water-based crystal carriers gave essentially the same results. In a comparison of the SFX and SR structures, clear differences were observed in the unit-cell parameters, in the alternate conformation of side chains, in the degree of water coordination and in the ligand-binding mode.

[Modulation of Kv4 channels by KChIPs clamping].

PubMed

Cui, Yuan-Yuan; Wang, Ke-Wei

2009-01-01

The rapidly inactivating (A-type) potassium channels regulate membrane excitability that defines the fundamental mechanism of neuronal functions such as pain signaling. Cytosolic Kv channel-interacting proteins KChIPs co-assemble with Kv4 (Shal) alpha subunits to form a native complex. The specific binding of auxiliary KChIPs to the Kv4 N-terminus results in modulation of gating properties, surface expression and subunit assembly of Kv4 channels. Based on recent structural efforts, here we attempt to emphasize the interaction between KChIPs and Kv4 channel complex in which a single KChIP1 molecule laterally clamps two neighboring Kv4.3 N-termini in a 4:4 manner. Greater insights into molecular mechanism between KChIPs and Kv4 interaction may provide therapeutic potentials by structure-based design of chemical compounds aimed at disrupting the protein-protein interaction for treatment of membrane excitability-related disorders.

Protein-protein structure prediction by scoring molecular dynamics trajectories of putative poses.

PubMed

Sarti, Edoardo; Gladich, Ivan; Zamuner, Stefano; Correia, Bruno E; Laio, Alessandro

2016-09-01

The prediction of protein-protein interactions and their structural configuration remains a largely unsolved problem. Most of the algorithms aimed at finding the native conformation of a protein complex starting from the structure of its monomers are based on searching the structure corresponding to the global minimum of a suitable scoring function. However, protein complexes are often highly flexible, with mobile side chains and transient contacts due to thermal fluctuations. Flexibility can be neglected if one aims at finding quickly the approximate structure of the native complex, but may play a role in structure refinement, and in discriminating solutions characterized by similar scores. We here benchmark the capability of some state-of-the-art scoring functions (BACH-SixthSense, PIE/PISA and Rosetta) in discriminating finite-temperature ensembles of structures corresponding to the native state and to non-native configurations. We produce the ensembles by running thousands of molecular dynamics simulations in explicit solvent starting from poses generated by rigid docking and optimized in vacuum. We find that while Rosetta outperformed the other two scoring functions in scoring the structures in vacuum, BACH-SixthSense and PIE/PISA perform better in distinguishing near-native ensembles of structures generated by molecular dynamics in explicit solvent. Proteins 2016; 84:1312-1320. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Protein and peptide-based therapeutics in periodontal regeneration.

PubMed

Reynolds, Mark A; Aichelmann-Reidy, Mary E

2012-09-01

Protein and peptide-based therapeutics provide a unique strategy for controlling highly specific and complex biologic actions that cannot be accomplished by simple devices or chemical compounds. This article reviews some of the key characteristics and summarizes the clinical effectiveness of protein and peptide-based therapeutics targeting periodontal regeneration. A literature search was conducted of randomized clinical trials and systematic reviews evaluating protein and peptide-based therapeutics for the regeneration of periodontal tissues of at least 6 months duration. Data sources included PubMed and Embase electronic databases, hand-searched journals, and the ClinicalTrials.gov registry. Commercially marketed protein and peptide-based therapeutics for periodontal regeneration provide gains in clinical attachment level and bone formation that are comparable or superior to other regenerative approaches. Results from several clinical trials indicate that protein and peptide-based therapies can accelerate repair and regeneration when compared with other treatments and that improvements in clinical parameters continue beyond 12 months. Protein and peptide-based therapies also exhibit the capacity to increase the predictability of treatment outcomes. Clinical and histologic studies support the effectiveness of protein- and peptide-based therapeutics for periodontal regeneration. Emerging evidence suggests that the delivery devices/scaffolds play a critical role in determining the effectiveness of this class of therapeutics. Copyright © 2012 Elsevier Inc. All rights reserved.

Proteomic Analysis of Virus-Host Interactions in an Infectious Context Using Recombinant Viruses*

PubMed Central

Komarova, Anastassia V.; Combredet, Chantal; Meyniel-Schicklin, Laurène; Chapelle, Manuel; Caignard, Grégory; Camadro, Jean-Michel; Lotteau, Vincent; Vidalain, Pierre-Olivier; Tangy, Frédéric

2011-01-01

RNA viruses exhibit small-sized genomes encoding few proteins, but still establish complex networks of interactions with host cell components to achieve replication and spreading. Ideally, these virus-host protein interactions should be mapped directly in infected cell culture, but such a high standard is often difficult to reach when using conventional approaches. We thus developed a new strategy based on recombinant viruses expressing tagged viral proteins to capture both direct and indirect physical binding partners during infection. As a proof of concept, we engineered a recombinant measles virus (MV) expressing one of its virulence factors, the MV-V protein, with a One-STrEP amino-terminal tag. This allowed virus-host protein complex analysis directly from infected cells by combining modified tandem affinity chromatography and mass spectrometry analysis. Using this approach, we established a prosperous list of 245 cellular proteins interacting either directly or indirectly with MV-V, and including four of the nine already known partners of this viral factor. These interactions were highly specific of MV-V because they were not recovered when the nucleoprotein MV-N, instead of MV-V, was tagged. Besides key components of the antiviral response, cellular proteins from mitochondria, ribosomes, endoplasmic reticulum, protein phosphatase 2A, and histone deacetylase complex were identified for the first time as prominent targets of MV-V and the critical role of the later protein family in MV replication was addressed. Most interestingly, MV-V showed some preferential attachment to essential proteins in the human interactome network, as assessed by centrality and interconnectivity measures. Furthermore, the list of MV-V interactors also showed a massive enrichment for well-known targets of other viruses. Altogether, this clearly supports our approach based on reverse genetics of viruses combined with high-throughput proteomics to probe the interaction network that viruses establish in infected cells. PMID:21911578

Molecular dynamic simulations and structure-based pharmacophore development for farnesyltransferase inhibitors discovery.

PubMed

Moorthy, N S Hari Narayana; Sousa, Sergio F; Ramos, Maria J; Fernandes, Pedro A

2016-12-01

Farnesyltransferase is one of the enzyme targets for the development of drugs for diseases, including cancer, malaria, progeria, etc. In the present study, the structure-based pharmacophore models have been developed from five complex structures (1LD7, 1NI1, 2IEJ, 2ZIR and 2ZIS) obtained from the protein data bank. Initially, molecular dynamic (MD) simulations were performed for the complexes for 10 ns using AMBER 12 software. The conformers of the complexes (75) generated from the equilibrated protein were undergone protein-ligand interaction fingerprint (PLIF) analysis. The results showed that some important residues, such as LeuB96, TrpB102, TrpB106, ArgB202, TyrB300, AspB359 and TyrB361, are predominantly present in most of the complexes for interactions. These residues form side chain acceptor and surface (hydrophobic or π-π) kind of interactions with the ligands present in the complexes. The structure-based pharmacophore models were generated from the fingerprint bits obtained from PLIF analysis. The pharmacophore models have 3-4 pharmacophore contours consist of acceptor and metal ligation (Acc & ML), hydrophobic (HydA) and extended acceptor (Acc2) features with the radius ranging between 1-3 Å for Acc & ML and 1-2 Å for HydA. The excluded volumes of the pharmacophore contours radius are between 1-2 Å. Further, the distance between the interacting groups, root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radial distribution function (RDF) analysis were performed for the MD-simulated proteins using PTRAJ module. The generated pharmacophore models were used to screen a set of natural compounds and database compounds to select significant HITs. We conclude that the developed pharmacophore model can be a significant model for the identification of HITs as FTase inhibitors.

Protein Degradation Rate in Arabidopsis thaliana Leaf Growth and Development[OPEN

PubMed Central

Nelson, Clark J.; Castleden, Ian

2017-01-01

We applied 15N labeling approaches to leaves of the Arabidopsis thaliana rosette to characterize their protein degradation rate and understand its determinants. The progressive labeling of new peptides with 15N and measuring the decrease in the abundance of >60,000 existing peptides over time allowed us to define the degradation rate of 1228 proteins in vivo. We show that Arabidopsis protein half-lives vary from several hours to several months based on the exponential constant of the decay rate for each protein. This rate was calculated from the relative isotope abundance of each peptide and the fold change in protein abundance during growth. Protein complex membership and specific protein domains were found to be strong predictors of degradation rate, while N-end amino acid, hydrophobicity, or aggregation propensity of proteins were not. We discovered rapidly degrading subunits in a variety of protein complexes in plastids and identified the set of plant proteins whose degradation rate changed in different leaves of the rosette and correlated with leaf growth rate. From this information, we have calculated the protein turnover energy costs in different leaves and their key determinants within the proteome. PMID:28138016

Isolation of integrin-based adhesion complexes.

PubMed

Jones, Matthew C; Humphries, Jonathan D; Byron, Adam; Millon-Frémillon, Angélique; Robertson, Joseph; Paul, Nikki R; Ng, Daniel H J; Askari, Janet A; Humphries, Martin J

2015-03-02

The integration of cells with their extracellular environment is facilitated by cell surface adhesion receptors, such as integrins, which play important roles in both normal development and the onset of pathologies. Engagement of integrins with their ligands in the extracellular matrix, or counter-receptors on other cells, initiates the intracellular assembly of a wide variety of proteins into adhesion complexes such as focal contacts, focal adhesions, and fibrillar adhesions. The proteins recruited to these complexes mediate bidirectional signaling across the plasma membrane, and, as such, help to coordinate and/or modulate the multitude of physical and chemical signals to which the cell is subjected. The protocols in this unit describe two approaches for the isolation or enrichment of proteins contained within integrin-associated adhesion complexes, together with their local plasma membrane/cytosolic environments, from cells in culture. In the first protocol, integrin-associated adhesion structures are affinity isolated using microbeads coated with extracellular ligands or antibodies. The second protocol describes the isolation of ventral membrane preparations that are enriched for adhesion complex structures. The protocols permit the determination of adhesion complex components via subsequent downstream analysis by western blotting or mass spectrometry. Copyright © 2015 John Wiley & Sons, Inc.

Radiation damage to nucleoprotein complexes in macromolecular crystallography

DOE PAGES

Bury, Charles; Garman, Elspeth F.; Ginn, Helen Mary; ...

2015-01-30

Significant progress has been made in macromolecular crystallography over recent years in both the understanding and mitigation of X-ray induced radiation damage when collecting diffraction data from crystalline proteins. Despite the large field that is productively engaged in the study of radiation chemistry of nucleic acids, particularly of DNA, there are currently very few X-ray crystallographic studies on radiation damage mechanisms in nucleic acids. Quantitative comparison of damage to protein and DNA crystals separately is challenging, but many of the issues are circumvented by studying pre-formed biological nucleoprotein complexes where direct comparison of each component can be made under themore » same controlled conditions. A model protein–DNA complex C.Esp1396I is employed to investigate specific damage mechanisms for protein and DNA in a biologically relevant complex over a large dose range (2.07–44.63 MGy). In order to allow a quantitative analysis of radiation damage sites from a complex series of macromolecular diffraction data, a computational method has been developed that is generally applicable to the field. Typical specific damage was observed for both the protein on particular amino acids and for the DNA on, for example, the cleavage of base-sugar N 1—C and sugar-phosphate C—O bonds. Strikingly the DNA component was determined to be far more resistant to specific damage than the protein for the investigated dose range. We observed the protein at low doses and found that they were susceptible to radiation damage while the DNA was far more resistant, damage only being observed at significantly higher doses.« less

iTRAQ-based Quantitative Proteomics Study in Patients with Refractory Mycoplasma pneumoniae Pneumonia.

PubMed

Yu, Jia-Lu; Song, Qi-Fang; Xie, Zhi-Wei; Jiang, Wen-Hui; Chen, Jia-Hui; Fan, Hui-Feng; Xie, Ya-Ping; Lu, Gen

2017-09-25

Mycoplasma pneumoniae (MP) is a leading cause of community-acquired pneumonia in children and young adults. Although MP pneumonia is usually benign and self-limited, in some cases it can develop into life-threating refractory MP pneumonia (RMPP). However, the pathogenesis of RMPP is poorly understood. The identification and characterization of proteins related to RMPP could provide a proof of principle to facilitate appropriate diagnostic and therapeutic strategies for treating paients with MP. In this study, we used a quantitative proteomic technique (iTRAQ) to analyze MP-related proteins in serum samples from 5 patients with RMPP, 5 patients with non-refractory MP pneumonia (NRMPP), and 5 healthy children. Functional classification, sub-cellular localization, and protein interaction network analysis were carried out based on protein annotation through evolutionary relationship (PANTHER) and Cytoscape analysis. A total of 260 differentially expressed proteins were identified in the RMPP and NRMPP groups. Compared to the control group, the NRMPP and RMPP groups showed 134 (70 up-regulated and 64 down-regulated) and 126 (63 up-regulated and 63 down-regulated) differentially expressed proteins, respectively. The complex functional classification and protein interaction network of the identified proteins reflected the complex pathogenesis of RMPP. Our study provides the first comprehensive proteome map of RMPP-related proteins from MP pneumonia. These profiles may be useful as part of a diagnostic panel, and the identified proteins provide new insights into the pathological mechanisms underlying RMPP.

THz frequency spectrum of protein-solvent interaction energy using a recurrence plot-based Wiener-Khinchin method.

PubMed

Karain, Wael

2016-10-01

The dynamics of a protein and the water surrounding it are coupled via nonbonded energy interactions. This coupling can exhibit a complex, nonlinear, and nonstationary nature. The THz frequency spectrum for this interaction energy characterizes both the vibration spectrum of the water hydrogen bond network, and the frequency range of large amplitude modes of proteins. We use a Recurrence Plot based Wiener-Khinchin method RPWK to calculate this spectrum, and the results are compared to those determined using the classical auto-covariance-based Wiener-Khinchin method WK. The frequency spectra for the total nonbonded interaction energy extracted from molecular dynamics simulations between the β-Lactamase Inhibitory Protein BLIP, and water molecules within a 10 Å distance from the protein surface, are calculated at 150, 200, 250, and 310 K, respectively. Similar calculations are also performed for the nonbonded interaction energy between the residues 49ASP, 53TYR, and 142PHE in BLIP, with water molecules within 10 Å from each residue respectively at 150, 200, 250, and 310 K. A comparison of the results shows that RPWK performs better than WK, and is able to detect some frequency data points that WK fails to detect. This points to the importance of using methods capable of taking the complex nature of the protein-solvent energy landscape into consideration, and not to rely on standard linear methods. In general, RPWK can be a valuable addition to the analysis tools for protein molecular dynamics simulations. Proteins 2016; 84:1549-1557. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Detecting transitions in protein dynamics using a recurrence quantification analysis based bootstrap method.

PubMed

Karain, Wael I

2017-11-28

Proteins undergo conformational transitions over different time scales. These transitions are closely intertwined with the protein's function. Numerous standard techniques such as principal component analysis are used to detect these transitions in molecular dynamics simulations. In this work, we add a new method that has the ability to detect transitions in dynamics based on the recurrences in the dynamical system. It combines bootstrapping and recurrence quantification analysis. We start from the assumption that a protein has a "baseline" recurrence structure over a given period of time. Any statistically significant deviation from this recurrence structure, as inferred from complexity measures provided by recurrence quantification analysis, is considered a transition in the dynamics of the protein. We apply this technique to a 132 ns long molecular dynamics simulation of the β-Lactamase Inhibitory Protein BLIP. We are able to detect conformational transitions in the nanosecond range in the recurrence dynamics of the BLIP protein during the simulation. The results compare favorably to those extracted using the principal component analysis technique. The recurrence quantification analysis based bootstrap technique is able to detect transitions between different dynamics states for a protein over different time scales. It is not limited to linear dynamics regimes, and can be generalized to any time scale. It also has the potential to be used to cluster frames in molecular dynamics trajectories according to the nature of their recurrence dynamics. One shortcoming for this method is the need to have large enough time windows to insure good statistical quality for the recurrence complexity measures needed to detect the transitions.

A method for rapid production of heteromultimeric protein complexes in plants: assembly of protective bluetongue virus-like particles.

PubMed

Thuenemann, Eva C; Meyers, Ann E; Verwey, Jeanette; Rybicki, Edward P; Lomonossoff, George P

2013-09-01

Plant expression systems based on nonreplicating virus-based vectors can be used for the simultaneous expression of multiple genes within the same cell. They therefore have great potential for the production of heteromultimeric protein complexes. This work describes the efficient plant-based production and assembly of Bluetongue virus-like particles (VLPs), requiring the simultaneous expression of four distinct proteins in varying amounts. Such particles have the potential to serve as a safe and effective vaccine against Bluetongue virus (BTV), which causes high mortality rates in ruminants and thus has a severe effect on the livestock trade. Here, VLPs produced and assembled in Nicotiana benthamiana using the cowpea mosaic virus-based HyperTrans (CPMV-HT) and associated pEAQ plant transient expression vector system were shown to elicit a strong antibody response in sheep. Furthermore, they provided protective immunity against a challenge with a South African BTV-8 field isolate. The results show that transient expression can be used to produce immunologically relevant complex heteromultimeric structures in plants in a matter of days. The results have implications beyond the realm of veterinary vaccines and could be applied to the production of VLPs for human use or the coexpression of multiple enzymes for the manipulation of metabolic pathways. © 2013 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

CSBB-ConeExclusion, adapting structure based solution virtual screening to libraries on solid support.

PubMed

Shave, Steven; Auer, Manfred

2013-12-23

Combinatorial chemical libraries produced on solid support offer fast and cost-effective access to a large number of unique compounds. If such libraries are screened directly on-bead, the speed at which chemical space can be explored by chemists is much greater than that addressable using solution based synthesis and screening methods. Solution based screening has a large supporting body of software such as structure-based virtual screening tools which enable the prediction of protein-ligand complexes. Use of these techniques to predict the protein bound complexes of compounds synthesized on solid support neglects to take into account the conjugation site on the small molecule ligand. This may invalidate predicted binding modes, the linker may be clashing with protein atoms. We present CSBB-ConeExclusion, a methodology and computer program which provides a measure of the applicability of solution dockings to solid support. Output is given in the form of statistics for each docking pose, a unique 2D visualization method which can be used to determine applicability at a glance, and automatically generated PyMol scripts allowing visualization of protein atom incursion into a defined exclusion volume. CSBB-ConeExclusion is then exemplarically used to determine the optimum attachment point for a purine library targeting cyclin-dependent kinase 2 CDK2.

Structure of human Fe-S assembly subcomplex reveals unexpected cysteine desulfurase architecture and acyl-ACP-ISD11 interactions.

PubMed

Cory, Seth A; Van Vranken, Jonathan G; Brignole, Edward J; Patra, Shachin; Winge, Dennis R; Drennan, Catherine L; Rutter, Jared; Barondeau, David P

2017-07-03

In eukaryotes, sulfur is mobilized for incorporation into multiple biosynthetic pathways by a cysteine desulfurase complex that consists of a catalytic subunit (NFS1), LYR protein (ISD11), and acyl carrier protein (ACP). This NFS1-ISD11-ACP (SDA) complex forms the core of the iron-sulfur (Fe-S) assembly complex and associates with assembly proteins ISCU2, frataxin (FXN), and ferredoxin to synthesize Fe-S clusters. Here we present crystallographic and electron microscopic structures of the SDA complex coupled to enzyme kinetic and cell-based studies to provide structure-function properties of a mitochondrial cysteine desulfurase. Unlike prokaryotic cysteine desulfurases, the SDA structure adopts an unexpected architecture in which a pair of ISD11 subunits form the dimeric core of the SDA complex, which clarifies the critical role of ISD11 in eukaryotic assemblies. The different quaternary structure results in an incompletely formed substrate channel and solvent-exposed pyridoxal 5'-phosphate cofactor and provides a rationale for the allosteric activator function of FXN in eukaryotic systems. The structure also reveals the 4'-phosphopantetheine-conjugated acyl-group of ACP occupies the hydrophobic core of ISD11, explaining the basis of ACP stabilization. The unexpected architecture for the SDA complex provides a framework for understanding interactions with acceptor proteins for sulfur-containing biosynthetic pathways, elucidating mechanistic details of eukaryotic Fe-S cluster biosynthesis, and clarifying how defects in Fe-S cluster assembly lead to diseases such as Friedreich's ataxia. Moreover, our results support a lock-and-key model in which LYR proteins associate with acyl-ACP as a mechanism for fatty acid biosynthesis to coordinate the expression, Fe-S cofactor maturation, and activity of the respiratory complexes.

X-ray and cryo-EM structures of inhibitor-bound cytochrome bc 1 complexes for structure-based drug discovery

PubMed Central

Amporndanai, Kangsa; O’Neill, Paul M.

2018-01-01

Cytochrome bc 1, a dimeric multi-subunit electron-transport protein embedded in the inner mitochondrial membrane, is a major drug target for the treatment and prevention of malaria and toxoplasmosis. Structural studies of cytochrome bc 1 from mammalian homologues co-crystallized with lead compounds have underpinned structure-based drug design to develop compounds with higher potency and selectivity. However, owing to the limited amount of cytochrome bc 1 that may be available from parasites, all efforts have been focused on homologous cytochrome bc 1 complexes from mammalian species, which has resulted in the failure of some drug candidates owing to toxicity in the host. Crystallographic studies of the native parasite proteins are not feasible owing to limited availability of the proteins. Here, it is demonstrated that cytochrome bc 1 is highly amenable to single-particle cryo-EM (which uses significantly less protein) by solving the apo and two inhibitor-bound structures to ∼4.1 Å resolution, revealing clear inhibitor density at the binding site. Therefore, cryo-EM is proposed as a viable alternative method for structure-based drug discovery using both host and parasite enzymes. PMID:29765610

Structure-based multiscale approach for identification of interaction partners of PDZ domains.

PubMed

Tiwari, Garima; Mohanty, Debasisa

2014-04-28

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.