Synergistic Inhibition of Protein Fibrillation by Proline and Sorbitol: Biophysical Investigations.

PubMed

Choudhary, Sinjan; Save, Shreyada N; Kishore, Nand; Hosur, Ramakrishna V

2016-01-01

We report here interesting synergistic effects of proline and sorbitol, two well-known chemical chaperones, in the inhibition of fibrillation of two proteins, insulin and lysozyme. A combination of many biophysical techniques has been used to understand the structural morphology and modes of interaction of the chaperones with the proteins during fibrillation. Both the chaperones establish stronger polar interactions in the elongation and saturation stages of fibrillation compared to that in the native stage. However, when presented as a mixture, we also see contribution of hydrophobic interactions. Thus, a co-operative adjustment of polar and hydrophobic interactions between the chaperones and the protein surface seems to drive the synergistic effects in the fibrillation process. In insulin, this synergy is quantitatively similar in all the stages of the fibrillation process. These observations would have significant implications for understanding protein folding concepts, in general, and for designing combination therapies against protein fibrillation, in particular.

Synergism and Antagonism between Bacillus thuringiensis Vip3A and Cry1 Proteins in Heliothis virescens, Diatraea saccharalis and Spodoptera frugiperda

PubMed Central

Lemes, Ana Rita Nunes; Davolos, Camila Chiaradia; Legori, Paula Cristina Brunini Crialesi; Fernandes, Odair Aparecido; Ferré, Juan; Lemos, Manoel Victor Franco; Desiderio, Janete Apparecida

2014-01-01

Second generation Bt crops (insect resistant crops carrying Bacillus thuringiensis genes) combine more than one gene that codes for insecticidal proteins in the same plant to provide better control of agricultural pests. Some of the new combinations involve co-expression of cry and vip genes. Because Cry and Vip proteins have different midgut targets and possibly different mechanisms of toxicity, it is important to evaluate possible synergistic or antagonistic interactions between these two classes of toxins. Three members of the Cry1 class of proteins and three from the Vip3A class were tested against Heliothis virescens for possible interactions. At the level of LC50, Cry1Ac was the most active protein, whereas the rest of proteins tested were similarly active. However, at the level of LC90, Cry1Aa and Cry1Ca were the least active proteins, and Cry1Ac and Vip3A proteins were not significantly different. Under the experimental conditions used in this study, we found an antagonistic effect of Cry1Ca with the three Vip3A proteins. The interaction between Cry1Ca and Vip3Aa was also tested on two other species of Lepidoptera. Whereas antagonism was observed in Spodoptera frugiperda, synergism was found in Diatraea saccharalis. In all cases, the interaction between Vip3A and Cry1 proteins was more evident at the LC90 level than at the LC50 level. The fact that the same combination of proteins may result in a synergistic or an antagonistic interaction may be an indication that there are different types of interactions within the host, depending on the insect species tested. PMID:25275646

Chemical cross-linking and native mass spectrometry: A fruitful combination for structural biology

PubMed Central

Sinz, Andrea; Arlt, Christian; Chorev, Dror; Sharon, Michal

2015-01-01

Mass spectrometry (MS) is becoming increasingly popular in the field of structural biology for analyzing protein three-dimensional-structures and for mapping protein–protein interactions. In this review, the specific contributions of chemical crosslinking and native MS are outlined to reveal the structural features of proteins and protein assemblies. Both strategies are illustrated based on the examples of the tetrameric tumor suppressor protein p53 and multisubunit vinculin-Arp2/3 hybrid complexes. We describe the distinct advantages and limitations of each technique and highlight synergistic effects when both techniques are combined. Integrating both methods is especially useful for characterizing large protein assemblies and for capturing transient interactions. We also point out the future directions we foresee for a combination of in vivo crosslinking and native MS for structural investigation of intact protein assemblies. PMID:25970732

Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

PubMed Central

Brorsson, C.; Hansen, N. T.; Lage, K.; Bergholdt, R.; Brunak, S.; Pociot, F.

2009-01-01

Aim To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1 genes. Methods We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein–protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation. Results A total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in β-cell development and diabetic complications. Conclusions The extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D. PMID:19143816

Protein-protein interaction specificity is captured by contact preferences and interface composition.

PubMed

Nadalin, Francesca; Carbone, Alessandra

2018-02-01

Large-scale computational docking will be increasingly used in future years to discriminate protein-protein interactions at the residue resolution. Complete cross-docking experiments make in silico reconstruction of protein-protein interaction networks a feasible goal. They ask for efficient and accurate screening of the millions structural conformations issued by the calculations. We propose CIPS (Combined Interface Propensity for decoy Scoring), a new pair potential combining interface composition with residue-residue contact preference. CIPS outperforms several other methods on screening docking solutions obtained either with all-atom or with coarse-grain rigid docking. Further testing on 28 CAPRI targets corroborates CIPS predictive power over existing methods. By combining CIPS with atomic potentials, discrimination of correct conformations in all-atom structures reaches optimal accuracy. The drastic reduction of candidate solutions produced by thousands of proteins docked against each other makes large-scale docking accessible to analysis. CIPS source code is freely available at http://www.lcqb.upmc.fr/CIPS. alessandra.carbone@lip6.fr. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Two Crinivirus-specific proteins of Lettuce infectious yellows virus (LIYV), P26 and P9, are self-interacting.

PubMed

Stewart, Lucy R; Hwang, Min Sook; Falk, Bryce W

2009-11-01

Interactions of Lettuce infectious yellows virus (LIYV)-encoded proteins were tested by yeast-two-hybrid (Y2H) assays. LIYV-encoded P34, Hsp70h, P59, CP, CPm, and P26 were tested in all possible pairwise combinations. Interaction was detected only for the P26-P26 combination. P26 self-interaction domains were mapped using a series of N- and C-terminal truncations. Orthologous P26 proteins from the criniviruses Beet pseudoyellows virus (BPYV), Cucurbit yellow stunting disorder virus (CYSDV), and Lettuce chlorosis virus (LCV) were also tested, and each exhibited strong self-interaction but no interaction with orthologous proteins. Two small putative proteins encoded by LIYV RNA2, P5 and P9, were also tested for interactions with the six aforementioned LIYV proteins and each other. No interactions were detected for P5, but P9-P9 self-interaction was detected. P26- and P9-encoding genes are present in all described members of the genus Crinivirus, but are not present in other members of the family Closteroviridae. LIYV P26 has previously been demonstrated to induce a unique LIYV cytopathology, plasmalemma deposits (PLDs), but no role is yet known for P9.

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions.

PubMed

Wallqvist, Anders; Wang, Hao; Zavaljevski, Nela; Memišević, Vesna; Kwon, Keehwan; Pieper, Rembert; Rajagopala, Seesandra V; Reifman, Jaques

2017-01-01

Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which translocates more than 100 effector proteins into the host cytosol to establish the infection, restructure the intracellular host environment, and create a parasitophorous vacuole where the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors against whole genome human and murine proteome libraries to generate a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a single host-pathogen interaction network containing 415 unique interactions between 25 C. burnetii and 363 human proteins. We further performed complementary pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions involving five pathogen proteins. We used the combined data to 1) perform enrichment analyses of target host cellular processes and pathways, 2) examine effectors with known infection phenotypes, and 3) infer potential mechanisms of action for four effectors with uncharacterized functions. The host-pathogen interaction profiles supported known Coxiella phenotypes, such as adapting cell morphology through cytoskeletal re-arrangements, protein processing and trafficking, organelle generation, cholesterol processing, innate immune modulation, and interactions with the ubiquitin and proteasome pathways. The generated dataset of PPIs-the largest collection of unbiased Coxiella host-pathogen interactions to date-represents a rich source of information with respect to secreted pathogen effector proteins and their interactions with human host proteins.

Interaction of classical platinum agents with the monomeric and dimeric Atox1 proteins: a molecular dynamics simulation study.

PubMed

Wang, Xiaolei; Li, Chaoqun; Wang, Yan; Chen, Guangju

2013-12-20

We carried out molecular dynamics simulations and free energy calculations for a series of binary and ternary models of the cisplatin, transplatin and oxaliplatin agents binding to a monomeric Atox1 protein and a dimeric Atox1 protein to investigate their interaction mechanisms. All three platinum agents could respectively combine with the monomeric Atox1 protein and the dimeric Atox1 protein to form a stable binary and ternary complex due to the covalent interaction of the platinum center with the Atox1 protein. The results suggested that the extra interaction from the oxaliplatin ligand-Atox1 protein interface increases its affinity only for the OxaliPt + Atox1 model. The binding of the oxaliplatin agent to the Atox1 protein might cause larger deformation of the protein than those of the cisplatin and transplatin agents due to the larger size of the oxaliplatin ligand. However, the extra interactions to facilitate the stabilities of the ternary CisPt + 2Atox1 and OxaliPt + 2Atox1 models come from the α1 helices and α2-β4 loops of the Atox1 protein-Atox1 protein interface due to the cis conformation of the platinum agents. The combinations of two Atox1 proteins in an asymmetric way in the three ternary models were analyzed. These investigations might provide detailed information for understanding the interaction mechanism of the platinum agents binding to the Atox1 protein in the cytoplasm.

Bioinspired Assemblies of Plant Cell Walls for Measuring Protein-Carbohydrate Interactions by FRAP.

PubMed

Paës, Gabriel

2017-01-01

The interactions of proteins involved in plant cell wall hydrolysis, such as enzymes and CBMs, significantly determine their role and efficiency. In order to go beyond the characterization of interactions with simple ligands, bioinspired assemblies combined with the measurement of diffusion and interaction by FRAP offer a relevant alternative for highlighting the importance of different parameters related to the protein affinity and to the assembly.

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

PubMed

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

2009-12-31

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

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

PubMed

Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics.

PubMed

Sun, Kaiwen; Zheng, Yuyu; Zhu, Ziqiang

2017-11-20

Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel protein-protein interaction pairs and monitoring protein interaction dynamics are of particular interest for revealing how plants respond to environmental factors and/or developmental signals. A plethora of approaches have been developed to examine protein-protein interactions, either in vitro or in vivo. Among them, the recently established luciferase complementation imaging (LCI) assay is the simplest and fastest method for demonstrating in vivo protein-protein interactions. In this assay, protein A or protein B is fused with the amino-terminal or carboxyl-terminal half of luciferase, respectively. When protein A interacts with protein B, the two halves of luciferase will be reconstituted to form a functional and active luciferase enzyme. Luciferase activity can be recorded with a luminometer or CCD-camera. Compared with other approaches, the LCI assay shows protein-protein interactions both qualitatively and quantitatively. Agrobacterium infiltration in Nicotiana benthamiana leaves is a widely used system for transient protein expression. With the combination of LCI and transient expression, these approaches show that the physical interaction between COP1 and SPA1 was gradually reduced after jasmonate treatment.

Overview of the main methods used to combine proteins with nanosystems: absorption, bioconjugation, and encapsulation

PubMed Central

Di Marco, Mariagrazia; Shamsuddin, Shaharum; Razak, Khairunisak Abdul; Aziz, Azlan Abdul; Devaux, Corinne; Borghi, Elsa; Levy, Laurent; Sadun, Claudia

2010-01-01

The latest development of protein engineering allows the production of proteins having desired properties and large potential markets, but the clinical advances of therapeutical proteins are still limited by their fragility. Nanotechnology could provide optimal vectors able to protect from degradation therapeutical biomolecules such as proteins, enzymes or specific polypeptides. On the other hand, some proteins can be also used as active ligands to help nanoparticles loaded with chemotherapeutic or other drugs to reach particular sites in the body. The aim of this review is to provide an overall picture of the general aspects of the most successful approaches used to combine proteins with nanosystems. This combination is mainly achieved by absorption, bioconjugation and encapsulation. Interactions of nanoparticles with biomolecules and caveats related to protein denaturation are also pointed out. A clear understanding of nanoparticle-protein interactions could make possible the design of precise and versatile hybrid nanosystems. This could further allow control of their pharmacokinetics as well as activity, and safety. PMID:20161986

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

NASA Astrophysics Data System (ADS)

Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Large-Scale Interaction Profiling of Protein Domains Through Proteomic Peptide-Phage Display Using Custom Peptidomes.

PubMed

Seo, Moon-Hyeong; Nim, Satra; Jeon, Jouhyun; Kim, Philip M

2017-01-01

Protein-protein interactions are essential to cellular functions and signaling pathways. We recently combined bioinformatics and custom oligonucleotide arrays to construct custom-made peptide-phage libraries for screening peptide-protein interactions, an approach we call proteomic peptide-phage display (ProP-PD). In this chapter, we describe protocols for phage display for the identification of natural peptide binders for a given protein. We finally describe deep sequencing for the analysis of the proteomic peptide-phage display.

Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.

PubMed

Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan

2015-06-01

Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Towards Inferring Protein Interactions: Challenges and Solutions

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

The Monitoring and Affinity Purification of Proteins Using Dual Tags with Tetracysteine Motifs

NASA Astrophysics Data System (ADS)

Giannone, Richard J.; Liu, Yie; Wang, Yisong

Identification and characterization of protein-protein interaction networks is essential for the elucidation of biochemical mechanisms and cellular function. Affinity purification in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as a very powerful tactic for the identification of specific protein-protein interactions. In this chapter, we describe a comprehensive methodology that uses our recently developed dual-tag affinity purification system for the enrichment and identification of mammalian protein complexes. The protocol covers a series of separate but sequentially related techniques focused on the facile monitoring and purification of a dual-tagged protein of interest and its interacting partners via a system built with tetracysteine motifs and various combinations of affinity tags. Using human telomeric repeat binding factor 2 (TRF2) as an example, we demonstrate the power of the system in terms of bait protein recovery after dual-tag affinity purification, detection of bait protein subcellular localization and expression, and successful identification of known and potentially novel TRF2 interacting proteins. Although the protocol described here has been optimized for the identification and characterization of TRF2-associated proteins, it is, in principle, applicable to the study of any other mammalian protein complexes that may be of interest to the research community.

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

PubMed Central

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

2014-01-01

The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

Time-resolved analysis of DNA-protein interactions in living cells by UV laser pulses.

PubMed

Nebbioso, Angela; Benedetti, Rosaria; Conte, Mariarosaria; Carafa, Vincenzo; De Bellis, Floriana; Shaik, Jani; Matarese, Filomena; Della Ventura, Bartolomeo; Gesuele, Felice; Velotta, Raffaele; Martens, Joost H A; Stunnenberg, Hendrik G; Altucci, Carlo; Altucci, Lucia

2017-09-15

Interactions between DNA and proteins are mainly studied through chemical procedures involving bi-functional reagents, mostly formaldehyde. Chromatin immunoprecipitation is used to identify the binding between transcription factors (TFs) and chromatin, and to evaluate the occurrence and impact of histone/DNA modifications. The current bottleneck in probing DNA-protein interactions using these approaches is caused by the fact that chemical crosslinkers do not discriminate direct and indirect bindings or short-lived chromatin occupancy. Here, we describe a novel application of UV laser-induced (L-) crosslinking and demonstrate that a combination of chemical and L-crosslinking is able to distinguish between direct and indirect DNA-protein interactions in a small number of living cells. The spatial and temporal dynamics of TF bindings to chromatin and their role in gene expression regulation may thus be assessed. The combination of chemical and L-crosslinking offers an exciting and unprecedented tool for biomedical applications.

ASSESSING AND COMBINING RELIABILITY OF PROTEIN INTERACTION SOURCES

PubMed Central

LEACH, SONIA; GABOW, AARON; HUNTER, LAWRENCE; GOLDBERG, DEBRA S.

2008-01-01

Integrating diverse sources of interaction information to create protein networks requires strategies sensitive to differences in accuracy and coverage of each source. Previous integration approaches calculate reliabilities of protein interaction information sources based on congruity to a designated ‘gold standard.’ In this paper, we provide a comparison of the two most popular existing approaches and propose a novel alternative for assessing reliabilities which does not require a gold standard. We identify a new method for combining the resultant reliabilities and compare it against an existing method. Further, we propose an extrinsic approach to evaluation of reliability estimates, considering their influence on the downstream tasks of inferring protein function and learning regulatory networks from expression data. Results using this evaluation method show 1) our method for reliability estimation is an attractive alternative to those requiring a gold standard and 2) the new method for combining reliabilities is less sensitive to noise in reliability assignments than the similar existing technique. PMID:17990508

Protein electrostatics: a review of the equations and methods used to model electrostatic equations in biomolecules--applications in biotechnology.

PubMed

Neves-Petersen, Maria Teresa; Petersen, Steffen B

2003-01-01

The molecular understanding of the initial interaction between a protein and, e.g., its substrate, a surface or an inhibitor is essentially an understanding of the role of electrostatics in intermolecular interactions. When studying biomolecules it is becoming increasingly evident that electrostatic interactions play a role in folding, conformational stability, enzyme activity and binding energies as well as in protein-protein interactions. In this chapter we present the key basic equations of electrostatics necessary to derive the equations used to model electrostatic interactions in biomolecules. We will also address how to solve such equations. This chapter is divided into two major sections. In the first part we will review the basic Maxwell equations of electrostatics equations called the Laws of Electrostatics that combined will result in the Poisson equation. This equation is the starting point of the Poisson-Boltzmann (PB) equation used to model electrostatic interactions in biomolecules. Concepts as electric field lines, equipotential surfaces, electrostatic energy and when can electrostatics be applied to study interactions between charges will be addressed. In the second part we will arrive at the electrostatic equations for dielectric media such as a protein. We will address the theory of dielectrics and arrive at the Poisson equation for dielectric media and at the PB equation, the main equation used to model electrostatic interactions in biomolecules (e.g., proteins, DNA). It will be shown how to compute forces and potentials in a dielectric medium. In order to solve the PB equation we will present the continuum electrostatic models, namely the Tanford-Kirkwood and the modified Tandord-Kirkwood methods. Priority will be given to finding the protonation state of proteins prior to solving the PB equation. We also present some methods that can be used to map and study the electrostatic potential distribution on the molecular surface of proteins. The combination of graphical visualisation of the electrostatic fields combined with knowledge about the location of key residues on the protein surface allows us to envision atomic models for enzyme function. Finally, we exemplify the use of some of these methods on the enzymes of the lipase family.

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.

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

PubMed

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

2017-10-03

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

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

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

Role for protein–protein interaction databases in human genetics

PubMed Central

Pattin, Kristine A; Moore, Jason H

2010-01-01

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

Determination of cell metabolite VEGF₁₆₅ and dynamic analysis of protein-DNA interactions by combination of microfluidic technique and luminescent switch-on probe.

PubMed

Lin, Xuexia; Leung, Ka-Ho; Lin, Ling; Lin, Luyao; Lin, Sheng; Leung, Chung-Hang; Ma, Dik-Lung; Lin, Jin-Ming

2016-05-15

In this paper, we rationally design a novel G-quadruplex-selective luminescent iridium (III) complex for rapid detection of oligonucleotide and VEGF165 in microfluidics. This new probe is applied as a convenient biosensor for label-free quantitative analysis of VEGF165 protein from cell metabolism, as well as for studying the kinetics of the aptamer-protein interaction combination with a microfluidic platform. As a result, we have successfully established a quantitative analysis of VEGF165 from cell metabolism. Furthermore, based on the principles of hydrodynamic focusing and diffusive mixing, different transient states during kinetics process were monitored and recorded. Thus, the combination of microfluidic technique and G-quadruplex luminescent probe will be potentially applied in the studies of intramolecular interactions and molecule recognition in the future. Copyright © 2015 Elsevier B.V. All rights reserved.

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

The advancement of chemical cross-linking and mass spectrometry for structural proteomics: from single proteins to protein interaction networks.

PubMed

Sinz, Andrea

2014-12-01

During the last 15 years, chemical cross-linking combined with mass spectrometry (MS) and computational modeling has advanced from investigating 3D-structures of isolated proteins to deciphering protein interaction networks. In this article, the author discusses the advent, the development and the current status of the chemical cross-linking/MS strategy in the context of recent technological developments. A direct way to probe in vivo protein-protein interactions is by site-specific incorporation of genetically encoded photo-reactive amino acids or by non-directed incorporation of photo-reactive amino acids. As the chemical cross-linking/MS approach allows the capture of transient and weak interactions, it has the potential to become a routine technique for unraveling protein interaction networks in their natural cellular environment.

Context-specific target definition in influenza a virus hemagglutinin-glycan receptor interactions.

PubMed

Shriver, Zachary; Raman, Rahul; Viswanathan, Karthik; Sasisekharan, Ram

2009-08-28

Protein-glycan interactions are important regulators of a variety of biological processes, ranging from immune recognition to anticoagulation. An important area of active research is directed toward understanding the role of host cell surface glycans as recognition sites for pathogen protein receptors. Recognition of cell surface glycans is a widely employed strategy for a variety of pathogens, including bacteria, parasites, and viruses. We present here a representative example of such an interaction: the binding of influenza A hemagglutinin (HA) to specific sialylated glycans on the cell surface of human upper airway epithelial cells, which initiates the infection cycle. We detail a generalizable strategy to understand the nature of protein-glycan interactions both structurally and biochemically, using HA as a model system. This strategy combines a top-down approach using available structural information to define important contacts between glycans and HA, with a bottom-up approach using data-mining and informatics approaches to identify the common motifs that distinguish glycan binders from nonbinders. By probing protein-glycan interactions simultaneously through top-down and bottom-up approaches, we can scientifically validate a series of observations. This in turn provides additional confidence and surmounts known challenges in the study of protein-glycan interactions, such as accounting for multivalency, and thus truly defines concepts such as specificity, affinity, and avidity. With the advent of new technologies for glycomics-including glycan arrays, data-mining solutions, and robust algorithms to model protein-glycan interactions-we anticipate that such combination approaches will become tractable for a wide variety of protein-glycan interactions.

The protein interaction map of bacteriophage lambda

PubMed Central

2011-01-01

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

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

PubMed

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

2010-04-20

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

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions.

PubMed

Wuchty, S; Rajagopala, S V; Blazie, S M; Parrish, J R; Khuri, S; Finley, R L; Uetz, P

2017-01-01

The functions of roughly a third of all proteins in Streptococcus pneumoniae , a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein's function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae . We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae , the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

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

PubMed

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

2008-01-01

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

Profiling cellular protein complexes by proximity ligation with dual tag microarray readout.

PubMed

Hammond, Maria; Nong, Rachel Yuan; Ericsson, Olle; Pardali, Katerina; Landegren, Ulf

2012-01-01

Patterns of protein interactions provide important insights in basic biology, and their analysis plays an increasing role in drug development and diagnostics of disease. We have established a scalable technique to compare two biological samples for the levels of all pairwise interactions among a set of targeted protein molecules. The technique is a combination of the proximity ligation assay with readout via dual tag microarrays. In the proximity ligation assay protein identities are encoded as DNA sequences by attaching DNA oligonucleotides to antibodies directed against the proteins of interest. Upon binding by pairs of antibodies to proteins present in the same molecular complexes, ligation reactions give rise to reporter DNA molecules that contain the combined sequence information from the two DNA strands. The ligation reactions also serve to incorporate a sample barcode in the reporter molecules to allow for direct comparison between pairs of samples. The samples are evaluated using a dual tag microarray where information is decoded, revealing which pairs of tags that have become joined. As a proof-of-concept we demonstrate that this approach can be used to detect a set of five proteins and their pairwise interactions both in cellular lysates and in fixed tissue culture cells. This paper provides a general strategy to analyze the extent of any pairwise interactions in large sets of molecules by decoding reporter DNA strands that identify the interacting molecules.

Coarse-Grained Model for Colloidal Protein Interactions, B22, and Protein Cluster Formation

PubMed Central

Blanco, Marco A.; Sahin, Eric; Robinson, Anne S.; Roberts, Christopher J.

2014-01-01

Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semi-quantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as the osmotic second virial coefficient (B22). Based on earlier work, this CG model treats proteins as rigid bodies composed of one bead per amino acid, with each amino acid having specific parameters for its size, hydrophobicity, and charge. The net interactions are a combination of steric repulsions, short-range attractions, and screened long-range charge-charge interactions. Model parametrization was done by fitting simulation results against experimental values of the B22 as a function of solution ionic strength for α-chymotrypsinogen A and γD-crystallin (gD-Crys). The CG model is applied to characterize the pairwise interactions and dimerization of gD-Crys and the dependance on temperature, protein concentration, and ionic strength. The results illustrate that at experimentally relevant conditions where stable dimers do not form, the entropic contributions are predominant in the free-energy of protein cluster formation and colloidal protein interactions, arguing against interpretations that treat B22 primarily from energetic considerations alone. Additionally, the results suggest that electrostatic interactions help to modulate the population of the different stable configurations for protein nearest-neighbor pairs, while short-range attractions determine the relative orientations of proteins within these configurations. Finally, simulation results are combined with Principal Component Analysis to identify those amino-acids / surface patches that form inter-protein contacts at conditions that favor dimerization of gD-Crys. The resulting regions agree with previously found aggregation-prone sites, as well as suggesting new ones that may be important. PMID:24289039

Fuzzy Clustering-Based Modeling of Surface Interactions and Emulsions of Selected Whey Protein Concentrate Combined to i-Carrageenan and Gum Arabic Solutions

USDA-ARS?s Scientific Manuscript database

Gums and proteins are valuable ingredients with a wide spectrum of applications. Surface properties (surface tension, interfacial tension, emulsion activity index “EAI” and emulsion stability index “ESI”) of 4% whey protein concentrate (WPC) in a combination with '- carrageenan (0.05%, 0.1%, and 0.5...

Complete genome sequence and integrated protein localization and interaction map for alfalfa dwarf virus, which combines properties of both cytoplasmic and nuclear plant rhabdoviruses

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

Bejerman, Nicolás, E-mail: n.bejerman@uq.edu.au; Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD 4072; Giolitti, Fabián

Summary: We have determined the full-length 14,491-nucleotide genome sequence of a new plant rhabdovirus, alfalfa dwarf virus (ADV). Seven open reading frames (ORFs) were identified in the antigenomic orientation of the negative-sense, single-stranded viral RNA, in the order 3′-N-P-P3-M-G-P6-L-5′. The ORFs are separated by conserved intergenic regions and the genome coding region is flanked by complementary 3′ leader and 5′ trailer sequences. Phylogenetic analysis of the nucleoprotein amino acid sequence indicated that this alfalfa-infecting rhabdovirus is related to viruses in the genus Cytorhabdovirus. When transiently expressed as GFP fusions in Nicotiana benthamiana leaves, most ADV proteins accumulated in the cellmore » periphery, but unexpectedly P protein was localized exclusively in the nucleus. ADV P protein was shown to have a homotypic, and heterotypic nuclear interactions with N, P3 and M proteins by bimolecular fluorescence complementation. ADV appears unique in that it combines properties of both cytoplasmic and nuclear plant rhabdoviruses. - Highlights: • The complete genome of alfalfa dwarf virus is obtained. • An integrated localization and interaction map for ADV is determined. • ADV has a genome sequence similarity and evolutionary links with cytorhabdoviruses. • ADV protein localization and interaction data show an association with the nucleus. • ADV combines properties of both cytoplasmic and nuclear plant rhabdoviruses.« less

Combining affinity enrichment, cross-linking with photo-amino acids, and mass spectrometry for probing protein kinase D2 interactions.

PubMed

Häupl, Björn; Ihling, Christian H; Sinz, Andrea

2017-04-07

We present a novel approach that relies on the affinity capture of protein interaction partners from a complex mixture, followed by covalent fixation via UV-induced activation of incorporated diazirine photo-reactive amino acids (photo-methionine and photo-leucine). The captured protein complexes are enzymatically digested and interacting proteins are identified and quantified by label-free LC/MS analysis. Using HeLa cell lysates with photo-methionine and photo-leucine-labeled proteins, we were able to capture and preserve protein interactions that are otherwise elusive in conventional pull-down experiments. Our approach is exemplified for mapping the protein interaction network of protein kinase D2, but has the potential be applied to any protein system. Data are available via ProteomeXchange with identifiers PXD005346 (photo-amino acid incorporation) and PXD005349 (enrichment experiments). This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Effective Identification of Akt Interacting Proteins by Two-Step Chemical Crosslinking, Co-Immunoprecipitation and Mass Spectrometry

PubMed Central

Huang, Bill X.; Kim, Hee-Yong

2013-01-01

Akt is a critical protein for cell survival and known to interact with various proteins. However, Akt binding partners that modulate or regulate Akt activation have not been fully elucidated. Identification of Akt-interacting proteins has been customarily achieved by co-immunoprecipitation combined with western blot and/or MS analysis. An intrinsic problem of the method is loss of interacting proteins during procedures to remove non-specific proteins. Moreover, antibody contamination often interferes with the detection of less abundant proteins. Here, we developed a novel two-step chemical crosslinking strategy to overcome these problems which resulted in a dramatic improvement in identifying Akt interacting partners. Akt antibody was first immobilized on protein A/G beads using disuccinimidyl suberate and allowed to bind to cellular Akt along with its interacting proteins. Subsequently, dithiobis[succinimidylpropionate], a cleavable crosslinker, was introduced to produce stable complexes between Akt and binding partners prior to the SDS-PAGE and nanoLC-MS/MS analysis. This approach enabled identification of ten Akt partners from cell lysates containing as low as 1.5 mg proteins, including two new potential Akt interacting partners. None of these but one protein was detectable without crosslinking procedures. The present method provides a sensitive and effective tool to probe Akt-interacting proteins. This strategy should also prove useful for other protein interactions, particularly those involving less abundant or weakly associating partners. PMID:23613850

Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases*

PubMed Central

Tinti, Michele; Paoluzi, Serena; Santonico, Elena; Masch, Antonia; Schutkowski, Mike

2017-01-01

Reversible tyrosine phosphorylation is a widespread post-translational modification mechanism underlying cell physiology. Thus, understanding the mechanisms responsible for substrate selection by kinases and phosphatases is central to our ability to model signal transduction at a system level. Classical protein-tyrosine phosphatases can exhibit substrate specificity in vivo by combining intrinsic enzymatic specificity with the network of protein-protein interactions, which positions the enzymes in close proximity to their substrates. Here we use a high throughput approach, based on high density phosphopeptide chips, to determine the in vitro substrate preference of 16 members of the protein-tyrosine phosphatase family. This approach helped identify one residue in the substrate binding pocket of the phosphatase domain that confers specificity for phosphopeptides in a specific sequence context. We also present a Bayesian model that combines intrinsic enzymatic specificity and interaction information in the context of the human protein interaction network to infer new phosphatase substrates at the proteome level. PMID:28159843

Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation.

PubMed

Blanco, Marco A; Sahin, Erinc; Robinson, Anne S; Roberts, Christopher J

2013-12-19

Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semiquantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as the osmotic second virial coefficient (B22). Based on earlier work (Grüenberger et al., J. Phys. Chem. B 2013, 117, 763), this CG model treats proteins as rigid bodies composed of one bead per amino acid, with each amino acid having specific parameters for its size, hydrophobicity, and charge. The net interactions are a combination of steric repulsions, short-range attractions, and screened long-range charge-charge interactions. Model parametrization was done by fitting simulation results against experimental value of B22 as a function of solution ionic strength for α-chymotrypsinogen A and γD-Crystallin (gD-Crys). The CG model is applied to characterize the pairwise interactions and dimerization of gD-Crys and the dependence on temperature, protein concentration, and ionic strength. The results illustrate that at experimentally relevant conditions where stable dimers do not form, the entropic contributions are predominant in the free-energy of protein cluster formation and colloidal protein interactions, arguing against interpretations that treat B22 primarily from energetic considerations alone. Additionally, the results suggest that electrostatic interactions help to modulate the population of the different stable configurations for protein nearest-neighbor pairs, while short-range attractions determine the relative orientations of proteins within these configurations. Finally, simulation results are combined with Principal Component Analysis to identify those amino-acids/surface patches that form interprotein contacts at conditions that favor dimerization of gD-Crys. The resulting regions agree with previously found aggregation-prone sites, as well as suggesting new ones that may be important.

RNA-binding Protein Immunoprecipitation (RIP) to Examine AUF1 Binding to Senescence-Associated Secretory Phenotype (SASP) Factor mRNA

PubMed Central

Alspach, Elise; Stewart, Sheila A.

2016-01-01

Immunoprecipitation and subsequent isolation of nucleic acids allows for the investigation of protein:nucleic acid interactions. RNA-binding protein immunoprecipitation (RIP) is used for the analysis of protein interactions with mRNA. Combining RIP with quantitative real-time PCR (qRT-PCR) further enhances the RIP technique by allowing for the quantitative assessment of RNA-binding protein interactions with their target mRNAs, and how these interactions change in different cellular settings. Here, we describe the immunoprecipitation of the RNA-binding protein AUF1 with several different factors associated with the senescence-associated secretory phenotype (SASP) (Alspach and Stewart, 2013), specifically IL6 and IL8. This protocol was originally published in Alspach et al. (2014). PMID:27453911

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

PubMed

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

2003-07-30

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

Rapid discovery of protein interactions by cell-free protein technologies.

PubMed

He, M; Taussig, M J

2007-11-01

Cell-free transcription and translation provides an open, controllable environment for production of correctly folded, soluble proteins and allows the rapid generation of proteins from DNA without the need for cloning. Thus it is becoming an increasingly attractive alternative to conventional in vivo expression systems, especially when parallel expression of multiple proteins is required. Through novel design and exploitation, powerful cell-free technologies of ribosome display and protein in situ arrays have been developed for in vitro production and isolation of protein-binding molecules from large libraries. These technologies can be combined for rapid detection of protein interactions.

In silico prediction of protein-protein interactions in human macrophages

PubMed Central

2014-01-01

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

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.

The identification of protein domains that mediate functional interactions between Rab-GTPases and RabGAPs using 3D protein modeling.

PubMed

Davie, Jeremiah J; Faitar, Silviu L

2017-01-01

Currently, time-consuming serial in vitro experimentation involving immunocytochemistry or radiolabeled materials is required to identify which of the numerous Rab-GTPases (Rab) and Rab-GTPase activating proteins (RabGAP) are capable of functional interactions. These interactions are essential for numerous cellular functions, and in silico methods of reducing in vitro trial and error would accelerate the pace of research in cell biology. We have utilized a combination of three-dimensional protein modeling and protein bioinformatics to identify domains present in Rab proteins that are predictive of their functional interaction with a specific RabGAP. The RabF2 and RabSF1 domains appear to play functional roles in mediating the interaction between Rabs and RabGAPs. Moreover, the RabSF1 domain can be used to make in silico predictions of functional Rab/RabGAP pairs. This method is expected to be a broadly applicable tool for predicting protein-protein interactions where existing crystal structures for homologs of the proteins of interest are available.

Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

PubMed

Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

2011-11-01

A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

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

PubMed

Yu, Jingkai; Finley, Russell L

2009-01-01

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

Inhibition of Protein-Protein Interactions and Signaling by Small Molecules

NASA Astrophysics Data System (ADS)

Freire, Ernesto

2010-03-01

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

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

PubMed Central

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

2013-01-01

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

Development of bimolecular fluorescence complementation using rsEGFP2 for detection and super-resolution imaging of protein-protein interactions in live cells

PubMed Central

Wang, Sheng; Ding, Miao; Chen, Xuanze; Chang, Lei; Sun, Yujie

2017-01-01

Direct visualization of protein-protein interactions (PPIs) at high spatial and temporal resolution in live cells is crucial for understanding the intricate and dynamic behaviors of signaling protein complexes. Recently, bimolecular fluorescence complementation (BiFC) assays have been combined with super-resolution imaging techniques including PALM and SOFI to visualize PPIs at the nanometer spatial resolution. RESOLFT nanoscopy has been proven as a powerful live-cell super-resolution imaging technique. With regard to the detection and visualization of PPIs in live cells with high temporal and spatial resolution, here we developed a BiFC assay using split rsEGFP2, a highly photostable and reversibly photoswitchable fluorescent protein previously developed for RESOLFT nanoscopy. Combined with parallelized RESOLFT microscopy, we demonstrated the high spatiotemporal resolving capability of a rsEGFP2-based BiFC assay by detecting and visualizing specifically the heterodimerization interactions between Bcl-xL and Bak as well as the dynamics of the complex on mitochondria membrane in live cells. PMID:28663931

Making the Bend: DNA Tertiary Structure and Protein-DNA Interactions

PubMed Central

Harteis, Sabrina; Schneider, Sabine

2014-01-01

DNA structure functions as an overlapping code to the DNA sequence. Rapid progress in understanding the role of DNA structure in gene regulation, DNA damage recognition and genome stability has been made. The three dimensional structure of both proteins and DNA plays a crucial role for their specific interaction, and proteins can recognise the chemical signature of DNA sequence (“base readout”) as well as the intrinsic DNA structure (“shape recognition”). These recognition mechanisms do not exist in isolation but, depending on the individual interaction partners, are combined to various extents. Driving force for the interaction between protein and DNA remain the unique thermodynamics of each individual DNA-protein pair. In this review we focus on the structures and conformations adopted by DNA, both influenced by and influencing the specific interaction with the corresponding protein binding partner, as well as their underlying thermodynamics. PMID:25026169

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

PubMed

Imai, Takashi; Kovalenko, Andriy; Hirata, Fumio

2005-04-14

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

Analysis of Protein-DNA Interaction by Chromatin Immunoprecipitation and DNA Tiling Microarray (ChIP-on-chip).

PubMed

Gao, Hui; Zhao, Chunyan

2018-01-01

Chromatin immunoprecipitation (ChIP) has become the most effective and widely used tool to study the interactions between specific proteins or modified forms of proteins and a genomic DNA region. Combined with genome-wide profiling technologies, such as microarray hybridization (ChIP-on-chip) or massively parallel sequencing (ChIP-seq), ChIP could provide a genome-wide mapping of in vivo protein-DNA interactions in various organisms. Here, we describe a protocol of ChIP-on-chip that uses tiling microarray to obtain a genome-wide profiling of ChIPed DNA.

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

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

NOXclass: prediction of protein-protein interaction types.

PubMed

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

2006-01-19

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

d-Omix: a mixer of generic protein domain analysis tools.

PubMed

Wichadakul, Duangdao; Numnark, Somrak; Ingsriswang, Supawadee

2009-07-01

Domain combination provides important clues to the roles of protein domains in protein function, interaction and evolution. We have developed a web server d-Omix (a Mixer of Protein Domain Analysis Tools) aiming as a unified platform to analyze, compare and visualize protein data sets in various aspects of protein domain combinations. With InterProScan files for protein sets of interest provided by users, the server incorporates four services for domain analyses. First, it constructs protein phylogenetic tree based on a distance matrix calculated from protein domain architectures (DAs), allowing the comparison with a sequence-based tree. Second, it calculates and visualizes the versatility, abundance and co-presence of protein domains via a domain graph. Third, it compares the similarity of proteins based on DA alignment. Fourth, it builds a putative protein network derived from domain-domain interactions from DOMINE. Users may select a variety of input data files and flexibly choose domain search tools (e.g. hmmpfam, superfamily) for a specific analysis. Results from the d-Omix could be interactively explored and exported into various formats such as SVG, JPG, BMP and CSV. Users with only protein sequences could prepare an InterProScan file using a service provided by the server as well. The d-Omix web server is freely available at http://www.biotec.or.th/isl/Domix.

On the influence of the mixture of denaturants on protein structure stability: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Shao, Qiang; Wang, Jinan; Zhu, Weiliang

2014-09-01

Mixtures of osmolytes and/or inorganic salts are present in the cell. Therefore, the understanding of the interplay of mixed osmolyte molecules and inorganic salts and their combined effects on protein structure is of fundamental importance. A novel test is presented to investigate the combined effects of urea and a chaotropic inorganic salt, potassium iodide (KI), on protein structure by using molecular dynamics simulation. It is found that the coexistence of KI and urea does not affect their respective distribution in solution. The solvation of KI salt in urea solution makes the electrostatic interactions of urea more favorable, promoting the hydrogen bonding between urea (and water) to protein backbone. The interactions from K+ and hydrogen bonding from urea and water to protein backbone work as the driving force for protein denaturation. The collaborative behavior of urea and KI salt thus enhances the denaturing ability of urea and KI mixed solution.

Deriving Heterospecific Self-Assembling Protein-Protein Interactions Using a Computational Interactome Screen.

PubMed

Crooks, Richard O; Baxter, Daniel; Panek, Anna S; Lubben, Anneke T; Mason, Jody M

2016-01-29

Interactions between naturally occurring proteins are highly specific, with protein-network imbalances associated with numerous diseases. For designed protein-protein interactions (PPIs), required specificity can be notoriously difficult to engineer. To accelerate this process, we have derived peptides that form heterospecific PPIs when combined. This is achieved using software that generates large virtual libraries of peptide sequences and searches within the resulting interactome for preferentially interacting peptides. To demonstrate feasibility, we have (i) generated 1536 peptide sequences based on the parallel dimeric coiled-coil motif and varied residues known to be important for stability and specificity, (ii) screened the 1,180,416 member interactome for predicted Tm values and (iii) used predicted Tm cutoff points to isolate eight peptides that form four heterospecific PPIs when combined. This required that all 32 hypothetical off-target interactions within the eight-peptide interactome be disfavoured and that the four desired interactions pair correctly. Lastly, we have verified the approach by characterising all 36 pairs within the interactome. In analysing the output, we hypothesised that several sequences are capable of adopting antiparallel orientations. We subsequently improved the software by removing sequences where doing so led to fully complementary electrostatic pairings. Our approach can be used to derive increasingly large and therefore complex sets of heterospecific PPIs with a wide range of potential downstream applications from disease modulation to the design of biomaterials and peptides in synthetic biology. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

PubMed

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

2015-02-23

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

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

PubMed Central

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

2015-01-01

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

Correlative Förster Resonance Electron Transfer-Proximity Ligation Assay (FRET-PLA) Technique for Studying Interactions Involving Membrane Proteins.

PubMed

Ivanusic, Daniel; Denner, Joachim; Bannert, Norbert

2016-08-01

This unit provides a guide and detailed protocol for studying membrane protein-protein interactions (PPI) using the acceptor-sensitized Förster resonance electron transfer (FRET) method in combination with the proximity ligation assay (PLA). The protocol in this unit is focused on the preparation of FRET-PLA samples and the detection of correlative FRET/PLA signals as well as on the analysis of FRET-PLA data and interpretation of correlative results when using cyan fluorescent protein (CFP) as a FRET donor and yellow fluorescent protein (YFP) as a FRET acceptor. The correlative application of FRET and PLA combines two powerful tools for monitoring PPI, yielding results that are more reliable than with either technique alone. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions

PubMed Central

Rajagopala, S. V.; Blazie, S. M.; Parrish, J. R.; Khuri, S.; Finley, R. L.

2017-01-01

ABSTRACT The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein’s function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins. PMID:28744484

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

PubMed Central

Yang, Mei; Wang, Danhua; Yu, Lingxiang; Guo, Chaonan; Guo, Xiaodong; Lin, Na

2013-01-01

Aim To screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation. Methods HCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated. Results In total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC. Conclusion This study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC. PMID:24391994

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

PubMed

Wuchty, Stefan

2006-05-23

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

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

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

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

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.

Influence of homology and node age on the growth of protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Bottinelli, Arianna; Bassetti, Bruno; Lagomarsino, Marco Cosentino; Gherardi, Marco

2012-10-01

Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so the dynamics of the two objects are intrinsically linked. Here we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions through the definition of three different node wiring or divergence schemes. A comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition and topology observables.

Hydrophobic interaction chromatography in dual salt system increases protein binding capacity.

PubMed

Senczuk, Anna M; Klinke, Ralph; Arakawa, Tsutomu; Vedantham, Ganesh; Yigzaw, Yinges

2009-08-01

Hydrophobic interaction chromatography (HIC) uses weakly hydrophobic resins and requires a salting-out salt to promote protein-resin interaction. The salting-out effects increase with protein and salt concentration. Dynamic binding capacity (DBC) is dependent on the binding constant, as well as on the flow characteristics during sample loading. DBC increases with the salt concentration but decreases with increasing flow rate. Dynamic and operational binding capacity have a major raw material cost/processing time impact on commercial scale production of monoclonal antibodies. In order to maximize DBC the highest salt concentration without causing precipitation is used. We report here a novel method to maintain protein solubility while increasing the DBC by using a combination of two salting-out salts (referred to as dual salt). In a series of experiments, we explored the dynamic capacity of a HIC resin (TosoBioscience Butyl 650M) with combinations of salts. Using a model antibody, we developed a system allowing us to increase the dynamic capacity up to twofold using the dual salt system over traditional, single salt system. We also investigated the application of this novel approach to several other proteins and salt combinations, and noted a similar protein solubility and DBC increase. The observed increase in DBC in the dual salt system was maintained at different linear flow rates and did not impact selectivity.

Alleles versus genotypes: Genetic interactions and the dynamics of selection in sexual populations

NASA Astrophysics Data System (ADS)

Neher, Richard

2010-03-01

Physical interactions between amino-acids are essential for protein structure and activity, while protein-protein interactions and regulatory interactions are central to cellular function. As a consequence of these interactions, the combined effect of two mutations can differ from the sum of the individual effects of the mutations. This phenomenon of genetic interaction is known as epistasis. However, the importance of epistasis and its effects on evolutionary dynamics are poorly understood, especially in sexual populations where recombination breaks up existing combinations of alleles to produce new ones. Here, we present a computational model of selection dynamics involving many epistatic loci in a recombining population. We demonstrate that a large number of polymorphic interacting loci can, despite frequent recombination, exhibit cooperative behavior that locks alleles into favorable genotypes leading to a population consisting of a set of competing clones. As the recombination rate exceeds a certain critical value this ``genotype selection'' phase disappears in an abrupt transition giving way to ``allele selection'' - the phase where different loci are only weakly correlated as expected in sexually reproducing populations. Clustering of interacting sets of genes on a chromosome leads to the emergence of an intermediate regime, where localized blocks of cooperating alleles lock into genetic modules. Large populations attain highest fitness at a recombination rate just below critical, suggesting that natural selection might tune recombination rates to balance the beneficial aspect of exploration of genotype space with the breaking up of synergistic allele combinations.

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.

UV-Visible and Infrared Methods for Investigating Lipid-Rhodopsin Membrane Interactions

PubMed Central

Brown, Michael F.

2017-01-01

Summary Experimental UV-visible and Fourier transform infrared (FTIR) spectroscopic methods are described for characterizing lipid-protein interactions for the example of rhodopsin in a membrane bilayer environment. The combined use of FTIR and UV-visible difference spectroscopy monitors the structural and functional changes during rhodopsin activation. Such studies investigate how membrane lipids stabilize the various rhodopsin photoproducts, analogous to mutating the protein. Interpretation of the results entails a non-specific flexible surface model for explaining the role of membrane lipid-protein interactions in biological functions. PMID:22976026

Diphenylpyrazoles as Replication Protein A inhibitors

DOE PAGES

Waterson, Alex G.; Kennedy, J. Phillip; Patrone, James D.; ...

2014-11-11

Replication Protein A is the primary eukaryotic ssDNA binding protein that has a central role in initiating the cellular response to DNA damage. RPA recruits multiple proteins to sites of DNA damage via the N-terminal domain of the 70 kDa subunit (RPA70N). Here we describe the optimization of a diphenylpyrazole carboxylic acid series of inhibitors of these RPA–protein interactions. Lastly, we evaluated substituents on the aromatic rings as well as the type and geometry of the linkers used to combine fragments, ultimately leading to submicromolar inhibitors of RPA70N protein–protein interactions.

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

PubMed

Sardiu, Mihaela E; Gilmore, Joshua M; Carrozza, Michael J; Li, Bing; Workman, Jerry L; Florens, Laurence; Washburn, Michael P

2009-10-06

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

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

PubMed Central

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

2017-01-01

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein–protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein–protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein–protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein–protein interactions. PMID:28923934

Molecular dynamics simulations and statistical coupling analysis reveal functional coevolution network of oncogenic mutations in the CDKN2A-CDK6 complex.

PubMed

Wang, Jingwen; Zhao, Yuqi; Wang, Yanjie; Huang, Jingfei

2013-01-16

Coevolution between proteins is crucial for understanding protein-protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural-functional integrity. In this study, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on the CDK6-CDKN2A protein complex to evaluate coevolution between proteins. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37 interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in the CDK6-CDKN2A complex can be helpful for designing protein engineering experiments. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

The Shape of Protein Crowders is a Major Determinant of Protein Diffusion

PubMed Central

Balbo, Jessica; Mereghetti, Paolo; Herten, Dirk-Peter; Wade, Rebecca C.

2013-01-01

As a model for understanding how molecular crowding influences diffusion and transport of proteins in cellular environments, we combined experimental and theoretical approaches to study the diffusion of proteins in highly concentrated protein solutions. Bovine serum albumin and γ-Globulin were chosen as molecular crowders and as tracers. These two proteins are representatives of the main types of plasma protein and have different shapes and sizes. Solutions consisting of one or both proteins were studied. The self-diffusion coefficients of the fluorescently labeled tracer proteins were measured by means of fluorescence correlation spectroscopy at a total protein concentration of up to 400 g/L. γ-Globulin is found to have a stronger influence as a crowder on the tracer self-diffusion coefficient than Bovine serum albumin. Brownian dynamics simulations show that the excluded volume and the shape of the crowding protein have a significantly stronger influence on translational and rotational diffusion coefficients, as well as transient oligomerization, than hydrodynamic or direct interactions. Anomalous subdiffusion, which is not observed at the experimental fluorescence correlation spectroscopy timescales (>100 μs), appears only at very short timescales (<1 μs) in the simulations due to steric effects of the proteins. We envision that the combined experimental and computational approach employed here can be developed to unravel the different biophysical contributions to protein motion and interaction in cellular environments by systematically varying protein properties such as molecular weight, size, shape, and electrostatic interactions. PMID:23561534

Protein-Protein Interaction Network and Gene Ontology

NASA Astrophysics Data System (ADS)

Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

Developing advanced X-ray scattering methods combined with crystallography and computation.

PubMed

Perry, J Jefferson P; Tainer, John A

2013-03-01

The extensive use of small angle X-ray scattering (SAXS) over the last few years is rapidly providing new insights into protein interactions, complex formation and conformational states in solution. This SAXS methodology allows for detailed biophysical quantification of samples of interest. Initial analyses provide a judgment of sample quality, revealing the potential presence of aggregation, the overall extent of folding or disorder, the radius of gyration, maximum particle dimensions and oligomerization state. Structural characterizations include ab initio approaches from SAXS data alone, and when combined with previously determined crystal/NMR, atomistic modeling can further enhance structural solutions and assess validity. This combination can provide definitions of architectures, spatial organizations of protein domains within a complex, including those not determined by crystallography or NMR, as well as defining key conformational states of a protein interaction. SAXS is not generally constrained by macromolecule size, and the rapid collection of data in a 96-well plate format provides methods to screen sample conditions. This includes screening for co-factors, substrates, differing protein or nucleotide partners or small molecule inhibitors, to more fully characterize the variations within assembly states and key conformational changes. Such analyses may be useful for screening constructs and conditions to determine those most likely to promote crystal growth of a complex under study. Moreover, these high throughput structural determinations can be leveraged to define how polymorphisms affect assembly formations and activities. This is in addition to potentially providing architectural characterizations of complexes and interactions for systems biology-based research, and distinctions in assemblies and interactions in comparative genomics. Thus, SAXS combined with crystallography/NMR and computation provides a unique set of tools that should be considered as being part of one's repertoire of biophysical analyses, when conducting characterizations of protein and other macromolecular interactions. Copyright © 2013 Elsevier Inc. All rights reserved.

Combined Biology and Bioinformatics Approaches to Breast Cancer

DTIC Science & Technology

2006-04-01

In these experiments, LMO4 interacted with the MH1 and linker domains of Smad3 ; no interaction was found with the MH2 domain (Figure 4b). Figure 2...transcriptional response to TGFb by interacting with Smad proteins, and that both the MH1 and linker domains of Smad3 participate in the interaction. LMO4 can...LMO4 interacts with the MH1 and linker regions of Smad proteins. (a) Full-length, 35S-labeled Smad2, Smad3 , Smad4, Smad5, and Smad8 were incubated with

New insights into protein-protein interaction data lead to increased estimates of the S. cerevisiae interactome size.

PubMed

Sambourg, Laure; Thierry-Mieg, Nicolas

2010-12-21

As protein interactions mediate most cellular mechanisms, protein-protein interaction networks are essential in the study of cellular processes. Consequently, several large-scale interactome mapping projects have been undertaken, and protein-protein interactions are being distilled into databases through literature curation; yet protein-protein interaction data are still far from comprehensive, even in the model organism Saccharomyces cerevisiae. Estimating the interactome size is important for evaluating the completeness of current datasets, in order to measure the remaining efforts that are required. We examined the yeast interactome from a new perspective, by taking into account how thoroughly proteins have been studied. We discovered that the set of literature-curated protein-protein interactions is qualitatively different when restricted to proteins that have received extensive attention from the scientific community. In particular, these interactions are less often supported by yeast two-hybrid, and more often by more complex experiments such as biochemical activity assays. Our analysis showed that high-throughput and literature-curated interactome datasets are more correlated than commonly assumed, but that this bias can be corrected for by focusing on well-studied proteins. We thus propose a simple and reliable method to estimate the size of an interactome, combining literature-curated data involving well-studied proteins with high-throughput data. It yields an estimate of at least 37, 600 direct physical protein-protein interactions in S. cerevisiae. Our method leads to higher and more accurate estimates of the interactome size, as it accounts for interactions that are genuine yet difficult to detect with commonly-used experimental assays. This shows that we are even further from completing the yeast interactome map than previously expected.

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

Selection of peptides interfering with protein-protein interaction.

PubMed

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

2009-01-01

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

Protein annotation from protein interaction networks and Gene Ontology.

PubMed

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

2011-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

The malaria parasite RhopH protein complex interacts with erythrocyte calmyrin identified from a comprehensive erythrocyte protein library.

PubMed

Miura, Toyokazu; Takeo, Satoru; Ntege, Edward H; Otsuki, Hitoshi; Sawasaki, Tatsuya; Ishino, Tomoko; Takashima, Eizo; Tsuboi, Takafumi

2018-06-02

Malaria merozoite apical organelles; microneme and rhoptry secreted proteins play functional roles during and following invasion of host erythrocytes. Among numerous proteins, the rhoptries discharge high molecular weight proteins known as RhopH complex. Recent reports suggest that the RhopH complex is essential for growth and survival of the malaria parasite within erythrocytes. However, an in-depth understanding of the host-parasite molecular interactions is indispensable. Here we utilized a comprehensive mouse erythrocyte protein library consisting of 443 proteins produced by a wheat germ cell-free system, combined with AlphaScreen technology to identify mouse erythrocyte calmyrin as an interacting molecule of the rodent malaria parasite Plasmodium yoelii RhopH complex (PyRhopH). The PyRhopH interaction was dependent on the calmyrin N-terminus and divalent cation capacity. The finding unveils a recommendable and invaluable usefulness of our comprehensive mouse erythrocyte protein library together with the AlphaScreen technology in investigating a wide-range of host-parasite molecular interactions. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessment of semantic similarity between proteins using information content and topological properties of the Gene Ontology graph.

PubMed

Dutta, Pritha; Basu, Subhadip; Kundu, Mahantapas

2017-03-31

The semantic similarity between two interacting proteins can be estimated by combining the similarity scores of the GO terms associated with the proteins. Greater number of similar GO annotations between two proteins indicates greater interaction affinity. Existing semantic similarity measures make use of the GO graph structure, the information content of GO terms, or a combination of both. In this paper, we present a hybrid approach which utilizes both the topological features of the GO graph and information contents of the GO terms. More specifically, we 1) consider a fuzzy clustering of the GO graph based on the level of association of the GO terms, 2) estimate the GO term memberships to each cluster center based on the respective shortest path lengths, and 3) assign weightage to GO term pairs on the basis of their dissimilarity with respect to the cluster centers. We test the performance of our semantic similarity measure against seven other previously published similarity measures using benchmark protein-protein interaction datasets of Homo sapiens and Saccharomyces cerevisiae based on sequence similarity, Pfam similarity, area under ROC curve and F1 measure.

PPCM: Combing multiple classifiers to improve protein-protein interaction prediction

DOE PAGES

Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

2015-08-01

Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using anmore » assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. Ultimately, this pipeline will be useful for predicting PPI in nonmodel species.« less

The BioPlex Network: A Systematic Exploration of the Human Interactome.

PubMed

Huttlin, Edward L; Ting, Lily; Bruckner, Raphael J; Gebreab, Fana; Gygi, Melanie P; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E; De Camilli, Pietro; Paulo, Joao A; Harper, J Wade; Gygi, Steven P

2015-07-16

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors. Copyright © 2015 Elsevier Inc. All rights reserved.

The BioPlex Network: A Systematic Exploration of the Human Interactome

PubMed Central

Huttlin, Edward L.; Ting, Lily; Bruckner, Raphael J.; Gebreab, Fana; Gygi, Melanie P.; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K.; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A.; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E.; DeCamilli, Pietro; Paulo, Joao A.; Harper, J. Wade; Gygi, Steven P.

2015-01-01

SUMMARY Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally-related proteins. Finally, BioPlex, in combination with other approaches can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial Amyotrophic Lateral Sclerosis perturb a defined community of interactors. PMID:26186194

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Constraints imposed by non-functional protein–protein interactions on gene expression and proteome size

PubMed Central

Zhang, Jingshan; Maslov, Sergei; Shakhnovich, Eugene I

2008-01-01

Crowded intracellular environments present a challenge for proteins to form functional specific complexes while reducing non-functional interactions with promiscuous non-functional partners. Here we show how the need to minimize the waste of resources to non-functional interactions limits the proteome diversity and the average concentration of co-expressed and co-localized proteins. Using the results of high-throughput Yeast 2-Hybrid experiments, we estimate the characteristic strength of non-functional protein–protein interactions. By combining these data with the strengths of specific interactions, we assess the fraction of time proteins spend tied up in non-functional interactions as a function of their overall concentration. This allows us to sketch the phase diagram for baker's yeast cells using the experimentally measured concentrations and subcellular localization of their proteins. The positions of yeast compartments on the phase diagram are consistent with our hypothesis that the yeast proteome has evolved to operate closely to the upper limit of its size, whereas keeping individual protein concentrations sufficiently low to reduce non-functional interactions. These findings have implication for conceptual understanding of intracellular compartmentalization, multicellularity and differentiation. PMID:18682700

Identification of Proteins Using iTRAQ and Virus-Induced Gene Silencing Reveals Three Bread Wheat Proteins Involved in the Response to Combined Osmotic-Cold Stress.

PubMed

Zhang, Ning; Zhang, Lingran; Shi, Chaonan; Zhao, Lei; Cui, Dangqun; Chen, Feng

2018-05-25

Crops are often subjected to a combination of stresses in the field. To date, studies on the physiological and molecular responses of common wheat to a combination of osmotic and cold stresses, however, remain unknown. In this study, wheat seedlings exposed to osmotic-cold stress for 24 h showed inhibited growth, as well as increased lipid peroxidation, relative electrolyte leakage, and soluble sugar contents. iTRAQ-based quantitative proteome method was employed to determine the proteomic profiles of the roots and leaves of wheat seedlings exposed to osmotic-cold stress conditions. A total of 250 and 258 proteins with significantly altered abundance in the roots and leaves were identified, respectively, and the majority of these proteins displayed differential abundance, thereby revealing organ-specific differences in adaptation to osmotic-cold stress. Yeast two hybrid assay examined five pairs of stress/defense-related protein-protein interactions in the predicted protein interaction network. Furthermore, quantitative real-time PCR analysis indicated that abiotic stresses increased the expression of three candidate protein genes, i.e., TaGRP2, CDCP, and Wcor410c in wheat leaves. Virus-induced gene silencing indicated that three genes TaGRP2, CDCP, and Wcor410c were involved in modulating osmotic-cold stress in common wheat. Our study provides useful information for the elucidation of molecular and genetics bases of osmotic-cold combined stress in bread wheat.

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

PubMed Central

Franzosa, Eric A.; Xia, Yu

2011-01-01

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

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

PubMed Central

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

2014-01-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein–protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB–EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB–EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB–EF-Tu interactions. PMID:25030837

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

PubMed

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

2006-11-15

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

Building blocks for protein interaction devices

PubMed Central

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

2010-01-01

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

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.

Distyrylbenzene-aldehydes: identification of proteins in water.

PubMed

Kumpf, Jan; Freudenberg, Jan; Bunz, Uwe H F

2015-05-07

Three different, water soluble, aldehyde-appended distyrylbenzene (DSB) derivatives were prepared. Their interaction with different albumin variants (human, porcine, bovine, lactalbumin, ovalbumin) was investigated (pH 11). All three fluorophores exhibit graded, protein-dependent fluorescence turn-on at slightly differing wavelengths. Linear discriminant analysis (LDA) differentiated all of the investigated albumins and was used to discern commercially available protein shakes. The three DSB derivatives barely react with the constituting amino acids but cysteine. In the proteins significant fluorescence signals are generated, probably due to a combination of imine/N,S-aminal formation and hydrophobic interactions between the DSBs and the proteins.

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

PubMed

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

2009-11-24

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

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

PubMed Central

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

2006-01-01

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

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.

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

PubMed

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

2010-02-02

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

Deciphering the Dynamic Interaction Profile of an Intrinsically Disordered Protein by NMR Exchange Spectroscopy.

PubMed

Delaforge, Elise; Kragelj, Jaka; Tengo, Laura; Palencia, Andrés; Milles, Sigrid; Bouvignies, Guillaume; Salvi, Nicola; Blackledge, Martin; Jensen, Malene Ringkjøbing

2018-01-24

Intrinsically disordered proteins (IDPs) display a large number of interaction modes including folding-upon-binding, binding without major structural transitions, or binding through highly dynamic, so-called fuzzy, complexes. The vast majority of experimental information about IDP binding modes have been inferred from crystal structures of proteins in complex with short peptides of IDPs. However, crystal structures provide a mainly static view of the complexes and do not give information about the conformational dynamics experienced by the IDP in the bound state. Knowledge of the dynamics of IDP complexes is of fundamental importance to understand how IDPs engage in highly specific interactions without concomitantly high binding affinity. Here, we combine rotating-frame R 1ρ , Carr-Purcell-Meiboom Gill relaxation dispersion as well as chemical exchange saturation transfer to decipher the dynamic interaction profile of an IDP in complex with its partner. We apply the approach to the dynamic signaling complex formed between the mitogen-activated protein kinase (MAPK) p38α and the intrinsically disordered regulatory domain of the MAPK kinase MKK4. Our study demonstrates that MKK4 employs a subtle combination of interaction modes in order to bind to p38α, leading to a complex displaying significantly different dynamics across the bound regions.

Dynamic interactions between Pit-1 and C/EBPalpha in the pituitary cell nucleus.

PubMed

Demarco, Ignacio A; Voss, Ty C; Booker, Cynthia F; Day, Richard N

2006-11-01

The homeodomain (HD) transcription factors are a structurally conserved family of proteins that, through networks of interactions with other nuclear proteins, control patterns of gene expression during development. For example, the network interactions of the pituitary-specific HD protein Pit-1 control the development of anterior pituitary cells and regulate the expression of the hormone products in the adult cells. Inactivating mutations in Pit-1 disrupt these processes, giving rise to the syndrome of combined pituitary hormone deficiency. Pit-1 interacts with CCAAT/enhancer-binding protein alpha (C/EBPalpha) to regulate prolactin transcription. Here, we used the combination of biochemical analysis and live-cell microscopy to show that two different point mutations in Pit-1, which disrupted distinct activities, affected the dynamic interactions between Pit-1 and C/EBPalpha in different ways. The results showed that the first alpha-helix of the POU-S domain is critical for the assembly of Pit-1 with C/EBPalpha, and they showed that DNA-binding activity conferred by the HD is critical for the final intranuclear positioning of the metastable complex. This likely reflects more general mechanisms that govern cell-type-specific transcriptional control, and the results from the analysis of the point mutations could indicate an important link between the mislocalization of transcriptional complexes and disease processes.

Protein Interaction Profile Sequencing (PIP-seq).

PubMed

Foley, Shawn W; Gregory, Brian D

2016-10-10

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

Mapping the local protein interactome of the NuA3 histone acetyltransferase

PubMed Central

Smart, Sherri K; Mackintosh, Samuel G; Edmondson, Ricky D; Taverna, Sean D; Tackett, Alan J

2009-01-01

Protein–protein interactions modulate cellular functions ranging from the activity of enzymes to signal transduction cascades. A technology termed transient isotopic differentiation of interactions as random or targeted (transient I-DIRT) is described for the identification of stable and transient protein–protein interactions in vivo. The procedure combines mild in vivo chemical cross-linking and non-stringent affinity purification to isolate low abundance chromatin-associated protein complexes. Using isotopic labeling and mass spectrometric readout, purified proteins are categorized with respect to the protein ‘bait’ as stable, transient, or contaminant. Here we characterize the local interactome of the chromatin-associated NuA3 histone lysine-acetyltransferase protein complex. We describe transient associations with the yFACT nucleosome assembly complex, RSC chromatin remodeling complex and a nucleosome assembly protein. These novel, physical associations with yFACT, RSC, and Nap1 provide insight into the mechanism of NuA3-associated transcription and chromatin regulation. PMID:19621382

Indentification and Analysis of Occludin Phosphosites: A Combined Mass Spectroscoy and Bioinformatics Approach

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

Sundstrom, J.; Tash, B; Murakami, T

2009-01-01

The molecular function of occludin, an integral membrane component of tight junctions, remains unclear. VEGF-induced phosphorylation sites were mapped on occludin by combining MS data analysis with bioinformatics. In vivo phosphorylation of Ser490 was validated and protein interaction studies combined with crystal structure analysis suggest that Ser490 phosphorylation attenuates the interaction between occludin and ZO-1. This study demonstrates that combining MS data and bioinformatics can successfully identify novel phosphorylation sites from limiting samples.

Functional integrative levels in the human interactome recapitulate organ organization.

PubMed

Souiai, Ouissem; Becker, Emmanuelle; Prieto, Carlos; Benkahla, Alia; De las Rivas, Javier; Brun, Christine

2011-01-01

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This 'Largest Common Interactome Network' represents a 'functional interactome core'. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

Combined effect of cortical cytoskeleton and transmembrane proteins on domain formation in biomembranes

PubMed Central

Sikder, Md. Kabir Uddin; Stone, Kyle A.; Kumar, P. B. Sunil; Laradji, Mohamed

2014-01-01

We investigate the combined effects of transmembrane proteins and the subjacent cytoskeleton on the dynamics of phase separation in multicomponent lipid bilayers using computer simulations of a particle-based implicit solvent model for lipid membranes with soft-core interactions. We find that microphase separation can be achieved by the protein confinement by the cytoskeleton. Our results have relevance to the finite size of lipid rafts in the plasma membrane of mammalian cells. PMID:25106608

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

Binding Linkage in a Telomere DNA–Protein Complex at the Ends of Oxytricha nova Chromosomes

PubMed Central

Buczek, Pawel; Orr, Rochelle S.; Pyper, Sean R.; Shum, Mili; Ota, Emily Kimmel Irene; Gerum, Shawn E.; Horvath, Martin P.

2005-01-01

Alpha and beta protein subunits of the telomere end binding protein from Oxytricha nova (OnTEBP) combine with telomere single strand DNA to form a protective cap at the ends of chromosomes. We tested how protein–protein interactions seen in the co-crystal structure relate to DNA binding through use of fusion proteins engineered as different combinations of domains and subunits derived from OnTEBP. Joining alpha and beta resulted in a protein that bound single strand telomere DNA with high affinity (KD-DNA=1.4 nM). Another fusion protein, constructed without the C-terminal protein–protein interaction domain of alpha, bound DNA with 200-fold diminished affinity (KD-DNA=290 nM) even though the DNA-binding domains of alpha and beta were joined through a peptide linker. Adding back the alpha C-terminal domain as a separate protein restored high-affinity DNA binding. The binding behaviors of these fusion proteins and the native protein subunits are consistent with cooperative linkage between protein-association and DNA-binding equilibria. Linking DNA–protein stability to protein–protein contacts at a remote site may provide a trigger point for DNA–protein disassembly during telomere replication when the single strand telomere DNA must exchange between a very stable OnTEBP complex and telomerase. PMID:15967465

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.

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.

Combinatorial interaction between CCM pathway genes precipitates hemorrhagic stroke.

PubMed

Gore, Aniket V; Lampugnani, Maria Grazia; Dye, Louis; Dejana, Elisabetta; Weinstein, Brant M

2008-01-01

Intracranial hemorrhage (ICH) is a particularly severe form of stroke whose etiology remains poorly understood, with a highly variable appearance and onset of the disease (Felbor et al., 2006; Frizzell, 2005; Lucas et al., 2003). In humans, mutations in any one of three CCM genes causes an autosomal dominant genetic ICH disorder characterized by cerebral cavernous malformations (CCM). Recent evidence highlighting multiple interactions between the three CCM gene products and other proteins regulating endothelial junctional integrity suggests that minor deficits in these other proteins could potentially predispose to, or help to initiate, CCM, and that combinations of otherwise silent genetic deficits in both the CCM and interacting proteins might explain some of the variability in penetrance and expressivity of human ICH disorders. Here, we test this idea by combined knockdown of CCM pathway genes in zebrafish. Reducing the function of rap1b, which encodes a Ras GTPase effector protein for CCM1/Krit1, disrupts endothelial junctions in vivo and in vitro, showing it is a crucial player in the CCM pathway. Importantly, a minor reduction of Rap1b in combination with similar reductions in the products of other CCM pathway genes results in a high incidence of ICH. These findings support the idea that minor polygenic deficits in the CCM pathway can strongly synergize to initiate ICH.

Combined Biology and Bioinformatics Approaches to Breast Cancer

DTIC Science & Technology

2005-04-01

interacted with the MH 1 and linker domains in both Smad3 and Smad4; no interaction was found with the MH2 domain (Fig. 7C). These data suggest that LMO4...LMO4 interacts with these Smads. GST protein-protein interaction assays showed that LMO4 binds to the MH1 and linker domain of Smad 1, Smad3 and Smad4...by facilitating the nuclear translocation and DNA-binding of a complex composed of an R-Smad (Smad2 and/or Smad3 ) and the co-Smad, Smad4 (10). To

A nano-bio interfacial protein corona on silica nanoparticle.

PubMed

Zhang, Hongyan; Peng, Jiaxi; Li, Xin; Liu, Shengju; Hu, Zhengyan; Xu, Guiju; Wu, Ren'an

2018-07-01

Nano-bio interaction takes the crucial role in bio-application of nanoparticles. The systematic mapping of interfacial proteins remains the big challenge as low level of proteins within interface regions and lack of appropriate technology. Here, a facile proteomic strategy was developed to characterize the interfacial protein corona (noted as IPC) that has strong interactions with silica nanoparticle, via the combination of the vigorous elution with high concentration sodium dodecyl sulfate (SDS) and the pre-isolation of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The trace level IPCs for silica nanoparticle were thus qualitatively and quantitatively identified. Bioinformatics analyses revealed the intrinsic compositions, relevance and potential regularity addressing the strong interactions between IPC and nanoparticle. This strategy in determining IPCs is opening an avenue to give a deep insight to understand the interaction between proteins and not only nanoparticles but also other bulk materials. Copyright © 2018 Elsevier B.V. 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.

Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast

PubMed Central

Ye, Ping; Peyser, Brian D; Spencer, Forrest A; Bader, Joel S

2005-01-01

Background In a genetic interaction, the phenotype of a double mutant differs from the combined phenotypes of the underlying single mutants. When the single mutants have no growth defect, but the double mutant is lethal or exhibits slow growth, the interaction is termed synthetic lethality or synthetic fitness. These genetic interactions reveal gene redundancy and compensating pathways. Recently available large-scale data sets of genetic interactions and protein interactions in Saccharomyces cerevisiae provide a unique opportunity to elucidate the topological structure of biological pathways and how genes function in these pathways. Results We have defined congruent genes as pairs of genes with similar sets of genetic interaction partners and constructed a genetic congruence network by linking congruent genes. By comparing path lengths in three types of networks (genetic interaction, genetic congruence, and protein interaction), we discovered that high genetic congruence not only exhibits correlation with direct protein interaction linkage but also exhibits commensurate distance with the protein interaction network. However, consistent distances were not observed between genetic and protein interaction networks. We also demonstrated that congruence and protein networks are enriched with motifs that indicate network transitivity, while the genetic network has both transitive (triangle) and intransitive (square) types of motifs. These results suggest that robustness of yeast cells to gene deletions is due in part to two complementary pathways (square motif) or three complementary pathways, any two of which are required for viability (triangle motif). Conclusion Genetic congruence is superior to genetic interaction in prediction of protein interactions and function associations. Genetically interacting pairs usually belong to parallel compensatory pathways, which can generate transitive motifs (any two of three pathways needed) or intransitive motifs (either of two pathways needed). PMID:16283923

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

PubMed

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

2015-12-01

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

High-Throughput Protein Expression Using a Combination of Ligation-Independent Cloning (LIC) and Infrared Fluorescent Protein (IFP) Detection

PubMed Central

Dortay, Hakan; Akula, Usha Madhuri; Westphal, Christin; Sittig, Marie; Mueller-Roeber, Bernd

2011-01-01

Protein expression in heterologous hosts for functional studies is a cumbersome effort. Here, we report a superior platform for parallel protein expression in vivo and in vitro. The platform combines highly efficient ligation-independent cloning (LIC) with instantaneous detection of expressed proteins through N- or C-terminal fusions to infrared fluorescent protein (IFP). For each open reading frame, only two PCR fragments are generated (with three PCR primers) and inserted by LIC into ten expression vectors suitable for protein expression in microbial hosts, including Escherichia coli, Kluyveromyces lactis, Pichia pastoris, the protozoon Leishmania tarentolae, and an in vitro transcription/translation system. Accumulation of IFP-fusion proteins is detected by infrared imaging of living cells or crude protein extracts directly after SDS-PAGE without additional processing. We successfully employed the LIC-IFP platform for in vivo and in vitro expression of ten plant and fungal proteins, including transcription factors and enzymes. Using the IFP reporter, we additionally established facile methods for the visualisation of protein-protein interactions and the detection of DNA-transcription factor interactions in microtiter and gel-free format. We conclude that IFP represents an excellent reporter for high-throughput protein expression and analysis, which can be easily extended to numerous other expression hosts using the setup reported here. PMID:21541323

Development of a gluten-free rice noodle by utilizing protein-polyphenol interaction between soy protein isolate and extract of Acanthopanax sessiliflorus.

PubMed

Lee, Da-Som; Kim, Yang; Song, Youngwoon; Lee, Ji-Hye; Lee, Suyong; Yoo, Sang-Ho

2016-02-01

The potential of the protein-polyphenol interaction was applied to crosslinking reinforced protein networks in gluten-free rice noodles. Specifically, inter-component interaction between soy protein isolate and extract of Acanthopanax sessiliflorus fruit (ogaja) was examined with a view to improving its quality. In a components-interacting model system, a mixture of soy protein isolate (SPI) and ogaja extract (OE) induced a drastic increase in absorbance at 660 nm by haze formation, while the major anthocyanin of ogaja, cyanidin-3-O-sambubioside, sparsely interacted with SPI or gelatin. Individual or combined treatment of SPI and OE on rice dough decreased all the viscosity parameters in rapid visco analysis. However, SPI-OE treatment significantly increased all the texture parameters of rice dough derived from Mixolab(®) analysis (P < 0.05). Incorporation of SPI in rice dough significantly reduced endothermic ΔH, and SPI-OE treatment further decreased this value. SPI-OE interaction significantly increased the tensile properties of cooked noodle and decreased 53.7% of cooking loss compared to the untreated rice noodle. SPI-OE treatment caused a considerable reinforcement of the network as shown by reducing cooking loss and suggested the potential for utilizing protein-polyphenol interaction for gluten-free rice noodle production. © 2015 Society of Chemical Industry.

Plasma membrane lipid–protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana

PubMed Central

Zauber, Henrik; Burgos, Asdrubal; Garapati, Prashanth; Schulze, Waltraud X.

2014-01-01

The plasma membrane is an important organelle providing structure, signaling and transport as major biological functions. Being composed of lipids and proteins with different physicochemical properties, the biological functions of membranes depend on specific protein–protein and protein–lipid interactions. Interactions of proteins with their specific sterol and lipid environment were shown to be important factors for protein recruitment into sub-compartmental structures of the plasma membrane. System-wide implications of altered endogenous sterol levels for membrane functions in living cells were not studied in higher plant cells. In particular, little is known how alterations in membrane sterol composition affect protein and lipid organization and interaction within membranes. Here, we conducted a comparative analysis of the plasma membrane protein and lipid composition in Arabidopsis sterol-biosynthesis mutants smt1 and ugt80A2;B1. smt1 shows general alterations in sterol composition while ugt80A2;B1 is significantly impaired in sterol glycosylation. By systematically analyzing different cellular fractions and combining proteomic with lipidomic data we were able to reveal contrasting alterations in lipid–protein interactions in both mutants, with resulting differential changes in plasma membrane signaling status. PMID:24672530

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

PubMed

Xie, Zhongqiu; Jia, Yuemeng; Li, Hui

2017-01-01

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

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

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

PubMed

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

2018-04-01

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

A comparative analysis of human plasma and serum proteins by combining native PAGE, whole-gel slicing and quantitative LC-MS/MS: Utilizing native MS-electropherograms in proteomic analysis for discovering structure and interaction-correlated differences.

PubMed

Wen, Meiling; Jin, Ya; Manabe, Takashi; Chen, Shumin; Tan, Wen

2017-12-01

MS identification has long been used for PAGE-separated protein bands, but global and systematic quantitation utilizing MS after PAGE has remained rare and not been reported for native PAGE. Here we reported on a new method combining native PAGE, whole-gel slicing and quantitative LC-MS/MS, aiming at comparative analysis on not only abundance, but also structures and interactions of proteins. A pair of human plasma and serum samples were used as test samples and separated on a native PAGE gel. Six lanes of each sample were cut, each lane was further sliced into thirty-five 1.1 mm × 1.1 mm squares and all the squares were subjected to standardized procedures of in-gel digestion and quantitative LC-MS/MS. The results comprised 958 data rows that each contained abundance values of a protein detected in one square in eleven gel lanes (one plasma lane excluded). The data were evaluated to have satisfactory reproducibility of assignment and quantitation. Totally 315 proteins were assigned, with each protein assigned in 1-28 squares. The abundance distributions in the plasma and serum gel lanes were reconstructed for each protein, named as "native MS-electropherograms". Comparison of the electropherograms revealed significant plasma-versus-serum differences on 33 proteins in 87 squares (fold difference > 2 or < 0.5, p < 0.05). Many of the differences matched with accumulated knowledge on protein interactions and proteolysis involved in blood coagulation, complement and wound healing processes. We expect this method would be useful to provide more comprehensive information in comparative proteomic analysis, on both quantities and structures/interactions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Balakrishnan, Swati; Sarma, Siddhartha P

2017-08-22

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

Virtual Interactomics of Proteins from Biochemical Standpoint

PubMed Central

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel

2012-01-01

Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109

Tracking transcription factor mobility and interaction in Arabidopsis roots with fluorescence correlation spectroscopy

PubMed Central

Clark, Natalie M; Hinde, Elizabeth; Winter, Cara M; Fisher, Adam P; Crosti, Giuseppe; Blilou, Ikram; Gratton, Enrico; Benfey, Philip N; Sozzani, Rosangela

2016-01-01

To understand complex regulatory processes in multicellular organisms, it is critical to be able to quantitatively analyze protein movement and protein-protein interactions in time and space. During Arabidopsis development, the intercellular movement of SHORTROOT (SHR) and subsequent interaction with its downstream target SCARECROW (SCR) control root patterning and cell fate specification. However, quantitative information about the spatio-temporal dynamics of SHR movement and SHR-SCR interaction is currently unavailable. Here, we quantify parameters including SHR mobility, oligomeric state, and association with SCR using a combination of Fluorescent Correlation Spectroscopy (FCS) techniques. We then incorporate these parameters into a mathematical model of SHR and SCR, which shows that SHR reaches a steady state in minutes, while SCR and the SHR-SCR complex reach a steady-state between 18 and 24 hr. Our model reveals the timing of SHR and SCR dynamics and allows us to understand how protein movement and protein-protein stoichiometry contribute to development. DOI: http://dx.doi.org/10.7554/eLife.14770.001 PMID:27288545

Lipid membrane-mediated attraction between curvature inducing objects

NASA Astrophysics Data System (ADS)

van der Wel, Casper; Vahid, Afshin; Šarić, Anđela; Idema, Timon; Heinrich, Doris; Kraft, Daniela J.

2016-09-01

The interplay of membrane proteins is vital for many biological processes, such as cellular transport, cell division, and signal transduction between nerve cells. Theoretical considerations have led to the idea that the membrane itself mediates protein self-organization in these processes through minimization of membrane curvature energy. Here, we present a combined experimental and numerical study in which we quantify these interactions directly for the first time. In our experimental model system we control the deformation of a lipid membrane by adhering colloidal particles. Using confocal microscopy, we establish that these membrane deformations cause an attractive interaction force leading to reversible binding. The attraction extends over 2.5 times the particle diameter and has a strength of three times the thermal energy (-3.3 kBT). Coarse-grained Monte-Carlo simulations of the system are in excellent agreement with the experimental results and prove that the measured interaction is independent of length scale. Our combined experimental and numerical results reveal membrane curvature as a common physical origin for interactions between any membrane-deforming objects, from nanometre-sized proteins to micrometre-sized particles.

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

PubMed Central

2011-01-01

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

Characterising protein, salt and water interactions with combined vibrational spectroscopic techniques.

PubMed

Perisic, Nebojsa; Afseth, Nils Kristian; Ofstad, Ragni; Hassani, Sahar; Kohler, Achim

2013-05-01

In this paper a combination of NIR spectroscopy and FTIR and Raman microspectroscopy was used to elucidate the effects of different salts (NaCl, KCl and MgSO(4)) on structural proteins and their hydration in muscle tissue. Multivariate multi-block technique Consensus Principal Component Analysis enabled integration of different vibrational spectroscopic techniques: macroscopic information obtained by NIR spectroscopy is directly related to microscopic information obtained by FTIR and Raman microspectroscopy. Changes in protein secondary structure observed at different concentrations of salts were linked to changes in protein hydration affinity. The evidence for this was given by connecting the underlying FTIR bands of the amide I region (1700-1600 cm(-1)) and the water region (3500-3000 cm(-1)) with water vibrations obtained by NIR spectroscopy. In addition, Raman microspectroscopy demonstrated that different cations affected structures of aromatic amino acid residues differently, which indicates that cation-π interactions play an important role in determination of the final structure of protein molecules. Copyright © 2012 Elsevier Ltd. All rights reserved.

Initiation of Phage Infection by Partial Unfolding and Prolyl Isomerization*♦

PubMed Central

Hoffmann-Thoms, Stephanie; Weininger, Ulrich; Eckert, Barbara; Jakob, Roman P.; Koch, Johanna R.; Balbach, Jochen; Schmid, Franz X.

2013-01-01

Infection of Escherichia coli by the filamentous phage fd starts with the binding of the N2 domain of the phage gene-3-protein to an F pilus. This interaction triggers partial unfolding of the gene-3-protein, cis → trans isomerization at Pro-213, and domain disassembly, thereby exposing its binding site for the ultimate receptor TolA. The trans-proline sets a molecular timer to maintain the binding-active state long enough for the phage to interact with TolA. We elucidated the changes in structure and local stability that lead to partial unfolding and thus to the activation of the gene-3-protein for phage infection. Protein folding and TolA binding experiments were combined with real-time NMR spectroscopy, amide hydrogen exchange measurements, and phage infectivity assays. In combination, the results provide a molecular picture of how a local unfolding reaction couples with prolyl isomerization not only to generate the activated state of a protein but also to maintain it for an extended time. PMID:23486474

A TRPV2 interactome-based signature for prognosis in glioblastoma patients.

PubMed

Doñate-Macián, Pau; Gómez, Antonio; Dégano, Irene R; Perálvarez-Marín, Alex

2018-04-06

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico , we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease.

A TRPV2 interactome-based signature for prognosis in glioblastoma patients

PubMed Central

Dégano, Irene R.; Perálvarez-Marín, Alex

2018-01-01

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico, we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease. PMID:29719613

Mixed retention mechanism of proteins in weak anion-exchange chromatography.

PubMed

Liu, Peng; Yang, Haiya; Geng, Xindu

2009-10-30

Using four commercial weak anion-exchange chromatography (WAX) columns and 11 kinds of different proteins, we experimentally examined the involvement of hydrophobic interaction chromatography (HIC) mechanism in protein retention on the WAX columns. The HIC mechanism was found to operate in all four WAX columns, and each of these columns had a better resolution in the HIC mode than in the corresponding WAX mode. Detailed analysis of the molecular interactions in a chromatographic system indicated that it is impossible to completely eliminate hydrophobic interactions from a WAX column. Based on these results, it may be possible to employ a single WAX column for protein separation by exploiting mixed modes (WAX and HIC) of retention. The stoichiometric displacement theory and two linear plots were used to show that mechanism of the mixed modes of retention in the system was a combination of two kinds of interactions, i.e., nonselective interactions in the HIC mode and selective interactions in the IEC mode. The obtained U-shaped elution curve of proteins could be distinguished into four different ranges of salt concentration, which also represent four retention regions.

PIP2-dependent coupling is prominent in Kv7.1 due to weakened interactions between S4-S5 and S6

NASA Astrophysics Data System (ADS)

Kasimova, Marina A.; Zaydman, Mark A.; Cui, Jianmin; Tarek, Mounir

2015-01-01

Among critical aspects of voltage-gated potassium (Kv) channels' functioning is the effective communication between their two composing domains, the voltage sensor (VSD) and the pore. This communication, called coupling, might be transmitted directly through interactions between these domains and, as recently proposed, indirectly through interactions with phosphatidylinositol-4,5-bisphosphate (PIP2), a minor lipid of the inner plasma membrane leaflet. Here, we show how the two components of coupling, mediated by protein-protein or protein-lipid interactions, both contribute in the Kv7.1 functioning. On the one hand, using molecular dynamics simulations, we identified a Kv7.1 PIP2 binding site that involves residues playing a key role in PIP2-dependent coupling. On the other hand, combined theoretical and experimental approaches have shown that the direct interaction between the segments of the VSD (S4-S5) and the pore (S6) is weakened by electrostatic repulsion. Finally, we conclude that due to weakened protein-protein interactions, the PIP2-dependent coupling is especially prominent in Kv7.1.

Functional Integrative Levels in the Human Interactome Recapitulate Organ Organization

PubMed Central

Prieto, Carlos; Benkahla, Alia; De Las Rivas, Javier; Brun, Christine

2011-01-01

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization. PMID:21799769

Characterizing natural colloidal/particulate-protein interactions using fluorescence-based techniques and principal component analysis.

PubMed

Peiris, Ramila H; Ignagni, Nicholas; Budman, Hector; Moresoli, Christine; Legge, Raymond L

2012-09-15

Characterization of the interactions between natural colloidal/particulate- and protein-like matter is important for understanding their contribution to different physiochemical phenomena like membrane fouling, adsorption of bacteria onto surfaces and various applications of nanoparticles in nanomedicine and nanotoxicology. Precise interpretation of the extent of such interactions is however hindered due to the limitations of most characterization methods to allow rapid, sensitive and accurate measurements. Here we report on a fluorescence-based excitation-emission matrix (EEM) approach in combination with principal component analysis (PCA) to extract information related to the interaction between natural colloidal/particulate- and protein-like matter. Surface plasmon resonance (SPR) analysis and fiber-optic probe based surface fluorescence measurements were used to confirm that the proposed approach can be used to characterize colloidal/particulate-protein interactions at the physical level. This method has potential to be a fundamental measurement of these interactions with the advantage that it can be performed rapidly and with high sensitivity. Copyright © 2012 Elsevier B.V. All rights reserved.

Osmotic second virial cross-coefficient measurements for binary combination of lysozyme, ovalbumin, and α-amylase in salt solutions.

PubMed

Mehta, Chirag M; White, Edward T; Litster, James D

2013-01-01

Interactions measurement is a valuable tool to predict equilibrium phase separation of a desired protein in the presence of unwanted macromolecules. In this study, cross-interactions were measured as the osmotic second virial cross-coefficients (B23 ) for the three binary protein systems involving lysozyme, ovalbumin, and α-amylase in salt solutions (sodium chloride and ammonium sulfate). They were correlated with solubility for the binary protein mixtures. The cross-interaction behavior at different salt concentrations was interpreted by either electrostatic or hydrophobic interaction forces. At low salt concentrations, the protein surface charge dominates cross-interaction behavior as a function of pH. With added ovalbumin, the lysozyme solubility decreased linearly at low salt concentration in sodium chloride and increased at high salt concentration in ammonium sulfate. The B23 value was found to be proportional to the slope of the lysozyme solubility against ovalbumin concentration and the correlation was explained by preferential interaction theory. © 2013 American Institute of Chemical Engineers.

Ethanol Concentration Influences the Mechanisms of Wine Tannin Interactions with Poly(L-proline) in Model Wine.

PubMed

McRae, Jacqui M; Ziora, Zyta M; Kassara, Stella; Cooper, Matthew A; Smith, Paul A

2015-05-06

Changes in ethanol concentration influence red wine astringency, and yet the effect of ethanol on wine tannin-salivary protein interactions is not well understood. Isothermal titration calorimetry (ITC) was used to measure the binding strength between the model salivary protein, poly(L-proline) (PLP) and a range of wine tannins (tannin fractions from a 3- and a 7-year old Cabernet Sauvignon wine) across different ethanol concentrations (5, 10, 15, and 40% v/v). Tannin-PLP interactions were stronger at 5% ethanol than at 40% ethanol. The mechanism of interaction changed for most tannin samples across the wine-like ethanol range (10-15%) from a combination of hydrophobic and hydrogen binding at 10% ethanol to only hydrogen binding at 15% ethanol. These results indicate that ethanol concentration can influence the mechanisms of wine tannin-protein interactions and that the previously reported decrease in wine astringency with increasing alcohol may, in part, relate to a decrease tannin-protein interaction strength.

Identification of Protein–Excipient Interaction Hotspots Using Computational Approaches

PubMed Central

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

2016-01-01

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

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

PubMed

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

2003-11-01

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

The conservation pattern of short linear motifs is highly correlated with the function of interacting protein domains.

PubMed

Ren, Siyuan; Yang, Guang; He, Youyu; Wang, Yiguo; Li, Yixue; Chen, Zhengjun

2008-10-01

Many well-represented domains recognize primary sequences usually less than 10 amino acids in length, called Short Linear Motifs (SLiMs). Accurate prediction of SLiMs has been difficult because they are short (often < 10 amino acids) and highly degenerate. In this study, we combined scoring matrixes derived from peptide library and conservation analysis to identify protein classes enriched of functional SLiMs recognized by SH2, SH3, PDZ and S/T kinase domains. Our combined approach revealed that SLiMs are highly conserved in proteins from functional classes that are known to interact with a specific domain, but that they are not conserved in most other protein groups. We found that SLiMs recognized by SH2 domains were highly conserved in receptor kinases/phosphatases, adaptor molecules, and tyrosine kinases/phosphatases, that SLiMs recognized by SH3 domains were highly conserved in cytoskeletal and cytoskeletal-associated proteins, that SLiMs recognized by PDZ domains were highly conserved in membrane proteins such as channels and receptors, and that SLiMs recognized by S/T kinase domains were highly conserved in adaptor molecules, S/T kinases/phosphatases, and proteins involved in transcription or cell cycle control. We studied Tyr-SLiMs recognized by SH2 domains in more detail, and found that SH2-recognized Tyr-SLiMs on the cytoplasmic side of membrane proteins are more highly conserved than those on the extra-cellular side. Also, we found that SH2-recognized Tyr-SLiMs that are associated with SH3 motifs and a tyrosine kinase phosphorylation motif are more highly conserved. The interactome of protein domains is reflected by the evolutionary conservation of SLiMs recognized by these domains. Combining scoring matrixes derived from peptide libraries and conservation analysis, we would be able to find those protein groups that are more likely to interact with specific domains.

The conservation pattern of short linear motifs is highly correlated with the function of interacting protein domains

PubMed Central

Ren, Siyuan; Yang, Guang; He, Youyu; Wang, Yiguo; Li, Yixue; Chen, Zhengjun

2008-01-01

Background Many well-represented domains recognize primary sequences usually less than 10 amino acids in length, called Short Linear Motifs (SLiMs). Accurate prediction of SLiMs has been difficult because they are short (often < 10 amino acids) and highly degenerate. In this study, we combined scoring matrixes derived from peptide library and conservation analysis to identify protein classes enriched of functional SLiMs recognized by SH2, SH3, PDZ and S/T kinase domains. Results Our combined approach revealed that SLiMs are highly conserved in proteins from functional classes that are known to interact with a specific domain, but that they are not conserved in most other protein groups. We found that SLiMs recognized by SH2 domains were highly conserved in receptor kinases/phosphatases, adaptor molecules, and tyrosine kinases/phosphatases, that SLiMs recognized by SH3 domains were highly conserved in cytoskeletal and cytoskeletal-associated proteins, that SLiMs recognized by PDZ domains were highly conserved in membrane proteins such as channels and receptors, and that SLiMs recognized by S/T kinase domains were highly conserved in adaptor molecules, S/T kinases/phosphatases, and proteins involved in transcription or cell cycle control. We studied Tyr-SLiMs recognized by SH2 domains in more detail, and found that SH2-recognized Tyr-SLiMs on the cytoplasmic side of membrane proteins are more highly conserved than those on the extra-cellular side. Also, we found that SH2-recognized Tyr-SLiMs that are associated with SH3 motifs and a tyrosine kinase phosphorylation motif are more highly conserved. Conclusion The interactome of protein domains is reflected by the evolutionary conservation of SLiMs recognized by these domains. Combining scoring matrixes derived from peptide libraries and conservation analysis, we would be able to find those protein groups that are more likely to interact with specific domains. PMID:18828911

Network-based prediction and knowledge mining of disease genes.

PubMed

Carson, Matthew B; Lu, Hui

2015-01-01

In recent years, high-throughput protein interaction identification methods have generated a large amount of data. When combined with the results from other in vivo and in vitro experiments, a complex set of relationships between biological molecules emerges. The growing popularity of network analysis and data mining has allowed researchers to recognize indirect connections between these molecules. Due to the interdependent nature of network entities, evaluating proteins in this context can reveal relationships that may not otherwise be evident. We examined the human protein interaction network as it relates to human illness using the Disease Ontology. After calculating several topological metrics, we trained an alternating decision tree (ADTree) classifier to identify disease-associated proteins. Using a bootstrapping method, we created a tree to highlight conserved characteristics shared by many of these proteins. Subsequently, we reviewed a set of non-disease-associated proteins that were misclassified by the algorithm with high confidence and searched for evidence of a disease relationship. Our classifier was able to predict disease-related genes with 79% area under the receiver operating characteristic (ROC) curve (AUC), which indicates the tradeoff between sensitivity and specificity and is a good predictor of how a classifier will perform on future data sets. We found that a combination of several network characteristics including degree centrality, disease neighbor ratio, eccentricity, and neighborhood connectivity help to distinguish between disease- and non-disease-related proteins. Furthermore, the ADTree allowed us to understand which combinations of strongly predictive attributes contributed most to protein-disease classification. In our post-processing evaluation, we found several examples of potential novel disease-related proteins and corresponding literature evidence. In addition, we showed that first- and second-order neighbors in the PPI network could be used to identify likely disease associations. We analyzed the human protein interaction network and its relationship to disease and found that both the number of interactions with other proteins and the disease relationship of neighboring proteins helped to determine whether a protein had a relationship to disease. Our classifier predicted many proteins with no annotated disease association to be disease-related, which indicated that these proteins have network characteristics that are similar to disease-related proteins and may therefore have disease associations not previously identified. By performing a post-processing step after the prediction, we were able to identify evidence in literature supporting this possibility. This method could provide a useful filter for experimentalists searching for new candidate protein targets for drug repositioning and could also be extended to include other network and data types in order to refine these predictions.

Interactions among the early Escherichia coli divisome proteins revealed by bimolecular fluorescence complementation.

PubMed

Pazos, Manuel; Natale, Paolo; Margolin, William; Vicente, Miguel

2013-12-01

We used bimolecular fluorescence complementation (BiFC) assays to detect protein-protein interactions of all possible pairs of the essential Escherichia coli proto-ring components, FtsZ, FtsA and ZipA, as well as the non-essential FtsZ-associated proteins ZapA and ZapB. We found an unexpected interaction between ZipA and ZapB at potential cell division sites, and when co-overproduced, they induced long narrow constrictions at division sites that were dependent on FtsZ. These assays also uncovered an interaction between ZipA and ZapA that was mediated by FtsZ. BiFC with ZapA and ZapB showed that in addition to their expected interaction at midcell, they also interact at the cell poles. BiFC detected interaction between FtsZ and ZapB at midcell and close to the poles. Results from the remaining pairwise combinations confirmed known interactions between FtsZ and ZipA, and ZapB with itself. © 2013 Society for Applied Microbiology and John Wiley & Sons Ltd.

Frontal affinity chromatography: A unique research tool for biospecific interaction that promotes glycobiology

PubMed Central

KASAI, Kenichi

2014-01-01

Combination of bioaffinity and chromatography gave birth to affinity chromatography. A further combination with frontal analysis resulted in creation of frontal affinity chromatography (FAC). This new versatile research tool enabled detailed analysis of weak interactions that play essential roles in living systems, especially those between complex saccharides and saccharide-binding proteins. FAC now becomes the best method for the investigation of saccharide-binding proteins (lectins) from viewpoints of sensitivity, accuracy, and efficiency, and is contributing greatly to the development of glycobiology. It opened a door leading to deeper understanding of the significance of saccharide recognition in life. The theory is also concisely described. PMID:25169774

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.

A fluorescent bimolecular complementation screen reveals MAF1, RNF7 and SETD3 as PCNA-associated proteins in human cells

PubMed Central

Cooper, Simon E; Hodimont, Elsie; Green, Catherine M

2015-01-01

The proliferating cell nuclear antigen (PCNA) is a conserved component of DNA replication factories, and interactions with PCNA mediate the recruitment of many essential DNA replication enzymes to these sites of DNA synthesis. A complete description of the structure and composition of these factories remains elusive, and a better knowledge of them will improve our understanding of how the maintenance of genome and epigenetic stability is achieved. To fully characterize the set of proteins that interact with PCNA we developed a bimolecular fluorescence complementation (BiFC) screen for PCNA-interactors in human cells. This 2-hybrid type screen for interactors from a human cDNA library is rapid and efficient. The fluorescent read-out for protein interaction enables facile selection of interacting clones, and we combined this with next generation sequencing to identify the cDNAs encoding the interacting proteins. This method was able to reproducibly identify previously characterized PCNA-interactors but importantly also identified RNF7, Maf1 and SetD3 as PCNA-interacting proteins. We validated these interactions by co-immunoprecipitation from human cell extracts and by interaction analyses using recombinant proteins. These results show that the BiFC screen is a valuable method for the identification of protein-protein interactions in living mammalian cells. This approach has potentially wide application as it is high throughput and readily automated. We suggest that, given this interaction with PCNA, Maf1, RNF7, and SetD3 are potentially involved in DNA replication, DNA repair, or associated processes. PMID:26030842

Signaling gateway molecule pages—a data model perspective

PubMed Central

Dinasarapu, Ashok Reddy; Saunders, Brian; Ozerlat, Iley; Azam, Kenan; Subramaniam, Shankar

2011-01-01

Summary: The Signaling Gateway Molecule Pages (SGMP) database provides highly structured data on proteins which exist in different functional states participating in signal transduction pathways. A molecule page starts with a state of a native protein, without any modification and/or interactions. New states are formed with every post-translational modification or interaction with one or more proteins, small molecules or class molecules and with each change in cellular location. State transitions are caused by a combination of one or more modifications, interactions and translocations which then might be associated with one or more biological processes. In a characterized biological state, a molecule can function as one of several entities or their combinations, including channel, receptor, enzyme, transcription factor and transporter. We have also exported SGMP data to the Biological Pathway Exchange (BioPAX) and Systems Biology Markup Language (SBML) as well as in our custom XML. Availability: SGMP is available at www.signaling-gateway.org/molecule. Contact: shankar@ucsd.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21505029

Comparison of Normal and Breast Cancer Cell lines using Proteome, Genome and Interactome data

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

Patwardhan, Anil J.; Strittmatter, Eric F.; Camp, David G.

2005-12-01

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of both protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled the confident identification of 2,235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multi-step search strategy was used to identify post-translational modifications and detected several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal andmore » cancer cell lines.« less

Sculpting proteins interactively: continual energy minimization embedded in a graphical modeling system.

PubMed

Surles, M C; Richardson, J S; Richardson, D C; Brooks, F P

1994-02-01

We describe a new paradigm for modeling proteins in interactive computer graphics systems--continual maintenance of a physically valid representation, combined with direct user control and visualization. This is achieved by a fast algorithm for energy minimization, capable of real-time performance on all atoms of a small protein, plus graphically specified user tugs. The modeling system, called Sculpt, rigidly constrains bond lengths, bond angles, and planar groups (similar to existing interactive modeling programs), while it applies elastic restraints to minimize the potential energy due to torsions, hydrogen bonds, and van der Waals and electrostatic interactions (similar to existing batch minimization programs), and user-specified springs. The graphical interface can show bad and/or favorable contacts, and individual energy terms can be turned on or off to determine their effects and interactions. Sculpt finds a local minimum of the total energy that satisfies all the constraints using an augmented Lagrange-multiplier method; calculation time increases only linearly with the number of atoms because the matrix of constraint gradients is sparse and banded. On a 100-MHz MIPS R4000 processor (Silicon Graphics Indigo), Sculpt achieves 11 updates per second on a 20-residue fragment and 2 updates per second on an 80-residue protein, using all atoms except non-H-bonding hydrogens, and without electrostatic interactions. Applications of Sculpt are described: to reverse the direction of bundle packing in a designed 4-helix bundle protein, to fold up a 2-stranded beta-ribbon into an approximate beta-barrel, and to design the sequence and conformation of a 30-residue peptide that mimics one partner of a protein subunit interaction. Computer models that are both interactive and physically realistic (within the limitations of a given force field) have 2 significant advantages: (1) they make feasible the modeling of very large changes (such as needed for de novo design), and (2) they help the user understand how different energy terms interact to stabilize a given conformation. The Sculpt paradigm combines many of the best features of interactive graphical modeling, energy minimization, and actual physical models, and we propose it as an especially productive way to use current and future increases in computer speed.

Toward a structure determination method for biomineral-associated protein using combined solid- state NMR and computational structure prediction.

PubMed

Masica, David L; Ash, Jason T; Ndao, Moise; Drobny, Gary P; Gray, Jeffrey J

2010-12-08

Protein-biomineral interactions are paramount to materials production in biology, including the mineral phase of hard tissue. Unfortunately, the structure of biomineral-associated proteins cannot be determined by X-ray crystallography or solution nuclear magnetic resonance (NMR). Here we report a method for determining the structure of biomineral-associated proteins. The method combines solid-state NMR (ssNMR) and ssNMR-biased computational structure prediction. In addition, the algorithm is able to identify lattice geometries most compatible with ssNMR constraints, representing a quantitative, novel method for investigating crystal-face binding specificity. We use this method to determine most of the structure of human salivary statherin interacting with the mineral phase of tooth enamel. Computation and experiment converge on an ensemble of related structures and identify preferential binding at three crystal surfaces. The work represents a significant advance toward determining structure of biomineral-adsorbed protein using experimentally biased structure prediction. This method is generally applicable to proteins that can be chemically synthesized. Copyright © 2010 Elsevier Ltd. All rights reserved.

Electrostatic Effects in Filamentous Protein Aggregation

PubMed Central

Buell, Alexander K.; Hung, Peter; Salvatella, Xavier; Welland, Mark E.; Dobson, Christopher M.; Knowles, Tuomas P.J.

2013-01-01

Electrostatic forces play a key role in mediating interactions between proteins. However, gaining quantitative insights into the complex effects of electrostatics on protein behavior has proved challenging, due to the wide palette of scenarios through which both cations and anions can interact with polypeptide molecules in a specific manner or can result in screening in solution. In this article, we have used a variety of biophysical methods to probe the steady-state kinetics of fibrillar protein self-assembly in a highly quantitative manner to detect how it is modulated by changes in solution ionic strength. Due to the exponential modulation of the reaction rate by electrostatic forces, this reaction represents an exquisitely sensitive probe of these effects in protein-protein interactions. Our approach, which involves a combination of experimental kinetic measurements and theoretical analysis, reveals a hierarchy of electrostatic effects that control protein aggregation. Furthermore, our results provide a highly sensitive method for the estimation of the magnitude of binding of a variety of ions to protein molecules. PMID:23473495

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

PubMed

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

2018-02-02

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

Click-MS: Tagless Protein Enrichment Using Bioorthogonal Chemistry for Quantitative Proteomics.

PubMed

Smits, Arne H; Borrmann, Annika; Roosjen, Mark; van Hest, Jan C M; Vermeulen, Michiel

2016-12-16

Epitope-tagging is an effective tool to facilitate protein enrichment from crude cell extracts. Traditionally, N- or C-terminal fused tags are employed, which, however, can perturb protein function. Unnatural amino acids (UAAs) harboring small reactive handles can be site-specifically incorporated into proteins, thus serving as a potential alternative for conventional protein tags. Here, we introduce Click-MS, which combines the power of site-specific UAA incorporation, bioorthogonal chemistry, and quantitative mass spectrometry-based proteomics to specifically enrich a single protein of interest from crude mammalian cell extracts. By genetic encoding of p-azido-l-phenylalanine, the protein of interest can be selectively captured using copper-free click chemistry. We use Click-MS to enrich proteins that function in different cellular compartments, and we identify protein-protein interactions, showing the great potential of Click-MS for interaction proteomics workflows.

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

PubMed

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

2014-06-24

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

A molecular modeling based method to predict elution behavior and binding patches of proteins in multimodal chromatography.

PubMed

Banerjee, Suvrajit; Parimal, Siddharth; Cramer, Steven M

2017-08-18

Multimodal (MM) chromatography provides a powerful means to enhance the selectivity of protein separations by taking advantage of multiple weak interactions that include electrostatic, hydrophobic and van der Waals interactions. In order to increase our understanding of such phenomena, a computationally efficient approach was developed that combines short molecular dynamics simulations and continuum solvent based coarse-grained free energy calculations in order to study the binding of proteins to Self Assembled Monolayers (SAM) presenting MM ligands. Using this method, the free energies of protein-MM SAM binding over a range of incident orientations of the protein can be determined. The resulting free energies were then examined to identify the more "strongly bound" orientations of different proteins with two multimodal surfaces. The overall free energy of protein-MM surface binding was then determined and correlated to retention factors from isocratic chromatography. This correlation, combined with analytical expressions from the literature, was then employed to predict protein gradient elution salt concentrations as well as selectivity reversals with different MM resin systems. Patches on protein surfaces that interacted strongly with MM surfaces were also identified by determining the frequency of heavy atom contacts with the atoms of the MM SAMs. A comparison of these patches to Electrostatic Potential and hydrophobicity maps indicated that while all of these patches contained significant positive charge, only the highest frequency sites also possessed hydrophobicity. The ability to identify key binding patches on proteins may have significant impact on process development for the separation of bioproduct related impurities. Copyright © 2017 Elsevier B.V. All rights reserved.

DockTrina: docking triangular protein trimers.

PubMed

Popov, Petr; Ritchie, David W; Grudinin, Sergei

2014-01-01

In spite of the abundance of oligomeric proteins within a cell, the structural characterization of protein-protein interactions is still a challenging task. In particular, many of these interactions involve heteromeric complexes, which are relatively difficult to determine experimentally. Hence there is growing interest in using computational techniques to model such complexes. However, assembling large heteromeric complexes computationally is a highly combinatorial problem. Nonetheless the problem can be simplified greatly by considering interactions between protein trimers. After dimers and monomers, triangular trimers (i.e. trimers with pair-wise contacts between all three pairs of proteins) are the most frequently observed quaternary structural motifs according to the three-dimensional (3D) complex database. This article presents DockTrina, a novel protein docking method for modeling the 3D structures of nonsymmetrical triangular trimers. The method takes as input pair-wise contact predictions from a rigid body docking program. It then scans and scores all possible combinations of pairs of monomers using a very fast root mean square deviation test. Finally, it ranks the predictions using a scoring function which combines triples of pair-wise contact terms and a geometric clash penalty term. The overall approach takes less than 2 min per complex on a modern desktop computer. The method is tested and validated using a benchmark set of 220 bound and seven unbound protein trimer structures. DockTrina will be made available at http://nano-d.inrialpes.fr/software/docktrina. Copyright © 2013 Wiley Periodicals, Inc.

Emory University: MEDICI (Mining Essentiality Data to Identify Critical Interactions) for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has developed a computational methodology to combine high-throughput knockdown data with known protein network topologies to infer the importance of protein-protein interactions (PPIs) for the survival of cancer cells.  Applying these data to the Achilles shRNA results, the CCLE cell line characterizations, and known and newly identified PPIs provides novel insights for potential new drug targets for cancer therapies and identifies important PPI hubs.

A mass spectrometry-based proteomic analysis of Homer2-interacting proteins in the mouse brain.

PubMed

Goulding, Scott P; Szumlinski, Karen K; Contet, Candice; MacCoss, Michael J; Wu, Christine C

2017-08-23

In the brain, the Homer protein family modulates excitatory signal transduction and receptor plasticity through interactions with other proteins in dendritic spines. Homer proteins are implicated in a variety of psychiatric disorders such as schizophrenia and addiction. Since long Homers serve as scaffolding proteins, identifying their interacting partners is an important first step in understanding their biological function and could help to guide the design of new therapeutic strategies. The present study set out to document Homer2-interacting proteins in the mouse brain using a co-immunoprecipitation-based mass spectrometry approach where Homer2 knockout samples were used to filter out non-specific interactors. We found that in the mouse brain, Homer2 interacts with a limited subset of its previously reported interacting partners (3 out of 31). Importantly, we detected an additional 15 novel Homer2-interacting proteins, most of which are part of the N-methyl-D-aspartate receptor signaling pathway. These results corroborate the central role Homer2 plays in glutamatergic transmission and expand the network of proteins potentially contributing to the behavioral abnormalities associated with altered Homer2 expression. Long Homer proteins are scaffolding proteins that regulate signal transduction in neurons. Identifying their interacting partners is key to understanding their function. We used co-immunoprecipitation in combination with mass spectrometry to establish the first comprehensive list of Homer2-interacting partners in the mouse brain. The specificity of interactions was evaluated using Homer2 knockout brain tissue as a negative control. The set of proteins that we identified minimally overlaps with previously reported interacting partners of Homer2; however, we identified novel interactors that are part of a signaling cascade activated by glutamatergic transmission, which improves our mechanistic understanding of the role of Homer2 in behavior. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Binding Mechanisms of Intrinsically Disordered Proteins: Theory, Simulation, and Experiment

PubMed Central

Mollica, Luca; Bessa, Luiza M.; Hanoulle, Xavier; Jensen, Malene Ringkjøbing; Blackledge, Martin; Schneider, Robert

2016-01-01

In recent years, protein science has been revolutionized by the discovery of intrinsically disordered proteins (IDPs). In contrast to the classical paradigm that a given protein sequence corresponds to a defined structure and an associated function, we now know that proteins can be functional in the absence of a stable three-dimensional structure. In many cases, disordered proteins or protein regions become structured, at least locally, upon interacting with their physiological partners. Many, sometimes conflicting, hypotheses have been put forward regarding the interaction mechanisms of IDPs and the potential advantages of disorder for protein-protein interactions. Whether disorder may increase, as proposed, e.g., in the “fly-casting” hypothesis, or decrease binding rates, increase or decrease binding specificity, or what role pre-formed structure might play in interactions involving IDPs (conformational selection vs. induced fit), are subjects of intense debate. Experimentally, these questions remain difficult to address. Here, we review experimental studies of binding mechanisms of IDPs using NMR spectroscopy and transient kinetic techniques, as well as the underlying theoretical concepts and numerical methods that can be applied to describe these interactions at the atomic level. The available literature suggests that the kinetic and thermodynamic parameters characterizing interactions involving IDPs can vary widely and that there may be no single common mechanism that can explain the different binding modes observed experimentally. Rather, disordered proteins appear to make combined use of features such as pre-formed structure and flexibility, depending on the individual system and the functional context. PMID:27668217

Heterodimerization of Msx and Dlx homeoproteins results in functional antagonism.

PubMed

Zhang, H; Hu, G; Wang, H; Sciavolino, P; Iler, N; Shen, M M; Abate-Shen, C

1997-05-01

Protein-protein interactions are known to be essential for specifying the transcriptional activities of homeoproteins. Here we show that representative members of the Msx and Dlx homeoprotein families form homo- and heterodimeric complexes. We demonstrate that dimerization by Msx and Dlx proteins is mediated through their homeodomains and that the residues required for this interaction correspond to those necessary for DNA binding. Unlike most other known examples of homeoprotein interactions, association of Msx and Dlx proteins does not promote cooperative DNA binding; instead, dimerization and DNA binding are mutually exclusive activities. In particular, we show that Msx and Dlx proteins interact independently and noncooperatively with homeodomain DNA binding sites and that dimerization is specifically blocked by the presence of such DNA sites. We further demonstrate that the transcriptional properties of Msx and Dlx proteins display reciprocal inhibition. Specifically, Msx proteins act as transcriptional repressors and Dlx proteins act as activators, while in combination, Msx and Dlx proteins counteract each other's transcriptional activities. Finally, we show that the expression patterns of representative Msx and Dlx genes (Msx1, Msx2, Dlx2, and Dlx5) overlap in mouse embryogenesis during limb bud and craniofacial development, consistent with the potential for their protein products to interact in vivo. Based on these observations, we propose that functional antagonism through heterodimer formation provides a mechanism for regulating the transcriptional actions of Msx and Dlx homeoproteins in vivo.

Pharmacological targeting of the transcription factor SOX18 delays breast cancer in mice.

PubMed

Overman, Jeroen; Fontaine, Frank; Moustaqil, Mehdi; Mittal, Deepak; Sierecki, Emma; Sacilotto, Natalia; Zuegg, Johannes; Robertson, Avril Ab; Holmes, Kelly; Salim, Angela A; Mamidyala, Sreeman; Butler, Mark S; Robinson, Ashley S; Lesieur, Emmanuelle; Johnston, Wayne; Alexandrov, Kirill; Black, Brian L; Hogan, Benjamin M; De Val, Sarah; Capon, Robert J; Carroll, Jason S; Bailey, Timothy L; Koopman, Peter; Jauch, Ralf; Smyth, Mark J; Cooper, Matthew A; Gambin, Yann; Francois, Mathias

2017-01-31

Pharmacological targeting of transcription factors holds great promise for the development of new therapeutics, but strategies based on blockade of DNA binding, nuclear shuttling, or individual protein partner recruitment have yielded limited success to date. Transcription factors typically engage in complex interaction networks, likely masking the effects of specifically inhibiting single protein-protein interactions. Here, we used a combination of genomic, proteomic and biophysical methods to discover a suite of protein-protein interactions involving the SOX18 transcription factor, a known regulator of vascular development and disease. We describe a small-molecule that is able to disrupt a discrete subset of SOX18-dependent interactions. This compound selectively suppressed SOX18 transcriptional outputs in vitro and interfered with vascular development in zebrafish larvae. In a mouse pre-clinical model of breast cancer, treatment with this inhibitor significantly improved survival by reducing tumour vascular density and metastatic spread. Our studies validate an interactome-based molecular strategy to interfere with transcription factor activity, for the development of novel disease therapeutics.

Synaptic activity induces input-specific rearrangements in a targeted synaptic protein interaction network.

PubMed

Lautz, Jonathan D; Brown, Emily A; VanSchoiack, Alison A Williams; Smith, Stephen E P

2018-05-27

Cells utilize dynamic, network level rearrangements in highly interconnected protein interaction networks to transmit and integrate information from distinct signaling inputs. Despite the importance of protein interaction network dynamics, the organizational logic underlying information flow through these networks is not well understood. Previously, we developed the quantitative multiplex co-immunoprecipitation platform, which allows for the simultaneous and quantitative measurement of the amount of co-association between large numbers of proteins in shared complexes. Here, we adapt quantitative multiplex co-immunoprecipitation to define the activity dependent dynamics of an 18-member protein interaction network in order to better understand the underlying principles governing glutamatergic signal transduction. We first establish that immunoprecipitation detected by flow cytometry can detect activity dependent changes in two known protein-protein interactions (Homer1-mGluR5 and PSD-95-SynGAP). We next demonstrate that neuronal stimulation elicits a coordinated change in our targeted protein interaction network, characterized by the initial dissociation of Homer1 and SynGAP-containing complexes followed by increased associations among glutamate receptors and PSD-95. Finally, we show that stimulation of distinct glutamate receptor types results in different modular sets of protein interaction network rearrangements, and that cells activate both modules in order to integrate complex inputs. This analysis demonstrates that cells respond to distinct types of glutamatergic input by modulating different combinations of protein co-associations among a targeted network of proteins. Our data support a model of synaptic plasticity in which synaptic stimulation elicits dissociation of preexisting multiprotein complexes, opening binding slots in scaffold proteins and allowing for the recruitment of additional glutamatergic receptors. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Rosetta stone method for detecting protein function and protein-protein interactions from genome sequences

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Pellegrini, Matteo; Thompson, Michael J.; Yeates, Todd O.

2002-10-15

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

Hybrid In Silico/In Vitro Approaches for the Identification of Functional Cholesterol-Binding Domains in Membrane Proteins.

PubMed

Di Scala, Coralie; Fantini, Jacques

2017-01-01

In eukaryotic cells, cholesterol is an important regulator of a broad range of membrane proteins, including receptors, transporters, and ion channels. Understanding how cholesterol interacts with membrane proteins is a difficult task because structural data of these proteins complexed with cholesterol are scarce. Here, we describe a dual approach based on in silico studies of protein-cholesterol interactions, combined with physico-chemical measurements of protein insertion into cholesterol-containing monolayers. Our algorithm is validated through careful analysis of the effect of key mutations within and outside the predicted cholesterol-binding site. Our method is illustrated by a complete analysis of cholesterol-binding to Alzheimer's β-amyloid peptide, a protein that penetrates the plasma membrane of brain cells through a cholesterol-dependent process.

Ectromelia virus encodes a novel family of F-box proteins that interact with the SCF complex.

PubMed

van Buuren, Nick; Couturier, Brianne; Xiong, Yue; Barry, Michele

2008-10-01

Poxviruses are notorious for encoding multiple proteins that regulate cellular signaling pathways, including the ubiquitin-proteasome system. Bioinformatics indicated that ectromelia virus, the causative agent of lethal mousepox, encoded four proteins, EVM002, EVM005, EVM154, and EVM165, containing putative F-box domains. In contrast to cellular F-box proteins, the ectromelia virus proteins contain C-terminal F-box domains in conjunction with N-terminal ankyrin repeats, a combination that has not been previously reported for cellular proteins. These observations suggested that the ectromelia virus F-box proteins interact with SCF (Skp1, cullin-1, and F-box) ubiquitin ligases. We focused our studies on EVM005, since this protein had only one ortholog in cowpox virus. Using mass spectrometry, we identified cullin-1 as a binding partner for EVM005, and this interaction was confirmed by overexpression of hemagglutinin (HA)-cullin-1. During infection, Flag-EVM005 and HA-cullin-1 colocalized to distinct cellular bodies. Significantly, EVM005 coprecipitated with endogenous Skp1, cullin-1, and Roc1 and associated with conjugated ubiquitin, suggesting that EVM005 interacted with the components of a functional ubiquitin ligase. Interaction of EVM005 with cullin-1 and Skp1 was abolished upon deletion of the F-box, indicating that the F-box played a crucial role in interaction with the SCF complex. Additionally, EVM002 and EVM154 interacted with Skp1 and conjugated ubiquitin, suggesting that ectromelia virus encodes multiple F-box-containing proteins that regulate the SCF complex. Our results indicate that ectromelia virus has evolved multiple proteins that interact with the SCF complex.

SIRIUS. An automated method for the analysis of the preferred packing arrangements between protein groups.

PubMed

Singh, J; Thornton, J M

1990-02-05

Automated methods have been developed to determine the preferred packing arrangement between interacting protein groups. A suite of FORTRAN programs, SIRIUS, is described for calculating and analysing the geometries of interacting protein groups using crystallographically derived atomic co-ordinates. The programs involved in calculating the geometries search for interacting pairs of protein groups using a distance criterion, and then calculate the spatial disposition and orientation of the pair. The second set of programs is devoted to analysis. This involves calculating the observed and expected distributions of the angles and assessing the statistical significance of the difference between the two. A database of the geometries of the 400 combinations of side-chain to side-chain interaction has been created. The approach used in analysing the geometrical information is illustrated here with specific examples of interactions between side-chains, peptide groups and particular types of atom. At the side-chain level, an analysis of aromatic-amino interactions, and the interactions of peptide carbonyl groups with arginine residues is presented. At the atomic level the analyses include the spatial disposition of oxygen atoms around tyrosine residues, and the frequency and type of contact between carbon, nitrogen and oxygen atoms. This information is currently being applied to the modelling of protein interactions.

Protein–Protein Interactions in Dilute to Concentrated Solutions: α-Chymotrypsinogen in Acidic Conditions

PubMed Central

2015-01-01

Protein–protein interactions were investigated for α-chymotrypsinogen by static and dynamic light scattering (SLS and DLS, respectively), as well as small-angle neutron scattering (SANS), as a function of protein and salt concentration at acidic conditions. Net protein–protein interactions were probed via the Kirkwood–Buff integral G22 and the static structure factor S(q) from SLS and SANS data. G22 was obtained by regressing the Rayleigh ratio versus protein concentration with a local Taylor series approach, which does not require one to assume the underlying form or nature of intermolecular interactions. In addition, G22 and S(q) were further analyzed by traditional methods involving fits to effective interaction potentials. Although the fitted model parameters were not always physically realistic, the numerical values for G22 and S(q → 0) were in good agreement from SLS and SANS as a function of protein concentration. In the dilute regime, fitted G22 values agreed with those obtained via the osmotic second virial coefficient B22 and showed that electrostatic interactions are the dominant contribution for colloidal interactions in α-chymotrypsinogen solutions. However, as protein concentration increases, the strength of protein–protein interactions decreases, with a more pronounced decrease at low salt concentrations. The results are consistent with an effective “crowding” or excluded volume contribution to G22 due to the long-ranged electrostatic repulsions that are prominent even at the moderate range of protein concentrations used here (<40 g/L). These apparent crowding effects were confirmed and quantified by assessing the hydrodynamic factor H(q → 0), which is obtained by combining measurements of the collective diffusion coefficient from DLS data with measurements of S(q → 0). H(q → 0) was significantly less than that for a corresponding hard-sphere system and showed that hydrodynamic nonidealities can lead to qualitatively incorrect conclusions regarding B22, G22, and static protein–protein interactions if one uses only DLS to assess protein interactions. PMID:24810917

BIOPS Interactive: An e-Learning Platform Focused on Protein Structure and DNA

ERIC Educational Resources Information Center

Pontelli, Enrico; Pinto, Jorge; Qin, Xiaoxiao; He, Jing; Bevan, David; MacCuish, Norah; MacCuish, John; Chapman, Mitch; Moreland, David

2009-01-01

One of the difficulties in teaching basic molecular biology concepts to the students with little biological background is the lack of hands-on exercises that combines the challenges of the concepts with visualization and immediate feedback. BIOPS Interactive is a web-based interactive learning environment for molecular biology that complements…

Accurate determination of interfacial protein secondary structure by combining interfacial-sensitive amide I and amide III spectral signals.

PubMed

Ye, Shuji; Li, Hongchun; Yang, Weilai; Luo, Yi

2014-01-29

Accurate determination of protein structures at the interface is essential to understand the nature of interfacial protein interactions, but it can only be done with a few, very limited experimental methods. Here, we demonstrate for the first time that sum frequency generation vibrational spectroscopy can unambiguously differentiate the interfacial protein secondary structures by combining surface-sensitive amide I and amide III spectral signals. This combination offers a powerful tool to directly distinguish random-coil (disordered) and α-helical structures in proteins. From a systematic study on the interactions between several antimicrobial peptides (including LKα14, mastoparan X, cecropin P1, melittin, and pardaxin) and lipid bilayers, it is found that the spectral profiles of the random-coil and α-helical structures are well separated in the amide III spectra, appearing below and above 1260 cm(-1), respectively. For the peptides with a straight backbone chain, the strength ratio for the peaks of the random-coil and α-helical structures shows a distinct linear relationship with the fraction of the disordered structure deduced from independent NMR experiments reported in the literature. It is revealed that increasing the fraction of negatively charged lipids can induce a conformational change of pardaxin from random-coil to α-helical structures. This experimental protocol can be employed for determining the interfacial protein secondary structures and dynamics in situ and in real time without extraneous labels.

Probing the Complex Architecture of Multimodular Carbohydrate-Active Enzymes Using a Combination of Small Angle X-Ray Scattering and X-Ray Crystallography.

PubMed

Czjzek, Mirjam; Ficko-Blean, Elizabeth

2017-01-01

The various modules in multimodular carbohydrate-active enzymes (CAZymes) may function in catalysis, carbohydrate binding, protein-protein interactions or as linkers. Here, we describe how combining the biophysical techniques of Small Angle X-ray Scattering (SAXS) and macromolecular X-ray crystallography (XRC) provides a powerful tool for examination into questions related to overall structural organization of ultra multimodular CAZymes.

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.

DNA-mediated engineering of multicomponent enzyme crystals

PubMed Central

Brodin, Jeffrey D.; Auyeung, Evelyn; Mirkin, Chad A.

2015-01-01

The ability to predictably control the coassembly of multiple nanoscale building blocks, especially those with disparate chemical and physical properties such as biomolecules and inorganic nanoparticles, has far-reaching implications in catalysis, sensing, and photonics, but a generalizable strategy for engineering specific contacts between these particles is an outstanding challenge. This is especially true in the case of proteins, where the types of possible interparticle interactions are numerous, diverse, and complex. Herein, we explore the concept of trading protein–protein interactions for DNA–DNA interactions to direct the assembly of two nucleic-acid–functionalized proteins with distinct surface chemistries into six unique lattices composed of catalytically active proteins, or of a combination of proteins and DNA-modified gold nanoparticles. The programmable nature of DNA–DNA interactions used in this strategy allows us to control the lattice symmetries and unit cell constants, as well as the compositions and habit, of the resulting crystals. This study provides a potentially generalizable strategy for constructing a unique class of materials that take advantage of the diverse morphologies, surface chemistries, and functionalities of proteins for assembling functional crystalline materials. PMID:25831510

Hydrogen Bond Networks and Hydrophobic Effects in the Amyloid β30-35 Chain in Water: A Molecular Dynamics Study.

PubMed

Jong, KwangHyok; Grisanti, Luca; Hassanali, Ali

2017-07-24

We have studied the conformational landscape of the C-terminal fragment of the amyloid protein Aβ 30-35 in water using well-tempered metadynamics simulations and found that it resembles an intrinsically disordered protein. The conformational fluctuations of the protein are facilitated by a collective reorganization of both protein and water hydrogen bond networks, combined with electrostatic interactions between termini as well as hydrophobic interactions of the side chains. The stabilization of hydrophobic interactions in one of the conformers involves a collective collapse of the side chains along with a squeeze-out of water sandwiched between them. The charged N- and C-termini play a critical role in stabilizing different types of protein conformations, including those involving contact-ion salt bridges as well as solvent-mediated interactions of the termini and the amide backbone. We have examined this by probing the distribution of directed water wires forming the hydrogen bond network enveloping the polypeptide. Water wires and their fluctuations form an integral part of structural signature of the protein conformation.

DNA-mediated engineering of multicomponent enzyme crystals

DOE PAGES

Brodin, Jeffrey D.; Auyeung, Evelyn; Mirkin, Chad A.

2015-03-23

The ability to predictably control the coassembly of multiple nanoscale building blocks, especially those with disparate chemical and physical properties such as biomolecules and inorganic nanoparticles, has far-reaching implications in catalysis, sensing, and photonics, but a generalizable strategy for engineering specific contacts between these particles is an outstanding challenge. This is especially true in the case of proteins, where the types of possible interparticle interactions are numerous, diverse, and complex. In this paper, we explore the concept of trading protein–protein interactions for DNA–DNA interactions to direct the assembly of two nucleic-acid–functionalized proteins with distinct surface chemistries into six unique latticesmore » composed of catalytically active proteins, or of a combination of proteins and DNA-modified gold nanoparticles. The programmable nature of DNA–DNA interactions used in this strategy allows us to control the lattice symmetries and unit cell constants, as well as the compositions and habit, of the resulting crystals. Finally, this study provides a potentially generalizable strategy for constructing a unique class of materials that take advantage of the diverse morphologies, surface chemistries, and functionalities of proteins for assembling functional crystalline materials.« less

Intrinsically-disordered N-termini in human parechovirus 1 capsid proteins bind encapsidated RNA.

PubMed

Shakeel, Shabih; Evans, James D; Hazelbaker, Mark; Kao, C Cheng; Vaughan, Robert C; Butcher, Sarah J

2018-04-11

Human parechoviruses (HPeV) are picornaviruses with a highly-ordered RNA genome contained within icosahedrally-symmetric capsids. Ordered RNA structures have recently been shown to interact with capsid proteins VP1 and VP3 and facilitate virus assembly in HPeV1. Using an assay that combines reversible cross-linking, RNA affinity purification and peptide mass fingerprinting (RCAP), we mapped the RNA-interacting regions of the capsid proteins from the whole HPeV1 virion in solution. The intrinsically-disordered N-termini of capsid proteins VP1 and VP3, and unexpectedly, VP0, were identified to interact with RNA. Comparing these results to those obtained using recombinantly-expressed VP0 and VP1 confirmed the virion binding regions, and revealed unique RNA binding regions in the isolated VP0 not previously observed in the crystal structure of HPeV1. We used RNA fluorescence anisotropy to confirm the RNA-binding competency of each of the capsid proteins' N-termini. These findings suggests that dynamic interactions between the viral RNA and the capsid proteins modulate virus assembly, and suggest a novel role for VP0.

Expansion of Protein Farnesyltransferase Specificity Using “Tunable” Active Site Interactions

PubMed Central

Hougland, James L.; Gangopadhyay, Soumyashree A.; Fierke, Carol A.

2012-01-01

Post-translational modifications play essential roles in regulating protein structure and function. Protein farnesyltransferase (FTase) catalyzes the biologically relevant lipidation of up to several hundred cellular proteins. Site-directed mutagenesis of FTase coupled with peptide selectivity measurements demonstrates that molecular recognition is determined by a combination of multiple interactions. Targeted randomization of these interactions yields FTase variants with altered and, in some cases, bio-orthogonal selectivity. We demonstrate that FTase specificity can be “tuned” using a small number of active site contacts that play essential roles in discriminating against non-substrates in the wild-type enzyme. This tunable selectivity extends in vivo, with FTase variants enabling the creation of bioengineered parallel prenylation pathways with altered substrate selectivity within a cell. Engineered FTase variants provide a novel avenue for probing both the selectivity of prenylation pathway enzymes and the effects of prenylation pathway modifications on the cellular function of a protein. PMID:22992747

SPR and electrochemical analyses of interactions between CYP3A4 or 3A5 and cytochrome b5

NASA Astrophysics Data System (ADS)

Gnedenko, O. V.; Yablokov, E. O.; Usanov, S. A.; Mukha, D. V.; Sergeev, G. V.; Bulko, T. V.; Kuzikov, A. V.; Moskaleva, N. E.; Shumyantseva, V. V.; Ivanov, A. S.; Archakov, A. I.

2014-02-01

The combination of SPR biosensor with electrochemical analysis was used for the study of protein-protein interaction between cytochromes CYP3A4 or 3А5 and cytochromes b5: the microsomal, mitochondrial forms of this protein, and 2 ≪chimeric≫ proteins. Kinetic constants of CYP3A4 and CYP3А5 complex formation with cytochromes b5 were determined by the SPR biosensor. Essential distinction between CYP3A4 and CYP3A5 was observed upon their interactions with mitochondrial cytochrome b5. The electrochemical analysis of CYP3A4, CYP3A5, and cytochromes b5 immobilized on screen printed graphite electrodes modified with membranous matrix revealed that these proteins have very close reduction potentials -0.435 to -0.350 V (vs. Ag/AgCl).

Virtual screening using combinatorial cyclic peptide libraries reveals protein interfaces readily targetable by cyclic peptides.

PubMed

Duffy, Fergal J; O'Donovan, Darragh; Devocelle, Marc; Moran, Niamh; O'Connell, David J; Shields, Denis C

2015-03-23

Protein-protein and protein-peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein-protein and protein-peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein-protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical "hot spot" interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.

Comparative analysis of Leishmania exoproteomes: implication for host-pathogen interactions.

PubMed

Peysselon, Franck; Launay, Guillaume; Lisacek, Frédérique; Duclos, Bertrand; Ricard-Blum, Sylvie

2013-12-01

Leishmaniasis is a vector-borne disease caused by the protozoa Leishmania. We have analyzed and compared the sequences of three experimental exoproteomes of Leishmania promastigotes from different species to determine their specific features and to identify new candidate proteins involved in interactions of Leishmania with the host. The exoproteomes differ from the proteomes by a decrease in the average molecular weight per protein, in disordered amino acid residues and in basic proteins. The exoproteome of the visceral species is significantly enriched in sites predicted to be phosphorylated as well as in features frequently associated with molecular interactions (intrinsic disorder, number of disordered binding regions per protein, interaction and/or trafficking motifs) compared to the other species. The visceral species might thus have a larger interaction repertoire with the host than the other species. Less than 10% of the exoproteomes contain heparin-binding and RGD sequences, and ~30% the host targeting signal RXLXE/D/Q. These latter proteins might thus be exported inside the host cell during the intracellular stage of the infection. Furthermore we have identified nine protein families conserved in the three exoproteomes with specific combinations of Pfam domains and selected eleven proteins containing at least three interaction and/or trafficking motifs including two splicing factors, phosphomannomutase, 2,3-bisphosphoglycerate-independent phosphoglycerate mutase, the paraflagellar rod protein-1D and a putative helicase. Their role in host-Leishmania interactions warrants further investigation but the putative ATP-dependent DEAD/H RNA helicase, which contains numerous interaction motifs, a host targeting signal and two disordered regions, is a very promising candidate. © 2013.

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

PubMed

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

2017-04-12

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

Wetting of nonconserved residue-backbones: A feature indicative of aggregation associated regions of proteins.

PubMed

Pradhan, Mohan R; Pal, Arumay; Hu, Zhongqiao; Kannan, Srinivasaraghavan; Chee Keong, Kwoh; Lane, David P; Verma, Chandra S

2016-02-01

Aggregation is an irreversible form of protein complexation and often toxic to cells. The process entails partial or major unfolding that is largely driven by hydration. We model the role of hydration in aggregation using "Dehydrons." "Dehydrons" are unsatisfied backbone hydrogen bonds in proteins that seek shielding from water molecules by associating with ligands or proteins. We find that the residues at aggregation interfaces have hydrated backbones, and in contrast to other forms of protein-protein interactions, are under less evolutionary pressure to be conserved. Combining evolutionary conservation of residues and extent of backbone hydration allows us to distinguish regions on proteins associated with aggregation (non-conserved dehydron-residues) from other interaction interfaces (conserved dehydron-residues). This novel feature can complement the existing strategies used to investigate protein aggregation/complexation. © 2015 Wiley Periodicals, Inc.

Functional Interaction Map of Lyssavirus Phosphoprotein: Identification of the Minimal Transcription Domains

PubMed Central

Jacob, Yves; Real, Eléonore; Tordo, Noël

2001-01-01

Lyssaviruses, the causative agents of rabies encephalitis, are distributed in seven genotypes. The phylogenetically distant rabies virus (PV strain, genotype 1) and Mokola virus (genotype 3) were used to develop a strategy to identify functional homologous interactive domains from two proteins (P and N) which participate in the viral ribonucleoprotein (RNP) transcription-replication complex. This strategy combined two-hybrid and green fluorescent protein–reverse two-hybrid assays in Saccharomyces cerevisiae to analyze protein-protein interactions and a reverse genetic assay in mammalian cells to study the transcriptional activity of the reconstituted RNP complex. Lyssavirus P proteins contain two N-binding domains (N-BDs), a strong one encompassing amino acid (aa) 176 to the C terminus and a weak one in the 189 N-terminal aa. The N-terminal portion of P (aa 52 to 189) also contains a homomultimerization site. Here we demonstrate that N-P interactions, although weaker, are maintained between proteins of the different genotypes. A minimal transcriptional module of the P protein was obtained by fusing the first 60 N-terminal aa containing the L protein binding site to the C-terminal strong N-BD. Random mutation of the strong N-BD on P protein identified three highly conserved K residues crucial for N-P interaction. Their mutagenesis in full-length P induced a transcriptionally defective RNP. The analysis of homologous interactive domains presented here and previously reported dissections of the P protein allowed us to propose a model of the functional interaction network of the lyssavirus P protein. This model underscores the central role of P at the interface between L protein and N-RNA template. PMID:11559793

The effect of the protein corona on the interaction between nanoparticles and lipid bilayers.

PubMed

Di Silvio, Desirè; Maccarini, Marco; Parker, Roger; Mackie, Alan; Fragneto, Giovanna; Baldelli Bombelli, Francesca

2017-10-15

It is known that nanoparticles (NPs) in a biological fluid are immediately coated by a protein corona (PC), composed of a hard (strongly bounded) and a soft (loosely associated) layers, which represents the real nano-interface interacting with the cellular membrane in vivo. In this regard, supported lipid bilayers (SLB) have extensively been used as relevant model systems for elucidating the interaction between biomembranes and NPs. Herein we show how the presence of a PC on the NP surface changes the interaction between NPs and lipid bilayers with particular care on the effects induced by the NPs on the bilayer structure. In the present work we combined Quartz Crystal Microbalance with Dissipation Monitoring (QCM-D) and Neutron Reflectometry (NR) experimental techniques to elucidate how the NP-membrane interaction is modulated by the presence of proteins in the environment and their effect on the lipid bilayer. Our study showed that the NP-membrane interaction is significantly affected by the presence of proteins and in particular we observed an important role of the soft corona in this phenomenon. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

Podder, Avijit; Jatana, Nidhi; Latha, N

2014-09-21

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

In Vitro Identification of Histatin 5 Salivary Complexes

PubMed Central

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

2015-01-01

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

Prioritization of orphan disease-causing genes using topological feature and GO similarity between proteins in interaction networks.

PubMed

Li, Min; Li, Qi; Ganegoda, Gamage Upeksha; Wang, JianXin; Wu, FangXiang; Pan, Yi

2014-11-01

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease studies. However, it is still time-consuming and laborious to determine the real disease-causing genes by biological experiments. With the advances of the high-throughput techniques, a large number of protein-protein interactions have been produced. Therefore, to address this issue, several methods based on protein interaction network have been proposed. In this paper, we propose a shortest path-based algorithm, named SPranker, to prioritize disease-causing genes in protein interaction networks. Considering the fact that diseases with similar phenotypes are generally caused by functionally related genes, we further propose an improved algorithm SPGOranker by integrating the semantic similarity of GO annotations. SPGOranker not only considers the topological similarity between protein pairs in a protein interaction network but also takes their functional similarity into account. The proposed algorithms SPranker and SPGOranker were applied to 1598 known orphan disease-causing genes from 172 orphan diseases and compared with three state-of-the-art approaches, ICN, VS and RWR. The experimental results show that SPranker and SPGOranker outperform ICN, VS, and RWR for the prioritization of orphan disease-causing genes. Importantly, for the case study of severe combined immunodeficiency, SPranker and SPGOranker predict several novel causal genes.

Large-scale protein-protein interactions detection by integrating big biosensing data with computational model.

PubMed

You, Zhu-Hong; Li, Shuai; Gao, Xin; Luo, Xin; Ji, Zhen

2014-01-01

Protein-protein interactions are the basis of biological functions, and studying these interactions on a molecular level is of crucial importance for understanding the functionality of a living cell. During the past decade, biosensors have emerged as an important tool for the high-throughput identification of proteins and their interactions. However, the high-throughput experimental methods for identifying PPIs are both time-consuming and expensive. On the other hand, high-throughput PPI data are often associated with high false-positive and high false-negative rates. Targeting at these problems, we propose a method for PPI detection by integrating biosensor-based PPI data with a novel computational model. This method was developed based on the algorithm of extreme learning machine combined with a novel representation of protein sequence descriptor. When performed on the large-scale human protein interaction dataset, the proposed method achieved 84.8% prediction accuracy with 84.08% sensitivity at the specificity of 85.53%. We conducted more extensive experiments to compare the proposed method with the state-of-the-art techniques, support vector machine. The achieved results demonstrate that our approach is very promising for detecting new PPIs, and it can be a helpful supplement for biosensor-based PPI data detection.

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model*

PubMed Central

Sjöholm, Kristoffer; Kilsgård, Ola; Teleman, Johan; Happonen, Lotta; Malmström, Lars; Malmström, Johan

2017-01-01

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions. PMID:28183813

Network-based prediction and knowledge mining of disease genes

PubMed Central

2015-01-01

Background In recent years, high-throughput protein interaction identification methods have generated a large amount of data. When combined with the results from other in vivo and in vitro experiments, a complex set of relationships between biological molecules emerges. The growing popularity of network analysis and data mining has allowed researchers to recognize indirect connections between these molecules. Due to the interdependent nature of network entities, evaluating proteins in this context can reveal relationships that may not otherwise be evident. Methods We examined the human protein interaction network as it relates to human illness using the Disease Ontology. After calculating several topological metrics, we trained an alternating decision tree (ADTree) classifier to identify disease-associated proteins. Using a bootstrapping method, we created a tree to highlight conserved characteristics shared by many of these proteins. Subsequently, we reviewed a set of non-disease-associated proteins that were misclassified by the algorithm with high confidence and searched for evidence of a disease relationship. Results Our classifier was able to predict disease-related genes with 79% area under the receiver operating characteristic (ROC) curve (AUC), which indicates the tradeoff between sensitivity and specificity and is a good predictor of how a classifier will perform on future data sets. We found that a combination of several network characteristics including degree centrality, disease neighbor ratio, eccentricity, and neighborhood connectivity help to distinguish between disease- and non-disease-related proteins. Furthermore, the ADTree allowed us to understand which combinations of strongly predictive attributes contributed most to protein-disease classification. In our post-processing evaluation, we found several examples of potential novel disease-related proteins and corresponding literature evidence. In addition, we showed that first- and second-order neighbors in the PPI network could be used to identify likely disease associations. Conclusions We analyzed the human protein interaction network and its relationship to disease and found that both the number of interactions with other proteins and the disease relationship of neighboring proteins helped to determine whether a protein had a relationship to disease. Our classifier predicted many proteins with no annotated disease association to be disease-related, which indicated that these proteins have network characteristics that are similar to disease-related proteins and may therefore have disease associations not previously identified. By performing a post-processing step after the prediction, we were able to identify evidence in literature supporting this possibility. This method could provide a useful filter for experimentalists searching for new candidate protein targets for drug repositioning and could also be extended to include other network and data types in order to refine these predictions. PMID:26043920

Ebola virus VP24 interacts with NP to facilitate nucleocapsid assembly and genome packaging.

PubMed

Banadyga, Logan; Hoenen, Thomas; Ambroggio, Xavier; Dunham, Eric; Groseth, Allison; Ebihara, Hideki

2017-08-09

Ebola virus causes devastating hemorrhagic fever outbreaks for which no approved therapeutic exists. The viral nucleocapsid, which is minimally composed of the proteins NP, VP35, and VP24, represents an attractive target for drug development; however, the molecular determinants that govern the interactions and functions of these three proteins are still unknown. Through a series of mutational analyses, in combination with biochemical and bioinformatics approaches, we identified a region on VP24 that was critical for its interaction with NP. Importantly, we demonstrated that the interaction between VP24 and NP was required for both nucleocapsid assembly and genome packaging. Not only does this study underscore the critical role that these proteins play in the viral replication cycle, but it also identifies a key interaction interface on VP24 that may serve as a novel target for antiviral therapeutic intervention.

Establishment of a robust dengue virus NS3-NS5 binding assay for identification of protein-protein interaction inhibitors.

PubMed

Takahashi, Hirotaka; Takahashi, Chikako; Moreland, Nicole J; Chang, Young-Tae; Sawasaki, Tatsuya; Ryo, Akihide; Vasudevan, Subhash G; Suzuki, Youichi; Yamamoto, Naoki

2012-12-01

Whereas the dengue virus (DENV) non-structural (NS) proteins NS3 and NS5 have been shown to interact in vitro and in vivo, the biological relevance of this interaction in viral replication has not been fully clarified. Here, we first applied a simple and robust in vitro assay based on AlphaScreen technology in combination with the wheat-germ cell-free protein production system to detect the DENV-2 NS3-NS5 interaction in a 384-well plate. The cell-free-synthesized NS3 and NS5 recombinant proteins were soluble and in possession of their respective enzymatic activities in vitro. In addition, AlphaScreen assays using the recombinant proteins detected a specific interaction between NS3 and NS5 with a robust Z' factor of 0.71. By employing the AlphaScreen assay, we found that both the N-terminal protease and C-terminal helicase domains of NS3 are required for its association with NS5. Furthermore, a competition assay revealed that the binding of full-length NS3 to NS5 was significantly inhibited by the addition of an excess of NS3 protease or helicase domains. Our results demonstrate that the AlphaScreen assay can be used to discover novel antiviral agents targeting the interactions between DENV NS proteins. Copyright © 2012 Elsevier B.V. All rights reserved.

Epitope mapping of imidazolium cations in ionic liquid-protein interactions unveils the balance between hydrophobicity and electrostatics towards protein destabilisation.

PubMed

Silva, Micael; Figueiredo, Angelo Miguel; Cabrita, Eurico J

2014-11-14

We investigated imidazolium-based ionic liquid (IL) interactions with human serum albumin (HSA) to discern the level of cation interactions towards protein stability. STD-NMR spectroscopy was used to observe the imidazolium IL protons involved in direct binding and to identify the interactions responsible for changes in Tm as accessed by differential scanning calorimetry (DSC). Cations influence protein stability less than anions but still significantly. It was found that longer alkyl side chains of imidazolium-based ILs (more hydrophobic) are associated with a higher destabilisation effect on HSA than short-alkyl groups (less hydrophobic). The reason for such destabilisation lies on the increased surface contact area of the cation with the protein, particularly on the hydrophobic contacts promoted by the terminus of the alkyl chain. The relevance of the hydrophobic contacts is clearly demonstrated by the introduction of a polar moiety in the alkyl chain: a methoxy or alcohol group. Such structural modification reduces the degree of hydrophobic contacts with HSA explaining the lesser extent of protein destabilisation when compared to longer alkyl side chain groups: above [C2mim](+). Competition STD-NMR experiments using [C2mim](+), [C4mim](+) and [C2OHmim](+) also validate the importance of the hydrophobic interactions. The combined effect of cation and anion interactions was explored using (35)Cl NMR. Such experiments show that the nature of the cation has no influence on the anion-protein contacts, still the nature of the anion modulates the cation-protein interaction. Herein we propose that more destabilising anions are likely to be a result of a partial contribution from the cation as a direct consequence of the different levels of interaction (cation-anion pair and cation-protein).

Synergistic interactions of biotic and abiotic environmental stressors on gene expression.

PubMed

Altshuler, Ianina; McLeod, Anne M; Colbourne, John K; Yan, Norman D; Cristescu, Melania E

2015-03-01

Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis - cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) - using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

PubMed Central

Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby-Joe; Hon, Gary C; Myers, Chad L; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G; Ideker, Trey; Dolinski, Kara; Batada, Nizar N; Tyers, Mike

2006-01-01

Background The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID () and SGD () databases. Conclusion Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks. PMID:16762047

Protein destabilisation in ionic liquids: the role of preferential interactions in denaturation.

PubMed

Figueiredo, Angelo Miguel; Sardinha, Joao; Moore, Geoffrey R; Cabrita, Eurico J

2013-12-07

The preferential binding of anions and cations in aqueous solutions of the ionic liquids (ILs) 1-butyl-3-methylimidazolium ([C4mim](+)) and 1-ethyl-3-methylimidazolium ([C2mim](+)) chloride and dicyanamide (dca(-)) with the small alpha-helical protein Im7 was investigated using a combination of differential scanning calorimetry, NMR spectroscopy and molecular dynamics (MD) simulations. Our results show that direct ion interactions are crucial to understand the effects of ILs on the stability of proteins and that an anion effect is dominant. We show that the binding of weakly hydrated anions to positively charged or polar residues leads to the partial dehydration of the backbone groups, and is critical to control stability, explaining why dca(-) is more denaturing than Cl(-). Direct cation-protein interactions also mediate stability; cation size and hydrophobicity are relevant to account for destabilisation as shown by the effect of [C4mim](+) compared to [C2mim](+). The specificity in the interaction of IL ions with protein residues established by weak favourable interactions is confirmed by NMR chemical shift perturbation, amide hydrogen exchange data and MD simulations. Differences in specificity are due to the balance of interaction established between ion pairs and ion-solvent that determine the type of residues affected. When the interaction of both cation and anion with the protein is strong the net result is similar to a non-specific interaction, leading ultimately to unfolding. Since the nature of the ions is a determinant of the level of interaction with the protein towards denaturation or stabilisation, ILs offer a unique possibility to modulate protein stabilisation or even folding events.

Mixed-Isotope Labeling with LC-IMS-MS for Characterization of Protein–Protein Interactions by Chemical Cross-Linking

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

Merkley, Eric D.; Baker, Erin S.; Crowell, Kevin L.

2013-02-20

Chemical cross-linking of proteins followed by proteolysis and mass spectrometric analysis of the resulting cross-linked peptides can provide insights into protein structure and protein-protein interactions. However, cross-linked peptides are by necessity of low stoichometry and have different physicochemical properties than linear peptides, routine unambiguous identification of the cross-linked peptides has remained difficult. To address this challenge, we demonstrated the use of liquid chromatography and ion mobility separations coupled with mass spectrometry in combination with a heavy-isotope labeling method. The combination of mixed-isotope cross-linking and ion mobility provided unique and easily interpretable spectral multiplet features for the intermolecular cross-linked peptides. Applicationmore » of the method to two different homodimeric proteins - SrfN, a virulence factor from Salmonella Typhimurium and SO_2176, a protein of unknown function from Shewanella oneidensis- revealed several cross-linked peptides from both proteins that were identified with a low false discovery rate (estimated using a decoy approach). A greater number of cross-linked peptides were identified using ion mobility drift time information in the analysis than when the data were summed across the drift time dimension before analysis. The identified cross-linked peptides migrated more quickly in the ion mobility drift tube than the unmodified peptides.« less

Determining protein function and interaction from genome analysis

DOEpatents

Eisenberg, David; Marcotte, Edward M.; Thompson, Michael J.; Pellegrini, Matteo; Yeates, Todd O.

2004-08-03

A computational method system, and computer program are provided for inferring functional links from genome sequences. One method is based on the observation that some pairs of proteins A' and B' have homologs in another organism fused into a single protein chain AB. A trans-genome comparison of sequences can reveal these AB sequences, which are Rosetta Stone sequences because they decipher an interaction between A' and B. Another method compares the genomic sequence of two or more organisms to create a phylogenetic profile for each protein indicating its presence or absence across all the genomes. The profile provides information regarding functional links between different families of proteins. In yet another method a combination of the above two methods is used to predict functional links.

An automated wide-field time-gated optically sectioning fluorescence lifetime imaging multiwell plate reader for high-content analysis of protein-protein interactions

NASA Astrophysics Data System (ADS)

Alibhai, Dominic; Kumar, Sunil; Kelly, Douglas; Warren, Sean; Alexandrov, Yuriy; Munro, Ian; McGinty, James; Talbot, Clifford; Murray, Edward J.; Stuhmeier, Frank; Neil, Mark A. A.; Dunsby, Chris; French, Paul M. W.

2011-03-01

We describe an optically-sectioned FLIM multiwell plate reader that combines Nipkow microscopy with wide-field time-gated FLIM, and its application to high content analysis of FRET. The system acquires sectioned FLIM images in <10 s/well, requiring only ~11 minutes to read a 96 well plate of live cells expressing fluorescent protein. It has been applied to study the formation of immature HIV virus like particles (VLPs) in live cells by monitoring Gag-Gag protein interactions using FLIM FRET of HIV-1 Gag transfected with CFP or YFP. VLP formation results in FRET between closely packed Gag proteins, as confirmed by our FLIM analysis that includes automatic image segmentation.

SPR Biosensors in Direct Molecular Fishing: Implications for Protein Interactomics.

PubMed

Florinskaya, Anna; Ershov, Pavel; Mezentsev, Yuri; Kaluzhskiy, Leonid; Yablokov, Evgeniy; Medvedev, Alexei; Ivanov, Alexis

2018-05-18

We have developed an original experimental approach based on the use of surface plasmon resonance (SPR) biosensors, applicable for investigation of potential partners involved in protein⁻protein interactions (PPI) as well as protein⁻peptide or protein⁻small molecule interactions. It is based on combining a SPR biosensor, size exclusion chromatography (SEC), mass spectrometric identification of proteins (LC-MS/MS) and direct molecular fishing employing principles of affinity chromatography for isolation of potential partner proteins from the total lysate of biological samples using immobilized target proteins (or small non-peptide compounds) as ligands. Applicability of this approach has been demonstrated within the frame of the Human Proteome Project (HPP) and PPI regulation by a small non-peptide biologically active compound, isatin.

Elucidation of the binding sites of sodium dodecyl sulfate to β-lactoglobulin using hydrogen/deuterium exchange mass spectrometry combined with docking simulation.

PubMed

Hu, Wenbing; Liu, Jianan; Luo, Qun; Han, Yumiao; Wu, Kui; Lv, Shuang; Xiong, Shaoxiang; Wang, Fuyi

2011-05-30

Hydrogen/deuterium exchange mass spectrometry (H/DX MS) has become a powerful tool to investigate protein-protein and protein-ligand interactions, but it is still challenging to localize the interaction regions/sites of ligands with pepsin-resistant proteins such as lipocalins. β-Lactoglobulin (BLG), a member of the lipocalin family, can bind a variety of small hydrophobic molecules including retinols, retinoic acids, and long linear fatty acids. However, whether the binding site of linear molecules locates in the external groove or internal cavity of BLG is controversial. In this study we used H/DX MS combined with docking simulation to localize the interaction sites of a tested ligand, sodium dodecyl sulfate (SDS), binding to BLG. H/DX MS results indicated that SDS can bind to both the external and the internal sites in BLG. However, neither of the sites is saturated with SDS, allowing a dynamic ligand exchange to occur between the sites at equilibrium state. Docking studies revealed that SDS forms H-bonds with Lys69 in the internal site and Lys138 and Lys141 in the external site in BLG via the sulfate group, and interacts with the hydrophobic residues valine, leucine, isoleucine and methionine within both of the sites via its hydrocarbon tail, stabilizing the BLG-SDS complex. Copyright © 2011 John Wiley & Sons, Ltd.

Variation of the chemical reactivity of Thermus thermophilus HB8 ribosomal proteins as a function of pH.

PubMed

Running, William E; Reilly, James P

2010-10-01

Ribosomes occupy a central position in cellular metabolism, converting stored genetic information into active cellular machinery. Ribosomal proteins modulate both the intrinsic function of the ribosome and its interaction with other cellular complexes, such as chaperonins or the signal recognition particle. Chemical modification of proteins combined with mass spectrometric detection of the extent and position of covalent modifications is a rapid, sensitive method for the study of protein structure and flexibility. By altering the pH of the solution, we have induced non-denaturing changes in the structure of bacterial ribosomal proteins and detected these conformational changes by covalent labeling. Changes in ribosomal protein modification across a pH range from 6.6 to 8.3 are unique to each protein, and correlate with their structural environment in the ribosome. Lysine residues whose extent of modification increases as a function of increasing pH are on the surface of proteins, but in close proximity either to glutamate and aspartate residues, or to rRNA backbone phosphates. Increasing pH disrupts tertiary and quaternary interactions mediated by hydrogen bonding or ionic interactions, and regions of protein structure whose conformations are sensitive to these changes are of potential importance in modulating the flexibility of the ribosome or its interaction with other cellular complexes.

Effect of polymer molecular weight on chitosan-protein interaction.

PubMed

Bekale, L; Agudelo, D; Tajmir-Riahi, H A

2015-01-01

We present a comprehensive study of the interactions between chitosan nanoparticles (15, 100 and 200 kDa with the same degree of deacetylation 90%) and two model proteins, i.e., bovine (BSA) and human serum albumins (HSA), with the aim of correlating chitosan molecular weight (Mw) and the binding affinity of these naturally occurring polymers to protein. The effect of chitosan on the protein secondary structure and the influence of protein complexation on the shape of chitosan nanoparticles are discussed. A combination of multiple spectroscopic methods, transmission electron microscopy (TEM) and thermodynamic analysis were used to assess the polymer-protein complex formation. Results revealed that the three chitosan nanoparticles interact with BSA to form chitosan-BSA complexes, mainly through hydrophobic contacts with the affinity order: 200>100>15 kDa. However, HSA-chitosan complexation is mainly via electrostatic interactions with the stability order: 100>200>15 kDa. Furthermore, the association between polymer and protein causes a partial protein conformational change by a major reduction of α-helix from 63% (free BSA) to 57% (chitosan-BSA) and 57% (free HSA) to 51% (chitosan-HSA). Finally, TEM micrographs clearly revealed that the binding of serum albumins with chitosan nanoparticles induces a significant change in protein morphology and the shape of the polymer. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

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

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.

Probing Membrane Order and Topography in Supported Lipid Bilayers by Combined Polarized Total Internal Reflection Fluorescence-Atomic Force Microscopy

PubMed Central

Oreopoulos, John; Yip, Christopher M.

2009-01-01

Determining the local structure, dynamics, and conformational requirements for protein-protein and protein-lipid interactions in membranes is critical to understanding biological processes ranging from signaling to the translocating and membranolytic action of antimicrobial peptides. We report here the application of a combined polarized total internal reflection fluorescence microscopy-in situ atomic force microscopy platform. This platform's ability to image membrane orientational order was demonstrated on DOPC/DSPC/cholesterol model membranes containing the fluorescent membrane probe, DiI-C20 or BODIPY-PC. Spatially resolved order parameters and fluorophore tilt angles extracted from the polarized total internal reflection fluorescence microscopy images were in good agreement with the topographical details resolved by in situ atomic force microscopy, portending use of this technique for high-resolution characterization of membrane domain structures and peptide-membrane interactions. PMID:19254557

Advances in proteomics research for peanut genetics and breeding

USDA-ARS?s Scientific Manuscript database

Crop trait improvement aimed at increased yield and quality relies on an understanding of the biology of the plant, particular protein-protein interactions. In this regard, the application of “-omics” techniques combined with field-level agronomy is poised to deliver novel insight into previously u...

Combining peptide recognition specificity and context information for the prediction of the 14-3-3-mediated interactome in S. cerevisiae and H. sapiens.

PubMed

Panni, Simona; Montecchi-Palazzi, Luisa; Kiemer, Lars; Cabibbo, Andrea; Paoluzi, Serena; Santonico, Elena; Landgraf, Christiane; Volkmer-Engert, Rudolf; Bachi, Angela; Castagnoli, Luisa; Cesareni, Gianni

2011-01-01

Large-scale interaction studies contribute the largest fraction of protein interactions information in databases. However, co-purification of non-specific or indirect ligands, often results in data sets that are affected by a considerable number of false positives. For the fraction of interactions mediated by short linear peptides, we present here a combined experimental and computational strategy for ranking the reliability of the inferred partners. We apply this strategy to the family of 14-3-3 domains. We have first characterized the recognition specificity of this domain family, largely confirming the results of previous analyses, while revealing new features of the preferred sequence context of 14-3-3 phospho-peptide partners. Notably, a proline next to the carboxy side of the phospho-amino acid functions as a potent inhibitor of 14-3-3 binding. The position-specific information about residue preference was encoded in a scoring matrix and two regular expressions. The integration of these three features in a single predictive model outperforms publicly available prediction tools. Next we have combined, by a naïve Bayesian approach, these "peptide features" with "protein features", such as protein co-expression and co-localization. Our approach provides an orthogonal reliability assessment and maps with high confidence the 14-3-3 peptide target on the partner proteins. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cytochrome c conjugated to ZnO-MAA nanoparticles: the study of interaction and influence on protein structure.

PubMed

Simšíková, Michaela; Antalík, Marián; Kaňuchová, Mária; Skvarla, Jiří

2013-08-01

Nanoparticle-protein conjugates have potential for numerous applications due to the combination of the properties of both components. In this paper we studied the conjugation of horse heart cytochrome c with ZnO nanoparticles modified by mercaptoacetic acid (MAA) which may be a material with great potential in anticancer therapy as a consequence of synergic effect of both components. Cyt c adsorption to the ZnO-MAA NPs surface was studied by UV-vis spectroscopy and by a dynamic light scattering in various pH. The results indicate that the optimal pH for the association of protein with modified nanoparticles is in range 5.8-8.5 where 90-96% of cytochrome c was assembled on ZnO-MAA nanoparticles. The interaction of proteins with nanoparticles often results in denaturation or loss of protein function. Our observations from UV-vis spectroscopy and circular dichroism performed preserved protein structure after the interaction with modified nanoparticles. Copyright © 2013 Elsevier B.V. All rights reserved.

A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways

PubMed Central

Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

2014-01-01

Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of co-factors (co-chaperones) that regulate their specificity and function. However, how these co-chaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We have combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone/co-chaperone/client interaction network in human cells. We uncover hundreds of novel chaperone clients, delineate their participation in specific co-chaperone complexes, and establish a surprisingly distinct network of protein/protein interactions for co-chaperones. As a salient example of the power of such analysis, we establish that NUDC family co-chaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network, its regulation in development and disease, and expand the use of chaperones as sensors for drug/target engagement. PMID:25036637

Binding Affinity Effects on Physical Characteristics of a Model Phase-Separated Protein Droplet

NASA Astrophysics Data System (ADS)

Chuang, Sara; Banani, Salman; Rosen, Michael; Brangwynne, Clifford

2015-03-01

Non-membrane bound organelles are associated with a range of biological functions. Several of these structures exhibit liquid-like properties, and may represent droplets of phase-separated RNA and/or proteins. These structures are often enriched in multi-valent molecules, however little is known about the interactions driving the assembly, properties, and function. Here, we address this question using a model multi-valent protein system consisting of repeats of Small Ubiquitin-like Modifier (SUMO) protein and a SUMO-interacting motif (SIM). These proteins undergo phase separation into liquid-like droplets. We combine microrheology and quantitative microscopy to determine affect of binding affinity on the viscosity, density and surface tension of these droplets. We also use fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS) and partitioning experiments to probe the structure and dynamics within these droplets. Our results shed light on how inter-molecular interactions manifests in droplet properties, and lay the groundwork for a comprehensive biophysical picture of intracellular RNA/protein organelles.

Identification of FBXO25-interacting Proteins Using an Integrated Proteomics Approach

PubMed Central

Teixeira, Felipe R.; Yokoo, Sami; Gartner, Carlos G.; Manfiolli, Adriana O.; Baqui, Munira M. A.; Assmann, Eliana M.; Maragno, Ana Leticia G. C.; Yu, Huijun; de Lanerolle, Primal; Kobarg, Jörg; Gygi, Steven P.; Gomes, Marcelo D.

2011-01-01

FBXO25 is one of 68 human F-box proteins that serve as specificity factors for a family of ubiquitin ligases composed of Skp1, Rbx1, Cullin1 and F-box protein (SCF1) that are involved in targeting proteins for destruction across the ubiquitin proteasome system. We recently reported that the FBXO25 protein accumulates in novel subnuclear structures named FBXO25-associated nuclear domains (FANDs). Combining two-step affinity purification followed by mass spectrometry with a classical two-hybrid screen, we identified 132 novel potential FBXO25 interacting partners. One of the identified proteins, β-actin, physically interacts through its N-terminus with FBXO25 and is enriched in the FBXO25 nuclear compartments. Inhibitors of actin polymerization promote a significant disruption of FANDs, indicating that they are compartments influenced by the organizational state of actin in the nucleus. Furthermore, FBXO25 antibodies interfered with RNA polymerase II transcription in vitro. Our results open new perspectives for the understanding of this novel compartment and its nuclear functions. PMID:20473970

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

PubMed

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

2017-01-01

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

Analyses of pea necrotic yellow dwarf virus-encoded proteins.

PubMed

Krenz, Björn; Schießl, Ingrid; Greiner, Eva; Krapp, Susanna

2017-06-01

Pea necrotic yellow dwarf virus (PNYDV) is a multipartite, circular, single-stranded DNA plant virus. PNYDV encodes eight proteins and the function of three of which remains unknown-U1, U2, and U4. PNYDV proteins cellular localization was analyzed by GFP tagging and bimolecular fluorescence complementation (BiFC) studies. The interactions of all eight PNYDV proteins were tested pairwise in planta (36 combinations in total). Seven interactions were identified and two (M-Rep with CP and MP with U4) were characterized further. MP and U4 complexes appeared as vesicle-like spots and were localized at the nuclear envelope and cell periphery. These vesicle-like spots were associated with the endoplasmatic reticulum. In addition, a nuclear localization signal (NLS) was mapped for U1, and a mutated U1 with NLS disrupted localized at plasmodesmata and therefore might also have a role in movement. Taken together, this study provides evidence for previously undescribed nanovirus protein-protein interactions and their cellular localization with novel findings not only for those proteins with unknown function, but also for characterized proteins such as the CP.

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

PubMed

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

2017-08-01

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

Nanoparticles for Protein Sensing in Primary Containers: Interaction Analysis and Application.

PubMed

Pérez Medina Martínez, Víctor; Espinosa-de la Garza, Carlos E; Méndez-Silva, Diego A; Bolívar-Vichido, Mariana; Flores-Ortiz, Luis F; Pérez, Néstor O

2018-05-01

Silver nanoparticles (AgNPs) are known to interact with proteins, leading to modifications of the plasmonic absorption that can be used to monitor this interaction, entailing a promising application for sensing adsorption of therapeutic proteins in primary containers. First, transmission electron microscopy in combination with plasmonic absorption and light scattering responses were used to characterize AgNPs and protein-AgNP complexes, including its concentration dependence, using two therapeutic molecules as models: a monoclonal antibody (mAb) and a synthetic copolymer (SC). Upon interaction, a protein corona was formed around AgNPs with the consequent shifting and broadening of their characteristic surface plasmon resonance (SPR) band (400 nm) to 410 nm and longer wavelenghts. Additional studies revealed secondary and three-dimensional structure modifications of model proteins upon interaction with AgNPs by circular dichroism and fluorescence techniques, respectively. Based on the modification of the SPR condition of AgNPs upon interaction with proteins, we developed a novel protein-sensing application of AgNPs in primary containers. This strategy was used to conduct a compatibility assessment of model proteins towards five commercially available prefillable glass syringe (PFS) models. mAb- and SC-exposed PFSs showed that 74 and 94% of cases were positive for protein adsorption, respectively. Interestingly, protein adsorption on 15% of total tested PFSs was negligible (below the nanogram level). Our results highlight the need of a case-by-case compatibility assessment of therapeutic proteins and their primary containers. This strategy has the potential to be easily applied on other containers and implemented during early-stage product development by pharmaceutical companies and for routine use during batch release by packaging manufacturers.

PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system

PubMed Central

Droit, Arnaud; Hunter, Joanna M; Rouleau, Michèle; Ethier, Chantal; Picard-Cloutier, Aude; Bourgais, David; Poirier, Guy G

2007-01-01

Background In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools. Description We herein describe "PARPs database," a data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics. PARPs database is a web-based tool whose features include experiment annotation, protein database searching, protein sequence management, as well as data-mining of the peptides and proteins identified. Conclusion Using this pipeline, we have successfully identified several interactions of biological significance between PARP-1 and other proteins, namely RFC-1, 2, 3, 4 and 5. PMID:18093328

Precise control of surface electrostatic forces on polymer brush layers with opposite charges for resistance to protein adsorption.

PubMed

Sakata, Sho; Inoue, Yuuki; Ishihara, Kazuhiko

2016-10-01

Various molecular interaction forces are generated during protein adsorption process on material surfaces. Thus, it is necessary to control them to suppress protein adsorption and the subsequent cell and tissue responses. A series of binary copolymer brush layers were prepared via surface-initiated atom transfer radical polymerization, by mixing the cationic monomer unit and anionic monomer unit randomly in various ratios. Surface characterization revealed that the constructed copolymer brush layers exhibited an uniform super-hydrophilic nature and different surface potentials. The strength of the electrostatic interaction forces operating on these mixed-charge copolymer brush surfaces was evaluated quantitatively using force-versus-distance (f-d) curve measurements by atomic force microscopy (AFM) and probes modified by negatively charged carboxyl groups or positively charged amino groups. The electrostatic interaction forces were determined based on the charge ratios of the copolymer brush layers. Notably, the surface containing equivalent cationic/anionic monomer units hardly interacted with both the charged groups. Furthermore, the protein adsorption force and the protein adsorption mass on these surfaces were examined by AFM f-d curve measurement and surface plasmon resonance measurement, respectively. To clarify the influence of the electrostatic interaction on the protein adsorption behavior on the surface, three kinds of proteins having negative, positive, and relatively neutral net charges under physiological conditions were used in this study. We quantitatively demonstrated that the amount of adsorbed proteins on the surfaces would have a strong correlation with the strength of surface-protein interaction forces, and that the strength of surface-protein interaction forces would be determined from the combination between the properties of the electrostatic interaction forces on the surfaces and the charge properties of the proteins. Especially, the copolymer brush surface composed of equivalent cationic/anionic monomer units exhibited no significant interaction forces, and dramatically suppressed the adsorption of proteins regardless of their charge properties. We conclude that the established methodology could elucidate relationship between the protein adsorption behavior and molecular interaction, especially the electrostatic interaction forces, and demonstrated that the suppression of the electrostatic interactions with the ionic functional groups would be important for the development of new polymeric biomaterials with a high repellency of protein adsorption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental–Computational Study

DOE PAGES

Song, Lingshuang; Yang, Lin; Meng, Jie; ...

2016-12-29

Here, we present a joint experimental-computational study to quantitatively describe the thermodynamics of hydrophobic leucine amino acids in aqueous solution. X-ray scattering data were acquired at a series of solute and salt concentrations to effectively measure inter-leucine interactions, indicating that a major scattering peak is observed consistently at q = 0.83 Å -1. Atomistic molecular dynamics simulations were then performed and compared with the scattering data, achieving high consistency at both small and wider scattering angles (q = 0$-$1.5 Å -1). This experimental-computational consistence enables a first glimpse of the leucineleucine interacting landscape, where two leucine molecules are aligned mostlymore » in a parallel fashion, as opposed to anti-parallel, but also allows us to derive effective leucine-leucine interactions in solution. Collectively, this combined approach of employing experimental scattering and molecular simulation enables a quantitative characterization on effective inter-molecular interactions of hydrophobic amino acids, critical for protein function and dynamics such as protein folding.« less

Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental–Computational Study

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

Song, Lingshuang; Yang, Lin; Meng, Jie

Here, we present a joint experimental-computational study to quantitatively describe the thermodynamics of hydrophobic leucine amino acids in aqueous solution. X-ray scattering data were acquired at a series of solute and salt concentrations to effectively measure inter-leucine interactions, indicating that a major scattering peak is observed consistently at q = 0.83 Å -1. Atomistic molecular dynamics simulations were then performed and compared with the scattering data, achieving high consistency at both small and wider scattering angles (q = 0$-$1.5 Å -1). This experimental-computational consistence enables a first glimpse of the leucineleucine interacting landscape, where two leucine molecules are aligned mostlymore » in a parallel fashion, as opposed to anti-parallel, but also allows us to derive effective leucine-leucine interactions in solution. Collectively, this combined approach of employing experimental scattering and molecular simulation enables a quantitative characterization on effective inter-molecular interactions of hydrophobic amino acids, critical for protein function and dynamics such as protein folding.« less

Combination therapy in a xenograft model of glioblastoma: enhancement of the antitumor activity of temozolomide by an MDM2 antagonist.

PubMed

Wang, Haiyan; Cai, Shanbao; Bailey, Barbara J; Reza Saadatzadeh, M; Ding, Jixin; Tonsing-Carter, Eva; Georgiadis, Taxiarchis M; Zachary Gunter, T; Long, Eric C; Minto, Robert E; Gordon, Kevin R; Sen, Stephanie E; Cai, Wenjing; Eitel, Jacob A; Waning, David L; Bringman, Lauren R; Wells, Clark D; Murray, Mary E; Sarkaria, Jann N; Gelbert, Lawrence M; Jones, David R; Cohen-Gadol, Aaron A; Mayo, Lindsey D; Shannon, Harlan E; Pollok, Karen E

2017-02-01

OBJECTIVE Improvement in treatment outcome for patients with glioblastoma multiforme (GBM) requires a multifaceted approach due to dysregulation of numerous signaling pathways. The murine double minute 2 (MDM2) protein may fulfill this requirement because it is involved in the regulation of growth, survival, and invasion. The objective of this study was to investigate the impact of modulating MDM2 function in combination with front-line temozolomide (TMZ) therapy in GBM. METHODS The combination of TMZ with the MDM2 protein-protein interaction inhibitor nutlin3a was evaluated for effects on cell growth, p53 pathway activation, expression of DNA repair proteins, and invasive properties. In vivo efficacy was assessed in xenograft models of human GBM. RESULTS In combination, TMZ/nutlin3a was additive to synergistic in decreasing growth of wild-type p53 GBM cells. Pharmacodynamic studies demonstrated that inhibition of cell growth following exposure to TMZ/nutlin3a correlated with: 1) activation of the p53 pathway, 2) downregulation of DNA repair proteins, 3) persistence of DNA damage, and 4) decreased invasion. Pharmacokinetic studies indicated that nutlin3a was detected in human intracranial tumor xenografts. To assess therapeutic potential, efficacy studies were conducted in a xenograft model of intracranial GBM by using GBM cells derived from a recurrent wild-type p53 GBM that is highly TMZ resistant (GBM10). Three 5-day cycles of TMZ/nutlin3a resulted in a significant increase in the survival of mice with GBM10 intracranial tumors compared with single-agent therapy. CONCLUSIONS Modulation of MDM2/p53-associated signaling pathways is a novel approach for decreasing TMZ resistance in GBM. To the authors' knowledge, this is the first study in a humanized intracranial patient-derived xenograft model to demonstrate the efficacy of combining front-line TMZ therapy and an inhibitor of MDM2 protein-protein interactions.

Electron spin-echo envelope modulation (ESEEM) reveals water and phosphate interactions with the KcsA potassium channel.

PubMed

Cieslak, John A; Focia, Pamela J; Gross, Adrian

2010-02-23

Electron spin-echo envelope modulation (ESEEM) spectroscopy is a well-established technique for the study of naturally occurring paramagnetic metal centers. The technique has been used to study copper complexes, hemes, enzyme mechanisms, micellar water content, and water permeation profiles in membranes, among other applications. In the present study, we combine ESEEM spectroscopy with site-directed spin labeling (SDSL) and X-ray crystallography in order to evaluate the technique's potential as a structural tool to describe the native environment of membrane proteins. Using the KcsA potassium channel as a model system, we demonstrate that deuterium ESEEM can detect water permeation along the lipid-exposed surface of the KcsA outer helix. We further demonstrate that (31)P ESEEM is able to identify channel residues that interact with the phosphate headgroup of the lipid bilayer. In combination with X-ray crystallography, the (31)P data may be used to define the phosphate interaction surface of the protein. The results presented here establish ESEEM as a highly informative technique for SDSL studies of membrane proteins.

Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

PubMed Central

Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra

2013-01-01

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/ PMID:24339765

A critical analysis of computational protein design with sparse residue interaction graphs

PubMed Central

Georgiev, Ivelin S.

2017-01-01

Protein design algorithms enumerate a combinatorial number of candidate structures to compute the Global Minimum Energy Conformation (GMEC). To efficiently find the GMEC, protein design algorithms must methodically reduce the conformational search space. By applying distance and energy cutoffs, the protein system to be designed can thus be represented using a sparse residue interaction graph, where the number of interacting residue pairs is less than all pairs of mutable residues, and the corresponding GMEC is called the sparse GMEC. However, ignoring some pairwise residue interactions can lead to a change in the energy, conformation, or sequence of the sparse GMEC vs. the original or the full GMEC. Despite the widespread use of sparse residue interaction graphs in protein design, the above mentioned effects of their use have not been previously analyzed. To analyze the costs and benefits of designing with sparse residue interaction graphs, we computed the GMECs for 136 different protein design problems both with and without distance and energy cutoffs, and compared their energies, conformations, and sequences. Our analysis shows that the differences between the GMECs depend critically on whether or not the design includes core, boundary, or surface residues. Moreover, neglecting long-range interactions can alter local interactions and introduce large sequence differences, both of which can result in significant structural and functional changes. Designs on proteins with experimentally measured thermostability show it is beneficial to compute both the full and the sparse GMEC accurately and efficiently. To this end, we show that a provable, ensemble-based algorithm can efficiently compute both GMECs by enumerating a small number of conformations, usually fewer than 1000. This provides a novel way to combine sparse residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse residue interaction graphs while avoiding their potential inaccuracies. PMID:28358804

Beyond Anchoring: the Expanding Role of the Hendra Virus Fusion Protein Transmembrane Domain in Protein Folding, Stability, and Function

PubMed Central

Smith, Everett Clinton; Culler, Megan R.; Hellman, Lance M.; Fried, Michael G.; Creamer, Trevor P.

2012-01-01

While work with viral fusion proteins has demonstrated that the transmembrane domain (TMD) can affect protein folding, stability, and membrane fusion promotion, the mechanism(s) remains poorly understood. TMDs could play a role in fusion promotion through direct TMD-TMD interactions, and we have recently shown that isolated TMDs from three paramyxovirus fusion (F) proteins interact as trimers using sedimentation equilibrium (SE) analysis (E. C. Smith, et al., submitted for publication). Immediately N-terminal to the TMD is heptad repeat B (HRB), which plays critical roles in fusion. Interestingly, addition of HRB decreased the stability of the trimeric TMD-TMD interactions. This result, combined with previous findings that HRB forms a trimeric coiled coil in the prefusion form of the whole protein though HRB peptides fail to stably associate in isolation, suggests that the trimeric TMD-TMD interactions work in concert with elements in the F ectodomain head to stabilize a weak HRB interaction. Thus, changes in TMD-TMD interactions could be important in regulating F triggering and refolding. Alanine insertions between the TMD and HRB demonstrated that spacing between these two regions is important for protein stability while not affecting TMD-TMD interactions. Additional mutagenesis of the C-terminal end of the TMD suggests that β-branched residues within the TMD play a role in membrane fusion, potentially through modulation of TMD-TMD interactions. Our results support a model whereby the C-terminal end of the Hendra virus F TMD is an important regulator of TMD-TMD interactions and show that these interactions help hold HRB in place prior to the triggering of membrane fusion. PMID:22238302

Kinetic Titration Series with Biolayer Interferometry

PubMed Central

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1–42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations. PMID:25229647

Kinetic titration series with biolayer interferometry.

PubMed

Frenzel, Daniel; Willbold, Dieter

2014-01-01

Biolayer interferometry is a method to analyze protein interactions in real-time. In this study, we illustrate the usefulness to quantitatively analyze high affinity protein ligand interactions employing a kinetic titration series for characterizing the interactions between two pairs of interaction patterns, in particular immunoglobulin G and protein G B1 as well as scFv IC16 and amyloid beta (1-42). Kinetic titration series are commonly used in surface plasmon resonance and involve sequential injections of analyte over a desired concentration range on a single ligand coated sensor chip without waiting for complete dissociation between the injections. We show that applying this method to biolayer interferometry is straightforward and i) circumvents problems in data evaluation caused by unavoidable sensor differences, ii) saves resources and iii) increases throughput if screening a multitude of different analyte/ligand combinations.

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

PubMed

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

2017-01-01

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

Metabolic interactions between cysteamine and epigallocatechin gallate.

PubMed

Izzo, Valentina; Pietrocola, Federico; Sica, Valentina; Durand, Sylvère; Lachkar, Sylvie; Enot, David; Bravo-San Pedro, José Manuel; Chery, Alexis; Esposito, Speranza; Raia, Valeria; Maiuri, Luigi; Maiuri, Maria Chiara; Kroemer, Guido

2017-02-01

Phase II clinical trials indicate that the combination of cysteamine plus epigallocatechin gallate (EGCG) is effective against cystic fibrosis in patients bearing the most frequent etiological mutation (CFTRΔF508). Here, we investigated the interaction between both agents on cultured respiratory epithelia cells from normal and CFTRΔF508-mutated donors. We observed that the combination of both agents affected metabolic circuits (and in particular the tricarboxylic acid cycle) in a unique way and that cysteamine plus EGCG reduced cytoplasmic protein acetylation more than each of the 2 components alone. In a cell-free system, protein cross-linking activity of EGCG was suppressed by cysteamine. Finally, EGCG was able to enhance the conversion of cysteamine into taurine in metabolic flux experiments. Altogether, these results indicate that multiple pharmacological interactions occur between cysteamine and EGCG, suggesting that they contribute to the unique synergy of both agents in restoring the function of mutated CFTRΔF508.

Metabolic interactions between cysteamine and epigallocatechin gallate

PubMed Central

Izzo, Valentina; Pietrocola, Federico; Sica, Valentina; Durand, Sylvère; Lachkar, Sylvie; Enot, David; Bravo-San Pedro, José Manuel; Chery, Alexis; Esposito, Speranza; Raia, Valeria; Maiuri, Luigi; Maiuri, Maria Chiara; Kroemer, Guido

2017-01-01

ABSTRACT Phase II clinical trials indicate that the combination of cysteamine plus epigallocatechin gallate (EGCG) is effective against cystic fibrosis in patients bearing the most frequent etiological mutation (CFTRΔF508). Here, we investigated the interaction between both agents on cultured respiratory epithelia cells from normal and CFTRΔF508-mutated donors. We observed that the combination of both agents affected metabolic circuits (and in particular the tricarboxylic acid cycle) in a unique way and that cysteamine plus EGCG reduced cytoplasmic protein acetylation more than each of the 2 components alone. In a cell-free system, protein cross-linking activity of EGCG was suppressed by cysteamine. Finally, EGCG was able to enhance the conversion of cysteamine into taurine in metabolic flux experiments. Altogether, these results indicate that multiple pharmacological interactions occur between cysteamine and EGCG, suggesting that they contribute to the unique synergy of both agents in restoring the function of mutated CFTRΔF508. PMID:28059601

Atomic Force Microscopy and Spectroscopic Ellipsometry combined analysis of Small Ubiquitin-like Modifier adsorption on functional monolayers

NASA Astrophysics Data System (ADS)

Solano, Ilaria; Parisse, Pietro; Gramazio, Federico; Ianeselli, Luca; Medagli, Barbara; Cavalleri, Ornella; Casalis, Loredana; Canepa, Maurizio

2017-11-01

The comprehension of mechanisms of interaction between functional layers and proteins is relevant for the development of sensitive and precise biosensors. Here we report our study which combines Atomic Force Microscopy and Spectroscopic Ellipsometry to investigate the His-Ni-NTA mediated interaction between 6His-tagged Small Ubiquitin-like Modifier (SUMO) protein with self assembled monolayers of NTA terminated alkanethiols. The use of AFM-based nanolithograhic tools and the analysis of ellipsometric spectra in situ and ex situ provided us a solid method to disentangle the effects of Ni(II)-mediated interaction between the NTA layer and the 6His-tagged SUMO and to accurately determine in physiological condition the thickness value of the SUMO layer. This investigation is a first step towards the study of layered systems of greater complexity of which the NTA/6His-tagged SUMO is a prototypical example.

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

PubMed

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

2018-06-20

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

Complementary cereals and legumes for health: Synergistic interaction of sorghum flavones and cowpea flavonols against LPS-induced inflammation in colonic myofibroblasts.

PubMed

Agah, Shima; Kim, Hyemee; Mertens-Talcott, Susanne U; Awika, Joseph M

2017-07-01

Cereals and legumes are traditionally consumed together in many cultures, and may provide complementary health benefits beyond what is known about improved indispensable amino acid intake. Here, we use an in vitro model of inflammatory pathways to investigate whether the different flavonoids in sorghum and cowpea could synergistically reduce inflammation. Interactive effect of combining apigenin and quercetin, as well as extracts (70% acetone, v/v) from a flavone-dominated white sorghum and flavonol-dominated white cowpea, against LPS-induced NF-κB and downstream cytokines (TNF-α, IL-6, IL-8) gene and protein expression was evaluated using the CCD18Co colon myofibroblasts. Combination of apigenin and quercetin, and sorghum and cowpea extracts synergistically downregulated LPS-induced NF-κB gene and protein expression in a dose-dependent manner, with additive effect producing IC 50 values that were 14.6 and 14.0 times, respectively, higher than 1:1 combined treatments. Similar strong synergistic interactions were observed for the downstream cytokines (IC 50 values for additive effect 8.3-21 times higher than combined treatments). Furthermore, the ratios of the different combined treatments significantly affected the magnitude of synergy. Combining the structurally related cereal flavones and legume flavonols elicit strong synergistic anti-inflammatory response in LPS-stimulated nonmalignant colonocytes, likely by targeting interdependent mechanisms. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.

PubMed

Lise, Stefano; Archambeau, Cedric; Pontil, Massimiliano; Jones, David T

2009-10-30

Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (DeltaDeltaG) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which DeltaDeltaG >or= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration.

Dengue-2 structural proteins associate with human proteins to produce a coagulation and innate immune response biased interactome.

PubMed

Folly, Brenda B; Weffort-Santos, Almeriane M; Fathman, C G; Soares, Luis R B

2011-01-31

Dengue virus infection is a public health threat to hundreds of millions of individuals in the tropical regions of the globe. Although Dengue infection usually manifests itself in its mildest, though often debilitating clinical form, dengue fever, life-threatening complications commonly arise in the form of hemorrhagic shock and encephalitis. The etiological basis for the virus-induced pathology in general, and the different clinical manifestations in particular, are not well understood. We reasoned that a detailed knowledge of the global biological processes affected by virus entry into a cell might help shed new light on this long-standing problem. A bacterial two-hybrid screen using DENV2 structural proteins as bait was performed, and the results were used to feed a manually curated, global dengue-human protein interaction network. Gene ontology and pathway enrichment, along with network topology and microarray meta-analysis, were used to generate hypothesis regarding dengue disease biology. Combining bioinformatic tools with two-hybrid technology, we screened human cDNA libraries to catalogue proteins physically interacting with the DENV2 virus structural proteins, Env, cap and PrM. We identified 31 interacting human proteins representing distinct biological processes that are closely related to the major clinical diagnostic feature of dengue infection: haemostatic imbalance. In addition, we found dengue-binding human proteins involved with additional key aspects, previously described as fundamental for virus entry into cells and the innate immune response to infection. Construction of a DENV2-human global protein interaction network revealed interesting biological properties suggested by simple network topology analysis. Our experimental strategy revealed that dengue structural proteins interact with human protein targets involved in the maintenance of blood coagulation and innate anti-viral response processes, and predicts that the interaction of dengue proteins with a proposed human protein interaction network produces a modified biological outcome that may be behind the hallmark pathologies of dengue infection.

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

PubMed

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

2017-09-01

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

Pharmacological targeting of the transcription factor SOX18 delays breast cancer in mice

PubMed Central

Overman, Jeroen; Fontaine, Frank; Moustaqil, Mehdi; Mittal, Deepak; Sierecki, Emma; Sacilotto, Natalia; Zuegg, Johannes; Robertson, Avril AB; Holmes, Kelly; Salim, Angela A; Mamidyala, Sreeman; Butler, Mark S; Robinson, Ashley S; Lesieur, Emmanuelle; Johnston, Wayne; Alexandrov, Kirill; Black, Brian L; Hogan, Benjamin M; De Val, Sarah; Capon, Robert J; Carroll, Jason S; Bailey, Timothy L; Koopman, Peter; Jauch, Ralf; Smyth, Mark J; Cooper, Matthew A; Gambin, Yann; Francois, Mathias

2017-01-01

Pharmacological targeting of transcription factors holds great promise for the development of new therapeutics, but strategies based on blockade of DNA binding, nuclear shuttling, or individual protein partner recruitment have yielded limited success to date. Transcription factors typically engage in complex interaction networks, likely masking the effects of specifically inhibiting single protein-protein interactions. Here, we used a combination of genomic, proteomic and biophysical methods to discover a suite of protein-protein interactions involving the SOX18 transcription factor, a known regulator of vascular development and disease. We describe a small-molecule that is able to disrupt a discrete subset of SOX18-dependent interactions. This compound selectively suppressed SOX18 transcriptional outputs in vitro and interfered with vascular development in zebrafish larvae. In a mouse pre-clinical model of breast cancer, treatment with this inhibitor significantly improved survival by reducing tumour vascular density and metastatic spread. Our studies validate an interactome-based molecular strategy to interfere with transcription factor activity, for the development of novel disease therapeutics. DOI: http://dx.doi.org/10.7554/eLife.21221.001 PMID:28137359

The Modular Organization of Protein Interactions in Escherichia coli

PubMed Central

Peregrín-Alvarez, José M.; Xiong, Xuejian; Su, Chong; Parkinson, John

2009-01-01

Escherichia coli serves as an excellent model for the study of fundamental cellular processes such as metabolism, signalling and gene expression. Understanding the function and organization of proteins within these processes is an important step towards a ‘systems’ view of E. coli. Integrating experimental and computational interaction data, we present a reliable network of 3,989 functional interactions between 1,941 E. coli proteins (∼45% of its proteome). These were combined with a recently generated set of 3,888 high-quality physical interactions between 918 proteins and clustered to reveal 316 discrete modules. In addition to known protein complexes (e.g., RNA and DNA polymerases), we identified modules that represent biochemical pathways (e.g., nitrate regulation and cell wall biosynthesis) as well as batteries of functionally and evolutionarily related processes. To aid the interpretation of modular relationships, several case examples are presented, including both well characterized and novel biochemical systems. Together these data provide a global view of the modular organization of the E. coli proteome and yield unique insights into structural and evolutionary relationships in bacterial networks. PMID:19798435

Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experiments

PubMed Central

Nesvizhskii, Alexey I.

2013-01-01

Analysis of protein interaction networks and protein complexes using affinity purification and mass spectrometry (AP/MS) is among most commonly used and successful applications of proteomics technologies. One of the foremost challenges of AP/MS data is a large number of false positive protein interactions present in unfiltered datasets. Here we review computational and informatics strategies for detecting specific protein interaction partners in AP/MS experiments, with a focus on incomplete (as opposite to genome-wide) interactome mapping studies. These strategies range from standard statistical approaches, to empirical scoring schemes optimized for a particular type of data, to advanced computational frameworks. The common denominator among these methods is the use of label-free quantitative information such as spectral counts or integrated peptide intensities that can be extracted from AP/MS data. We also discuss related issues such as combining multiple biological or technical replicates, and dealing with data generated using different tagging strategies. Computational approaches for benchmarking of scoring methods are discussed, and the need for generation of reference AP/MS datasets is highlighted. Finally, we discuss the possibility of more extended modeling of experimental AP/MS data, including integration with external information such as protein interaction predictions based on functional genomics data. PMID:22611043

Volumetrically Derived Thermodynamic Profile of Interactions of Urea with a Native Protein.

PubMed

Son, Ikbae; Chalikian, Tigran V

2016-11-29

We report the first experimental characterization of the full thermodynamic profile for binding of urea to a native protein. We measured the volumetric parameters of lysozyme at pH 7.0 as a function of urea within a temperature range of 18-45 °C. At neutral pH, lysozyme retains its native conformation between 0 and 8 M urea over the entire range of temperatures studied. Consequently, our measured volumetric properties reflect solely the interactions of urea with the native protein and do not involve contributions from urea-induced conformational transitions. We analyzed our data within the framework of a statistical thermodynamic analytical model in which urea-protein interactions are viewed as solvent exchange in the vicinity of the protein. The analysis produced the equilibrium constant, k, for an elementary reaction of urea-protein binding with a change in standard state free energy (ΔG° = -RT ln k) at each experimental temperature. We used the van't Hoff equation to compute from the temperature dependence of the equilibrium constant, k, changes in enthalpy, ΔH°, and entropy, ΔS°, accompanying binding. The thermodynamic profile of urea-protein interactions, in conjunction with published molecular dynamics simulation results, is consistent with the picture in which urea molecules, being underhydrated in the bulk, form strong, enthalpically favorable interactions with the surface protein groups while paying a high entropic price. We discuss ramifications of our results for providing insights into the combined effects of urea, temperature, and pressure on the conformational preferences of proteins.

The distinctive cell division interactome of Neisseria gonorrhoeae.

PubMed

Zou, Yinan; Li, Yan; Dillon, Jo-Anne R

2017-12-12

Bacterial cell division is an essential process driven by the formation of a Z-ring structure, as a cytoskeletal scaffold at the mid-cell, followed by the recruitment of various proteins which form the divisome. The cell division interactome reflects the complement of different interactions between all divisome proteins. To date, only two cell division interactomes have been characterized, in Escherichia coli and in Streptococcus pneumoniae. The cell divison proteins encoded by Neisseria gonorrhoeae include FtsZ, FtsA, ZipA, FtsK, FtsQ, FtsI, FtsW, and FtsN. The purpose of the present study was to characterize the cell division interactome of N. gonorrhoeae using several different methods to identify protein-protein interactions. We also characterized the specific subdomains of FtsA implicated in interactions with FtsZ, FtsQ, FtsN and FtsW. Using a combination of bacterial two-hybrid (B2H), glutathione S-transferase (GST) pull-down assays, and surface plasmon resonance (SPR), nine interactions were observed among the eight gonococcal cell division proteins tested. ZipA did not interact with any other cell division proteins. Comparisons of the N. gonorrhoeae cell division interactome with the published interactomes from E. coli and S. pneumoniae indicated that FtsA-FtsZ and FtsZ-FtsK interactions were common to all three species. FtsA-FtsW and FtsK-FtsN interactions were only present in N. gonorrhoeae. The 2A and 2B subdomains of FtsA Ng were involved in interactions with FtsQ, FtsZ, and FtsN, and the 2A subdomain was involved in interaction with FtsW. Results from this research indicate that N. gonorrhoeae has a distinctive cell division interactome as compared with other microorganisms.

Optimization of proximity ligation assay (PLA) for detection of protein interactions and fusion proteins in non-adherent cells: application to pre-B lymphocytes.

PubMed

Debaize, Lydie; Jakobczyk, Hélène; Rio, Anne-Gaëlle; Gandemer, Virginie; Troadec, Marie-Bérengère

2017-01-01

Genetic abnormalities, including chromosomal translocations, are described for many hematological malignancies. From the clinical perspective, detection of chromosomal abnormalities is relevant not only for diagnostic and treatment purposes but also for prognostic risk assessment. From the translational research perspective, the identification of fusion proteins and protein interactions has allowed crucial breakthroughs in understanding the pathogenesis of malignancies and consequently major achievements in targeted therapy. We describe the optimization of the Proximity Ligation Assay (PLA) to ascertain the presence of fusion proteins, and protein interactions in non-adherent pre-B cells. PLA is an innovative method of protein-protein colocalization detection by molecular biology that combines the advantages of microscopy with the advantages of molecular biology precision, enabling detection of protein proximity theoretically ranging from 0 to 40 nm. We propose an optimized PLA procedure. We overcome the issue of maintaining non-adherent hematological cells by traditional cytocentrifugation and optimized buffers, by changing incubation times, and modifying washing steps. Further, we provide convincing negative and positive controls, and demonstrate that optimized PLA procedure is sensitive to total protein level. The optimized PLA procedure allows the detection of fusion proteins and protein interactions on non-adherent cells. The optimized PLA procedure described here can be readily applied to various non-adherent hematological cells, from cell lines to patients' cells. The optimized PLA protocol enables detection of fusion proteins and their subcellular expression, and protein interactions in non-adherent cells. Therefore, the optimized PLA protocol provides a new tool that can be adopted in a wide range of applications in the biological field.

Screening of the binding of small molecules to proteins by desorption electrospray ionization mass spectrometry combined with protein microarray.

PubMed

Yao, Chenxi; Wang, Tao; Zhang, Buqing; He, Dacheng; Na, Na; Ouyang, Jin

2015-11-01

The interaction between bioactive small molecule ligands and proteins is one of the important research areas in proteomics. Herein, a simple and rapid method is established to screen small ligands that bind to proteins. We designed an agarose slide to immobilize different proteins. The protein microarrays were allowed to interact with different small ligands, and after washing, the microarrays were screened by desorption electrospray ionization mass spectrometry (DESI MS). This method can be applied to screen specific protein binding ligands and was shown for seven proteins and 34 known ligands for these proteins. In addition, a high-throughput screening was achieved, with the analysis requiring approximately 4 s for one sample spot. We then applied this method to determine the binding between the important protein matrix metalloproteinase-9 (MMP-9) and 88 small compounds. The molecular docking results confirmed the MS results, demonstrating that this method is suitable for the rapid and accurate screening of ligands binding to proteins. Graphical Abstract ᅟ.

Gcn4-Mediator Specificity Is Mediated by a Large and Dynamic Fuzzy Protein-Protein Complex.

PubMed

Tuttle, Lisa M; Pacheco, Derek; Warfield, Linda; Luo, Jie; Ranish, Jeff; Hahn, Steven; Klevit, Rachel E

2018-03-20

Transcription activation domains (ADs) are inherently disordered proteins that often target multiple coactivator complexes, but the specificity of these interactions is not understood. Efficient transcription activation by yeast Gcn4 requires its tandem ADs and four activator-binding domains (ABDs) on its target, the Mediator subunit Med15. Multiple ABDs are a common feature of coactivator complexes. We find that the large Gcn4-Med15 complex is heterogeneous and contains nearly all possible AD-ABD interactions. Gcn4-Med15 forms via a dynamic fuzzy protein-protein interface, where ADs bind the ABDs in multiple orientations via hydrophobic regions that gain helicity. This combinatorial mechanism allows individual low-affinity and specificity interactions to generate a biologically functional, specific, and higher affinity complex despite lacking a defined protein-protein interface. This binding strategy is likely representative of many activators that target multiple coactivators, as it allows great flexibility in combinations of activators that can cooperate to regulate genes with variable coactivator requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Interaction effects of dietary supplementation of heat-killed Lactobacillus plantarum and β-glucan on growth performance, digestibility and immune response of juvenile red sea bream, Pagrus major.

PubMed

Dawood, Mahmoud A O; Koshio, Shunsuke; Ishikawa, Manabu; Yokoyama, Saichiro

2015-07-01

Both heat-killed Lactobacillus plantarum (HK-LP) and β-glucan (BG) play important roles in growth performance, feed utilization and health status of fish. Therefore, a feeding trial was conducted to determine the interactive effects of dietary HK-LP and BG on growth performance, digestibility, oxidative status and immune response of red sea bream for 56 days. A significant interaction was found between HK-LP and BG on final body weight, total plasma protein, glucose, serum bactericidal activity (BA), total serum protein, serum alternative complement pathway (ACP) activity, protein and dry matter digestibility coefficients (P < 0.05). In addition, body weight gain, specific growth rate, feed intake, protein efficiency ratio as well as serum lysozyme activity, ACP activity and mucus secretion were significantly affected by either HK-LP or BG (P < 0.05). Further, feeding 0.025% HK-LP combined with 0.1% BG significantly increased serum peroxidase activity compared with the other groups (P < 0.05). However, protein body content, somatic parameters, total bilirubin, blood urea nitrogen, glutamyl oxaloacetic transaminase (GOT), glutamic-pyruvate transaminase (GPT), triglycerides and mucus BA were not significantly altered by supplementations (P > 0.05). Interestingly, fish fed with both HK-LP at (0.025 and 0.1%) in combination with BG at (0 and 0.1%) showed higher oxidative stress resistance. Under the experimental conditions, dietary HK-LP and BG had a significant interaction on enhancing the growth, digestibility and immune responses of red sea bream. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-12-06

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

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.

Molecular Recognition of PPARγ by Kinase Cdk5/p25: Insights from a Combination of Protein-Protein Docking and Adaptive Biasing Force Simulations.

PubMed

Mottin, Melina; Souza, Paulo C T; Skaf, Munir S

2015-07-02

The peroxisome proliferator-activated receptor γ (PPARγ) is an important transcription factor that plays a major role in the regulation of glucose and lipid metabolisms and has, therefore, many implications in modern-life metabolic disorders such as diabetes, obesity, and cardiovascular diseases. Phosphorylation of PPARγ by the cyclin-dependent kinase 5 (Cdk5) has been recently proved to promote obesity and loss of insulin sensitivity. The inhibition of this reaction is currently being pursued to develop PPARγ ligands for type 2 diabetes treatments. The knowledge of the protein-protein interactions between Cdk5/p25 and PPARγ can be an important asset for better understanding of the molecular basis of the Cdk5-meditated phosphorylation of PPARγ and its inhibition. By means of a computational approach that combines protein-protein docking and adaptive biasing force molecular dynamics simulations, we obtained PPARγ-Cdk5/p25 structural models that are consistent with the mechanism of the enzymatic reaction and with overall structural features of the full length PPARγ-RXRα heterodimer bound to DNA. In addition to the active site, our model shows that the interacting regions between the two proteins should involve two distal docking sites, comprising the PPARγ Ω-loop and Cdk5 N-terminal lobe and the PPARγ β-sheet and Cdk5 C-terminal lobe. These sites are related to PPARγ transactivation and directly interact with PPARγ ligands. Our results suggest that β-sheets and Ω-loop stabilization promoted by PPARγ agonists could be important to inhibit Cdk5-mediated phosphorylation.

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

PubMed Central

2012-01-01

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

The creation of a biomimetic interface between boron-doped diamond and immobilized proteins.

PubMed

Hoffmann, René; Kriele, Armin; Obloh, Harald; Tokuda, Norio; Smirnov, Waldemar; Yang, Nianjun; Nebel, Christoph E

2011-10-01

Immobilization of proteins on a solid electrode is to date done by chemical cross-linking or by addition of an adjustable intermediate. In this paper we introduce a concept where a solid with variable surface properties is optimized to mediate binding of the electron-transfer protein Cytochrome c (Cyt c) by mimicking the natural binding environment. It is shown that, as a carbon-based material, boron-doped diamond can be adjusted by simple electrochemical surface treatments to the specific biochemical requirements of Cyt c. The structure and functionality of passively adsorbed Cyt c on variously terminated diamond surfaces were characterized in detail using a combination of electrochemical techniques and atomic force microscopy with single-molecule resolution. Partially oxidized diamond allowed stable immobilization of Cyt c together with high electron transfer activity, driven by a combination of electrostatic and hydrophobic interactions. This surface mimics the natural binding partner, where coarse orientation is governed by electrostatic interaction of the protein's dipole and hydrophobic interactions assist in formation of the electron transfer complex. The optimized surface mediated electron transfer kinetics around 100 times faster than those reported for other solids and even faster kinetics than on self-assembled monolayers of alkanethiols. Copyright © 2011 Elsevier Ltd. All rights reserved.

Single-molecule spectroscopy of the unexpected collapse of an unfolded protein at low pH

NASA Astrophysics Data System (ADS)

Hofmann, Hagen; Nettels, Daniel; Schuler, Benjamin

2013-09-01

The dimensions of intrinsically disordered and unfolded proteins critically depend on the solution conditions, such as temperature, pH, ionic strength, and osmolyte or denarurant concentration. However, a quantitative understanding of how the complex combination of chain-chain and chain-solvent interactions is affected by the solvent is still missing. Here, we take a step towards this goal by investigating the combined effect of pH and denaturants on the dimensions of an unfolded protein. We use single-molecule fluorescence spectroscopy to extract the dimensions of unfolded cold shock protein (CspTm) in mixtures of the denaturants urea and guanidinium chloride (GdmCl) at neutral and acidic pH. Surprisingly, even though a change in pH from 7 to 2.9 increases the net charge of CspTm from -3.8 to +10.2, the radius of gyration of the chain is very similar under both conditions, indicating that protonation of acidic side chains at low pH results in additional hydrophobic interactions. We use a simple shared binding site model that describes the joint effect of urea and GdmCl, together with polyampholyte theory and an ion cloud model that includes the chemical free energy of counterion interactions and side chain protonation, to quantify this effect.

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

PubMed

Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Complementary uses of small angle X-ray scattering and X-ray crystallography.

PubMed

Pillon, Monica C; Guarné, Alba

2017-11-01

Most proteins function within networks and, therefore, protein interactions are central to protein function. Although stable macromolecular machines have been extensively studied, dynamic protein interactions remain poorly understood. Small-angle X-ray scattering probes the size, shape and dynamics of proteins in solution at low resolution and can be used to study samples in a large range of molecular weights. Therefore, it has emerged as a powerful technique to study the structure and dynamics of biomolecular systems and bridge fragmented information obtained using high-resolution techniques. Here we review how small-angle X-ray scattering can be combined with other structural biology techniques to study protein dynamics. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.

An ALuc-Based Molecular Tension Probe for Sensing Intramolecular Protein-Protein Interactions.

PubMed

Kim, Sung-Bae; Nishihara, Ryo; Suzuki, Koji

2016-01-01

Optical imaging of protein-protein interactions (PPIs) facilitates comprehensive elucidation of intracellular molecular events. The present protocol demonstrates an optical measure for visualizing molecular tension triggered by any PPI in mammalian cells. A unique design of single-chain probes was fabricated, in which a full-length artificial luciferase (ALuc(®)) was sandwiched between two model proteins of interest, e.g., FKBP and FRB. A molecular tension probe comprising ALuc23 greatly enhances the bioluminescence in response to varying concentrations of rapamycin, and named "tension probe (TP)." The basic probe design can be further modified towards eliminating the C-terminal end of ALuc and was found to improve signal-to-background ratios, named "combinational probe." TPs may become an important addition to the tool box of bioassays in the determination of protein dynamics of interest in mammalian cells.

Prediction and functional analysis of the sweet orange protein-protein interaction network.

PubMed

Ding, Yu-Duan; Chang, Ji-Wei; Guo, Jing; Chen, Dijun; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Cheng, Yun-Jiang; Chen, Ling-Ling

2014-08-05

Sweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species. In this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The final predicted PPI network, CitrusNet, contained 8,195 proteins with 124,491 interactions. The quality of CitrusNet was evaluated using gene ontology (GO) and Mapman annotations, which confirmed the reliability of the network. In addition, we calculated the expression difference of interacting genes (EDI) in CitrusNet using RNA-seq data from four sweet orange tissues, and also analyzed the EDI distribution and variation in different sub-networks. Gene expression in CitrusNet has significant modular features. Target of rapamycin (TOR) protein served as the central node of the hormone-signaling sub-network. All evidence supported the idea that TOR can integrate various hormone signals and affect plant growth. CitrusNet provides valuable resources for the study of biological functions in sweet orange.

Regulation of Nucleocytoplasmic Shuttling of Bruton's Tyrosine Kinase (Btk) through a Novel SH3-Dependent Interaction with Ankyrin Repeat Domain 54 (ANKRD54)

PubMed Central

Hussain, Alamdar; Mohammad, Dara K.; Mohamed, Abdalla J.; Nguyen, Vivian; Metalnikov, Pavel; Colwill, Karen; Pawson, Tony; Nore, Beston F.

2012-01-01

Bruton's tyrosine kinase (Btk), belonging to the Tec family of tyrosine kinases (TFKs), is essential for B-lymphocyte development. Abrogation of Btk signaling causes human X-linked agammaglobulinemia (XLA) and murine X-linked immunodeficiency (Xid). We employed affinity purification of Flag-tagged Btk, combined with tandem mass spectrometry, to capture and identify novel interacting proteins. We here characterize the interaction with ankryin repeat domain 54 protein (ANKRD54), also known as Lyn-interacting ankyrin repeat protein (Liar). While Btk is a nucleocytoplasmic protein, the Liar pool was found to shuttle at a higher rate than Btk. Importantly, our results suggest that Liar mediates nuclear export of both Btk and another TFK, Txk/Rlk. Liar-mediated Btk shuttling was enriched for activation loop, nonphosphorylated Btk and entirely dependent on Btk's SH3 domain. Liar also showed reduced binding to an aspartic acid phosphomimetic SH3 mutant. Three other investigated nucleus-located proteins, Abl, estrogen receptor β (ERβ), and transcription factor T-bet, were all unaffected by Liar. We mapped the interaction site to the C terminus of the Btk SH3 domain. A biotinylated, synthetic Btk peptide, ARDKNGQEGYIPSNYVTEAEDS, was sufficient for this interaction. Liar is the first protein identified that specifically influences the nucleocytoplasmic shuttling of Btk and Txk and belongs to a rare group of known proteins carrying out this activity in a Crm1-dependent manner. PMID:22527282

[Intermolecular hydrogen bond between protein and flavonoid and its contribution to the stability of the flavonoids].

PubMed

Fang, Ru; Leng, Xiao-jing; Wu, Xia; Li, Qi; Hao, Rui-fang; Ren, Fa-zheng; Jing, Hao

2012-01-01

The interactions between three proteins (BSA, lysozyme and myoglobin) and three flavonoids (quercetin, kaempferol and rutin) were analyzed, using three-dimensional fluorescence spectrometry in combination with UV-Vis spectrometry and Fourier transform infrared (FTIR) spectroscopy. The stabilities of unbound flavonoids and protein-bound flavonoids were compared. The correlation between the interaction and stability was analyzed. The results showed that the hydrophobic interaction was the main binding code in all proteins and flavonoids systems. However, the hydrogen bond has been involved merely in the BSA system. The stability of all three flavonoids (quercetin, kaempferol and rutin) was improved by BSA. There was a great correlation between the hydrogen bonding and the stability of the flavonoids in the presence of BSA. It suggested that the protection of BSA on the flavonoids was due to the intermolecular hydrogen bonding between BSA and flavonoid, and the stronger hydrogen bonding resulted in more protection.

PHOTOSYNTHESIS. A 12 Å carotenoid translocation in a photoswitch associated with cyanobacterial photoprotection.

PubMed

Leverenz, Ryan L; Sutter, Markus; Wilson, Adjélé; Gupta, Sayan; Thurotte, Adrien; Bourcier de Carbon, Céline; Petzold, Christopher J; Ralston, Corie; Perreau, François; Kirilovsky, Diana; Kerfeld, Cheryl A

2015-06-26

Pigment-protein and pigment-pigment interactions are of fundamental importance to the light-harvesting and photoprotective functions essential to oxygenic photosynthesis. The orange carotenoid protein (OCP) functions as both a sensor of light and effector of photoprotective energy dissipation in cyanobacteria. We report the atomic-resolution structure of an active form of the OCP consisting of the N-terminal domain and a single noncovalently bound carotenoid pigment. The crystal structure, combined with additional solution-state structural data, reveals that OCP photoactivation is accompanied by a 12 angstrom translocation of the pigment within the protein and a reconfiguration of carotenoid-protein interactions. Our results identify the origin of the photochromic changes in the OCP triggered by light and reveal the structural determinants required for interaction with the light-harvesting antenna during photoprotection. Copyright © 2015, American Association for the Advancement of Science.

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

Protein-Water and Protein-Buffer Interactions in the Aqueous Solution of an Intrinsically Unstructured Plant Dehydrin: NMR Intensity and DSC Aspects

PubMed Central

Tompa, P.; Bánki, P.; Bokor, M.; Kamasa, P.; Kovács, D.; Lasanda, G.; Tompa, K.

2006-01-01

Proton NMR intensity and differential scanning calorimetry measurements were carried out on an intrinsically unstructured late embryogenesis abundant protein, ERD10, the globular BSA, and various buffer solutions to characterize water and ion binding of proteins by this novel combination of experimental approaches. By quantifying the number of hydration water molecules, the results demonstrate the interaction between the protein and NaCl and between buffer and NaCl on a microscopic level. The findings overall provide direct evidence that the intrinsically unstructured ERD10 not only has a high hydration capacity but can also bind a large amount of charged solute ions. In accord, the dehydration stress function of this protein probably results from its simultaneous action of retaining water in the drying cells and preventing an adverse increase in ionic strength, thus countering deleterious effects such as protein denaturation. PMID:16798808

Dual Coordination of Post Translational Modifications in Human Protein Networks

PubMed Central

Woodsmith, Jonathan; Kamburov, Atanas; Stelzl, Ulrich

2013-01-01

Post-translational modifications (PTMs) regulate protein activity, stability and interaction profiles and are critical for cellular functioning. Further regulation is gained through PTM interplay whereby modifications modulate the occurrence of other PTMs or act in combination. Integration of global acetylation, ubiquitination and tyrosine or serine/threonine phosphorylation datasets with protein interaction data identified hundreds of protein complexes that selectively accumulate each PTM, indicating coordinated targeting of specific molecular functions. A second layer of PTM coordination exists in these complexes, mediated by PTM integration (PTMi) spots. PTMi spots represent very dense modification patterns in disordered protein regions and showed an equally high mutation rate as functional protein domains in cancer, inferring equivocal importance for cellular functioning. Systematic PTMi spot identification highlighted more than 300 candidate proteins for combinatorial PTM regulation. This study reveals two global PTM coordination mechanisms and emphasizes dataset integration as requisite in proteomic PTM studies to better predict modification impact on cellular signaling. PMID:23505349

Structure elucidation of dimeric transmembrane domains of bitopic proteins.

PubMed

Bocharov, Eduard V; Volynsky, Pavel E; Pavlov, Konstantin V; Efremov, Roman G; Arseniev, Alexander S

2010-01-01

The interaction between transmembrane helices is of great interest because it directly determines biological activity of a membrane protein. Either destroying or enhancing such interactions can result in many diseases related to dysfunction of different tissues in human body. One much studied form of membrane proteins known as bitopic protein is a dimer containing two membrane-spanning helices associating laterally. Establishing structure-function relationship as well as rational design of new types of drugs targeting membrane proteins requires precise structural information about this class of objects. At present time, to investigate spatial structure and internal dynamics of such transmembrane helical dimers, several strategies were developed based mainly on a combination of NMR spectroscopy, optical spectroscopy, protein engineering and molecular modeling. These approaches were successfully applied to homo- and heterodimeric transmembrane fragments of several bitopic proteins, which play important roles in normal and in pathological conditions of human organism.

Impact of Protein-Metal Ion Interactions on the Crystallization of Silk Fibroin Protein

NASA Astrophysics Data System (ADS)

Hu, Xiao; Lu, Qiang; Kaplan, David; Cebe, Peggy

2009-03-01

Proteins can easily form bonds with a variety of metal ions, which provides many unique biological functions for the protein structures, and therefore controls the overall structural transformation of proteins. We use advanced thermal analysis methods such as temperature modulated differential scanning calorimetry and quasi-isothermal TMDSC, combined with Fourier transform infrared spectroscopy, and scanning electron microscopy, to investigate the protein-metallic ion interactions in Bombyx mori silk fibroin proteins. Silk samples were mixed with different metal ions (Ca^2+, K^+, Ma^2+, Na^+, Cu^2+, Mn^2+) with different mass ratios, and compared with the physical conditions in the silkworm gland. Results show that all metallic ions can directly affect the crystallization behavior and glass transition of silk fibroin. However, different ions tend to have different structural impact, including their role as plasticizer or anti-plasticizer. Detailed studies reveal important information allowing us better to understand the natural silk spinning and crystallization process.

Gα and regulator of G-protein signaling (RGS) protein pairs maintain functional compatibility and conserved interaction interfaces throughout evolution despite frequent loss of RGS proteins in plants.

PubMed

Hackenberg, Dieter; McKain, Michael R; Lee, Soon Goo; Roy Choudhury, Swarup; McCann, Tyler; Schreier, Spencer; Harkess, Alex; Pires, J Chris; Wong, Gane Ka-Shu; Jez, Joseph M; Kellogg, Elizabeth A; Pandey, Sona

2017-10-01

Signaling pathways regulated by heterotrimeric G-proteins exist in all eukaryotes. The regulator of G-protein signaling (RGS) proteins are key interactors and critical modulators of the Gα protein of the heterotrimer. However, while G-proteins are widespread in plants, RGS proteins have been reported to be missing from the entire monocot lineage, with two exceptions. A single amino acid substitution-based adaptive coevolution of the Gα:RGS proteins was proposed to enable the loss of RGS in monocots. We used a combination of evolutionary and biochemical analyses and homology modeling of the Gα and RGS proteins to address their expansion and its potential effects on the G-protein cycle in plants. Our results show that RGS proteins are widely distributed in the monocot lineage, despite their frequent loss. There is no support for the adaptive coevolution of the Gα:RGS protein pair based on single amino acid substitutions. RGS proteins interact with, and affect the activity of, Gα proteins from species with or without endogenous RGS. This cross-functional compatibility expands between the metazoan and plant kingdoms, illustrating striking conservation of their interaction interface. We propose that additional proteins or alternative mechanisms may exist which compensate for the loss of RGS in certain plant species. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

PubMed

Pandey, Naresh; Nobles, Christopher L; Zechiedrich, Lynn; Maresso, Anthony W; Silberg, Jonathan J

2015-05-15

Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein-protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein-protein interactions within whole animals.

Direct interaction of the Usher syndrome 1G protein SANS and myomegalin in the retina.

PubMed

Overlack, Nora; Kilic, Dilek; Bauss, Katharina; Märker, Tina; Kremer, Hannie; van Wijk, Erwin; Wolfrum, Uwe

2011-10-01

The human Usher syndrome (USH) is the most frequent cause of combined hereditary deaf-blindness. USH is genetically heterogeneous with at least 11 chromosomal loci assigned to 3 clinical types, USH1-3. We have previously demonstrated that all USH1 and 2 proteins in the eye and the inner ear are organized into protein networks by scaffold proteins. This has contributed essentially to our current understanding of the function of USH proteins and explains why defects in proteins of different families cause very similar phenotypes. We have previously shown that the USH1G protein SANS (scaffold protein containing ankyrin repeats and SAM domain) contributes to the periciliary protein network in retinal photoreceptor cells. This study aimed to further elucidate the role of SANS by identifying novel interaction partners. In yeast two-hybrid screens of retinal cDNA libraries we identified 30 novel putative interacting proteins binding to the central domain of SANS (CENT). We confirmed the direct binding of the phosphodiesterase 4D interacting protein (PDE4DIP), a Golgi associated protein synonymously named myomegalin, to the CENT domain of SANS by independent assays. Correlative immunohistochemical and electron microscopic analyses showed a co-localization of SANS and myomegalin in mammalian photoreceptor cells in close association with microtubules. Based on the present results we propose a role of the SANS-myomegalin complex in microtubule-dependent inner segment cargo transport towards the ciliary base of photoreceptor cells. Copyright © 2011 Elsevier B.V. All rights reserved.

Interaction of 4.1G and cGMP-gated channels in rod photoreceptor outer segments.

PubMed

Cheng, Christiana L; Molday, Robert S

2013-12-15

In photoreceptors, the assembly of signaling molecules into macromolecular complexes is important for phototransduction and maintaining the structural integrity of rod outer segments (ROSs). However, the molecular composition and formation of these complexes are poorly understood. Using immunoprecipitation and mass spectrometry, 4.1G was identified as a new interacting partner for the cyclic-nucleotide gated (CNG) channels in ROSs. 4.1G is a widely expressed multifunctional protein that plays a role in the assembly and stability of membrane protein complexes. Multiple splice variants of 4.1G were cloned from bovine retina. A smaller splice variant of 4.1G selectively interacted with CNG channels not associated with peripherin-2-CNG channel complex. A combination of truncation studies and domain-binding assays demonstrated that CNG channels selectively interacted with 4.1G through their FERM and CTD domains. Using immunofluorescence, labeling of 4.1G was seen to be punctate and partially colocalized with CNG channels in the ROS. Our studies indicate that 4.1G interacts with a subset of CNG channels in the ROS and implicate this protein-protein interaction in organizing the spatial arrangement of CNG channels in the plasma membrane of outer segments.

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

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

PubMed

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

α/β-Peptide Foldamers Targeting Intracellular Protein-Protein Interactions with Activity in Living Cells

PubMed Central

Checco, James W.; Lee, Erinna F.; Evangelista, Marco; Sleebs, Nerida J.; Rogers, Kelly; Pettikiriarachchi, Anne; Kershaw, Nadia J.; Eddinger, Geoffrey A.; Belair, David G.; Wilson, Julia L.; Eller, Chelcie H.; Raines, Ronald T.; Murphy, William L.; Smith, Brian J.; Gellman, Samuel H.; Fairlie, W. Douglas

2015-01-01

Peptides can be developed as effective antagonists of protein-protein interactions, but conventional peptides (i.e., oligomers of L-α-amino acids) suffer from significant limitations in vivo. Short half-lives due to rapid proteolytic degradation and an inability to cross cell membranes often preclude biological applications of peptides. Oligomers that contain both α- and β-amino acid residues (“α/β-peptides”) manifest decreased susceptibility to proteolytic degradation, and when properly designed these unnatural oligomers can mimic the protein-recognition properties of analogous “α-peptides”. This report documents an extension of the α/β-peptide approach to target intracellular protein-protein interactions. Specifically, we have generated α/β-peptides based on a “stapled” Bim BH3 α-peptide, which contains a hydrocarbon crosslink to enhance α-helix stability. We show that a stapled α/β-peptide can structurally and functionally mimic the parent stapled α-peptide in its ability to enter certain types of cells and block protein-protein interactions associated with apoptotic signaling. However, the α/β-peptide is nearly 100-fold more resistant to proteolysis than is the parent α-peptide. These results show that backbone modification, a strategy that has received relatively little attention in terms of peptide engineering for biomedical applications, can be combined with more commonly deployed peripheral modifications such as side chain crosslinking to produce synergistic benefits. PMID:26317395

α/β-Peptide Foldamers Targeting Intracellular Protein-Protein Interactions with Activity in Living Cells.

PubMed

Checco, James W; Lee, Erinna F; Evangelista, Marco; Sleebs, Nerida J; Rogers, Kelly; Pettikiriarachchi, Anne; Kershaw, Nadia J; Eddinger, Geoffrey A; Belair, David G; Wilson, Julia L; Eller, Chelcie H; Raines, Ronald T; Murphy, William L; Smith, Brian J; Gellman, Samuel H; Fairlie, W Douglas

2015-09-09

Peptides can be developed as effective antagonists of protein-protein interactions, but conventional peptides (i.e., oligomers of l-α-amino acids) suffer from significant limitations in vivo. Short half-lives due to rapid proteolytic degradation and an inability to cross cell membranes often preclude biological applications of peptides. Oligomers that contain both α- and β-amino acid residues ("α/β-peptides") manifest decreased susceptibility to proteolytic degradation, and when properly designed these unnatural oligomers can mimic the protein-recognition properties of analogous "α-peptides". This report documents an extension of the α/β-peptide approach to target intracellular protein-protein interactions. Specifically, we have generated α/β-peptides based on a "stapled" Bim BH3 α-peptide, which contains a hydrocarbon cross-link to enhance α-helix stability. We show that a stapled α/β-peptide can structurally and functionally mimic the parent stapled α-peptide in its ability to enter certain types of cells and block protein-protein interactions associated with apoptotic signaling. However, the α/β-peptide is nearly 100-fold more resistant to proteolysis than is the parent stapled α-peptide. These results show that backbone modification, a strategy that has received relatively little attention in terms of peptide engineering for biomedical applications, can be combined with more commonly deployed peripheral modifications such as side chain cross-linking to produce synergistic benefits.

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

The genetic landscape of a physical interaction

PubMed Central

Diss, Guillaume

2018-01-01

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions. PMID:29638215

Integration of cell-free protein coexpression with an enzyme-linked immunosorbent assay enables rapid analysis of protein–protein interactions directly from DNA

PubMed Central

Layton, Curtis J; Hellinga, Homme W

2011-01-01

Assays that integrate detection of binding with cell-free protein expression directly from DNA can dramatically increase the pace at which protein–protein interactions (PPIs) can be analyzed by mutagenesis. In this study, we present a method that combines in vitro protein production with an enzyme-linked immunosorbent assay (ELISA) to measure PPIs. This method uses readily available commodity instrumentation and generic antibody–affinity tag interactions. It is straightforward and rapid to execute, enabling many interactions to be assessed in parallel. In traditional ELISAs, reporter complexes are assembled stepwise with one layer at a time. In the method presented here, all the members of the reporter complex are present and assembled together. The signal strength is dependent on all the intercomponent interaction affinities and concentrations. Although this assay is straightforward to execute, establishing proper conditions and analysis of the results require a thorough understanding of the processes that determine the signal strength. The formation of the fully assembled reporter sandwich can be modeled as a competition between Langmuir adsorption isotherms for the immobilized components and binding equilibria of the solution components. We have shown that modeling this process provides semiquantitative understanding of the effects of affinity and concentration and can guide strategies for the development of experimental protocols. We tested the method experimentally using the interaction between a synthetic ankyrin repeat protein (Off7) and maltose-binding protein. Measurements obtained for a collection of alanine mutations in the interface between these two proteins demonstrate that a range of affinities can be analyzed. PMID:21674663

Identifying interacting proteins of a Caenorhabditis elegans voltage-gated chloride channel CLH-1 using GFP-Trap and mass spectrometry.

PubMed

Zhou, Zi-Liang; Jiang, Jing; Yin, Jiang-An; Cai, Shi-Qing

2014-06-25

Chloride channels belong to a superfamily of ion channels that permit passive passage of anions, mainly chloride, across cell membrane. They play a variety of important physiological roles in regulation of cytosolic pH, cell volume homeostasis, organic solute transport, cell migration, cell proliferation, and differentiation. However, little is known about the functional regulation of these channels. In this study, we generated an integrated transgenic worm strain expressing green fluorescence protein (GFP) fused CLC-type chloride channel 1 (CLH-1::GFP), a voltage-gated chloride channel in Caenorhabditis elegans (C. elegans). CLH-1::GFP was expressed in some unidentified head neurons and posterior intestinal cells of C. elegans. Interacting proteins of CLH-1::GFP were purified by GFP-Trap, a novel system for efficient isolation of GFP fusion proteins and their interacting factors. Mass spectrometry (MS) analysis revealed that a total of 27 high probability interacting proteins were co-trapped with CLHp-1::GFP. Biochemical evidence showed that eukaryotic translation elongation factor 1 (EEF-1), one of these co-trapped proteins identified by MS, physically interacted with CLH-1, in consistent with GFP-Trap experiments. Further immunostaining data revealed that the protein level of CLH-1 was significantly increased upon co-expression with EEF-1. These results suggest that the combination of GFP-Trap purification with MS is an excellent tool to identify novel interacting proteins of voltage-gated chloride channels in C. elegans. Our data also show that EEF-1 is a regulator of voltage-gated chloride channel CLH-1.

Solid-state NMR spectroscopy of 18.5 kDa myelin basic protein reconstituted with lipid vesicles: spectroscopic characterisation and spectral assignments of solvent-exposed protein fragments.

PubMed

Zhong, Ligang; Bamm, Vladimir V; Ahmed, Mumdooh A M; Harauz, George; Ladizhansky, Vladimir

2007-12-01

Myelin basic protein (MBP, 18.5 kDa isoform) is a peripheral membrane protein that is essential for maintaining the structural integrity of the multilamellar myelin sheath of the central nervous system. Reconstitution of the most abundant 18.5 kDa MBP isoform with lipid vesicles yields an aggregated assembly mimicking the protein's natural environment, but which is not amenable to standard solution NMR spectroscopy. On the other hand, the mobility of MBP in such a system is variable, depends on the local strength of the protein-lipid interaction, and in general is of such a time scale that the dipolar interactions are averaged out. Here, we used a combination of solution and solid-state NMR (ssNMR) approaches: J-coupling-driven polarization transfers were combined with magic angle spinning and high-power decoupling to yield high-resolution spectra of the mobile fragments of 18.5 kDa murine MBP in membrane-associated form. To partially circumvent the problem of short transverse relaxation, we implemented three-dimensional constant-time correlation experiments (NCOCX, NCACX, CONCACX, and CAN(CO)CX) that were able to provide interresidue and intraresidue backbone correlations. These experiments resulted in partial spectral assignments for mobile fragments of the protein. Additional nuclear Overhauser effect spectroscopy (NOESY)-based experiments revealed that the mobile fragments were exposed to solvent and were likely located outside the lipid bilayer, or in its hydrophilic portion. Chemical shift index analysis showed that the fragments were largely disordered under these conditions. These combined approaches are applicable to ssNMR investigations of other peripheral membrane proteins reconstituted with lipids.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family.

PubMed

Danisman, Selahattin; van Dijk, Aalt D J; Bimbo, Andrea; van der Wal, Froukje; Hennig, Lars; de Folter, Stefan; Angenent, Gerco C; Immink, Richard G H

2013-12-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein-protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein-protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family.

Investigation of the molecular interactions between beta-lactoglobulin and low methoxyl pectin by multi-detection high performance size exclusion chromatography

USDA-ARS?s Scientific Manuscript database

Combining milk proteins and polysaccharides may result in new food ingredients with enhanced properties, compared to the single protein or polysaccharide, that are especially useful for improving the nutritional value, textural properties and stability of foods. However, formulations of these ingre...

Protein discovery: combined transcriptomic and proteomic analyses of venom from the endoparasitoid Cotesia chilonis (Hymenoptera: Brachonidae)

USDA-ARS?s Scientific Manuscript database

Background: Many species of endoparasitoid wasps provide biological control services in agroecosystems. Although there is a great deal of information on the ecology and physiology of host/parasitoid interactions, relatively little is known on the protein composition of venom and how specific venom p...

Electrostatic and dispersion interactions during protein adsorption on topographic nanostructures.

PubMed

Elter, Patrick; Lange, Regina; Beck, Ulrich

2011-07-19

Recently, biomaterials research has focused on developing functional implant surfaces with well-defined topographic nanostructures in order to influence protein adsorption and cellular behavior. To enhance our understanding of how proteins interact with such surfaces, we analyze the adsorption of lysozyme on an oppositely charged nanostructure using a computer simulation. We present an algorithm that combines simulated Brownian dynamics with numerical field calculation methods to predict the preferred adsorption sites for arbitrarily shaped substrates. Either proteins can be immobilized at their initial adsorption sites or surface diffusion can be considered. Interactions are analyzed on the basis of Derjaguin-Landau-Verway-Overbeek (DLVO) theory, including electrostatic and London dispersion forces, and numerical solutions are derived using the Poisson-Boltzmann and Hamaker equations. Our calculations show that for a grooved nanostructure (i.e., groove and plateau width 8 nm, height 4 nm), proteins first contact the substrate primarily near convex edges because of better geometric accessibility and increased electric field strengths. Subsequently, molecules migrate by surface diffusion into grooves and concave corners, where short-range dispersion interactions are maximized. In equilibrium, this mechanism leads to an increased surface protein concentration in the grooves, demonstrating that the total amount of protein per surface area can be increased if substrates have concave nanostructures.

Identification of potential novel interaction partners of the sodium-activated potassium channels Slick and Slack in mouse brain.

PubMed

Rizzi, Sandra; Schwarzer, Christoph; Kremser, Leopold; Lindner, Herbert H; Knaus, Hans-Günther

2015-12-01

The sodium-activated potassium channels Slick (Slo2.1, KCNT2) and Slack (Slo2.2, KCNT1) are paralogous channels of the Slo family of high-conductance potassium channels. Slick and Slack channels are widely distributed in the mammalian CNS and they play a role in slow afterhyperpolarization, generation of depolarizing afterpotentials and in setting and stabilizing the resting potential. In the present study we used a combined approach of (co)-immunoprecipitation studies, Western blot analysis, double immunofluorescence and mass spectrometric sequencing in order to investigate protein-protein interactions of the Slick and Slack channels. The data strongly suggest that Slick and Slack channels co-assemble into identical cellular complexes. Double immunofluorescence experiments revealed that Slick and Slack channels co-localize in distinct mouse brain regions. Moreover, we identified the small cytoplasmic protein beta-synuclein and the transmembrane protein 263 (TMEM 263) as novel interaction partners of both, native Slick and Slack channels. In addition, the inactive dipeptidyl-peptidase (DPP 10) and the synapse associated protein 102 (SAP 102) were identified as constituents of the native Slick and Slack channel complexes in the mouse brain. This study presents new insights into protein-protein interactions of native Slick and Slack channels in the mouse brain.

An automated decision-tree approach to predicting protein interaction hot spots.

PubMed

Darnell, Steven J; Page, David; Mitchell, Julie C

2007-09-01

Protein-protein interactions can be altered by mutating one or more "hot spots," the subset of residues that account for most of the interface's binding free energy. The identification of hot spots requires a significant experimental effort, highlighting the practical value of hot spot predictions. We present two knowledge-based models that improve the ability to predict hot spots: K-FADE uses shape specificity features calculated by the Fast Atomic Density Evaluation (FADE) program, and K-CON uses biochemical contact features. The combined K-FADE/CON (KFC) model displays better overall predictive accuracy than computational alanine scanning (Robetta-Ala). In addition, because these methods predict different subsets of known hot spots, a large and significant increase in accuracy is achieved by combining KFC and Robetta-Ala. The KFC analysis is applied to the calmodulin (CaM)/smooth muscle myosin light chain kinase (smMLCK) interface, and to the bone morphogenetic protein-2 (BMP-2)/BMP receptor-type I (BMPR-IA) interface. The results indicate a strong correlation between KFC hot spot predictions and mutations that significantly reduce the binding affinity of the interface. 2007 Wiley-Liss, Inc.

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PubMed Central

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

PubMed

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

A New Method, "Reverse Yeast Two-Hybrid Array" (RYTHA), Identifies Mutants that Dissociate the Physical Interaction Between Elg1 and Slx5.

PubMed

Lev, Ifat; Shemesh, Keren; Volpe, Marina; Sau, Soumitra; Levinton, Nelly; Molco, Maya; Singh, Shivani; Liefshitz, Batia; Ben Aroya, Shay; Kupiec, Martin

2017-07-01

The vast majority of processes within the cell are carried out by proteins working in conjunction. The Yeast Two-Hybrid (Y2H) methodology allows the detection of physical interactions between any two interacting proteins. Here, we describe a novel systematic genetic methodology, "Reverse Yeast Two-Hybrid Array" (RYTHA), that allows the identification of proteins required for modulating the physical interaction between two given proteins. Our assay starts with a yeast strain in which the physical interaction of interest can be detected by growth on media lacking histidine, in the context of the Y2H methodology. By combining the synthetic genetic array technology, we can systematically screen mutant libraries of the yeast Saccharomyces cerevisiae to identify trans -acting mutations that disrupt the physical interaction of interest. We apply this novel method in a screen for mutants that disrupt the interaction between the N-terminus of Elg1 and the Slx5 protein. Elg1 is part of an alternative replication factor C-like complex that unloads PCNA during DNA replication and repair. Slx5 forms, together with Slx8, a SUMO-targeted ubiquitin ligase (STUbL) believed to send proteins to degradation. Our results show that the interaction requires both the STUbL activity and the PCNA unloading by Elg1, and identify topoisomerase I DNA-protein cross-links as a major factor in separating the two activities. Thus, we demonstrate that RYTHA can be applied to gain insights about particular pathways in yeast, by uncovering the connection between the proteasomal ubiquitin-dependent degradation pathway, DNA replication, and repair machinery, which can be separated by the topoisomerase-mediated cross-links to DNA. Copyright © 2017 by the Genetics Society of America.

Effects of arginine on heat-induced aggregation of concentrated protein solutions.

PubMed

Shah, Dhawal; Shaikh, Abdul Rajjak; Peng, Xinxia; Rajagopalan, Raj

2011-01-01

Arginine is one of the commonly used additives to enhance refolding yield of proteins, to suppress aggregation of proteins, and to increase solubility of proteins, and yet the molecular interactions that contribute to the role of arginine are unclear. Here, we present experiments, using bovine serum albumin (BSA), lysozyme (LYZ), and β-lactoglobulin (BLG) as model proteins, to show that arginine can enhance heat-induced aggregation of concentrated protein solutions, contrary to the conventional belief that arginine is a universal suppressor of aggregation. Results show that the enhancement in aggregation is caused only for BSA and BLG, but not for LYZ, indicating that arginine's preferential interactions with certain residues over others could determine the effect of the additive on aggregation. We use this previously unrecognized behavior of arginine, in combination with density functional theory calculations, to identify the molecular-level interactions of arginine with various residues that determine arginine's role as an enhancer or suppressor of aggregation of proteins. The experimental and computational results suggest that the guanidinium group of arginine promotes aggregation through the hydrogen-bond-based bridging interactions with the acidic residues of a protein, whereas the binding of the guanidinium group to aromatic residues (aggregation-prone) contributes to the stability and solubilization of the proteins. The approach, we describe here, can be used to select suitable additives to stabilize a protein solution at high concentrations based on an analysis of the amino acid content of the protein. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

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

Klopffleisch, Karsten; Phan, Nguyen; Chen, Jay

2011-01-01

The heterotrimeric G-protein complex is minimally composed of G{alpha}, G{beta}, and G{gamma} subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, wemore » detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.« less

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis.

PubMed

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-09-27

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

PubMed Central

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-01-01

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification. PMID:21952135

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model.

PubMed

Sjöholm, Kristoffer; Kilsgård, Ola; Teleman, Johan; Happonen, Lotta; Malmström, Lars; Malmström, Johan

2017-04-01

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Protein-like Nanoparticles Based on Orthogonal Self-Assembly of Chimeric Peptides.

PubMed

Jiang, Linhai; Xu, Dawei; Namitz, Kevin E; Cosgrove, Michael S; Lund, Reidar; Dong, He

2016-10-01

A novel two-component self-assembling chimeric peptide is designed where two orthogonal protein folding motifs are linked side by side with precisely defined position relative to one another. The self-assembly is driven by a combination of symmetry controlled molecular packing, intermolecular interactions, and geometric constraint to limit the assembly into compact dodecameric protein nanoparticles. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Membrane receptor location defines receptor interaction with signaling proteins in a polarized epithelium.

PubMed

Amsler, K; Kuwada, S K

1999-01-01

Signal transduction from receptors is mediated by the interaction of activated receptors with proximate downstream signaling proteins. In polarized epithelial cells, the membrane is divided into subdomains: the apical and basolateral membranes. Membrane receptors may be present in one or both subdomains. Using a combination of immunoprecipitation and Western blot analyses, we tested the hypothesis that a tyrosine kinase growth factor receptor, epidermal growth factor receptor (EGFR), interacts with distinct signaling proteins when present at the apical vs. basolateral membrane of a polarized renal epithelial cell. We report here that tyrosine phosphorylation of phospholipase C-gamma (PLC-gamma) was induced only when basolateral EGFR was activated. In contrast, tyrosine phosphorylation of several other signaling proteins was increased by activation of receptor at either surface. All signaling proteins were distributed diffusely throughout the cytoplasm; however, PLC-gamma protein also displayed a concentration at lateral cell borders. These results demonstrate that in polarized epithelial cells the array of signaling pathways initiated by activation of a membrane receptor is defined, at least in part, by the membrane location of the receptor.

Combining Random Gene Fission and Rational Gene Fusion To Discover Near-Infrared Fluorescent Protein Fragments That Report on Protein–Protein Interactions

PubMed Central

2015-01-01

Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein–protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein–protein interactions within whole animals. PMID:25265085

PAXIP1 potentiates the combination of WEE1 inhibitor AZD1775 and platinum agents in lung cancer

PubMed Central

Jhuraney, Ankita; Woods, Nicholas T.; Wright, Gabriela; Rix, Lily; Kinose, Fumi; Kroeger, Jodi L.; Remily-Wood, Elizabeth; Cress, W. Douglas; Koomen, John M.; Brantley, Stephen G.; Gray, Jhanelle E.; Haura, Eric B.; Rix, Uwe; Monteiro, Alvaro N.

2016-01-01

The DNA damage response (DDR) involves a complex network of signaling events mediated by modular protein domains such as the BRCT (BRCA1 C-terminal) domain. Thus, proteins that interact with BRCT domains and are a part of the DDR constitute potential targets for sensitization to DNA damaging chemotherapy agents. We performed a pharmacological screen to evaluate seventeen kinases, identified in a BRCT-mediated interaction network as targets to enhance platinum-based chemotherapy in lung cancer. Inhibition of mitotic kinase WEE1 was found to have the most effective response in combination with platinum compounds in lung cancer cell lines. In the BRCT-mediated interaction network, WEE1 was found in complex with PAXIP1, a protein containing six BRCT domains involved in transcription and in the cellular response to DNA damage. We show that PAXIP1 BRCT domains regulate WEE1-mediated phosphorylation of CDK1. Further, ectopic expression of PAXIP1 promotes enhanced caspase 3-mediated apoptosis in cells treated with WEE1 inhibitor AZD1775 (formerly, MK-1775) and cisplatin compared with cells treated with AZD1775 alone. Cell lines and patient-derived xenograft models expressing both PAXIP1 and WEE1 exhibited synergistic effects of AZD1775 and cisplatin. In summary, PAXIP1 is involved in sensitizing lung cancer cells to the WEE1 inhibitor AZD1775 in combination with platinum-based treatment. We propose that WEE1 and PAXIP1 levels may be used as mechanism-based biomarkers of response when WEE1 inhibitor AZD1775 is combined with DNA damaging agents. PMID:27196765

Identification of differentially accumulated proteins involved in regulating independent and combined osmosis and cadmium stress response in Brachypodium seedling roots.

PubMed

Chen, Ziyan; Zhu, Dong; Wu, Jisu; Cheng, Zhiwei; Yan, Xing; Deng, Xiong; Yan, Yueming

2018-05-17

In this study, we aimed to identify differentially accumulated proteins (DAPs) involved in PEG mock osmotic stress, cadmium (Cd 2+ ) stress, and their combined stress responses in Brachypodium distachyon seedling roots. The results showed that combined PEG and Cd 2+ stresses had more significant effects on Brachypodium seedling root growth, physiological traits, and ultrastructures when compared with each individual stress. Totally, 106 DAPs were identified that are responsive to individual and combined stresses in roots. These DAPs were mainly involved in energy metabolism, detoxification and stress defense and protein metabolism. Principal component analysis revealed that DAPs from Cd 2+ and combined stress treatments were grouped closer than those from osmotic stress treatment, indicating that Cd 2+ and combined stresses had more severe influences on the root proteome than osmotic stress alone. Protein-protein interaction analyses highlighted a 14-3-3 centered sub-network that synergistically responded to osmotic and Cd 2+ stresses and their combined stresses. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis of 14 key DAP genes revealed that most genes showed consistency between transcriptional and translational expression patterns. A putative pathway of proteome metabolic changes in Brachypodium seedling roots under different stresses was proposed, which revealed a complicated synergetic responsive network of plant roots to adverse environments.

Combining blue native polyacrylamide gel electrophoresis with liquid chromatography tandem mass spectrometry as an effective strategy for analyzing potential membrane protein complexes of Mycobacterium bovis bacillus Calmette-Guérin

PubMed Central

2011-01-01

Background Tuberculosis is an infectious bacterial disease in humans caused primarily by Mycobacterium tuberculosis, and infects one-third of the world's total population. Mycobacterium bovis bacillus Calmette-Guérin (BCG) vaccine has been widely used to prevent tuberculosis worldwide since 1921. Membrane proteins play important roles in various cellular processes, and the protein-protein interactions involved in these processes may provide further information about molecular organization and cellular pathways. However, membrane proteins are notoriously under-represented by traditional two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and little is known about mycobacterial membrane and membrane-associated protein complexes. Here we investigated M. bovis BCG by an alternative proteomic strategy coupling blue native PAGE to liquid chromatography tandem mass spectrometry (LC-MS/MS) to characterize potential protein-protein interactions in membrane fractions. Results Using this approach, we analyzed native molecular composition of protein complexes in BCG membrane fractions. As a result, 40 proteins (including 12 integral membrane proteins), which were organized in 9 different gel bands, were unambiguous identified. The proteins identified have been experimentally confirmed using 2-D SDS PAGE. We identified MmpL8 and four neighboring proteins that were involved in lipid transport complexes, and all subunits of ATP synthase complex in their monomeric states. Two phenolpthiocerol synthases and three arabinosyltransferases belonging to individual operons were obtained in different gel bands. Furthermore, two giant multifunctional enzymes, Pks7 and Pks8, and four mycobacterial Hsp family members were determined. Additionally, seven ribosomal proteins involved in polyribosome complex and two subunits of the succinate dehydrogenase complex were also found. Notablely, some proteins with high hydrophobicity or multiple transmembrane helixes were identified well in our work. Conclusions In this study, we utilized LC-MS/MS in combination with blue native PAGE to characterize modular components of multiprotein complexes in BCG membrane fractions. The results demonstrated that the proteomic strategy was a reliable and reproducible tool for analysis of BCG multiprotein complexes. The identification in our study may provide some evidence for further study of BCG protein interaction. PMID:21241518

PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation.

PubMed

Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei

2016-09-01

Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Insulin Regulates Astrocytic Glucose Handling Through Cooperation With IGF-I.

PubMed

Fernandez, Ana M; Hernandez-Garzón, Edwin; Perez-Domper, Paloma; Perez-Alvarez, Alberto; Mederos, Sara; Matsui, Takashi; Santi, Andrea; Trueba-Saiz, Angel; García-Guerra, Lucía; Pose-Utrilla, Julia; Fielitz, Jens; Olson, Eric N; Fernandez de la Rosa, Ruben; Garcia Garcia, Luis; Pozo, Miguel Angel; Iglesias, Teresa; Araque, Alfonso; Soya, Hideaki; Perea, Gertrudis; Martin, Eduardo D; Torres Aleman, Ignacio

2017-01-01

Brain activity requires a flux of glucose to active regions to sustain increased metabolic demands. Insulin, the main regulator of glucose handling in the body, has been traditionally considered not to intervene in this process. However, we now report that insulin modulates brain glucose metabolism by acting on astrocytes in concert with IGF-I. The cooperation of insulin and IGF-I is needed to recover neuronal activity after hypoglycemia. Analysis of underlying mechanisms show that the combined action of IGF-I and insulin synergistically stimulates a mitogen-activated protein kinase/protein kinase D pathway resulting in translocation of GLUT1 to the cell membrane through multiple protein-protein interactions involving the scaffolding protein GAIP-interacting protein C terminus and the GTPase RAC1. Our observations identify insulin-like peptides as physiological modulators of brain glucose handling, providing further support to consider the brain as a target organ in diabetes. © 2017 by the American Diabetes Association.

Molecular dynamics simulations of the adsorption of bone morphogenetic protein-2 on surfaces with medical relevance.

PubMed

Utesch, Tillmann; Daminelli, Grazia; Mroginski, Maria Andrea

2011-11-01

Bone morphogenetic protein-2 (BMP-2) plays a crucial role in osteoblast differentiation and proliferation. Its effective therapeutic use for ectopic bone and cartilage regeneration depends, among other factors, on the interaction with the carrier at the implant site. In this study, we used classical molecular dynamics (MD) and a hybrid approach of steered molecular dynamics (SMD) combined with MD simulations to investigate the initial stages of the adsorption of BMP-2 when approaching two implant surfaces, hydrophobic graphite and hydrophilic titanium dioxide rutile. Surface adsorption was evaluated for six different orientations of the protein, two end-on and four side-on, in explicit water environment. On graphite, we observed a weak but stable adsorption. Depending on the initial orientation, hydrophobic patches as well as flexible loops of the protein were involved in the interaction with graphite. On the contrary, BMP-2 adsorbed only loosely to hydrophilic titanium dioxide. Despite a favorable interaction energy between protein and the TiO(2) surface, the rapid formation of a two-layer water structure prevented the direct interaction between protein and titanium dioxide. The first water adlayer had a strong repulsive effect on the protein, while the second attracted the protein toward the surface. For both surfaces, hydrophobic graphite and hydrophilic titanium dioxide, denaturation of BMP-2 induced by adsorption was not observed on the nanosecond time scale.

Atomic force microscopy and force spectroscopy on the assessment of protein folding and functionality.

PubMed

Carvalho, Filomena A; Martins, Ivo C; Santos, Nuno C

2013-03-01

Atomic force microscopy (AFM) applied to biological systems can, besides generating high-quality and well-resolved images, be employed to study protein folding via AFM-based force spectroscopy. This approach allowed remarkable advances in the measurement of inter- and intramolecular interaction forces with piconewton resolution. The detection of specific interaction forces between molecules based on the AFM sensitivity and the manipulation of individual molecules greatly advanced the understanding of intra-protein and protein-ligand interactions. Apart from the academic interest in the resolution of basic scientific questions, this technique has also key importance on the clarification of several biological questions of immediate biomedical relevance. Force spectroscopy is an especially appropriate technique for "mechanical proteins" that can provide crucial information on single protein molecules and/or domains. Importantly, it also has the potential of combining in a single experiment spatial and kinetic measurements. Here, the main principles of this methodology are described, after which the ability to measure interactions at the single-molecule level is discussed, in the context of relevant protein-folding examples. We intend to demonstrate the potential of AFM-based force spectroscopy in the study of protein folding, especially since this technique is able to circumvent some of the difficulties typically encountered in classical thermal/chemical denaturation studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Interaction of S-layer proteins of Lactobacillus kefir with model membranes and cells.

PubMed

Hollmann, Axel; Delfederico, Lucrecia; Santos, Nuno C; Disalvo, E Anibal; Semorile, Liliana

2018-06-01

In previous works, it was shown that S-layer proteins from Lactobacillus kefir were able to recrystallize and stabilize liposomes, this feature reveling a great potential for developing liposomal-based carriers. Despite previous studies on this subject are important milestones, a number of questions remain unanswered. In this context, the feasibility of S-layer proteins as a biomaterial for drug delivery was evaluated in this work. First, S-layer proteins were fully characterized by electron microscopy, 2D-electrophoresis, and anionic exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD). Afterward, interactions of S-layer proteins with model lipid membranes were evaluated, showing that proteins adsorb to the lipid surface following a non-fickean or anomalous diffusion, when positively charged lipid were employed, suggesting that electrostatic interaction is a key factor in the recrystallization process on these proteins. Finally, the interaction of S-layer coated liposomes with Caco-2 cell line was assessed: First, cytotoxicity of formulations was tested showing no cytotoxic effects in S-layer coated vesicles. Second, by flow cytometry, it was observed an increased ability to transfer cargo molecules into Caco-2 cells from S-layer coated liposomes in comparison to control ones. All data put together, supports the idea that a combination of adhesive properties of S-layer proteins concomitant with higher stability of S-layer coated liposomes represents an exciting starting point in the development of new drug carriers.

Aldolase directly interacts with ARNO and modulates cell morphology and acidic vesicle distribution

PubMed Central

Merkulova, Maria; Hurtado-Lorenzo, Andrés; Hosokawa, Hiroyuki; Zhuang, Zhenjie; Brown, Dennis; Ausiello, Dennis A.

2011-01-01

Previously, we demonstrated that the vacuolar-type H+-ATPase (V-ATPase) a2-subunit functions as an endosomal pH sensor that interacts with the ADP-ribosylation factor (Arf) guanine nucleotide exchange factor, ARNO. In the present study, we showed that ARNO directly interacts not only with the a2-subunit but with all a-isoforms (a1–a4) of the V-ATPase, indicating a widespread regulatory interaction between V-ATPase and Arf GTPases. We then extended our search for other ARNO effectors that may modulate V-ATPase-dependent vesicular trafficking events and actin cytoskeleton remodeling. Pull-down experiments using cytosol of mouse proximal tubule cells (MTCs) showed that ARNO interacts with aldolase, but not with other enzymes of the glycolytic pathway. Direct interaction of aldolase with the pleckstrin homology domain of ARNO was revealed by pull-down assays using recombinant proteins, and surface plasmon resonance revealed their high avidity interaction with a dissociation constant: KD = 2.84 × 10−10 M. MTC cell fractionation revealed that aldolase is also associated with membranes of early endosomes. Functionally, aldolase knockdown in HeLa cells produced striking morphological changes accompanied by long filamentous cell protrusions and acidic vesicle redistribution. However, the 50% knockdown we achieved did not modulate the acidification capacity of endosomal/lysosomal compartments. Finally, a combination of small interfering RNA knockdown and overexpression revealed that the expression of aldolase is inversely correlated with gelsolin levels in HeLa cells. In summary, we have shown that aldolase forms a complex with ARNO/Arf6 and the V-ATPase and that it may contribute to remodeling of the actin cytoskeleton and/or the trafficking and redistribution of V-ATPase-dependent acidic compartments via a combination of protein-protein interaction and gene expression mechanisms. PMID:21307348

Establishment of a protein frequency library and its application in the reliable identification of specific protein interaction partners.

PubMed

Boulon, Séverine; Ahmad, Yasmeen; Trinkle-Mulcahy, Laura; Verheggen, Céline; Cobley, Andy; Gregor, Peter; Bertrand, Edouard; Whitehorn, Mark; Lamond, Angus I

2010-05-01

The reliable identification of protein interaction partners and how such interactions change in response to physiological or pathological perturbations is a key goal in most areas of cell biology. Stable isotope labeling with amino acids in cell culture (SILAC)-based mass spectrometry has been shown to provide a powerful strategy for characterizing protein complexes and identifying specific interactions. Here, we show how SILAC can be combined with computational methods drawn from the business intelligence field for multidimensional data analysis to improve the discrimination between specific and nonspecific protein associations and to analyze dynamic protein complexes. A strategy is shown for developing a protein frequency library (PFL) that improves on previous use of static "bead proteomes." The PFL annotates the frequency of detection in co-immunoprecipitation and pulldown experiments for all proteins in the human proteome. It can provide a flexible and objective filter for discriminating between contaminants and specifically bound proteins and can be used to normalize data values and facilitate comparisons between data obtained in separate experiments. The PFL is a dynamic tool that can be filtered for specific experimental parameters to generate a customized library. It will be continuously updated as data from each new experiment are added to the library, thereby progressively enhancing its utility. The application of the PFL to pulldown experiments is especially helpful in identifying either lower abundance or less tightly bound specific components of protein complexes that are otherwise lost among the large, nonspecific background.

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.

Structural Disorder within Henipavirus Nucleoprotein and Phosphoprotein: From Predictions to Experimental Assessment

PubMed Central

Darbon, Hervé; Longhi, Sonia

2010-01-01

Henipaviruses are newly emerged viruses within the Paramyxoviridae family. Their negative-strand RNA genome is packaged by the nucleoprotein (N) within α-helical nucleocapsid that recruits the polymerase complex made of the L protein and the phosphoprotein (P). To date structural data on Henipaviruses are scarce, and their N and P proteins have never been characterized so far. Using both computational and experimental approaches we herein show that Henipaviruses N and P proteins possess large intrinsically disordered regions. By combining several disorder prediction methods, we show that the N-terminal domain of P (PNT) and the C-terminal domain of N (NTAIL) are both mostly disordered, although they contain short order-prone segments. We then report the cloning, the bacterial expression, purification and characterization of Henipavirus PNT and NTAIL domains. By combining gel filtration, dynamic light scattering, circular dichroism and nuclear magnetic resonance, we show that both NTAIL and PNT belong to the premolten globule sub-family within the class of intrinsically disordered proteins. This study is the first reported experimental characterization of Henipavirus P and N proteins. The evidence that their respective N-terminal and C-terminal domains are highly disordered under native conditions is expected to be invaluable for future structural studies by helping to delineate N and P protein domains amenable to crystallization. In addition, following previous hints establishing a relationship between structural disorder and protein interactivity, the present results suggest that Henipavirus PNT and NTAIL domains could be involved in manifold protein-protein interactions. PMID:20657787

Modular protein domains: an engineering approach toward functional biomaterials.

PubMed

Lin, Charng-Yu; Liu, Julie C

2016-08-01

Protein domains and peptide sequences are a powerful tool for conferring specific functions to engineered biomaterials. Protein sequences with a wide variety of functionalities, including structure, bioactivity, protein-protein interactions, and stimuli responsiveness, have been identified, and advances in molecular biology continue to pinpoint new sequences. Protein domains can be combined to make recombinant proteins with multiple functionalities. The high fidelity of the protein translation machinery results in exquisite control over the sequence of recombinant proteins and the resulting properties of protein-based materials. In this review, we discuss protein domains and peptide sequences in the context of functional protein-based materials, composite materials, and their biological applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sliding of proteins non-specifically bound to DNA: Brownian dynamics studies with coarse-grained protein and DNA models.

PubMed

Ando, Tadashi; Skolnick, Jeffrey

2014-12-01

DNA binding proteins efficiently search for their cognitive sites on long genomic DNA by combining 3D diffusion and 1D diffusion (sliding) along the DNA. Recent experimental results and theoretical analyses revealed that the proteins show a rotation-coupled sliding along DNA helical pitch. Here, we performed Brownian dynamics simulations using newly developed coarse-grained protein and DNA models for evaluating how hydrodynamic interactions between the protein and DNA molecules, binding affinity of the protein to DNA, and DNA fluctuations affect the one dimensional diffusion of the protein on the DNA. Our results indicate that intermolecular hydrodynamic interactions reduce 1D diffusivity by 30%. On the other hand, structural fluctuations of DNA give rise to steric collisions between the CG-proteins and DNA, resulting in faster 1D sliding of the protein. Proteins with low binding affinities consistent with experimental estimates of non-specific DNA binding show hopping along the CG-DNA. This hopping significantly increases sliding speed. These simulation studies provide additional insights into the mechanism of how DNA binding proteins find their target sites on the genome.

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

Structural and Functional Analysis of a Novel Interaction Motif within UFM1-activating Enzyme 5 (UBA5) Required for Binding to Ubiquitin-like Proteins and Ufmylation*

PubMed Central

Habisov, Sabrina; Huber, Jessica; Ichimura, Yoshinobu; Akutsu, Masato; Rogova, Natalia; Loehr, Frank; McEwan, David G.; Johansen, Terje; Dikic, Ivan; Doetsch, Volker; Komatsu, Masaaki; Rogov, Vladimir V.; Kirkin, Vladimir

2016-01-01

The covalent conjugation of ubiquitin-fold modifier 1 (UFM1) to proteins generates a signal that regulates transcription, response to cell stress, and differentiation. Ufmylation is initiated by ubiquitin-like modifier activating enzyme 5 (UBA5), which activates and transfers UFM1 to ubiquitin-fold modifier-conjugating enzyme 1 (UFC1). The details of the interaction between UFM1 and UBA5 required for UFM1 activation and its downstream transfer are however unclear. In this study, we described and characterized a combined linear LC3-interacting region/UFM1-interacting motif (LIR/UFIM) within the C terminus of UBA5. This single motif ensures that UBA5 binds both UFM1 and light chain 3/γ-aminobutyric acid receptor-associated proteins (LC3/GABARAP), two ubiquitin (Ub)-like proteins. We demonstrated that LIR/UFIM is required for the full biological activity of UBA5 and for the effective transfer of UFM1 onto UFC1 and a downstream protein substrate both in vitro and in cells. Taken together, our study provides important structural and functional insights into the interaction between UBA5 and Ub-like modifiers, improving the understanding of the biology of the ufmylation pathway. PMID:26929408

ABA signaling in guard cells entails a dynamic protein-protein interaction relay from the PYL-RCAR family receptors to ion channels.

PubMed

Lee, Sung Chul; Lim, Chae Woo; Lan, Wenzhi; He, Kai; Luan, Sheng

2013-03-01

Plant hormone abscisic acid (ABA) serves as an integrator of environmental stresses such as drought to trigger stomatal closure by regulating specific ion channels in guard cells. We previously reported that SLAC1, an outward anion channel required for stomatal closure, was regulated via reversible protein phosphorylation events involving ABA signaling components, including protein phosphatase 2C members and a SnRK2-type kinase (OST1). In this study, we reconstituted the ABA signaling pathway as a protein-protein interaction relay from the PYL/RCAR-type receptors, to the PP2C-SnRK2 phosphatase-kinase pairs, to the ion channel SLAC1. The ABA receptors interacted with and inhibited PP2C phosphatase activity against the SnRK2-type kinase, releasing active SnRK2 kinase to phosphorylate, and activate the SLAC1 channel, leading to reduced guard cell turgor and stomatal closure. Both yeast two-hybrid and bimolecular fluorescence complementation assays were used to verify the interactions among the components in the pathway. These biochemical assays demonstrated activity modifications of phosphatases and kinases by their interaction partners. The SLAC1 channel activity was used as an endpoint readout for the strength of the signaling pathway, depending on the presence of different combinations of signaling components. Further study using transgenic plants overexpressing one of the ABA receptors demonstrated that changing the relative level of interacting partners would change ABA sensitivity.

In situ analysis of proteins at high temperatures mediated by capillary-flow hydrothermal UV-vis spectrophotometer with a water-soluble chromogenic reagent.

PubMed

Kawamura, Kunio; Nagayoshi, Hiroki; Yao, Toshio

2010-05-14

In situ monitoring of quantities, interactions, and conformations of proteins is essential for the study of biochemistry under hydrothermal environments and the analysis of hyperthermophilic organisms in natural hydrothermal systems on Earth. We have investigated the potential of a capillary-flow hydrothermal UV-vis spectrophotometer (CHUS) for performing in situ measurements of proteins and determining their behavior at extremely high temperatures, in combination with a chromogenic reagents probe, which interacts with the proteins. The spectral shift obtained using a combination of water-soluble porphyrin (TPPS) and bovine serum albumin (BSA) was the best among the spectral shifts obtained using different combinations of chromogenic reagents and proteins. The association behavior of TPPS with BSA was investigated in detail using CHUS at temperatures up to 175 degrees C and the association constant (K(ass)) of TPPS with BSA was successfully determined at temperatures up to 100 degrees C. The lnK(ass) values were inversely proportional to the T(-1) values in the temperature range 50-100 degrees C. These analyses showed for the first time that the decrease of association of TPPS with BSA is due to the conformational change, fragmentation, and/or denaturing of BSA rather than the decrease of the hydrophobic association between TPPS and BSA. This study conclusively demonstrates the usability of the CHUS system with a chromogenic reagent as an in situ detection and measurement system for thermostable proteins at extremely high temperatures. Copyright 2010 Elsevier B.V. All rights reserved.

Protein expression and purification of integrin I domains and IgSF ligands for crystallography.

PubMed

Zhang, Hongmin; Wang, Jia-Huai

2012-01-01

Cell adhesion depends on combinational expression and interactions of a large number of adhesion molecules at cell-to-cell or cell-to-matrix contact sites. Integrins and their immunoglobulin superfamily (IgSF) ligands represent foremost classes of cell adhesion molecules in immune system. Structural study is critical for a better understanding of the interactions between integrins and their IgSF ligands. Here we describe protocols for protein expression of integrin αL I domain and its IgSF ligand ICAM-5 D1D2 fragment for crystallography.

Protein recognition by a pattern-generating fluorescent molecular probe.

PubMed

Pode, Zohar; Peri-Naor, Ronny; Georgeson, Joseph M; Ilani, Tal; Kiss, Vladimir; Unger, Tamar; Markus, Barak; Barr, Haim M; Motiei, Leila; Margulies, David

2017-12-01

Fluorescent molecular probes have become valuable tools in protein research; however, the current methods for using these probes are less suitable for analysing specific populations of proteins in their native environment. In this study, we address this gap by developing a unimolecular fluorescent probe that combines the properties of small-molecule-based probes and cross-reactive sensor arrays (the so-called chemical 'noses/tongues'). On the one hand, the probe can detect different proteins by generating unique identification (ID) patterns, akin to cross-reactive arrays. On the other hand, its unimolecular scaffold and selective binding enable this ID-generating probe to identify combinations of specific protein families within complex mixtures and to discriminate among isoforms in living cells, where macroscopic arrays cannot access. The ability to recycle the molecular device and use it to track several binding interactions simultaneously further demonstrates how this approach could expand the fluorescent toolbox currently used to detect and image proteins.

Protein recognition by a pattern-generating fluorescent molecular probe

NASA Astrophysics Data System (ADS)

Pode, Zohar; Peri-Naor, Ronny; Georgeson, Joseph M.; Ilani, Tal; Kiss, Vladimir; Unger, Tamar; Markus, Barak; Barr, Haim M.; Motiei, Leila; Margulies, David

2017-12-01

Fluorescent molecular probes have become valuable tools in protein research; however, the current methods for using these probes are less suitable for analysing specific populations of proteins in their native environment. In this study, we address this gap by developing a unimolecular fluorescent probe that combines the properties of small-molecule-based probes and cross-reactive sensor arrays (the so-called chemical 'noses/tongues'). On the one hand, the probe can detect different proteins by generating unique identification (ID) patterns, akin to cross-reactive arrays. On the other hand, its unimolecular scaffold and selective binding enable this ID-generating probe to identify combinations of specific protein families within complex mixtures and to discriminate among isoforms in living cells, where macroscopic arrays cannot access. The ability to recycle the molecular device and use it to track several binding interactions simultaneously further demonstrates how this approach could expand the fluorescent toolbox currently used to detect and image proteins.

Interaction of ABC multidrug transporters with anticancer protein kinase inhibitors: substrates and/or inhibitors?

PubMed

Hegedus, Csilla; Ozvegy-Laczka, Csilla; Szakács, Gergely; Sarkadi, Balázs

2009-05-01

Protein kinase inhibitors (PKI) are becoming key agents in modern cancer chemotherapy, and combination of PKIs with classical chemotherapeutic drugs may help to overcome currently untreatable metastatic cancers. Since chemotherapy resistance is a recurrent problem, mechanisms of resistance should be clarified in order to help further drug development. Here we suggest that in addition to PKI resistance based on altered target structures, the active removal of these therapeutic agents by the MDR-ABC transporters should also be considered as a major cause of clinical resistance. We discuss the occurring systemic and cellular mechanisms, which may hamper PKI efficiency, and document the role of selected MDR-ABC transporters in these phenomena through their interactions with these anticancer agents. Moreover, we suggest that PKI interactions with ABC transporters may modulate overall drug metabolism, including the fate of diverse, chemically or target-wise unrelated drugs. These effects are based on multiple forms of MDR-ABC transporter interaction with PKIs, as these compounds may be both substrates and/or inhibitors of an ABC transporter. We propose that these interactions should be carefully considered in clinical application, and a combined MDR-ABC transporter and PKI effect may bring a major advantage in future drug development.

Targeting Heat Shock Protein 90 Overrides the Resistance of Lung Cancer Cells by Blocking Radiation-induced Stabilization of Hypoxia-inducible Factor 1α

PubMed Central

Kim, Woo-Young; Oh, Seung Hyun; Woo, Jong-Kyu; Hong, Waun Ki; Lee, Ho-Young

2008-01-01

Hypoxia-inducible factor-1 (HIF-1) has been suggested to play a major role in tumor radioresistance. However, the mechanisms through which irradiation regulates HIF-1α expression remain unclear. The purpose of this study was to investigate the mechanisms that mediate HIF-1 activation and thus radioresistance. Here we show that irradiation induces survival and angiogenic activity in a subset of radioresistant lung cancer cell lines by elevating HIF-1α protein expression. Radiation induced HIF-1α protein expression mainly through two distinct pathways, including an increase in de novo protein synthesis via activation of PI3K/Akt/mTOR and stabilization of HIF-1α protein via augmenting the interaction between heat shock protein 90 (Hsp90) and HIF-1α protein. While the PI3K/Akt/mTOR pathway was activated by irradiation in all the lung cancer cells examined, the HSP90-HIF-1α interaction was enhanced in the resistant cells only. Inhibition of Hsp90 function by 17-AAG or deguelin, a novel natural inhibitor of HSP90, suppressed increases in HIF-1α/Hsp90 interaction and HIF-1α expression in radioresistant cells. Furthermore, combined treatment of radiation with deguelin significantly decreased the survival and angiogenic potential of radioresistant lung cancer cells in vitro. We finally determined in vivo that systemic administration of deguelin resulted in profound inhibition of tumor growth and angiogenesis when combined with radiation. These results provide a strong rationale to target Hsp90 as a means to block radiation-induced HIF-1α and thus to circumvent radioresistance in lung cancer cells. PMID:19176399

Cooperative interactions between paired domain and homeodomain.

PubMed

Jun, S; Desplan, C

1996-09-01

The Pax proteins are a family of transcriptional regulators involved in many developmental processes in all higher eukaryotes. They are characterized by the presence of a paired domain (PD), a bipartite DNA binding domain composed of two helix-turn-helix (HTH) motifs,the PAI and RED domains. The PD is also often associated with a homeodomain (HD) which is itself able to form homo- and hetero-dimers on DNA. Many of these proteins therefore contain three HTH motifs each able to recognize DNA. However, all PDs recognize highly related DNA sequences, and most HDs also recognize almost identical sites. We show here that different Pax proteins use multiple combinations of their HTHs to recognize several types of target sites. For instance, the Drosophila Paired protein can bind, in vitro, exclusively through its PAI domain, or through a dimer of its HD, or through cooperative interaction between PAI domain and HD. However, prd function in vivo requires the synergistic action of both the PAI domain and the HD. Pax proteins with only a PD appear to require both PAI and RED domains, while a Pax-6 isoform and a new Pax protein, Lune, may rely on the RED domain and HD. We propose a model by which Pax proteins recognize different target genes in vivo through various combinations of their DNA binding domains, thus expanding their recognition repertoire.

Analysis of Protein Interactions at Native Chloroplast Membranes by Ellipsometry

PubMed Central

Kriechbaumer, Verena; Nabok, Alexei; Mustafa, Mohd K.; Al-Ammar, Rukaiah; Tsargorodskaya, Anna; Smith, David P.; Abell, Ben M.

2012-01-01

Membrane bound receptors play vital roles in cell signaling, and are the target for many drugs, yet their interactions with ligands are difficult to study by conventional techniques due to the technical difficulty of monitoring these interactions in lipid environments. In particular, the ability to analyse the behaviour of membrane proteins in their native membrane environment is limited. Here, we have developed a quantitative approach to detect specific interactions between low-abundance chaperone receptors within native chloroplast membranes and their soluble chaperone partners. Langmuir-Schaefer film deposition was used to deposit native chloroplasts onto gold-coated glass slides, and interactions between the molecular chaperones Hsp70 and Hsp90 and their receptors in the chloroplast membranes were detected and quantified by total internal reflection ellipsometry (TIRE). We show that native chloroplast membranes deposited on gold-coated glass slides using Langmuir-Schaefer films retain functional receptors capable of binding chaperones with high specificity and affinity. Taking into account the low chaperone receptor abundance in native membranes, these binding properties are consistent with data generated using soluble forms of the chloroplast chaperone receptors, OEP61 and Toc64. Therefore, we conclude that chloroplasts have the capacity to selectively bind chaperones, consistent with the notion that chaperones play an important role in protein targeting to chloroplasts. Importantly, this method of monitoring by TIRE does not require any protein labelling. This novel combination of techniques should be applicable to a wide variety of membranes and membrane protein receptors, thus presenting the opportunity to quantify protein interactions involved in fundamental cellular processes, and to screen for drugs that target membrane proteins. PMID:22479632

A study on the nature of interactions of mixed-mode ligands HEA and PPA HyperCel using phenylglyoxal modified lysozyme.

PubMed

Pezzini, J; Cabanne, C; Dupuy, J-W; Gantier, R; Santarelli, X

2014-06-01

Mixed mode chromatography, or multimodal chromatography, involves the exploitation of combinations of several interactions in a controlled manner, to facilitate the rapid capture of proteins. Mixed-mode ligands like HEA and PPA HyperCel™ facilitate different kinds of interactions (hydrophobic, ionic, etc.) under different conditions. In order to better characterize the nature of this multi-modal interaction, we sought to study a protein, lysozyme, which is normally not retained by these mixed mode resins under normal binding conditions. Lysozyme was modified specifically at Arginine residues by the action of phenylglyoxal, and was extensively studied in this work to better characterize the mixed-mode interactions of HEA HyperCel™ and PPA HyperCel™ chromatographic supports. We show here that the adsorption behaviour of lysozyme on HEA and PPA HyperCel™ mixed mode sorbents varies depending on the degree of charge modification at the surface of the protein. Experiments using conventional cation exchange and hydrophobic interaction chromatography confirm that both charge and hydrophobicity modification occurs at the surface of the protein after lysozyme reaction with phenylglyoxal. The results emanating from this work using HEA and PPA HyperCel sorbents strongly suggest that mixed mode chromatography can efficiently separate closely related proteins of only minor surface charge and/or hydrophobicity differences. Copyright © 2014 Elsevier B.V. All rights reserved.

Applications of hydrophilic interaction chromatography to amino acids, peptides, and proteins.

PubMed

Periat, Aurélie; Krull, Ira S; Guillarme, Davy

2015-02-01

This review summarizes the recent advances in the analysis of amino acids, peptides, and proteins using hydrophilic interaction chromatography. Various reports demonstrate the successful analysis of amino acids under such conditions. However, a baseline resolution of the 20 natural amino acids has not yet been published and for this reason, there is often a need to use mass spectrometry for detection to further improve selectivity. Hydrophilic interaction chromatography is also recognized as a powerful technique for peptide analysis, and there are a lot of papers showing its applicability for proteomic applications (peptide mapping). It is expected that its use for peptide mapping will continue to grow in the future, particularly because this analytical strategy can be combined with reversed-phase liquid chromatography, in a two-dimensional setup, to reach very high resolving power. Finally, the interest in hydrophilic interaction chromatography for intact proteins analysis is less evident due to possible solubility issues and a lack of suitable hydrophilic interaction chromatography stationary phases. To date, it has been successfully employed only for the characterization of membrane proteins, histones, and the separation of glycosylated isoforms of an intact glycoprotein. From our point of view, the number of hydrophilic interaction chromatography columns compatible with intact proteins (higher upper temperature limit, large pore size, etc.) is still too limited. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Synthetic Coiled-Coil Interactome Provides Heterospecific Modules for Molecular Engineering

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

Reinke, Aaron W.; Grant, Robert A.; Keating, Amy E.

2010-06-21

The versatile coiled-coil protein motif is widely used to induce and control macromolecular interactions in biology and materials science. Yet the types of interaction patterns that can be constructed using known coiled coils are limited. Here we greatly expand the coiled-coil toolkit by measuring the complete pairwise interactions of 48 synthetic coiled coils and 7 human bZIP coiled coils using peptide microarrays. The resulting 55-member protein 'interactome' includes 27 pairs of interacting peptides that preferentially heteroassociate. The 27 pairs can be used in combinations to assemble sets of 3 to 6 proteins that compose networks of varying topologies. Of specialmore » interest are heterospecific peptide pairs that participate in mutually orthogonal interactions. Such pairs provide the opportunity to dimerize two separate molecular systems without undesired crosstalk. Solution and structural characterization of two such sets of orthogonal heterodimers provide details of their interaction geometries. The orthogonal pair, along with the many other network motifs discovered in our screen, provide new capabilities for synthetic biology and other applications.« less

High-Affinity Small-Molecule Inhibitors of the Menin-Mixed Lineage Leukemia (MLL) Interaction Closely Mimic a Natural Protein-Protein Interaction

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

He, Shihan; Senter, Timothy J.; Pollock, Jonathan

2014-10-02

The protein–protein interaction (PPI) between menin and mixed lineage leukemia (MLL) plays a critical role in acute leukemias, and inhibition of this interaction represents a new potential therapeutic strategy for MLL leukemias. We report development of a novel class of small-molecule inhibitors of the menin–MLL interaction, the hydroxy- and aminomethylpiperidine compounds, which originated from HTS of ~288000 small molecules. We determined menin–inhibitor co-crystal structures and found that these compounds closely mimic all key interactions of MLL with menin. Extensive crystallography studies combined with structure-based design were applied for optimization of these compounds, resulting in MIV-6R, which inhibits the menin–MLL interactionmore » with IC 50 = 56 nM. Treatment with MIV-6 demonstrated strong and selective effects in MLL leukemia cells, validating specific mechanism of action. Our studies provide novel and attractive scaffold as a new potential therapeutic approach for MLL leukemias and demonstrate an example of PPI amenable to inhibition by small molecules.« less

Modeling synthetic lethality

PubMed Central

Le Meur, Nolwenn; Gentleman, Robert

2008-01-01

Background Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units. Results In Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products. Conclusions Modeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions. PMID:18789146

An in vivo screen reveals protein-lipid interactions crucial for gating a mechanosensitive channel

PubMed Central

Iscla, Irene; Wray, Robin; Blount, Paul

2011-01-01

The bacterial mechanosensitive channel MscL is the best-studied mechanosensor, thus serving as a paradigm of how a protein senses and responds to mechanical force. Models for the transition of Escherichia coli MscL from closed to open states propose a tilting of the transmembrane domains in the plane of the membrane, suggesting dynamic protein-lipid interactions. Here, we used a rapid in vivo assay to assess the function of channels that were post-translationally modified at several different sites in a region just distal to the cytoplasmic end of the second transmembrane helix. We utilized multiple probes with various affinities for the membrane environment. The in vivo functional data, combined with site-directed mutagenesis, single-channel analyses, and tryptophan fluorescence measurements, confirmed that lipid interactions within this region are critical for MscL gating. The data suggest a model in which this region acts as an anchor for the transmembrane domain tilting during gating. Furthermore, the conservation of analogous motifs among many other channels suggests a conserved protein-lipid dynamic mechanism.—Iscla, I., Wray, R., Blount, P. An in vivo screen reveals protein-lipid interactions crucial for gating a mechanosensitive channel. PMID:21068398

Fluorescent Protein Aided Insights on Plastids and their Extensions: A Critical Appraisal

PubMed Central

Delfosse, Kathleen; Wozny, Michael R.; Jaipargas, Erica-Ashley; Barton, Kiah A.; Anderson, Cole; Mathur, Jaideep

2016-01-01

Multi-colored fluorescent proteins targeted to plastids have provided new insights on the dynamic behavior of these organelles and their interactions with other cytoplasmic components and compartments. Sub-plastidic components such as thylakoids, stroma, the inner and outer membranes of the plastid envelope, nucleoids, plastoglobuli, and starch grains have been efficiently highlighted in living plant cells. In addition, stroma filled membrane extensions called stromules have drawn attention to the dynamic nature of the plastid and its interactions with the rest of the cell. Use of dual and triple fluorescent protein combinations has begun to reveal plastid interactions with mitochondria, the nucleus, the endoplasmic reticulum and F-actin and suggests integral roles of plastids in retrograde signaling, cell to cell communication as well as plant-pathogen interactions. While the rapid advances and insights achieved through fluorescent protein based research on plastids are commendable it is necessary to endorse meaningful observations but subject others to closer scrutiny. Here, in order to develop a better and more comprehensive understanding of plastids and their extensions we provide a critical appraisal of recent information that has been acquired using targeted fluorescent protein probes. PMID:26834765

Quantifying Additive Interactions of the Osmolyte Proline with Individual Functional Groups of Proteins: Comparisons with Urea and Glycine Betaine, Interpretation of m-Values

PubMed Central

Diehl, Roger C.; Guinn, Emily J.; Capp, Michael W.; Tsodikov, Oleg V.; Record, M. Thomas

2013-01-01

To quantify interactions of the osmolyte L-proline with protein functional groups and predict its effects on protein processes, we use vapor pressure osmometry to determine chemical potential derivatives dµ2/dm3 = µ23 quantifying preferential interactions of proline (component 3) with 21 solutes (component 2) selected to display different combinations of aliphatic or aromatic C, amide, carboxylate, phosphate or hydroxyl O, and/or amide or cationic N surface. Solubility data yield µ23 values for 4 less-soluble solutes. Values of µ23 are dissected using an ASA-based analysis to test the hypothesis of additivity and obtain α-values (proline interaction potentials) for these eight surface types and three inorganic ions. Values of µ23 predicted from these α-values agree with experiment, demonstrating additivity. Molecular interpretation of α-values using the solute partitioning model yields partition coefficients (Kp) quantifying the local accumulation or exclusion of proline in the hydration water of each functional group. Interactions of proline with native protein surface and effects of proline on protein unfolding are predicted from α-values and ASA information and compared with experimental data, with results for glycine betaine and urea, and with predictions from transfer free energy analysis. We conclude that proline stabilizes proteins because of its unfavorable interactions with (exclusion from) amide oxygens and aliphatic hydrocarbon surface exposed in unfolding, and that proline is an effective in vivo osmolyte because of the osmolality increase resulting from its unfavorable interactions with anionic (carboxylate and phosphate) and amide oxygens and aliphatic hydrocarbon groups on the surface of cytoplasmic proteins and nucleic acids. PMID:23909383

Bio-Inspired Nanomaterials: Protein Cage Nano-Architectures

DTIC Science & Technology

2008-04-01

chemical modification of protein cage materials and controlled chemical synthesis under mild biological conditions. High- resolution structural...properties based on a combination of controlled mobility and metal ligand interactions. Using the exterior surface of the CCMV viral cage we have chemically ...follows: Patterning by microplotter was achieved by depositing a preselected antibody solution directly onto chemically activated silicon or gold

Combinatorial multispectral, thermodynamics, docking and site-directed mutagenesis reveal the cognitive characteristics of honey bee chemosensory protein to plant semiochemical.

PubMed

Tan, Jing; Song, Xinmi; Fu, Xiaobin; Wu, Fan; Hu, Fuliang; Li, Hongliang

2018-08-05

In the chemoreceptive system of insects, there are always some soluble binding proteins, such as some antennal-specific chemosensory proteins (CSPs), which are abundantly distributed in the chemosensory sensillar lymph. The antennal-specific CSPs usually have strong capability to bind diverse semiochemicals, while the detailed interaction between CSPs and the semiochemicals remain unclear. Here, by means of the combinatorial multispectral, thermodynamics, docking and site-directed mutagenesis, we detailedly interpreted a binding interaction between a plant semiochemical β-ionone and antennal-specific CSP1 from the worker honey bee. Thermodynamic parameters (ΔH < 0, ΔS > 0) indicate that the interaction is mainly driven by hydrophobic forces and electrostatic interactions. Docking prediction results showed that there are two key amino acids, Phe44 and Gln63, may be involved in the interacting process of CSP1 to β-ionone. In order to confirm the two key amino acids, site-directed mutagenesis were performed and the binding constant (K A ) for two CSP1 mutant proteins was reduced by 60.82% and 46.80% compared to wild-type CSP1. The thermodynamic analysis of mutant proteins furtherly verified that Phe44 maintained an electrostatic interaction and Gln63 contributes hydrophobic and electrostatic forces. Our investigation initially elucidates the physicochemical mechanism of the interaction between antennal-special CSPs in insects including bees to plant semiochemicals, as well as the development of twice thermodynamic analysis (wild type and mutant proteins) combined with multispectral and site-directed mutagenesis methods. Copyright © 2018 Elsevier B.V. All rights reserved.

Anaplasma phagocytophilum MSP4 and HSP70 Proteins Are Involved in Interactions with Host Cells during Pathogen Infection

PubMed Central

Contreras, Marinela; Alberdi, Pilar; Mateos-Hernández, Lourdes; Fernández de Mera, Isabel G.; García-Pérez, Ana L.; Vancová, Marie; Villar, Margarita; Ayllón, Nieves; Cabezas-Cruz, Alejandro; Valdés, James J.; Stuen, Snorre; Gortazar, Christian; de la Fuente, José

2017-01-01

Anaplasma phagocytophilum transmembrane and surface proteins play a role during infection and multiplication in host neutrophils and tick vector cells. Recently, A. phagocytophilum Major surface protein 4 (MSP4) and Heat shock protein 70 (HSP70) were shown to be localized on the bacterial membrane, with a possible role during pathogen infection in ticks. In this study, we hypothesized that A. phagocytophilum MSP4 and HSP70 have similar functions in tick-pathogen and host-pathogen interactions. To address this hypothesis, herein we characterized the role of these bacterial proteins in interaction and infection of vertebrate host cells. The results showed that A. phagocytophilum MSP4 and HSP70 are involved in host-pathogen interactions, with a role for HSP70 during pathogen infection. The analysis of the potential protective capacity of MSP4 and MSP4-HSP70 antigens in immunized sheep showed that MSP4-HSP70 was only partially protective against pathogen infection. This limited protection may be associated with several factors, including the recognition of non-protective epitopes by IgG in immunized lambs. Nevertheless, these antigens may be combined with other candidate protective antigens for the development of vaccines for the control of human and animal granulocytic anaplasmosis. Focusing on the characterization of host protective immune mechanisms and protein-protein interactions at the host-pathogen interface may lead to the discovery and design of new effective protective antigens. PMID:28725639

Celecoxib Encapsulation in β-Casein Micelles: Structure, Interactions, and Conformation.

PubMed

Turovsky, Tanya; Khalfin, Rafail; Kababya, Shifi; Schmidt, Asher; Barenholz, Yechezkel; Danino, Dganit

2015-07-07

β-Casein is a 24 kDa natural protein that has an open conformation and almost no folded or secondary structure, and thus is classified as an intrinsically unstructured protein. At neutral pH, β-casein has an amphiphilic character. Therefore, in contrast to most unstructured proteins that remain monomeric in solution, β-casein self-assembles into well-defined core-shell micelles. We recently developed these micelles as potential carriers for oral administration of poorly water-soluble pharmaceuticals, using celecoxib as a model drug. Herein we present deep and precise insight into the physicochemical characteristics of the protein-drug formulation, both in bulk solution and in dry form, emphasizing drug conformation, packing properties and aggregation state. In addition, the formulation is extensively studied in terms of structure and morphology, protein/drug interactions and physical stability. Particularly, NMR measurements indicated strong drug-protein interactions and noncrystalline drug conformation, which is expected to improve drug solubility and bioavailability. Small-angle X-ray scattering (SAXS) and cryogenic transmission electron microscopy (cryo-TEM) were combined for nanostructural characterization, proving that drug-protein interactions lead to well-defined spheroidal micelles that become puffier and denser upon drug loading. Dynamice light scattering (DLS), turbidity measurements, and visual observations complemented the analysis for determining formulation structure, interactions, and stability. Additionally, it was shown that the loaded micelles retain their properties through freeze-drying and rehydration, providing long-term physical and chemical stability. Altogether, the formulation seems greatly promising for oral drug delivery.

Anaplasma phagocytophilum MSP4 and HSP70 Proteins Are Involved in Interactions with Host Cells during Pathogen Infection.

PubMed

Contreras, Marinela; Alberdi, Pilar; Mateos-Hernández, Lourdes; Fernández de Mera, Isabel G; García-Pérez, Ana L; Vancová, Marie; Villar, Margarita; Ayllón, Nieves; Cabezas-Cruz, Alejandro; Valdés, James J; Stuen, Snorre; Gortazar, Christian; de la Fuente, José

2017-01-01

Anaplasma phagocytophilum transmembrane and surface proteins play a role during infection and multiplication in host neutrophils and tick vector cells. Recently, A. phagocytophilum Major surface protein 4 (MSP4) and Heat shock protein 70 (HSP70) were shown to be localized on the bacterial membrane, with a possible role during pathogen infection in ticks. In this study, we hypothesized that A. phagocytophilum MSP4 and HSP70 have similar functions in tick-pathogen and host-pathogen interactions. To address this hypothesis, herein we characterized the role of these bacterial proteins in interaction and infection of vertebrate host cells. The results showed that A. phagocytophilum MSP4 and HSP70 are involved in host-pathogen interactions, with a role for HSP70 during pathogen infection. The analysis of the potential protective capacity of MSP4 and MSP4-HSP70 antigens in immunized sheep showed that MSP4-HSP70 was only partially protective against pathogen infection. This limited protection may be associated with several factors, including the recognition of non-protective epitopes by IgG in immunized lambs. Nevertheless, these antigens may be combined with other candidate protective antigens for the development of vaccines for the control of human and animal granulocytic anaplasmosis. Focusing on the characterization of host protective immune mechanisms and protein-protein interactions at the host-pathogen interface may lead to the discovery and design of new effective protective antigens.

Quaternary structure of a G-protein-coupled receptor heterotetramer in complex with Gi and Gs.

PubMed

Navarro, Gemma; Cordomí, Arnau; Zelman-Femiak, Monika; Brugarolas, Marc; Moreno, Estefania; Aguinaga, David; Perez-Benito, Laura; Cortés, Antoni; Casadó, Vicent; Mallol, Josefa; Canela, Enric I; Lluís, Carme; Pardo, Leonardo; García-Sáez, Ana J; McCormick, Peter J; Franco, Rafael

2016-04-05

G-protein-coupled receptors (GPCRs), in the form of monomers or homodimers that bind heterotrimeric G proteins, are fundamental in the transfer of extracellular stimuli to intracellular signaling pathways. Different GPCRs may also interact to form heteromers that are novel signaling units. Despite the exponential growth in the number of solved GPCR crystal structures, the structural properties of heteromers remain unknown. We used single-particle tracking experiments in cells expressing functional adenosine A1-A2A receptors fused to fluorescent proteins to show the loss of Brownian movement of the A1 receptor in the presence of the A2A receptor, and a preponderance of cell surface 2:2 receptor heteromers (dimer of dimers). Using computer modeling, aided by bioluminescence resonance energy transfer assays to monitor receptor homomerization and heteromerization and G-protein coupling, we predict the interacting interfaces and propose a quaternary structure of the GPCR tetramer in complex with two G proteins. The combination of results points to a molecular architecture formed by a rhombus-shaped heterotetramer, which is bound to two different interacting heterotrimeric G proteins (Gi and Gs). These novel results constitute an important advance in understanding the molecular intricacies involved in GPCR function.

Multi-Harmony: detecting functional specificity from sequence alignment

PubMed Central

Brandt, Bernd W.; Feenstra, K. Anton; Heringa, Jaap

2010-01-01

Many protein families contain sub-families with functional specialization, such as binding different ligands or being involved in different protein–protein interactions. A small number of amino acids generally determine functional specificity. The identification of these residues can aid the understanding of protein function and help finding targets for experimental analysis. Here, we present multi-Harmony, an interactive web sever for detecting sub-type-specific sites in proteins starting from a multiple sequence alignment. Combining our Sequence Harmony (SH) and multi-Relief (mR) methods in one web server allows simultaneous analysis and comparison of specificity residues; furthermore, both methods have been significantly improved and extended. SH has been extended to cope with more than two sub-groups. mR has been changed from a sampling implementation to a deterministic one, making it more consistent and user friendly. For both methods Z-scores are reported. The multi-Harmony web server produces a dynamic output page, which includes interactive connections to the Jalview and Jmol applets, thereby allowing interactive analysis of the results. Multi-Harmony is available at http://www.ibi.vu.nl/ programs/shmrwww. PMID:20525785

OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Free-energy calculations reveal the subtle differences in the interactions of DNA bases with α-hemolysin.

PubMed

Manara, Richard M A; Guy, Andrew T; Wallace, E Jayne; Khalid, Syma

2015-02-10

Next generation DNA sequencing methods that utilize protein nanopores have the potential to revolutionize this area of biotechnology. While the technique is underpinned by simple physics, the wild-type protein pores do not have all of the desired properties for efficient and accurate DNA sequencing. Much of the research efforts have focused on protein nanopores, such as α-hemolysin from Staphylococcus aureus. However, the speed of DNA translocation has historically been an issue, hampered in part by incomplete knowledge of the energetics of translocation. Here we have utilized atomistic molecular dynamics simulations of nucleotide fragments in order to calculate the potential of mean force (PMF) through α-hemolysin. Our results reveal specific regions within the pore that play a key role in the interaction with DNA. In particular, charged residues such as D127 and K131 provide stabilizing interactions with the anionic DNA and therefore are likely to reduce the speed of translocation. These regions provide rational targets for pore optimization. Furthermore, we show that the energetic contributions to the protein-DNA interactions are a complex combination of electrostatics and short-range interactions, often mediated by water molecules.

Mediator binds to boundaries of chromosomal interaction domains and to proteins involved in DNA looping, RNA metabolism, chromatin remodeling, and actin assembly

PubMed Central

Chereji, Răzvan V.; Bharatula, Vasudha; Elfving, Nils; Blomberg, Jeanette; Larsson, Miriam; Morozov, Alexandre V.; Broach, James R.

2017-01-01

Abstract Mediator is a multi-unit molecular complex that plays a key role in transferring signals from transcriptional regulators to RNA polymerase II in eukaryotes. We have combined biochemical purification of the Saccharomyces cerevisiae Mediator from chromatin with chromatin immunoprecipitation in order to reveal Mediator occupancy on DNA genome-wide, and to identify proteins interacting specifically with Mediator on the chromatin template. Tandem mass spectrometry of proteins in immunoprecipitates of mediator complexes revealed specific interactions between Mediator and the RSC, Arp2/Arp3, CPF, CF 1A and Lsm complexes in chromatin. These factors are primarily involved in chromatin remodeling, actin assembly, mRNA 3′-end processing, gene looping and mRNA decay, but they have also been shown to enter the nucleus and participate in Pol II transcription. Moreover, we have found that Mediator, in addition to binding Pol II promoters, occupies chromosomal interacting domain (CID) boundaries and that Mediator in chromatin associates with proteins that have been shown to interact with CID boundaries, such as Sth1, Ssu72 and histone H4. This suggests that Mediator plays a significant role in higher-order genome organization. PMID:28575439

Calculations of the free energy of interaction of the c-Fos-c-Jun coiled coil: effects of the solvation model and the inclusion of polarization effects.

PubMed

Zuo, Zhili; Gandhi, Neha S; Mancera, Ricardo L

2010-12-27

The leucine zipper region of activator protein-1 (AP-1) comprises the c-Jun and c-Fos proteins and constitutes a well-known coiled coil protein-protein interaction motif. We have used molecular dynamics (MD) simulations in conjunction with the molecular mechanics/Poisson-Boltzmann generalized-Born surface area [MM/PB(GB)SA] methods to predict the free energy of interaction of these proteins. In particular, the influence of the choice of solvation model, protein force field, and water potential on the stability and dynamic properties of the c-Fos-c-Jun complex were investigated. Use of the AMBER polarizable force field ff02 in combination with the polarizable POL3 water potential was found to result in increased stability of the c-Fos-c-Jun complex. MM/PB(GB)SA calculations revealed that MD simulations using the POL3 water potential give the lowest predicted free energies of interaction compared to other nonpolarizable water potentials. In addition, the calculated absolute free energy of binding was predicted to be closest to the experimental value using the MM/GBSA method with independent MD simulation trajectories using the POL3 water potential and the polarizable ff02 force field, while all other binding affinities were overestimated.

Mass Spectrometry Based Proteomic Analysis of Salivary Glands of Urban Malaria Vector Anopheles stephensi

PubMed Central

Vijay, Sonam

2014-01-01

Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE), ion trap liquid chromatography mass spectrometry (LC/MS/MS), and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes. PMID:25126571

Mass spectrometry based proteomic analysis of salivary glands of urban malaria vector Anopheles stephensi.

PubMed

Vijay, Sonam; Rawat, Manmeet; Sharma, Arun

2014-01-01

Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE), ion trap liquid chromatography mass spectrometry (LC/MS/MS), and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes.

Computational design of protein interactions: designing proteins that neutralize influenza by inhibiting its hemagglutinin surface protein

NASA Astrophysics Data System (ADS)

Fleishman, Sarel

2012-02-01

Molecular recognition underlies all life processes. Design of interactions not seen in nature is a test of our understanding of molecular recognition and could unlock the vast potential of subtle control over molecular interaction networks, allowing the design of novel diagnostics and therapeutics for basic and applied research. We developed the first general method for designing protein interactions. The method starts by computing a region of high affinity interactions between dismembered amino acid residues and the target surface and then identifying proteins that can harbor these residues. Designs are tested experimentally for binding the target surface and successful ones are affinity matured using yeast cell surface display. Applied to the conserved stem region of influenza hemagglutinin we designed two unrelated proteins that, following affinity maturation, bound hemagglutinin at subnanomolar dissociation constants. Co-crystal structures of hemagglutinin bound to the two designed binders were within 1Angstrom RMSd of their models, validating the accuracy of the design strategy. One of the designed proteins inhibits the conformational changes that underlie hemagglutinin's cell-invasion functions and blocks virus infectivity in cell culture, suggesting that such proteins may in future serve as diagnostics and antivirals against a wide range of pathogenic influenza strains. We have used this method to obtain experimentally validated binders of several other target proteins, demonstrating the generality of the approach. We discuss the combination of modeling and high-throughput characterization of design variants which has been key to the success of this approach, as well as how we have used the data obtained in this project to enhance our understanding of molecular recognition. References: Science 332:816 JMB, in press Protein Sci 20:753

Modular biological function is most effectively captured by combining molecular interaction data types.

PubMed

Ames, Ryan M; Macpherson, Jamie I; Pinney, John W; Lovell, Simon C; Robertson, David L

2013-01-01

Large-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function.

Combination of Cyclopamine and Tamoxifen Promotes Survival and Migration of MCF-7 Breast Cancer Cells – Interaction of Hedgehog-Gli and Estrogen Receptor Signaling Pathways

PubMed Central

Uzarevic, Zvonimir; Ozretic, Petar; Musani, Vesna; Rafaj, Maja; Cindric, Mario; Levanat, Sonja

2014-01-01

Hedgehog-Gli (Hh-Gli) signaling pathway is one of the new molecular targets found upregulated in breast tumors. Estrogen receptor alpha (ERα) signaling has a key role in the development of hormone-dependent breast cancer. We aimed to investigate the effects of inhibiting both pathways simultaneously on breast cancer cell survival and the potential interactions between these two signaling pathways. ER-positive MCF-7 cells show decreased viability after treatment with cyclopamine, a Hh-Gli pathway inhibitor, as well as after tamoxifen (an ERα inhibitor) treatment. Simultaneous treatment with cyclopamine and tamoxifen on the other hand, causes short-term survival of cells, and increased migration. We found upregulated Hh-Gli signaling under these conditions and protein profiling revealed increased expression of proteins involved in cell proliferation and migration. Therefore, even though Hh-Gli signaling seems to be a good potential target for breast cancer therapy, caution must be advised, especially when combining therapies. In addition, we also show a potential direct interaction between the Shh protein and ERα in MCF-7 cells. Our data suggest that the Shh protein is able to activate ERα independently of the canonical Hh-Gli signaling pathway. Therefore, this may present an additional boost for ER-positive cells that express Shh, even in the absence of estrogen. PMID:25503972

Electrostatic Interactions between OmpG Nanopore and Analyte Protein Surface Can Distinguish between Glycosylated Isoforms.

PubMed

Fahie, Monifa A; Chen, Min

2015-08-13

The flexible loops decorating the entrance of OmpG nanopore move dynamically during ionic current recording. The gating caused by these flexible loops changes when a target protein is bound. The gating is characterized by parameters including frequency, duration, and open-pore current, and these features combine to reveal the identity of a specific analyte protein. Here, we show that OmpG nanopore equipped with a biotin ligand can distinguish glycosylated and deglycosylated isoforms of avidin by their differences in surface charge. Our studies demonstrate that the direct interaction between the nanopore and analyte surface, induced by the electrostatic attraction between the two molecules, is essential for protein isoform detection. Our technique is remarkably sensitive to the analyte surface, which may provide a useful tool for glycoprotein profiling.

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

PubMed

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

2012-01-01

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

Essential protein discovery based on a combination of modularity and conservatism.

PubMed

Zhao, Bihai; Wang, Jianxin; Li, Xueyong; Wu, Fang-Xiang

2016-11-01

Essential proteins are indispensable for the survival of a living organism and play important roles in the emerging field of synthetic biology. Many computational methods have been proposed to identify essential proteins by using the topological features of interactome networks. However, most of these methods ignored intrinsic biological meaning of proteins. Researches show that essentiality is tied not only to the protein or gene itself, but also to the molecular modules to which that protein belongs. The results of this study reveal the modularity of essential proteins. On the other hand, essential proteins are more evolutionarily conserved than nonessential proteins and frequently bind each other. That is to say, conservatism is another important feature of essential proteins. Multiple networks are constructed by integrating protein-protein interaction (PPI) networks, time course gene expression data and protein domain information. Based on these networks, a new essential protein identification method is proposed based on a combination of modularity and conservatism of proteins. Experimental results show that the proposed method outperforms other essential protein identification methods in terms of a number essential protein out of top ranked candidates. Copyright © 2016. Published by Elsevier Inc.

Protein Discovery: Combined Transcriptomic and Proteomic Analyses of Venom from the Endoparasitoid Cotesia chilonis (Hymenoptera: Braconidae)

PubMed Central

Teng, Zi-Wen; Xiong, Shi-Jiao; Xu, Gang; Gan, Shi-Yu; Chen, Xuan; Stanley, David; Yan, Zhi-Chao; Ye, Gong-Yin; Fang, Qi

2017-01-01

Many species of endoparasitoid wasps provide biological control services in agroecosystems. Although there is a great deal of information on the ecology and physiology of host/parasitoid interactions, relatively little is known about the protein composition of venom and how specific venom proteins influence physiological systems within host insects. This is a crucial gap in our knowledge because venom proteins act in modulating host physiology in ways that favor parasitoid development. Here, we identified 37 possible venom proteins from the polydnavirus-carrying endoparasitoid Cotesia chilonis by combining transcriptomic and proteomic analyses. The most abundant proteins were hydrolases, such as proteases, peptidases, esterases, glycosyl hydrolase, and endonucleases. Some components are classical parasitoid venom proteins with known functions, including extracellular superoxide dismutase 3, serine protease inhibitor and calreticulin. The venom contains novel proteins, not recorded from any other parasitoid species, including tolloid-like proteins, chitooligosaccharidolytic β-N-acetylglucosaminidase, FK506-binding protein 14, corticotropin-releasing factor-binding protein and vascular endothelial growth factor receptor 2. These new data generate hypotheses and provide a platform for functional analysis of venom components. PMID:28417942

Direct optical detection of protein-ligand interactions.

PubMed

Gesellchen, Frank; Zimmermann, Bastian; Herberg, Friedrich W

2005-01-01

Direct optical detection provides an excellent means to investigate interactions of molecules in biological systems. The dynamic equilibria inherent to these systems can be described in greater detail by recording the kinetics of a biomolecular interaction. Optical biosensors allow direct detection of interaction patterns without the need for labeling. An overview covering several commercially available biosensors is given, with a focus on instruments based on surface plasmon resonance (SPR) and reflectometric interference spectroscopy (RIFS). Potential assay formats and experimental design, appropriate controls, and calibration procedures, especially when handling low molecular weight substances, are discussed. The single steps of an interaction analysis combined with practical tips for evaluation, data processing, and interpretation of kinetic data are described in detail. In a practical example, a step-by-step procedure for the analysis of a low molecular weight compound interaction with serum protein, determined on a commercial SPR sensor, is presented.

Rubber particle proteins REF1 and SRPP1 interact differently with native lipids extracted from Hevea brasiliensis latex.

PubMed

Wadeesirisak, Kanthida; Castano, Sabine; Berthelot, Karine; Vaysse, Laurent; Bonfils, Frédéric; Peruch, Frédéric; Rattanaporn, Kittipong; Liengprayoon, Siriluck; Lecomte, Sophie; Bottier, Céline

2017-02-01

Rubber particle membranes from the Hevea latex contain predominantly two proteins, REF1 and SRPP1 involved in poly(cis-1,4-isoprene) synthesis or rubber quality. The repartition of both proteins on the small or large rubber particles seems to differ, but their role in the irreversible coagulation of the rubber particle is still unknown. In this study we highlighted the different modes of interactions of both recombinant proteins with different classes of lipids extracted from Hevea brasiliensis latex, and defined as phospholipids (PL), glycolipids (GL) and neutral lipids (NL). We combined two biophysical methods, polarization modulated-infrared reflection adsorption spectroscopy (PM-IRRAS) and ellipsometry to elucidate their interactions with monolayers of each class of lipids. REF1 and SRPP1 interactions with native lipids are clearly different; SRPP1 interacts mostly in surface with PL, GL or NL, without modification of its structure. In contrast REF1 inserts deeply in the lipid monolayers with all lipid classes. With NL, REF1 is even able to switch from α-helice conformation to β-sheet structure, as in its aggregated form (amyloid form). Interaction between REF1 and NL may therefore have a specific role in the irreversible coagulation of rubber particles. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Recombinant domains III of Tick-Borne Encephalitis Virus envelope protein in combination with dextran and CpGs induce immune response and partial protectiveness against TBE virus infection in mice.

PubMed

Ershova, Anna S; Gra, Olga A; Lyaschuk, Alexander M; Grunina, Tatyana M; Tkachuk, Artem P; Bartov, Mikhail S; Savina, Darya M; Sergienko, Olga V; Galushkina, Zoya M; Gudov, Vladimir P; Kozlovskaya, Liubov I; Kholodilov, Ivan S; Gmyl, Larissa V; Karganova, Galina G; Lunin, Vladimir G; Karyagina, Anna S; Gintsburg, Alexander L

2016-10-07

E protein of tick-borne encephalitis virus (TBEV) and other flaviviruses is located on the surface of the viral particle. Domain III of this protein seems to be a promising component of subunit vaccines for prophylaxis of TBE and kits for diagnostics of TBEV. Three variants of recombinant TBEV E protein domain III of European, Siberian and Far Eastern subtypes fused with dextran-binding domain of Leuconostoc citreum KM20 were expressed in E. coli and purified. The native structure of domain III was confirmed by ELISA antibody kit and sera of patients with tick-borne encephalitis. Immunogenic and protective properties of the preparation comprising these recombinant proteins immobilized on a dextran carrier with CpG oligonucleotides as an adjuvant were investigated on the mice model. All 3 variants of recombinant proteins immobilized on dextran demonstrate specific interaction with antibodies from the sera of TBE patients. Thus, constructed recombinant proteins seem to be promising for TBE diagnostics. The formulation comprising the 3 variants of recombinant antigens immobilized on dextran and CpG oligonucleotides, induces the production of neutralizing antibodies against TBEV of different subtypes and demonstrates partial protectivity against TBEV infection. Studied proteins interact with the sera of TBE patients, and, in combination with dextran and CPGs, demonstrate immunogenicity and limited protectivity on mice compared with reference "Tick-E-Vac" vaccine.

Single-Molecule Microscopy and Force Spectroscopy of Membrane Proteins

NASA Astrophysics Data System (ADS)

Engel, Andreas; Janovjak, Harald; Fotiadis, Dimtrios; Kedrov, Alexej; Cisneros, David; Müller, Daniel J.

Single-molecule atomic force microscopy (AFM) provides novel ways to characterize the structure-function relationship of native membrane proteins. High-resolution AFM topographs allow observing the structure of single proteins at sub-nanometer resolution as well as their conformational changes, oligomeric state, molecular dynamics and assembly. We will review these feasibilities illustrating examples of membrane proteins in native and reconstituted membranes. Classification of individual topographs of single proteins allows understanding the principles of motions of their extrinsic domains, to learn about their local structural flexibilities and to find the entropy minima of certain conformations. Combined with the visualization of functionally related conformational changes these insights allow understanding why certain flexibilities are required for the protein to function and how structurally flexible regions allow certain conformational changes. Complementary to AFM imaging, single-molecule force spectroscopy (SMFS) experiments detect molecular interactions established within and between membrane proteins. The sensitivity of this method makes it possible to measure interactions that stabilize secondary structures such as transmembrane α-helices, polypeptide loops and segments within. Changes in temperature or protein-protein assembly do not change the locations of stable structural segments, but influence their stability established by collective molecular interactions. Such changes alter the probability of proteins to choose a certain unfolding pathway. Recent examples have elucidated unfolding and refolding pathways of membrane proteins as well as their energy landscapes.

Proteomics of rice and Cochliobolus miyabeanus fungal interaction: insight into proteins at intracellular and extracellular spaces.

PubMed

Kim, Jin Yeong; Wu, Jingni; Kwon, Soon Jae; Oh, Haram; Lee, So Eui; Kim, Sang Gon; Wang, Yiming; Agrawal, Ganesh Kumar; Rakwal, Randeep; Kang, Kyu Young; Ahn, Il-Pyung; Kim, Beom-Gi; Kim, Sun Tae

2014-10-01

Necrotrophic fungal pathogen Cochliobolus miyabeanus causes brown spot disease in rice leaves upon infection, resulting in critical rice yield loss. To better understand the rice-C. miyabeanus interaction, we employed proteomic approaches to establish differential proteomes of total and secreted proteins from the inoculated leaves. The 2DE approach after PEG-fractionation of total proteins coupled with MS (MALDI-TOF/TOF and nESI-LC-MS/MS) analyses led to identification of 49 unique proteins out of 63 differential spots. SDS-PAGE in combination with nESI-LC-MS/MS shotgun approach was applied to identify secreted proteins in the leaf apoplast upon infection and resulted in cataloging of 501 unique proteins, of which 470 and 31 proteins were secreted from rice and C. miyabeanus, respectively. Proteins mapped onto metabolic pathways implied their reprogramming upon infection. The enzymes involved in Calvin cycle and glycolysis decreased in their protein abundance, whereas enzymes in the TCA cycle, amino acids, and ethylene biosynthesis increased. Differential proteomes also generated distribution of identified proteins in the intracellular and extracellular spaces, providing a better insight into defense responses of proteins in rice against C. miyabeanus. Established proteome of the rice-C. miyabeanus interaction serves not only as a good resource for the scientific community but also highlights its significance from biological aspects. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

POP1 might be recruiting its type-Ia interface for NLRP3-mediated PYD-PYD interaction: Insights from MD simulation.

PubMed

Maharana, Jitendra; Vats, Ashutosh; Gautam, Santwana; Nayak, Bibhu Prasad; Kumar, Sushil; Sendha, Jasobanta; De, Sachinandan

2017-09-01

Inflammasomes are multiprotein caspase-activating complexes that enhance the maturation and release of proinflammatory cytokines (IL-1β and IL-18) in response to the invading pathogen and/or host-derived cellular stress. These are assembled by the sensory proteins (viz NLRC4, NLRP1, NLRP3, and AIM-2), adaptor protein (ASC), and effector molecule procaspase-1. In NLRP3-mediated inflammasome activation, ASC acts as a mediator between NLRP3 and procaspase-1 for the transmission of signals. A series of homotypic protein-protein interactions (NLRP3 PYD :ASC PYD and ASC CARD :CASP1 CARD ) propagates the downstream signaling for the production of proinflammatory cytokines. Pyrin-only protein 1 (POP1) is known to act as the regulator of inflammasome. It modulates the ASC-mediated inflammasome assembly by interacting with pyrin domain (PYD) of ASC. However, despite similar electrostatic surface potential, the interaction of POP1 with NLRP3 PYD is obscured till date. Herein, to explore the possible PYD-PYD interactions between NLRP3 PYD and POP1, a combined approach of protein-protein docking and molecular dynamics simulation was adapted. The current study revealed that POP1's type-Ia interface and type-Ib interface of NLRP3 PYD might be crucial for 1:1 PYD-PYD interaction. In addition to type-I mode of interaction, we also observed type-II and type-III interaction modes in two different dynamically stable heterotrimeric complexes (POP1-NLRP3-NLRP3 and POP1-NLRP3-POP1). The inter-residual/atomic distance calculation exposed several critical residues that possibly govern the said interaction, which need further investigation. Overall, the findings of this study will shed new light on hitherto concealed molecular mechanisms underlying NLRP3-mediated inflammasome, which will have strong future therapeutic implications. Copyright © 2017 John Wiley & Sons, Ltd.

Structural Elements in the Gαs and Gαq C Termini That Mediate Selective G Protein-coupled Receptor (GPCR) Signaling.

PubMed

Semack, Ansley; Sandhu, Manbir; Malik, Rabia U; Vaidehi, Nagarajan; Sivaramakrishnan, Sivaraj

2016-08-19

Although the importance of the C terminus of the α subunit of the heterotrimeric G protein in G protein-coupled receptor (GPCR)-G protein pairing is well established, the structural basis of selective interactions remains unknown. Here, we combine live cell FRET-based measurements and molecular dynamics simulations of the interaction between the GPCR and a peptide derived from the C terminus of the Gα subunit (Gα peptide) to dissect the molecular mechanisms of G protein selectivity. We observe a direct link between Gα peptide binding and stabilization of the GPCR conformational ensemble. We find that cognate and non-cognate Gα peptides show deep and shallow binding, respectively, and in distinct orientations within the GPCR. Binding of the cognate Gα peptide stabilizes the agonist-bound GPCR conformational ensemble resulting in favorable binding energy and lower flexibility of the agonist-GPCR pair. We identify three hot spot residues (Gαs/Gαq-Gln-384/Leu-349, Gln-390/Glu-355, and Glu-392/Asn-357) that contribute to selective interactions between the β2-adrenergic receptor (β2-AR)-Gαs and V1A receptor (V1AR)-Gαq The Gαs and Gαq peptides adopt different orientations in β2-AR and V1AR, respectively. The β2-AR/Gαs peptide interface is dominated by electrostatic interactions, whereas the V1AR/Gαq peptide interactions are predominantly hydrophobic. Interestingly, our study reveals a role for both favorable and unfavorable interactions in G protein selection. Residue Glu-355 in Gαq prevents this peptide from interacting strongly with β2-AR. Mutagenesis to the Gαs counterpart (E355Q) imparts a cognate-like interaction. Overall, our study highlights the synergy in molecular dynamics and FRET-based approaches to dissect the structural basis of selective G protein interactions. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

The interaction between thermodynamic stability and buried free cysteines in regulating the functional half-life of fibroblast growth factor-1.

PubMed

Lee, Jihun; Blaber, Michael

2009-10-16

Protein biopharmaceuticals are an important and growing area of human therapeutics; however, the intrinsic property of proteins to adopt alternative conformations (such as during protein unfolding and aggregation) presents numerous challenges, limiting their effective application as biopharmaceuticals. Using fibroblast growth factor-1 as model system, we describe a cooperative interaction between the intrinsic property of thermostability and the reactivity of buried free-cysteine residues that can substantially modulate protein functional half-life. A mutational strategy that combines elimination of buried free cysteines and secondary mutations that enhance thermostability to achieve a substantial gain in functional half-life is described. Furthermore, the implementation of this design strategy utilizing stabilizing mutations within the core region resulted in a mutant protein that is essentially indistinguishable from wild type as regard protein surface and solvent structure, thus minimizing the immunogenic potential of the mutations. This design strategy should be generally applicable to soluble globular proteins containing buried free-cysteine residues.

Free-energy landscape of protein oligomerization from atomistic simulations.

PubMed

Barducci, Alessandro; Bonomi, Massimiliano; Prakash, Meher K; Parrinello, Michele

2013-12-03

In the realm of protein-protein interactions, the assembly process of homooligomers plays a fundamental role because the majority of proteins fall into this category. A comprehensive understanding of this multistep process requires the characterization of the driving molecular interactions and the transient intermediate species. The latter are often short-lived and thus remain elusive to most experimental investigations. Molecular simulations provide a unique tool to shed light onto these complex processes complementing experimental data. Here we combine advanced sampling techniques, such as metadynamics and parallel tempering, to characterize the oligomerization landscape of fibritin foldon domain. This system is an evolutionarily optimized trimerization motif that represents an ideal model for experimental and computational mechanistic studies. Our results are fully consistent with previous experimental nuclear magnetic resonance and kinetic data, but they provide a unique insight into fibritin foldon assembly. In particular, our simulations unveil the role of nonspecific interactions and suggest that an interplay between thermodynamic bias toward native structure and residual conformational disorder may provide a kinetic advantage.

PTEN status is a crucial determinant of the functional outcome of combined MEK and mTOR inhibition in cancer.

PubMed

Milella, Michele; Falcone, Italia; Conciatori, Fabiana; Matteoni, Silvia; Sacconi, Andrea; De Luca, Teresa; Bazzichetto, Chiara; Corbo, Vincenzo; Simbolo, Michele; Sperduti, Isabella; Benfante, Antonina; Del Curatolo, Anais; Cesta Incani, Ursula; Malusa, Federico; Eramo, Adriana; Sette, Giovanni; Scarpa, Aldo; Konopleva, Marina; Andreeff, Michael; McCubrey, James Andrew; Blandino, Giovanni; Todaro, Matilde; Stassi, Giorgio; De Maria, Ruggero; Cognetti, Francesco; Del Bufalo, Donatella; Ciuffreda, Ludovica

2017-02-21

Combined MAPK/PI3K pathway inhibition represents an attractive, albeit toxic, therapeutic strategy in oncology. Since PTEN lies at the intersection of these two pathways, we investigated whether PTEN status determines the functional response to combined pathway inhibition. PTEN (gene, mRNA, and protein) status was extensively characterized in a panel of cancer cell lines and combined MEK/mTOR inhibition displayed highly synergistic pharmacologic interactions almost exclusively in PTEN-loss models. Genetic manipulation of PTEN status confirmed a mechanistic role for PTEN in determining the functional outcome of combined pathway blockade. Proteomic analysis showed greater phosphoproteomic profile modification(s) in response to combined MEK/mTOR inhibition in PTEN-loss contexts and identified JAK1/STAT3 activation as a potential mediator of synergistic interactions. Overall, our results show that PTEN-loss is a crucial determinant of synergistic interactions between MAPK and PI3K pathway inhibitors, potentially exploitable for the selection of cancer patients at the highest chance of benefit from combined therapeutic strategies.

PTEN status is a crucial determinant of the functional outcome of combined MEK and mTOR inhibition in cancer

PubMed Central

Milella, Michele; Falcone, Italia; Conciatori, Fabiana; Matteoni, Silvia; Sacconi, Andrea; De Luca, Teresa; Bazzichetto, Chiara; Corbo, Vincenzo; Simbolo, Michele; Sperduti, Isabella; Benfante, Antonina; Del Curatolo, Anais; Cesta Incani, Ursula; Malusa, Federico; Eramo, Adriana; Sette, Giovanni; Scarpa, Aldo; Konopleva, Marina; Andreeff, Michael; McCubrey, James Andrew; Blandino, Giovanni; Todaro, Matilde; Stassi, Giorgio; De Maria, Ruggero; Cognetti, Francesco; Del Bufalo, Donatella; Ciuffreda, Ludovica

2017-01-01

Combined MAPK/PI3K pathway inhibition represents an attractive, albeit toxic, therapeutic strategy in oncology. Since PTEN lies at the intersection of these two pathways, we investigated whether PTEN status determines the functional response to combined pathway inhibition. PTEN (gene, mRNA, and protein) status was extensively characterized in a panel of cancer cell lines and combined MEK/mTOR inhibition displayed highly synergistic pharmacologic interactions almost exclusively in PTEN-loss models. Genetic manipulation of PTEN status confirmed a mechanistic role for PTEN in determining the functional outcome of combined pathway blockade. Proteomic analysis showed greater phosphoproteomic profile modification(s) in response to combined MEK/mTOR inhibition in PTEN-loss contexts and identified JAK1/STAT3 activation as a potential mediator of synergistic interactions. Overall, our results show that PTEN-loss is a crucial determinant of synergistic interactions between MAPK and PI3K pathway inhibitors, potentially exploitable for the selection of cancer patients at the highest chance of benefit from combined therapeutic strategies. PMID:28220839

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

PubMed

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

2017-07-13

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

Protein Stability in Mixed Solvents: A Balance of Contact Interaction and Excluded Volume

PubMed Central

Schellman, John A.

2003-01-01

Changes in excluded volume and contact interaction with the surface of a protein have been suggested as mechanisms for the changes in stability induced by cosolvents. The aim of the present paper is to present an analysis that combines both effects in a quantitative manner. The result is that both processes are present in both stabilizing and destabilizing interactions and neither can be ignored. Excluded volume was estimated using accessible surface area calculations of the kind introduced by Lee and Richards. The change in excluded volume on unfolding, ΔX, is quite large. For example, ΔX for ribonuclease is 6.7 L in urea and ∼16 L in sucrose. The latter number is greater than the molar volume of the protein. Direct interaction with the protein is represented as the solvent exchange mechanism, which differs from ordinary association theory because of the weakness of the interaction and the high concentrations of cosolvents. The balance between the two effects and their contribution to overall stability are most simply presented as bar diagrams as in Fig. 3. Our finding for five proteins is that excluded volume contributes to the stabilization of the native structure and that contact interaction contributes to destabilization. This is true for five proteins and four cosolvents including both denaturants and osmolytes. Whether a substance stabilizes a protein or destabilizes it depends on the relative size of these two contributions. The constant for the cosolvent contact with the protein is remarkably uniform for four of the proteins, indicating a similarity of groups exposed during unfolding. One protein, staphylococcus nuclease, is anomalous in almost all respects. In general, the strength of the interaction with guanidinium is about twice that of urea, which is about twice that of trimethylamine-N-oxide and sucrose. Arguments are presented for the use of volume fractions in equilibrium equations and the ignoring of activity coefficients of the cosolvent. It is shown in the Appendix that both the excluded volume and the direct interaction can be extracted in a unified way from the McMillan-Mayer formula for the second virial coefficient. PMID:12829469

Specific binding of a Pop6/Pop7 heterodimer to the P3 stem of the yeast RNase MRP and RNase P RNAs.

PubMed

Perederina, Anna; Esakova, Olga; Koc, Hasan; Schmitt, Mark E; Krasilnikov, Andrey S

2007-10-01

Pop6 and Pop7 are protein subunits of Saccharomyces cerevisiae RNase MRP and RNase P. Here we show that bacterially expressed Pop6 and Pop7 form a soluble heterodimer that binds the RNA components of both RNase MRP and RNase P. Footprint analysis of the interaction between the Pop6/7 heterodimer and the RNase MRP RNA, combined with gel mobility assays, demonstrates that the Pop6/7 complex binds to a conserved region of the P3 domain. Binding of these proteins to the MRP RNA leads to local rearrangement in the structure of the P3 loop and suggests that direct interaction of the Pop6/7 complex with the P3 domain of the RNA components of RNases MRP and P may mediate binding of other protein components. These results suggest a role for a key element in the RNase MRP and RNase P RNAs in protein binding, and demonstrate the feasibility of directly studying RNA-protein interactions in the eukaryotic RNases MRP and P complexes.

Chimeric Saccharomyces cerevisiae Msh6 protein with an Msh3 mispair-binding domain combines properties of both proteins.

PubMed

Shell, Scarlet S; Putnam, Christopher D; Kolodner, Richard D

2007-06-26

Msh2-Msh3 and Msh2-Msh6 are two partially redundant mispair-recognition complexes that initiate mismatch repair in eukaryotes. Crystal structures of the prokaryotic homolog MutS suggest the mechanism by which Msh6 interacts with mispairs because key mispair-contacting residues are conserved in these two proteins. Because Msh3 lacks these conserved residues, we constructed a series of mutants to investigate the requirements for mispair interaction by Msh3. We found that a chimeric protein in which the mispair-binding domain (MBD) of Msh6 was replaced by the equivalent domain of Msh3 was functional for mismatch repair. This chimera possessed the mispair-binding specificity of Msh3 and revealed that communication between the MBD and the ATPase domain is conserved between Msh2-Msh3 and Msh2-Msh6. Further, the chimeric protein retained Msh6-like properties with respect to genetic interactions with the MutL homologs and an Msh2 MBD deletion mutant, indicating that Msh3-like behaviors beyond mispair specificity are not features controlled by the MBD.

Text mining for metabolic pathways, signaling cascades, and protein networks.

PubMed

Hoffmann, Robert; Krallinger, Martin; Andres, Eduardo; Tamames, Javier; Blaschke, Christian; Valencia, Alfonso

2005-05-10

The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.

Characterization of the Saccharomyces cerevisiae ATP-Interactome using the iTRAQ-SPROX Technique

NASA Astrophysics Data System (ADS)

Geer, M. Ariel; Fitzgerald, Michael C.

2016-02-01

The stability of proteins from rates of oxidation (SPROX) technique was used in combination with an isobaric mass tagging strategy to identify adenosine triphosphate (ATP) interacting proteins in the Saccharomyces cerevisiae proteome. The SPROX methodology utilized in this work enabled 373 proteins in a yeast cell lysate to be assayed for ATP interactions (both direct and indirect) using the non-hydrolyzable ATP analog, adenylyl imidodiphosphate (AMP-PNP). A total of 28 proteins were identified with AMP-PNP-induced thermodynamic stability changes. These protein hits included 14 proteins that were previously annotated as ATP-binding proteins in the Saccharomyces Genome Database (SGD). The 14 non-annotated ATP-binding proteins included nine proteins that were previously found to be ATP-sensitive in an earlier SPROX study using a stable isotope labeling with amino acids in cell culture (SILAC)-based approach. A bioinformatics analysis of the protein hits identified here and in the earlier SILAC-SPROX experiments revealed that many of the previously annotated ATP-binding protein hits were kinases, ligases, and chaperones. In contrast, many of the newly discovered ATP-sensitive proteins were not from these protein classes, but rather were hydrolases, oxidoreductases, and nucleic acid-binding proteins.

Free energy determinants of secondary structure formation: III. beta-turns and their role in protein folding.

PubMed

Yang, A S; Hitz, B; Honig, B

1996-06-21

The stability of beta-turns is calculated as a function of sequence and turn type with a Monte Carlo sampling technique. The conformational energy of four internal hydrogen-bonded turn types, I, I', II and II', is obtained by evaluating their gas phase energy with the CHARMM force field and accounting for solvation effects with the Finite Difference Poisson-Boltzmann (FDPB) method. All four turn types are found to be less stable than the coil state, independent of the sequence in the turn. The free-energy penalties associated with turn formation vary between 1.6 kcal/mol and 7.7 kcal/mol, depending on the sequence and turn type. Differences in turn stability arise mainly from intraresidue interactions within the two central residues of the turn. For each combination of the two central residues, except for -Gly-Gly-, the most stable beta-turn type is always found to occur most commonly in native proteins. The fact that a model based on local interactions accounts for the observed preference of specific sequences suggests that long-range tertiary interactions tend to play a secondary role in determining turn conformation. In contrast, for beta-hairpins, long-range interactions appear to dominate. Specifically, due to the right-handed twist of beta-strands, type I' turns for -Gly-Gly- are found to occur with high frequency, even when local energetics would dictate otherwise. The fact that any combination of two residues is found able to adopt a relatively low-energy turn structure explains why the amino acid sequence in turns is highly variable. The calculated free-energy cost of turn formation, when combined with related numbers obtained for alpha-helices and beta-sheets, suggests a model for the initiation of protein folding based on metastable fragments of secondary structure.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

PubMed

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

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.

Computational and theoretical approaches for studies of a lipid recognition protein on biological membranes

PubMed Central

Yamamoto, Eiji

2017-01-01

Many cellular functions, including cell signaling and related events, are regulated by the association of peripheral membrane proteins (PMPs) with biological membranes containing anionic lipids, e.g., phosphatidylinositol phosphate (PIP). This association is often mediated by lipid recognition modules present in many PMPs. Here, I summarize computational and theoretical approaches to investigate the molecular details of the interactions and dynamics of a lipid recognition module, the pleckstrin homology (PH) domain, on biological membranes. Multiscale molecular dynamics simulations using combinations of atomistic and coarse-grained models yielded results comparable to those of actual experiments and could be used to elucidate the molecular mechanisms of the formation of protein/lipid complexes on membrane surfaces, which are often difficult to obtain using experimental techniques. Simulations revealed some modes of membrane localization and interactions of PH domains with membranes in addition to the canonical binding mode. In the last part of this review, I address the dynamics of PH domains on the membrane surface. Local PIP clusters formed around the proteins exhibit anomalous fluctuations. This dynamic change in protein-lipid interactions cause temporally fluctuating diffusivity of proteins, i.e., the short-term diffusivity of the bound protein changes substantially with time, and may in turn contribute to the formation/dissolution of protein complexes in membranes. PMID:29159013

Directed Evolution of a Cyclized Peptoid-Peptide Chimera against a Cell-Free Expressed Protein and Proteomic Profiling of the Interacting Proteins to Create a Protein-Protein Interaction Inhibitor.

PubMed

Kawakami, Takashi; Ogawa, Koji; Hatta, Tomohisa; Goshima, Naoki; Natsume, Tohru

2016-06-17

N-alkyl amino acids are useful building blocks for the in vitro display evolution of ribosomally synthesized peptides because they can increase the proteolytic stability and cell permeability of these peptides. However, the translation initiation substrate specificity of nonproteinogenic N-alkyl amino acids has not been investigated. In this study, we screened various N-alkyl amino acids and nonamino carboxylic acids for translation initiation with an Escherichia coli reconstituted cell-free translation system (PURE system) and identified those that efficiently initiated translation. Using seven of these efficiently initiating acids, we next performed in vitro display evolution of cyclized peptidomimetics against an arbitrarily chosen model human protein (β-catenin) cell-free expressed from its cloned cDNA (HUPEX) and identified a novel β-catenin-binding cyclized peptoid-peptide chimera. Furthermore, by a proteomic approach using direct nanoflow liquid chromatography-tandem mass spectrometry (DNLC-MS/MS), we successfully identified which protein-β-catenin interaction is inhibited by the chimera. The combination of in vitro display evolution of cyclized N-alkyl peptidomimetics and in vitro expression of human proteins would be a powerful approach for the high-speed discovery of diverse human protein-targeted cyclized N-alkyl peptidomimetics.

New AdoMet Analogues as Tools for Enzymatic Transfer of Photo-Cross-Linkers and Capturing RNA-Protein Interactions.

PubMed

Muttach, Fabian; Mäsing, Florian; Studer, Armido; Rentmeister, Andrea

2017-05-02

Elucidation of biomolecular interactions is of utmost importance in biochemistry. Photo-cross-linking offers the possibility to precisely determine RNA-protein interactions. However, despite the inherent specificity of enzymes, approaches for site-specific introduction of photo-cross-linking moieties into nucleic acids are scarce. Methyltransferases in combination with synthetic analogues of their natural cosubstrate S-adenosyl-l-methionine (AdoMet) allow for the post-synthetic site-specific modification of biomolecules. We report on three novel AdoMet analogues bearing the most widespread photo-cross-linking moieties (aryl azide, diazirine, and benzophenone). We show that these photo-cross-linkers can be enzymatically transferred to the methyltransferase target, that is, the mRNA cap, with high efficiency. Photo-cross-linking of the resulting modified mRNAs with the cap interacting protein eIF4E was successful with aryl azide and diazirine but not benzophenone, reflecting the affinity of the modified 5' caps. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization of Glutaredoxin Fe-S Cluster-Binding Interactions Using Circular Dichroism Spectroscopy.

PubMed

Albetel, Angela-Nadia; Outten, Caryn E

2018-01-01

Monothiol glutaredoxins (Grxs) with a conserved Cys-Gly-Phe-Ser (CGFS) active site are iron-sulfur (Fe-S) cluster-binding proteins that interact with a variety of partner proteins and perform crucial roles in iron metabolism including Fe-S cluster transfer, Fe-S cluster repair, and iron signaling. Various analytical and spectroscopic methods are currently being used to monitor and characterize glutaredoxin Fe-S cluster-dependent interactions at the molecular level. The electronic, magnetic, and vibrational properties of the protein-bound Fe-S cluster provide a convenient handle to probe the structure, function, and coordination chemistry of Grx complexes. However, some limitations arise from sample preparation requirements, complexity of individual techniques, or the necessity for combining multiple methods in order to achieve a complete investigation. In this chapter, we focus on the use of UV-visible circular dichroism spectroscopy as a fast and simple initial approach for investigating glutaredoxin Fe-S cluster-dependent interactions. © 2018 Elsevier Inc. All rights reserved.

Interaction between IGFBP7 and insulin: a theoretical and experimental study

NASA Astrophysics Data System (ADS)

Ruan, Wenjing; Kang, Zhengzhong; Li, Youzhao; Sun, Tianyang; Wang, Lipei; Liang, Lijun; Lai, Maode; Wu, Tao

2016-04-01

Insulin-like growth factor binding protein 7 (IGFBP7) can bind to insulin with high affinity which inhibits the early steps of insulin action. Lack of recognition mechanism impairs our understanding of insulin regulation before it binds to insulin receptor. Here we combine computational simulations with experimental methods to investigate the interaction between IGFBP7 and insulin. Molecular dynamics simulations indicated that His200 and Arg198 in IGFBP7 were key residues. Verified by experimental data, the interaction remained strong in single mutation systems R198E and H200F but became weak in double mutation system R198E-H200F relative to that in wild-type IGFBP7. The results and methods in present study could be adopted in future research of discovery of drugs by disrupting protein-protein interactions in insulin signaling. Nevertheless, the accuracy, reproducibility, and costs of free-energy calculation are still problems that need to be addressed before computational methods can become standard binding prediction tools in discovery pipelines.

Combined vitamin B-12 and balanced protein-energy supplementation affect homocysteine remethylation in the methionine cycle in pregnant south Indian women of low vitamin B-12 status

USDA-ARS?s Scientific Manuscript database

Low-quality dietary protein intake and vitamin B-12 deficiency could interact to decrease methionine transmethylation and remethylation rates during pregnancy, and may affect epigenetic modifications of the fetal genome. The objective of this randomized, partially open-labeled intervention trial was...

Bidirectional immobilization of affinity-tagged cytochrome c on electrode surfaces.

PubMed

Schröper, Florian; Baumann, Arnd; Offenhäusser, Andreas; Mayer, Dirk

2010-08-07

Here, we report a new strategy for the directed bivalent immobilization of cyt c on or between gold electrodes. C-terminal modification with cys- or his-tag did not affect the functional integrity of the protein. In combination with electrostatic protein binding, these tags enable a bifunctional immobilization between two electrodes or alternatively one electrode and interacting enzymes.

Inhibitors of Ras-SOS Interactions.

PubMed

Lu, Shaoyong; Jang, Hyunbum; Zhang, Jian; Nussinov, Ruth

2016-04-19

Activating Ras mutations are found in about 30 % of human cancers. Ras activation is regulated by guanine nucleotide exchange factors, such as the son of sevenless (SOS), which form protein-protein interactions (PPIs) with Ras and catalyze the exchange of GDP by GTP. This is the rate-limiting step in Ras activation. However, Ras surfaces lack any evident suitable pockets where a molecule might bind tightly, rendering Ras proteins still 'undruggable' for over 30 years. Among the alternative approaches is the design of inhibitors that target the Ras-SOS PPI interface, a strategy that is gaining increasing recognition for treating Ras mutant cancers. Herein we focus on data that has accumulated over the past few years pertaining to the design of small-molecule modulators or peptide mimetics aimed at the interface of the Ras-SOS PPI. We emphasize, however, that even if such Ras-SOS therapeutics are potent, drug resistance may emerge. To counteract this development, we propose "pathway drug cocktails", that is, drug combinations aimed at parallel (or compensatory) pathways. A repertoire of classified cancer, cell/tissue, and pathway/protein combinations would be beneficial toward this goal. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Aggregation factor analysis for protein formulation by a systematic approach using FTIR, SEC and design of experiments techniques.

PubMed

Feng, Yan Wen; Ooishi, Ayako; Honda, Shinya

2012-01-05

A simple systematic approach using Fourier transform infrared (FTIR) spectroscopy, size exclusion chromatography (SEC) and design of experiments (DOE) techniques was applied to the analysis of aggregation factors for protein formulations in stress and accelerated testings. FTIR and SEC were used to evaluate protein conformational and storage stabilities, respectively. DOE was used to determine the suitable formulation and to analyze both the main effect of single factors and the interaction effect of combined factors on aggregation. Our results indicated that (i) analysis at a low protein concentration is not always applicable to high concentration formulations; (ii) an investigation of interaction effects of combined factors as well as main effects of single factors is effective for improving conformational stability of proteins; (iii) with the exception of pH, the results of stress testing with regard to aggregation factors would be available for suitable formulation instead of performing time-consuming accelerated testing; (iv) a suitable pH condition should not be determined in stress testing but in accelerated testing, because of inconsistent effects of pH on conformational and storage stabilities. In summary, we propose a three-step strategy, using FTIR, SEC and DOE techniques, to effectively analyze the aggregation factors and perform a rapid screening for suitable conditions of protein formulation. Copyright © 2011 Elsevier B.V. All rights reserved.

Molecular modelling of protein-protein/protein-solvent interactions

NASA Astrophysics Data System (ADS)

Luchko, Tyler

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

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

PubMed

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

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the ability to influence interactions among host proteins are important components for F. tularensis to avoid host-cell defense mechanisms and successfully establish an infection. Although direct host-pathogen protein-protein binding is only one aspect of Francisella virulence, it is a critical component in directly manipulating and interfering with cellular processes in the host cell.

BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations.

PubMed

Dehouck, Yves; Kwasigroch, Jean Marc; Rooman, Marianne; Gilis, Dimitri

2013-07-01

The ability of proteins to establish highly selective interactions with a variety of (macro)molecular partners is a crucial prerequisite to the realization of their biological functions. The availability of computational tools to evaluate the impact of mutations on protein-protein binding can therefore be valuable in a wide range of industrial and biomedical applications, and help rationalize the consequences of non-synonymous single-nucleotide polymorphisms. BeAtMuSiC (http://babylone.ulb.ac.be/beatmusic) is a coarse-grained predictor of the changes in binding free energy induced by point mutations. It relies on a set of statistical potentials derived from known protein structures, and combines the effect of the mutation on the strength of the interactions at the interface, and on the overall stability of the complex. The BeAtMuSiC server requires as input the structure of the protein-protein complex, and gives the possibility to assess rapidly all possible mutations in a protein chain or at the interface, with predictive performances that are in line with the best current methodologies.

Enhanced plastic deformations of nanofibrillated cellulose film by adsorbed moisture and protein-mediated interactions.

PubMed

Malho, Jani-Markus; Ouellet-Plamondon, Claudiane; Rüggeberg, Markus; Laaksonen, Päivi; Ikkala, Olli; Burgert, Ingo; Linder, Markus B

2015-01-12

Biological composites are typically based on an adhesive matrix that interlocks rigid reinforcing elements in fiber composite or brick-and-mortar assemblies. In nature, the adhesive matrix is often made up of proteins, which are also interesting model systems, as they are unique among polymers in that we know how to engineer their structures with atomic detail and to select protein elements for specific interactions with other components. Here we studied how fusion proteins that consist of cellulose binding proteins linked to proteins that show a natural tendency to form multimer complexes act as an adhesive matrix in combination with nanofibrillated cellulose. We found that the fusion proteins are retained with the cellulose and that the proteins mainly affect the plastic yield behavior of the cellulose material as a function of water content. Interestingly, the proteins increased the moisture absorption of the composite, but the well-known plastifying effect of water was clearly decreased. The work helps to understand the functional basis of nanocellulose composites as materials and aims toward building model systems for molecular biomimetic materials.

Exploring the interactome: microfluidic isolation of proteins and interacting partners for quantitative analysis by electron microscopy.

PubMed

Giss, Dominic; Kemmerling, Simon; Dandey, Venkata; Stahlberg, Henning; Braun, Thomas

2014-05-20

Multimolecular protein complexes are important for many cellular processes. However, the stochastic nature of the cellular interactome makes the experimental detection of complex protein assemblies difficult and quantitative analysis at the single molecule level essential. Here, we present a fast and simple microfluidic method for (i) the quantitative isolation of endogenous levels of untagged protein complexes from minute volumes of cell lysates under close to physiological conditions and (ii) the labeling of specific components constituting these complexes. The method presented uses specific antibodies that are conjugated via a photocleavable linker to magnetic beads that are trapped in microcapillaries to immobilize the target proteins. Proteins are released by photocleavage, eluted, and subsequently analyzed by quantitative transmission electron microscopy at the single molecule level. Additionally, before photocleavage, immunogold can be employed to label proteins that interact with the primary target protein. Thus, the presented method provides a new way to study the interactome and, in combination with single molecule transmission electron microscopy, to structurally characterize the large, dynamic, heterogeneous multimolecular protein complexes formed.

High Throughput, Label-free Screening Small Molecule Compound Libraries for Protein-Ligands using Combination of Small Molecule Microarrays and a Special Ellipsometry-based Optical Scanner.

PubMed

Landry, James P; Fei, Yiyan; Zhu, X D

2011-12-01

Small-molecule compounds remain the major source of therapeutic and preventative drugs. Developing new drugs against a protein target often requires screening large collections of compounds with diverse structures for ligands or ligand fragments that exhibit sufficiently affinity and desirable inhibition effect on the target before further optimization and development. Since the number of small molecule compounds is large, high-throughput screening (HTS) methods are needed. Small-molecule microarrays (SMM) on a solid support in combination with a suitable binding assay form a viable HTS platform. We demonstrate that by combining an oblique-incidence reflectivity difference optical scanner with SMM we can screen 10,000 small-molecule compounds on a single glass slide for protein ligands without fluorescence labeling. Furthermore using such a label-free assay platform we can simultaneously acquire binding curves of a solution-phase protein to over 10,000 immobilized compounds, thus enabling full characterization of protein-ligand interactions over a wide range of affinity constants.

Theory of nematic order with aggregate dehydration for reversibly assembling proteins in concentrated solutions: Application to sickle-cell hemoglobin polymers

NASA Astrophysics Data System (ADS)

Hentschke, Reinhard; Herzfeld, Judith

1991-06-01

The reversible association of globular protein molecules in concentrated solution leads to highly polydisperse fibers, e.g., actin filaments, microtubules, and sickle-cell hemoglobin fibers. At high concentrations, excluded-volume interactions between the fibers lead to spontaneous alignment analogous to that in simple lyotropic liquid crystals. However, the phase behavior of reversibly associating proteins is complicated by the threefold coupling between the growth, alignment, and hydration of the fibers. In protein systems aggregates contain substantial solvent, which may cause them to swell or shrink, depending on osmotic stress. Extending previous work, we present a model for the equilibrium phase behavior of the above-noted protein systems in terms of simple intra- and interaggregate interactions, combined with equilibration of fiber-incorporated solvent with the bulk solvent. Specifically, we compare our model results to recent osmotic pressure data for sickle-cell hemoglobin and find excellent agreement. This comparison shows that particle interactions sufficient to cause alignment are also sufficient to squeeze significant amounts of solvent out of protein fibers. In addition, the model is in accord with findings from independent sedimentation and birefringence studies on sickle-cell hemoglobin.

DNA-repair protein hHR23a alters its protein structure upon binding proteasomal subunit S5a

PubMed Central

Walters, Kylie J.; Lech, Patrycja J.; Goh, Amanda M.; Wang, Qinghua; Howley, Peter M.

2003-01-01

The Rad23 family of proteins, including the human homologs hHR23a and hHR23b, stimulates nucleotide excision repair and has been shown to provide a novel link between proteasome-mediated protein degradation and DNA repair. In this work, we illustrate how the proteasomal subunit S5a regulates hHR23a protein structure. By using NMR spectroscopy, we have elucidated the structure and dynamic properties of the 40-kDa hHR23a protein and show it to contain four structured domains connected by flexible linker regions. In addition, we reveal that these domains interact in an intramolecular fashion, and by using residual dipolar coupling data in combination with chemical shift perturbation analysis, we present the hHR23a structure. By itself, hHR23a adopts a closed conformation defined by the interaction of an N-terminal ubiquitin-like domain with two ubiquitin-associated domains. Interestingly, binding of the proteasomal subunit S5a disrupts the hHR23a interdomain interactions and thereby causes it to adopt an opened conformation. PMID:14557549

Structural and Biological Interaction of hsc-70 Protein with Phosphatidylserine in Endosomal Microautophagy*

PubMed Central

Morozova, Kateryna; Clement, Cristina C.; Kaushik, Susmita; Stiller, Barbara; Arias, Esperanza; Ahmad, Atta; Rauch, Jennifer N.; Chatterjee, Victor; Melis, Chiara; Scharf, Brian; Gestwicki, Jason E.; Cuervo, Ana-Maria; Zuiderweg, Erik R. P.; Santambrogio, Laura

2016-01-01

hsc-70 (HSPA8) is a cytosolic molecular chaperone, which plays a central role in cellular proteostasis, including quality control during protein refolding and regulation of protein degradation. hsc-70 is pivotal to the process of macroautophagy, chaperone-mediated autophagy, and endosomal microautophagy. The latter requires hsc-70 interaction with negatively charged phosphatidylserine (PS) at the endosomal limiting membrane. Herein, by combining plasmon resonance, NMR spectroscopy, and amino acid mutagenesis, we mapped the C terminus of the hsc-70 LID domain as the structural interface interacting with endosomal PS, and we estimated an hsc-70/PS equilibrium dissociation constant of 4.7 ± 0.1 μm. This interaction is specific and involves a total of 4–5 lysine residues. Plasmon resonance and NMR results were further experimentally validated by hsc-70 endosomal binding experiments and endosomal microautophagy assays. The discovery of this previously unknown contact surface for hsc-70 in this work elucidates the mechanism of hsc-70 PS/membrane interaction for cytosolic cargo internalization into endosomes. PMID:27405763

Structural and Biological Interaction of hsc-70 Protein with Phosphatidylserine in Endosomal Microautophagy.

PubMed

Morozova, Kateryna; Clement, Cristina C; Kaushik, Susmita; Stiller, Barbara; Arias, Esperanza; Ahmad, Atta; Rauch, Jennifer N; Chatterjee, Victor; Melis, Chiara; Scharf, Brian; Gestwicki, Jason E; Cuervo, Ana-Maria; Zuiderweg, Erik R P; Santambrogio, Laura

2016-08-26

hsc-70 (HSPA8) is a cytosolic molecular chaperone, which plays a central role in cellular proteostasis, including quality control during protein refolding and regulation of protein degradation. hsc-70 is pivotal to the process of macroautophagy, chaperone-mediated autophagy, and endosomal microautophagy. The latter requires hsc-70 interaction with negatively charged phosphatidylserine (PS) at the endosomal limiting membrane. Herein, by combining plasmon resonance, NMR spectroscopy, and amino acid mutagenesis, we mapped the C terminus of the hsc-70 LID domain as the structural interface interacting with endosomal PS, and we estimated an hsc-70/PS equilibrium dissociation constant of 4.7 ± 0.1 μm. This interaction is specific and involves a total of 4-5 lysine residues. Plasmon resonance and NMR results were further experimentally validated by hsc-70 endosomal binding experiments and endosomal microautophagy assays. The discovery of this previously unknown contact surface for hsc-70 in this work elucidates the mechanism of hsc-70 PS/membrane interaction for cytosolic cargo internalization into endosomes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Electronic distributions within protein phenylalanine aromatic rings are reflected by the three-dimensional oxygen atom environments.

PubMed Central

Thomas, K A; Smith, G M; Thomas, T B; Feldmann, R J

1982-01-01

The atomic environments of 170 phenylalanine-residue aromatic rings from 28 protein crystal structures are transformed into a common orientation and combined to calculate an average three-dimensional environment. The spatial distribution of atom types in this environment reveals a preferred interaction between oxygen atoms and the edge of the planar aromatic rings. From the difference in frequency of interaction of oxygen atoms with the edge and the top of the ring, an apparent net free energy difference of interaction favoring the edge of the ring is estimated to be about -1 kcal/mol (1 cal = 4.184 J). Ab initio quantum mechanical calculations, performed on a model consisting of benzene and formamide, indicate that the observed geometry is stabilized by a favorable enthalpic interaction. Although benzene rings are considered to be nonpolar, the electron distribution is a complex multipole with no net dipole moment. The observed interaction orientation frequencies demonstrate that these multipolar electron distributions, when occurring at the short distances encountered in densely packed protein molecules, are significant determinants of internal packing geometries. PMID:6956896

Models of globular proteins in aqueous solutions

NASA Astrophysics Data System (ADS)

Wentzel, Nathaniel James

Protein crystallization is a continuing area of research. Currently, there is no universal theory for the conditions required to crystallize proteins. A better understanding of protein crystallization will be helpful in determining protein structure and preventing and treating certain diseases. In this thesis, we will extend the understanding of globular proteins in aqueous solutions by analyzing various models for protein interactions. Experiments have shown that the liquid-liquid phase separation curves for lysozyme in solution with salt depend on salt type and salt concentration. We analyze a simple square well model for this system whose well depth depends on salt type and salt concentration, to determine the phase coexistence surfaces from experimental data. The surfaces, calculated from a single Monte Carlo simulation and a simple scaling argument, are shown as a function of temperature, salt concentration and protein concentration for two typical salts. Urate Oxidase from Asperigillus flavus is a protein used for studying the effects of polymers on the crystallization of large proteins. Experiments have determined some aspects of the phase diagram. We use Monte Carlo techniques and perturbation theory to predict the phase diagram for a model of urate oxidase in solution with PEG. The model used includes an electrostatic interaction, van der Waals attraction, and a polymerinduced depletion interaction. The results agree quantitatively with experiments. Anisotropy plays a role in globular protein interactions, including the formation of hemoglobin fibers in sickle cell disease. Also, the solvent conditions have been shown to play a strong role in the phase behavior of some aqueous protein solutions. Each has previously been treated separately in theoretical studies. Here we propose and analyze a simple, combined model that treats both anisotropy and solvent effects. We find that this model qualitatively explains some phase behavior, including the existence of a lower critical point under certain conditions.

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

Computational Modeling of Allosteric Regulation in the Hsp90 Chaperones: A Statistical Ensemble Analysis of Protein Structure Networks and Allosteric Communications

PubMed Central

Blacklock, Kristin; Verkhivker, Gennady M.

2014-01-01

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks. PMID:24922508

Computational modeling of allosteric regulation in the hsp90 chaperones: a statistical ensemble analysis of protein structure networks and allosteric communications.

PubMed

Blacklock, Kristin; Verkhivker, Gennady M

2014-06-01

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.

Viral Disease Networks?

NASA Astrophysics Data System (ADS)

Gulbahce, Natali; Yan, Han; Vidal, Marc; Barabasi, Albert-Laszlo

2010-03-01

Viral infections induce multiple perturbations that spread along the links of the biological networks of the host cells. Understanding the impact of these cascading perturbations requires an exhaustive knowledge of the cellular machinery as well as a systems biology approach that reveals how individual components of the cellular system function together. Here we describe an integrative method that provides a new approach to studying virus-human interactions and its correlations with diseases. Our method involves the combined utilization of protein - protein interactions, protein -- DNA interactions, metabolomics and gene - disease associations to build a ``viraldiseasome''. By solely using high-throughput data, we map well-known viral associated diseases and predict new candidate viral diseases. We use microarray data of virus-infected tissues and patient medical history data to further test the implications of the viral diseasome. We apply this method to Epstein-Barr virus and Human Papillomavirus and shed light into molecular development of viral diseases and disease pathways.

Towards structural models of molecular recognition in olfactory receptors.

PubMed

Afshar, M; Hubbard, R E; Demaille, J

1998-02-01

The G protein coupled receptors (GPCR) are an important class of proteins that act as signal transducers through the cytoplasmic membrane. Understanding the structure and activation mechanism of these proteins is crucial for understanding many different aspects of cellular signalling. The olfactory receptors correspond to the largest family of GPCRs. Very little is known about how the structures of the receptors govern the specificity of interaction which enables identification of particular odorant molecules. In this paper, we review recent developments in two areas of molecular modelling: methods for modelling the configuration of trans-membrane helices and methods for automatic docking of ligands into receptor structures. We then show how a subset of these methods can be combined to construct a model of a rat odorant receptor interacting with lyral for which experimental data are available. This modelling can help us make progress towards elucidating the specificity of interactions between receptors and odorant molecules.

Exploring the molecular mechanisms of parasite-host interactions with a view towards new therapeutics and vaccines.

PubMed

Cross, Megan; Klepzig, Emma; Dallaston, Madeleine; Young, Neil D; Bailey, Ulla-Maja; Mason, Lyndel; Jones, Malcolm K; Gasser, Robin B; Hofmann, Andreas

Despite the massive disease burden worldwide caused by parasitic nematodes and other infectious pathogens, the molecular basis of many infectious diseases caused by these pathogens has been unduly neglected for a long time. Therefore, accelerated progress towards novel therapeutics, and ultimately control of such infectious diseases, is of crucial importance. Capitalising on the wealth of data becoming available from proteomic and genomic studies, new protein targets at the pathogen-host interface can be identified and subjected to protein-based explorations of the molecular basis of pathogen-host interactions. By combining the use of systems and structural biology methodologies, insights into the structural and molecular mechanisms of these interactions can assist in the development of therapeutics and/or vaccines. This brief review examines two different proteins from the body wall of blood flukes - annexins and the stress-induced phosphoprotein 1 - both of which are presently interesting targets for the development of therapeutics.

Functional diversification of Arabidopsis SEC1-related SM proteins in cytokinetic and secretory membrane fusion.

PubMed

Karnahl, Matthias; Park, Misoon; Krause, Cornelia; Hiller, Ulrike; Mayer, Ulrike; Stierhof, York-Dieter; Jürgens, Gerd

2018-06-12

Sec1/Munc18 (SM) proteins contribute to membrane fusion by interacting with Qa-SNAREs or nascent trans -SNARE complexes. Gymnosperms and the basal angiosperm Amborella have only a single SEC1 gene related to the KEULE gene in Arabidopsis However, the genomes of most angiosperms including Arabidopsis encode three SEC1-related SM proteins of which only KEULE has been functionally characterized as interacting with the cytokinesis-specific Qa-SNARE KNOLLE during cell-plate formation. Here we analyze the closest paralog of KEULE named SEC1B. In contrast to the cytokinesis defects of keule mutants, sec1b mutants are homozygous viable. However, the keule sec1b double mutant was nearly gametophytically lethal, displaying collapsed pollen grains, which suggests substantial overlap between SEC1B and KEULE functions in secretion-dependent growth. SEC1B had a strong preference for interaction with the evolutionarily ancient Qa-SNARE SYP132 involved in secretion and cytokinesis, whereas KEULE interacted with both KNOLLE and SYP132. This differential interaction with Qa-SNAREs is likely conferred by domains 1 and 2a of the two SM proteins. Comparative analysis of all four possible combinations of the relevant SEC1 Qa-SNARE double mutants revealed that in cytokinesis, the interaction of SEC1B with KNOLLE plays no role, whereas the interaction of KEULE with KNOLLE is prevalent and functionally as important as the interactions of both SEC1B and KEU with SYP132 together. Our results suggest that functional diversification of the two SEC1-related SM proteins during angiosperm evolution resulted in enhanced interaction of SEC1B with Qa-SNARE SYP132, and thus a predominant role of SEC1B in secretion.

Detection of membrane protein-protein interaction in planta based on dual-intein-coupled tripartite split-GFP association.

PubMed

Liu, Tzu-Yin; Chou, Wen-Chun; Chen, Wei-Yuan; Chu, Ching-Yi; Dai, Chen-Yi; Wu, Pei-Yu

2018-05-01

Despite the great interest in identifying protein-protein interactions (PPIs) in biological systems, only a few attempts have been made at large-scale PPI screening in planta. Unlike biochemical assays, bimolecular fluorescence complementation allows visualization of transient and weak PPIs in vivo at subcellular resolution. However, when the non-fluorescent fragments are highly expressed, spontaneous and irreversible self-assembly of the split halves can easily generate false positives. The recently developed tripartite split-GFP system was shown to be a reliable PPI reporter in mammalian and yeast cells. In this study, we adapted this methodology, in combination with the β-estradiol-inducible expression cassette, for the detection of membrane PPIs in planta. Using a transient expression assay by agroinfiltration of Nicotiana benthamiana leaves, we demonstrate the utility of the tripartite split-GFP association in plant cells and affirm that the tripartite split-GFP system yields no spurious background signal even with abundant fusion proteins readily accessible to the compartments of interaction. By validating a few of the Arabidopsis PPIs, including the membrane PPIs implicated in phosphate homeostasis, we proved the fidelity of this assay for detection of PPIs in various cellular compartments in planta. Moreover, the technique combining the tripartite split-GFP association and dual-intein-mediated cleavage of polyprotein precursor is feasible in stably transformed Arabidopsis plants. Our results provide a proof-of-concept implementation of the tripartite split-GFP system as a potential tool for membrane PPI screens in planta. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Carbon-Binding Designer Proteins that Discriminate between sp2- and sp3-Hybridized Carbon Surfaces

PubMed Central

Coyle, Brandon L.; Rolandi, Marco; Baneyx, François

2013-01-01

Robust and simple strategies to directly functionalize graphene- and diamond-based nanostructures with proteins are of considerable interest for biologically driven manufacturing, biosensing and bioimaging. Here, we identify a new set of carbon binding peptides that vary in overall hydrophobicity and charge, and engineer two of these sequences (Car9 and Car15) within the framework of E. coli Thioredoxin 1 (TrxA). We develop purification schemes to recover the resulting TrxA derivatives in a soluble form and conduct a detailed analysis of the mechanisms that underpin the interaction of the fusion proteins with carbonaceous surfaces. Although equilibrium quartz crystal microbalance measurements show that TrxA∷Car9 and TrxA∷Car15 have similar affinity for sp2-hybridized graphitic carbon (Kd = 50 and 90 nM, respectively), only the latter protein is capable of dispersing carbon nanotubes. Further investigation by surface plasmon resonance and atomic force microscopy reveals that TrxA∷Car15 interacts with sp2-bonded carbon through a combination of hydrophobic and π-π interactions but that TrxA∷Car9 exhibits a cooperative mode of binding which relies on a combination of electrostatics and weaker π-stacking. Consequently, we find that TrxA∷Car9 binds equally well to sp2- and sp3-bonded (diamond-like) carbon particles, while TrxA∷Car15 is capable of discriminating between the two carbon allotropes. Our results emphasize the importance of understanding both bulk and molecular recognition events when exploiting the adhesive properties of solid-binding peptides and proteins in technological applications. PMID:23510486

How Structure Defines Affinity in Protein-Protein Interactions

PubMed Central

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

2014-01-01

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

Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications.

PubMed

Kobayashi, Hiroki; Harada, Hiroko; Nakamura, Masaomi; Futamura, Yushi; Ito, Akihiro; Yoshida, Minoru; Iemura, Shun-Ichiro; Shin-Ya, Kazuo; Doi, Takayuki; Takahashi, Takashi; Natsume, Tohru; Imoto, Masaya; Sakakibara, Yasubumi

2012-04-05

Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis. We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system.As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins. This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules.

The centrosomin CM2 domain is a multi-functional binding domain with distinct cell cycle roles.

PubMed

Citron, Y Rose; Fagerstrom, Carey J; Keszthelyi, Bettina; Huang, Bo; Rusan, Nasser M; Kelly, Mark J S; Agard, David A

2018-01-01

The centrosome serves as the main microtubule-organizing center in metazoan cells, yet despite its functional importance, little is known mechanistically about the structure and organizational principles that dictate protein organization in the centrosome. In particular, the protein-protein interactions that allow for the massive structural transition between the tightly organized interphase centrosome and the highly expanded matrix-like arrangement of the mitotic centrosome have been largely uncharacterized. Among the proteins that undergo a major transition is the Drosophila melanogaster protein centrosomin that contains a conserved carboxyl terminus motif, CM2. Recent crystal structures have shown this motif to be dimeric and capable of forming an intramolecular interaction with a central region of centrosomin. Here we use a combination of in-cell microscopy and in vitro oligomer assessment to show that dimerization is not necessary for CM2 recruitment to the centrosome and that CM2 alone undergoes significant cell cycle dependent rearrangement. We use NMR binding assays to confirm this intramolecular interaction and show that residues involved in solution are consistent with the published crystal structure and identify L1137 as critical for binding. Additionally, we show for the first time an in vitro interaction of CM2 with the Drosophila pericentrin-like-protein that exploits the same set of residues as the intramolecular interaction. Furthermore, NMR experiments reveal a calcium sensitive interaction between CM2 and calmodulin. Although unexpected because of sequence divergence, this suggests that centrosomin-mediated assemblies, like the mammalian pericentrin, may be calcium regulated. From these results, we suggest an expanded model where during interphase CM2 interacts with pericentrin-like-protein to form a layer of centrosomin around the centriole wall and that at the onset of mitosis this population acts as a nucleation site of intramolecular centrosomin interactions that support the expansion into the metaphase matrix.

A decision tree-based combination of ezrin-interacting proteins to estimate the prognostic risk of patients with esophageal squamous cell carcinoma.

PubMed

He, Jian-Zhong; Wu, Zhi-Yong; Wang, Shao-Hong; Ji, Xia; Yang, Cui-Xia; Xu, Xiu-E; Liao, Lian-Di; Wu, Jian-Yi; Li, En-Min; Zhang, Kai; Xu, Li-Yan

2017-08-01

Our previous studies have highlighted the importance of ezrin in esophageal squamous cell carcinoma (ESCC). Here our objective was to explore the clinical significance of ezrin-interacting proteins, which would provide a theoretical basis for understanding the function of ezrin and potential therapeutic targets for ESCC. We used affinity purification and mass spectrometry to identify PDIA3, CNPY2, and STMN1 as potential ezrin-interacting proteins. Confocal microscopy and coimmunoprecipitation analysis further confirmed the colocalization and interaction of ezrin with PDIA3, CNPY2, and STMN1. Tissue microarray data of ESCC samples (n=263) showed that the 5-year overall survival (OS) and disease-free survival (DFS) were significantly lower for the CNPY2 (OS, P=.003; DFS, P=.011) and STMN1 (OS, P=.010; DFS, P=.002) high-expression groups compared with the low-expression groups. By contrast, overexpression of PDIA3 was significantly correlated with favorable survival (OS, P<.001; DFS, P=.001). Cox regression demonstrated the prognostic value of PDIA3, CNPY2, and STMN1 in ESCC. Furthermore, decision tree analysis revealed that the resulting classifier of both ezrin and its interacting proteins could be used to better predict OS and DFS of patients with ESCC. In conclusion, a signature of ezrin-interacting proteins accurately predicts ESCC patient survival or tumor recurrence. Copyright © 2017 Elsevier Inc. All rights reserved.

The binding domain of the HMGB1 inhibitor carbenoxolone: Theory and experiment

NASA Astrophysics Data System (ADS)

Mollica, Luca; Curioni, Alessandro; Andreoni, Wanda; Bianchi, Marco E.; Musco, Giovanna

2008-05-01

We present a combined computational and experimental study of the interaction of the Box A of the HMGB1 protein and carbenoxolone, an inhibitor of its pro-inflammatory activity. The computational approach consists of classical molecular dynamics (MD) simulations based on the GROMOS force field with quantum-refined (QRFF) atomic charges for the ligand. Experimental data consist of fluorescence intensities, chemical shift displacements, saturation transfer differences and intermolecular Nuclear Overhauser Enhancement signals. Good agreement is found between observations and the conformation of the ligand-protein complex resulting from QRFF-MD. In contrast, simple docking procedures and MD based on the unrefined force field provide models inconsistent with experiment. The ligand-protein binding is dominated by non-directional interactions.

DASS: efficient discovery and p-value calculation of substructures in unordered data.

PubMed

Hollunder, Jens; Friedel, Maik; Beyer, Andreas; Workman, Christopher T; Wilhelm, Thomas

2007-01-01

Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

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

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

Lee, Jae-Hyung

2007-01-01

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

Structural characterizations of human periostin dimerization and cysteinylation.

PubMed

Liu, Jianmei; Zhang, Junying; Xu, Fei; Lin, Zhaohan; Li, Zhiqiang; Liu, Heli

2018-05-12

Human periostin plays a multifaceted role in remodeling the extracellular matrix milieu by interacting with other proteins and itself in both a heterophilic and homophilic manner. However, the structural mechanism for its extensive interactions has remained elusive. Here, we report the crystal structures of human periostin (EMI-Fas1 I- IV ) and its Cys60Ala mutant. In combination with multi-angle light scattering analysis and biochemical assays, the crystal structures reveal that periostin mainly exists as a dimer in solution and its homophilic interaction is mainly mediated by the EMI domain. Furthermore, Cys60 undergoes cysteinylation as confirmed by mass spectroscopy, and this site hardly affects the homophilic interaction. Also, the structures yield insights into how periostin forms heterophilic interactions with other proteins under physiological or pathological conditions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Hydrophilic interaction liquid chromatography-solid phase extraction directly combined with protein precipitation for the determination of triptorelin in plasma.

PubMed

Wang, Jixia; Kong, Song; Yan, Jingyu; Jin, Gaowa; Guo, Zhimou; Shen, Aijin; Xu, Junyan; Zhang, Xiuli; Zou, Lijuan; Liang, Xinmiao

2014-06-01

Peptide drugs play a critical role in therapeutic treatment. However, as the complexity of plasma, determination of peptide drugs using liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a daunting task. To solve this problem, hydrophilic interaction liquid chromatography-solid phase extraction (HILIC-SPE) directly combined with protein precipitation (PPT) was developed for the selective extraction of triptorelin from plasma. The extracts were analyzed by reversed-phase liquid chromatography (RPLC). Proteins, phospholipids and highly polar interferences could be removed from plasma by the efficient combination of PPT, HILIC-SPE and RPLC-MS/MS. This method was evaluated by matrix effect, recovery and process efficiency at different concentration levels (50, 500 and 5,000 ng/mL) of triptorelin. Furthermore, the performance of HILIC-SPE was compared with that of reversed-phase C18 SPE and hydrophilic lipophilic balance (Oasis HLB) SPE. Among them, HILIC-SPE provided the minimum matrix effect (ranging from 96.02% to 103.41%), the maximum recovery (ranging from 80.68% to 90.54%) and the satisfactory process efficiency (ranging from 82.83% to 92.95%). The validated method was successfully applied to determine triptorelin in rat plasma. Copyright © 2014 Elsevier B.V. All rights reserved.

Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition.

PubMed

Huang, Yu-An; You, Zhu-Hong; Chen, Xing; Yan, Gui-Ying

2016-12-23

Protein-protein interactions (PPIs) are essential to most biological processes. Since bioscience has entered into the era of genome and proteome, there is a growing demand for the knowledge about PPI network. High-throughput biological technologies can be used to identify new PPIs, but they are expensive, time-consuming, and tedious. Therefore, computational methods for predicting PPIs have an important role. For the past years, an increasing number of computational methods such as protein structure-based approaches have been proposed for predicting PPIs. The major limitation in principle of these methods lies in the prior information of the protein to infer PPIs. Therefore, it is of much significance to develop computational methods which only use the information of protein amino acids sequence. Here, we report a highly efficient approach for predicting PPIs. The main improvements come from the use of a novel protein sequence representation by combining continuous wavelet descriptor and Chou's pseudo amino acid composition (PseAAC), and from adopting weighted sparse representation based classifier (WSRC). This method, cross-validated on the PPIs datasets of Saccharomyces cerevisiae, Human and H. pylori, achieves an excellent results with accuracies as high as 92.50%, 95.54% and 84.28% respectively, significantly better than previously proposed methods. Extensive experiments are performed to compare the proposed method with state-of-the-art Support Vector Machine (SVM) classifier. The outstanding results yield by our model that the proposed feature extraction method combing two kinds of descriptors have strong expression ability and are expected to provide comprehensive and effective information for machine learning-based classification models. In addition, the prediction performance in the comparison experiments shows the well cooperation between the combined feature and WSRC. Thus, the proposed method is a very efficient method to predict PPIs and may be a useful supplementary tool for future proteomics studies.

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition

PubMed Central

Kulp, John L.; Cloudsdale, Ian S.; Kulp, John L.

2017-01-01

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition. PMID:28837642

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition.

PubMed

Kulp, John L; Cloudsdale, Ian S; Kulp, John L; Guarnieri, Frank

2017-01-01

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.

REEPs Are Membrane Shaping Adapter Proteins That Modulate Specific G Protein-Coupled Receptor Trafficking by Affecting ER Cargo Capacity

PubMed Central

Ho, Vincent K.; Angelotti, Timothy

2013-01-01

Receptor expression enhancing proteins (REEPs) were identified by their ability to enhance cell surface expression of a subset of G protein-coupled receptors (GPCRs), specifically GPCRs that have proven difficult to express in heterologous cell systems. Further analysis revealed that they belong to the Yip (Ypt-interacting protein) family and that some REEP subtypes affect ER structure. Yip family comparisons have established other potential roles for REEPs, including regulation of ER-Golgi transport and processing/neuronal localization of cargo proteins. However, these other potential REEP functions and the mechanism by which they selectively enhance GPCR cell surface expression have not been clarified. By utilizing several REEP family members (REEP1, REEP2, and REEP6) and model GPCRs (α2A and α2C adrenergic receptors), we examined REEP regulation of GPCR plasma membrane expression, intracellular processing, and trafficking. Using a combination of immunolocalization and biochemical methods, we demonstrated that this REEP subset is localized primarily to ER, but not plasma membranes. Single cell analysis demonstrated that these REEPs do not specifically enhance surface expression of all GPCRs, but affect ER cargo capacity of specific GPCRs and thus their surface expression. REEP co-expression with α2 adrenergic receptors (ARs) revealed that this REEP subset interacts with and alter glycosidic processing of α2C, but not α2A ARs, demonstrating selective interaction with cargo proteins. Specifically, these REEPs enhanced expression of and interacted with minimally/non-glycosylated forms of α2C ARs. Most importantly, expression of a mutant REEP1 allele (hereditary spastic paraplegia SPG31) lacking the carboxyl terminus led to loss of this interaction. Thus specific REEP isoforms have additional intracellular functions besides altering ER structure, such as enhancing ER cargo capacity, regulating ER-Golgi processing, and interacting with select cargo proteins. Therefore, some REEPs can be further described as ER membrane shaping adapter proteins. PMID:24098485

Convergent targeting of a common host protein-network by pathogen effectors from three kingdoms of life

PubMed Central

Weßling, Ralf; Epple, Petra; Altmann, Stefan; He, Yijian; Yang, Li; Henz, Stefan R.; McDonald, Nathan; Wiley, Kristin; Bader, Kai Christian; Gläßer, Christine; Mukhtar, M. Shahid; Haigis, Sabine; Ghamsari, Lila; Stephens, Amber E.; Ecker, Joseph R.; Vidal, Marc; Jones, Jonathan D. G.; Mayer, Klaus F. X.; van Themaat, Emiel Ver Loren; Weigel, Detlef; Schulze-Lefert, Paul; Dangl, Jeffery L.; Panstruga, Ralph; Braun, Pascal

2014-01-01

SUMMARY While conceptual principles governing plant immunity are becoming clear, its systems-level organization and the evolutionary dynamic of the host-pathogen interface are still obscure. We generated a systematic protein-protein interaction network of virulence effectors from the ascomycete pathogen Golovinomyces orontii and Arabidopsis thaliana host proteins. We combined this dataset with corresponding data for the eubacterial pathogen Pseudomonas syringae and the oomycete pathogen Hyaloperonospora arabidopsidis. The resulting network identifies host proteins onto which intraspecies and interspecies pathogen effectors converge. Phenotyping of 124 Arabidopsis effector-interactor mutants revealed a correlation between intra- and interspecies convergence and several altered immune response phenotypes. The effectors and most heavily targeted host protein co-localized in sub-nuclear foci. Products of adaptively selected Arabidopsis genes are enriched for interactions with effector targets. Our data suggest the existence of a molecular host-pathogen interface that is conserved across Arabidopsis accessions, while evolutionary adaptation occurs in the immediate network neighborhood of effector targets. PMID:25211078

Global analysis of host-pathogen interactions that regulate early stage HIV-1 replication

PubMed Central

König, Renate; Zhou, Yingyao; Elleder, Daniel; Diamond, Tracy L.; Bonamy, Ghislain M.C.; Irelan, Jeffrey T.; Chiang, Chih-yuan; Tu, Buu P.; De Jesus, Paul D.; Lilley, Caroline E.; Seidel, Shannon; Opaluch, Amanda M.; Caldwell, Jeremy S.; Weitzman, Matthew D.; Kuhen, Kelli L.; Bandyopadhyay, Sourav; Ideker, Trey; Orth, Anthony P.; Miraglia, Loren J.; Bushman, Frederic D.; Young, John A.; Chanda, Sumit K.

2008-01-01

Human Immunodeficiency Viruses (HIV-1 and HIV-2) rely upon host-encoded proteins to facilitate their replication. Here we combined genome-wide siRNA analyses with interrogation of human interactome databases to assemble a host-pathogen biochemical network containing 213 confirmed host cellular factors and 11 HIV-1-encoded proteins. Protein complexes that regulate ubiquitin conjugation, proteolysis, DNA damage response and RNA splicing were identified as important modulators of early stage HIV-1 infection. Additionally, over 40 new factors were shown to specifically influence initiation and/or kinetics of HIV-1 DNA synthesis, including cytoskeletal regulatory proteins, modulators of post-translational modification, and nucleic acid binding proteins. Finally, fifteen proteins with diverse functional roles, including nuclear transport, prostaglandin synthesis, ubiquitination, and transcription, were found to influence nuclear import or viral DNA integration. Taken together, the multi-scale approach described here has uncovered multiprotein virus-host interactions that likely act in concert to facilitate early steps of HIV-1 infection. PMID:18854154

Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

PubMed

Li, Lishuang; Zhang, Panpan; Zheng, Tianfu; Zhang, Hongying; Jiang, Zhenchao; Huang, Degen

2014-01-01

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT) by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH). We evaluate our method with Support Vector Machine (SVM) and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing.

PubMed

Jankowsky, Eckhard; Harris, Michael E

2017-04-15

To function in a biological setting, RNA binding proteins (RBPs) have to discriminate between alternative binding sites in RNAs. This discrimination can occur in the ground state of an RNA-protein binding reaction, in its transition state, or in both. The extent by which RBPs discriminate at these reaction states defines RBP specificity landscapes. Here, we describe the HiTS-Kin and HiTS-EQ techniques, which combine kinetic and equilibrium binding experiments with high throughput sequencing to quantitatively assess substrate discrimination for large numbers of substrate variants at ground and transition states of RNA-protein binding reactions. We discuss experimental design, practical considerations and data analysis and outline how a combination of HiTS-Kin and HiTS-EQ allows the mapping of RBP specificity landscapes. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

PubMed

Smith, Colin A; Kortemme, Tanja

2011-01-01

Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

Protein social behavior makes a stronger signal for partner identification than surface geometry.

PubMed

Laine, Elodie; Carbone, Alessandra

2017-01-01

Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico-chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross-docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S-index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface-based (ranking) score to discriminate partners from non-interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137-154. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

PubMed

Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A

2017-04-24

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

The DUF1669 domain of FAM83 family proteins anchor casein kinase 1 isoforms.

PubMed

Fulcher, Luke J; Bozatzi, Polyxeni; Tachie-Menson, Theresa; Wu, Kevin Z L; Cummins, Timothy D; Bufton, Joshua C; Pinkas, Daniel M; Dunbar, Karen; Shrestha, Sabin; Wood, Nicola T; Weidlich, Simone; Macartney, Thomas J; Varghese, Joby; Gourlay, Robert; Campbell, David G; Dingwell, Kevin S; Smith, James C; Bullock, Alex N; Sapkota, Gopal P

2018-05-22

Members of the casein kinase 1 (CK1) family of serine-threonine protein kinases are implicated in the regulation of many cellular processes, including the cell cycle, circadian rhythms, and Wnt and Hedgehog signaling. Because these kinases exhibit constitutive activity in biochemical assays, it is likely that their activity in cells is controlled by subcellular localization, interactions with inhibitory proteins, targeted degradation, or combinations of these mechanisms. We identified members of the FAM83 family of proteins as partners of CK1 in cells. All eight members of the FAM83 family (FAM83A to FAM83H) interacted with the α and α-like isoforms of CK1; FAM83A, FAM83B, FAM83E, and FAM83H also interacted with the δ and ε isoforms of CK1. We detected no interaction between any FAM83 member and the related CK1γ1, CK1γ2, and CK1γ3 isoforms. Each FAM83 protein exhibited a distinct pattern of subcellular distribution and colocalized with the CK1 isoform(s) to which it bound. The interaction of FAM83 proteins with CK1 isoforms was mediated by the conserved domain of unknown function 1669 (DUF1669) that characterizes the FAM83 family. Mutations in FAM83 proteins that prevented them from binding to CK1 interfered with the proper subcellular localization and cellular functions of both the FAM83 proteins and their CK1 binding partners. On the basis of its function, we propose that DUF1669 be renamed the polypeptide anchor of CK1 domain. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Supramolecular structure of the casein micelle.

PubMed

McMahon, D J; Oommen, B S

2008-05-01

The supramolecular structure of colloidal casein micelles in milk was investigated by using a sample preparation protocol based on adsorption of proteins onto a poly-l-lysine and parlodion-coated copper grid, staining of proteins and calcium phosphate by uranyl oxalate, instantaneous freezing, and drying under a high vacuum. High-resolution transmission electron microscopy stereo-images were obtained showing the interior structure of casein micelles. On the basis of our interpretation of these images, an interlocked lattice model was developed in which both casein-calcium phosphate aggregates and casein polymer chains act together to maintain casein micelle integrity. The caseins form linear and branched chains (2 to 5 proteins long) interlocked by the casein-stabilized calcium phosphate nanoclusters. This model suggests that stabilization of calcium phosphate nanoclusters by phosphoserine domains of alpha(s1)-, alpha(s2)-, or beta-casein, or their combination, would orient their hydrophobic domains outward, allowing interaction and binding to other casein molecules. Other interactions between the caseins, such as calcium bridging, could also occur and further stabilize the supramolecule. The combination of having an interlocked lattice structure and multiple interactions results in an open, sponge-like colloidal supramolecule that is resistant to spatial changes and disintegration. Hydrophobic interactions between caseins surrounding a calcium phosphate nanocluster would prevent complete dissociation of casein micelles when the calcium phosphate nanoclusters are solubilized. Likewise, calcium bridging and other electrostatic interactions between caseins would prevent dissociation of the casein micelles into casein-calcium phosphate nanocluster aggregates when milk is cooled or urea is added to milk, and hydrophobic interactions are reduced. The appearance of both polymer chains and small aggregate particles during milk synthesis would also be expected based on this interlocked lattice model of casein micelles, and its supramolecule structure thus exhibits the principles of self-aggregation, interdependence, and diversity observed in nature.

RNA Whole-Mount In situ Hybridisation Proximity Ligation Assay (rISH-PLA), an Assay for Detecting RNA-Protein Complexes in Intact Cells.

PubMed

Roussis, Ioannis M; Guille, Matthew; Myers, Fiona A; Scarlett, Garry P

2016-01-01

Techniques for studying RNA-protein interactions have lagged behind those for DNA-protein complexes as a consequence of the complexities associated with working with RNA. Here we present a method for the modification of the existing In Situ Hybridisation-Proximity Ligation Assay (ISH-PLA) protocol to adapt it to the study of RNA regulation (rISH-PLA). As proof of principle we used the well-characterised interaction of the Xenopus laevis Staufen RNA binding protein with Vg1 mRNA, the complex of which co-localises to the vegetal pole of Xenopus oocytes. The applicability of both the Stau1 antibody and the Locked Nucleic Acid probe (LNA) recognising Vg1 mRNA were independently validated by whole-mount Immunohistochemistry and whole-mount in situ hybridisation assays respectively prior to combining them in the rISH-PLA assay. The rISH-PLA assay allows the identification of a given RNA-protein complex at subcellular and single cell resolution, thus avoiding the lack of spatial resolution and sensitivity associated with assaying heterogenous cell populations from which conventional RNA-protein interaction detection techniques suffer. This technique will be particularly usefully for studying the activity of RNA binding proteins (RBPs) in complex mixtures of cells, for example tissue sections or whole embryos.

Chromophore maturation and fluorescence fluctuation spectroscopy of fluorescent proteins in a cell-free expression system

PubMed Central

Macdonald, Patrick J.; Chen, Yan; Mueller, Joachim D.

2012-01-01

Cell-free synthesis, a method for the rapid expression of proteins, is increasingly used to study interactions of complex biological systems. GFP and its variants have become indispensable for fluorescence studies in live cells and are equally attractive as reporters for cell-free systems. This work investigates the use of fluorescence fluctuation spectroscopy (FFS) as a tool for quantitative analysis of protein interactions in cell-free expression systems. We also explore chromophore maturation of fluorescent proteins, which is of crucial importance for fluorescence studies. A droplet sample protocol was developed that ensured sufficient oxygenation for chromophore maturation and ease of manipulation for titration studies. The kinetics of chromophore maturation of EGFP, EYFP, and mCherry were analyzed as a function of temperature. A strong increase in the rate from room temperature to 37 °C was observed. We further demonstrate that all EGFP proteins fully mature in the cell-free solution and that brightness is a robust parameter specifying stoichiometry. Finally, FFS is applied to study the stoichiometry of the nuclear transport factor 2 in a cell-free system over a broad concentration range. We conclude that combining cell-free expression and FFS provides a powerful technique for quick, quantitative study of chromophore maturation and protein-protein interaction. PMID:22093611

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.

Fundamentals of nanoscale polymer-protein interactions and potential contributions to solid-state nanobioarrays.

PubMed

Hahm, Jong-in

2014-08-26

Protein adsorption onto polymer surfaces is a very complex, ubiquitous, and integrated process, impacting essential areas of food processing and packaging, health devices, diagnostic tools, and medical products. The nature of protein-surface interactions is becoming much more complicated with continuous efforts toward miniaturization, especially for the development of highly compact protein detection and diagnostic devices. A large body of literature reports on protein adsorption from the perspective of ensemble-averaged behavior on macroscopic, chemically homogeneous, polymeric surfaces. However, protein-surface interactions governing the nanoscale size regime may not be effectively inferred from their macroscopic and microscopic characteristics. Recently, research efforts have been made to produce periodically arranged, nanoscopic protein patterns on diblock copolymer surfaces solely through self-assembly. Intriguing protein adsorption phenomena are directly probed on the individual biomolecule level for a fundamental understanding of protein adsorption on nanoscale surfaces exhibiting varying degrees of chemical heterogeneity. Insight gained from protein assembly on diblock copolymers can be effectively used to control the surface density, conformation, orientation, and biofunctionality of prebound proteins in highly miniaturized applications, now approaching the nanoscale. This feature article will highlight recent experimental and theoretical advances made on these fronts while focusing on single-biomolecule-level investigations of protein adsorption behavior combined with surface chemical heterogeneity on the length scale commensurate with a single protein. This article will also address advantages and challenges of the self-assembly-driven patterning technology used to produce protein nanoarrays and its implications for ultrahigh density, functional, and quantifiable protein detection in a highly miniaturized format.

FTIR studies of the redox partner interaction in cytochrome P450: the Pdx-P450cam couple.

PubMed

Karyakin, Andrey; Motiejunas, Domantas; Wade, Rebecca C; Jung, Christiane

2007-03-01

Recently we have developed a new approach to study protein-protein interactions using Fourier transform infrared spectroscopy in combination with titration experiments and principal component analysis (FTIR-TPCA). In the present paper we review the FTIR-TPCA results obtained for the interaction between cytochrome P450 and the redox partner protein in two P450 systems, the Pseudomonas putida P450cam (CYP101) with putidaredoxin (P450cam-Pdx), and the Bacillus megaterium P450BM-3 (CYP102) heme domain with the FMN domain (P450BMP-FMND). Both P450 systems reveal similarities in the structural changes that occur upon redox partner complex formation. These involve an increase in beta-sheets and alpha-helix content, a decrease in the population of random coil/3(10)-helix structure, a redistribution of turn structures within the interacting proteins and changes in the protonation states or hydrogen-bonding of amino acid carboxylic side chains. We discuss in detail the P450cam-Pdx interaction in comparison with literature data and conclusions drawn from experiments obtained by other spectroscopic techniques. The results are also interpreted in the context of a 3D structural model of the Pdx-P450cam complex.

Tyrosine dephosphorylation enhances the therapeutic target activity of epidermal growth factor receptor (EGFR) by disrupting its interaction with estrogen receptor (ER).

PubMed

Ma, Shao; Yin, Ning; Qi, Xiaomei; Pfister, Sandra L; Zhang, Mei-Jie; Ma, Rong; Chen, Guan

2015-05-30

Protein-protein interactions can increase or decrease its therapeutic target activity and the determining factors involved, however, are largely unknown. Here, we report that tyrosine-dephosphorylation of epidermal growth factor receptor (EGFR) increases its therapeutic target activity by disrupting its interaction with estrogen receptor (ER). Protein tyrosine phosphatase H1 (PTPH1) dephosphorylates the tyrosine kinase EGFR, disrupts its interaction with the nuclear receptor ER, and increases breast cancer sensitivity to small molecule tyrosine kinase inhibitors (TKIs). These effects require PTPH1 catalytic activity and its interaction with EGFR, suggesting that the phosphatase may increase the sensitivity by dephosphorylating EGFR leading to its dissociation with ER. Consistent with this notion, a nuclear-localization defective ER has a higher EGFR-binding activity and confers the resistance to TKI-induced growth inhibition. Additional analysis show that PTPH1 stabilizes EGFR, stimulates the membranous EGFR accumulation, and enhances the growth-inhibitory activity of a combination therapy of TKIs with an anti-estrogen. Since EGFR and ER both are substrates for PTPH1 in vitro and in intact cells, these results indicate that an inhibitory EGFR-ER protein complex can be switched off through a competitive enzyme-substrate binding. Our results would have important implications for the treatment of breast cancer with targeted therapeutics.

Mediator binds to boundaries of chromosomal interaction domains and to proteins involved in DNA looping, RNA metabolism, chromatin remodeling, and actin assembly.

PubMed

Chereji, Razvan V; Bharatula, Vasudha; Elfving, Nils; Blomberg, Jeanette; Larsson, Miriam; Morozov, Alexandre V; Broach, James R; Björklund, Stefan

2017-09-06

Mediator is a multi-unit molecular complex that plays a key role in transferring signals from transcriptional regulators to RNA polymerase II in eukaryotes. We have combined biochemical purification of the Saccharomyces cerevisiae Mediator from chromatin with chromatin immunoprecipitation in order to reveal Mediator occupancy on DNA genome-wide, and to identify proteins interacting specifically with Mediator on the chromatin template. Tandem mass spectrometry of proteins in immunoprecipitates of mediator complexes revealed specific interactions between Mediator and the RSC, Arp2/Arp3, CPF, CF 1A and Lsm complexes in chromatin. These factors are primarily involved in chromatin remodeling, actin assembly, mRNA 3'-end processing, gene looping and mRNA decay, but they have also been shown to enter the nucleus and participate in Pol II transcription. Moreover, we have found that Mediator, in addition to binding Pol II promoters, occupies chromosomal interacting domain (CID) boundaries and that Mediator in chromatin associates with proteins that have been shown to interact with CID boundaries, such as Sth1, Ssu72 and histone H4. This suggests that Mediator plays a significant role in higher-order genome organization. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Direct protein photoinduced conformational changes using porphyrins.

NASA Astrophysics Data System (ADS)

Brancaleon, Lorenzo; Silva, Ivan; Fernandez, Nicholas; Johnson, Eric; Sansone, Samuel

2008-03-01

Most proteins functions depend on the interaction with other ligands. These interactions depend on uniquely structured binding sites formed by the folding of the proteins. Ligands can often prompt intended as well as ``accidental'' protein structural changes. One can foresee that the ability to prompt and control post-translational protein folding could be a powerful tool to investigate protein folding mechanisms but also to inhibit certain proteins or induce new properties to proteins. One possible way to produce such structural disruption is the combination of light and photoactive ligands. This option has been investigated in recent years by exploiting photoisomerization and other properties of non-physiological dyes. We used an alternative approach which uses porphyrins as the ``triggers'' of structural changes. The advantage of porphyrins is that they can be found naturally in living cells. The photophysical properties of porphyrins can induce local as well as long range effects on the structure of the bound protein. Porphyrins are known to produce structural changes in porphyrin-specific proteins, however the novelty of our results is that we demonstrated that these dyes can also produce structural changes in non-porphyrin-specific globular proteins. We will present an overview of our research to-date in this field and its potential applications.

Joint Toxicity of Arsenic, Copper and Glyphosate on Behavior, Reproduction and Heat Shock Protein Response in Caenorhabditis elegans.

PubMed

Wang, Yunbiao; Ezemaduka, Anastasia N; Li, Zhuheng; Chen, Zhanyan; Song, Chuantao

2017-04-01

The soil nematode Caenorhabditis elegans was used in 24-h acute exposures to arsenic (As), copper (Cu) and glyphosate (GPS) and to mixtures of As/Cu and As/GPS to investigate the effects of mixture exposures in the worms. A synergistic type of interaction was observed for acute toxicity with the As/Cu and As/GPS mixtures. Sublethal 24-h exposures of 1/1000, 1/100 and 1/10 of the LC50 concentrations for As, Cu and GPS individually and for As/Cu and As/GPS mixtures were conducted to observe responses in locomotory behavior (head thrashing), reproduction, and heat shock protein expression. Head thrash frequency and reproduction exhibited concentration dependent decreases in both individual and combined exposures to the tested chemical stressors, and showed synergistic interactions even at micromolar concentrations. Furthermore, the HSP70 protein level was significantly increased following exposure to individual and combined chemical stressors in wild-type C. elegans. Our findings establish for the first time the effects of exposure to As/GPS and As/Cu mixtures in C. elegans.

Identifying cooperative transcriptional regulations using protein–protein interactions

PubMed Central

Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

2005-01-01

Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

Molecular dynamics simulations and structure-based network analysis reveal structural and functional aspects of G-protein coupled receptor dimer interactions.

PubMed

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

2016-06-01

A significant amount of experimental evidence suggests that G-protein coupled receptors (GPCRs) do not act exclusively as monomers but also form biologically relevant dimers and oligomers. However, the structural determinants, stoichiometry and functional importance of GPCR oligomerization remain topics of intense speculation. In this study we attempted to evaluate the nature and dynamics of GPCR oligomeric interactions. A representative set of GPCR homodimers were studied through Coarse-Grained Molecular Dynamics simulations, combined with interface analysis and concepts from network theory for the construction and analysis of dynamic structural networks. Our results highlight important structural determinants that seem to govern receptor dimer interactions. A conserved dynamic behavior was observed among different GPCRs, including receptors belonging in different GPCR classes. Specific GPCR regions were highlighted as the core of the interfaces. Finally, correlations of motion were observed between parts of the dimer interface and GPCR segments participating in ligand binding and receptor activation, suggesting the existence of mechanisms through which dimer formation may affect GPCR function. The results of this study can be used to drive experiments aimed at exploring GPCR oligomerization, as well as in the study of transmembrane protein-protein interactions in general.

Molecular dynamics simulations and structure-based network analysis reveal structural and functional aspects of G-protein coupled receptor dimer interactions

NASA Astrophysics Data System (ADS)

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

2016-06-01

A significant amount of experimental evidence suggests that G-protein coupled receptors (GPCRs) do not act exclusively as monomers but also form biologically relevant dimers and oligomers. However, the structural determinants, stoichiometry and functional importance of GPCR oligomerization remain topics of intense speculation. In this study we attempted to evaluate the nature and dynamics of GPCR oligomeric interactions. A representative set of GPCR homodimers were studied through Coarse-Grained Molecular Dynamics simulations, combined with interface analysis and concepts from network theory for the construction and analysis of dynamic structural networks. Our results highlight important structural determinants that seem to govern receptor dimer interactions. A conserved dynamic behavior was observed among different GPCRs, including receptors belonging in different GPCR classes. Specific GPCR regions were highlighted as the core of the interfaces. Finally, correlations of motion were observed between parts of the dimer interface and GPCR segments participating in ligand binding and receptor activation, suggesting the existence of mechanisms through which dimer formation may affect GPCR function. The results of this study can be used to drive experiments aimed at exploring GPCR oligomerization, as well as in the study of transmembrane protein-protein interactions in general.

Deconstructing thermodynamic parameters of a coupled system from site-specific observables.

PubMed

Chowdhury, Sandipan; Chanda, Baron

2010-11-02

Cooperative interactions mediate information transfer between structural domains of a protein molecule and are major determinants of protein function and modulation. The prevalent theories to understand the thermodynamic origins of cooperativity have been developed to reproduce the complex behavior of a global thermodynamic observable such as ligand binding or enzyme activity. However, in most cases the measurement of a single global observable cannot uniquely define all the terms that fully describe the energetics of the system. Here we establish a theoretical groundwork for analyzing protein thermodynamics using site-specific information. Our treatment involves extracting a site-specific parameter (defined as χ value) associated with a structural unit. We demonstrate that, under limiting conditions, the χ value is related to the direct interaction terms associated with the structural unit under observation and its intrinsic activation energy. We also introduce a site-specific interaction energy term (χ(diff)) that is a function of the direct interaction energy of that site with every other site in the system. When combined with site-directed mutagenesis and other molecular level perturbations, analyses of χ values of site-specific observables may provide valuable insights into protein thermodynamics and structure.

Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

PubMed

Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

2015-03-01

Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new potentially true human protein complexes were suggested as candidates for further validation using experimental techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Influence of lysozyme on the precipitation of calcium carbonate: a kinetic and morphologic study

NASA Astrophysics Data System (ADS)

Jimenez-Lopez, Concepcion; Rodriguez-Navarro, Alejandro; Dominguez-Vera, Jose M.; Garcia-Ruiz, Juan M.

2003-05-01

Several mechanisms have been proposed to explain the interactions between proteins and mineral surfaces, among them a combination of electrostatic, stereochemical interactions and molecular recognition between the protein and the crystal surface. To identify the mechanisms of interaction in the lysozyme-calcium carbonate model system, the effect of this protein on the precipitation kinetics and morphology of calcite crystals was examined. The solution chemistry and morphology of the solid were monitored over time in a set of time-series free-drift experiments in which CaCO 3 was precipitated from solution in a closed system at 25°C and 1 atm total pressure, in the presence and absence of lysozyme. The precipitation of calcite was preceded by the precipitation of a metastable phase that later dissolved and gave rise to calcite as the sole phase. With increasing lysozyme concentration, the nucleation of both the metastable phase and calcite occurred at lower Ω calcite, indicating that lysozyme favored the nucleation of both phases. Calcite growth rate was not affected by the presence of lysozyme, at least at protein concentrations ranging from 0 mg/mL to 10 mg/mL. Lysozyme modified the habit of calcite crystals. The degree of habit modification changed with protein concentration. At lower concentrations of lysozyme, the typical rhombohedral habit of calcite crystals was modified by the expression of {110} faces, which resulted from the preferential adsorption of protein on these faces. With increasing lysozyme concentration, the growth of {110}, {100}, and finally {001} faces was sequentially inhibited. This adsorption sequence may be explained by an electrostatic interaction between lysozyme and calcite, in which the inhibition of the growth of {110}, {100}, and {001} faces could be explained by a combined effect of the density of carbonate groups in the calcite face and the specific orientation (perpendicular) of these carbonate groups with respect to the calcite surface. Overgrowth of calcite in the presence of lysozyme demonstrated that the protein favored and controlled the nucleation on the calcite substrate. Overgrowth crystals nucleated epitaxially in lines which run diagonal to rhombohedral {104} faces.

Synergistic effects in the antiviral activity of the three Mx proteins from gilthead seabream (Sparus aurata).

PubMed

Fernández-Trujillo, M A; García-Rosado, E; Alonso, M C; Álvarez, M C; Béjar, J

2015-11-15

Due to their direct antiviral activity, Mx proteins play a main role in the response mediated by type I interferon against viral infections. The study on gilthead seabream Mx proteins is especially interesting, since this species is unusually resistant to viral diseases, being asymptomatic carrier of several viruses pathogenic to other fish species. Gilthead seabream has three Mx proteins (Mx1, Mx2 and Mx3) that, separately, display antiviral activity against a wide range of viruses, showing interesting differences in their antiviral specificities. In this work, the possible synergy between the three Mx isoforms has been studied using in vitro systems consisting of CHSE-214 cells stably expressing two or the three gilthead seabream Mx proteins. The antiviral activity of these Mx combinations has been tested against the Infectious Pancreatic Necrosis Virus (IPNV), the Viral Haemorrhagic Septicaemia Virus (VHSV), the European Sheatfish Virus (ESV) and the Lymphocystis Disease Virus (LCDV). A synergistic effect of the Mx proteins was only detected against ESV, no synergy was observed against LCDV, and a negative interference was detected against the two RNA viruses tested, IPNV and VHSV, as viral replication was higher in cells expressing certain Mx combinations than in cells expressing these proteins separately. These results suggest a functional interaction between gilthead seabream Mx isoforms, which results in a higher or lower antiviral activity depending on the virus tested, thus supporting the idea of complex virus-host interactions and finely tuned mechanisms controlling the antiviral activity of Mx proteins. Copyright © 2015 Elsevier B.V. All rights reserved.

Monitoring the Assembly of a Secreted Bacterial Virulence Factor Using Site-specific Crosslinking

PubMed Central

Pavlova, Olga; Ieva, Raffaele; Bernstein, Harris D

2013-01-01

This article describes a method to detect and analyze dynamic interactions between a protein of interest and other factors in vivo. Our method is based on the amber suppression technology that was originally developed by Peter Schultz and colleagues1. An amber mutation is first introduced at a specific codon of the gene encoding the protein of interest. The amber mutant is then expressed in E. coli together with genes encoding an amber suppressor tRNA and an amino acyl-tRNA synthetase derived from Methanococcus jannaschii. Using this system, the photo activatable amino acid analog p-benzoylphenylalanine (Bpa) is incorporated at the amber codon. Cells are then irradiated with ultraviolet light to covalently link the Bpa residue to proteins that are located within 3-8 Å. Photocrosslinking is performed in combination with pulse-chase labeling and immunoprecipitation of the protein of interest in order to monitor changes in protein-protein interactions that occur over a time scale of seconds to minutes. We optimized the procedure to study the assembly of a bacterial virulence factor that consists of two independent domains, a domain that is integrated into the outer membrane and a domain that is translocated into the extracellular space, but the method can be used to study many different assembly processes and biological pathways in both prokaryotic and eukaryotic cells. In principle interacting factors and even specific residues of interacting factors that bind to a protein of interest can be identified by mass spectrometry. PMID:24378574

Nuclear γ-tubulin associates with nucleoli and interacts with tumor suppressor protein C53.

PubMed

Hořejší, Barbora; Vinopal, Stanislav; Sládková, Vladimíra; Dráberová, Eduarda; Sulimenko, Vadym; Sulimenko, Tetyana; Vosecká, Věra; Philimonenko, Anatoly; Hozák, Pavel; Katsetos, Christos D; Dráber, Pavel

2012-01-01

γ-Tubulin is assumed to be a typical cytosolic protein necessary for nucleation of microtubules from microtubule organizing centers. Using immunolocalization and cell fractionation techniques in combination with siRNAi and expression of FLAG-tagged constructs, we have obtained evidence that γ-tubulin is also present in nucleoli of mammalian interphase cells of diverse cellular origins. Immunoelectron microscopy has revealed γ-tubulin localization outside fibrillar centers where transcription of ribosomal DNA takes place. γ-Tubulin was associated with nucleolar remnants after nuclear envelope breakdown and could be translocated to nucleoli during mitosis. Pretreatment of cells with leptomycin B did not affect the distribution of nuclear γ-tubulin, making it unlikely that rapid active transport via nuclear pores participates in the transport of γ-tubulin into the nucleus. This finding was confirmed by heterokaryon assay and time-lapse imaging of photoconvertible protein Dendra2 tagged to γ-tubulin. Immunoprecipitation from nuclear extracts combined with mass spectrometry revealed an association of γ-tubulin with tumor suppressor protein C53 located at multiple subcellular compartments including nucleoli. The notion of an interaction between γ-tubulin and C53 was corroborated by pull-down and co-immunoprecipitation experiments. Overexpression of γ-tubulin antagonized the inhibitory effect of C53 on DNA damage G(2) /M checkpoint activation. The combined results indicate that aside from its known role in microtubule nucleation, γ-tubulin may also have nuclear-specific function(s). Copyright © 2011 Wiley Periodicals, Inc.

My 65 years in protein chemistry.

PubMed

Scheraga, Harold A

2015-05-01

This is a tour of a physical chemist through 65 years of protein chemistry from the time when emphasis was placed on the determination of the size and shape of the protein molecule as a colloidal particle, with an early breakthrough by James Sumner, followed by Linus Pauling and Fred Sanger, that a protein was a real molecule, albeit a macromolecule. It deals with the recognition of the nature and importance of hydrogen bonds and hydrophobic interactions in determining the structure, properties, and biological function of proteins until the present acquisition of an understanding of the structure, thermodynamics, and folding pathways from a linear array of amino acids to a biological entity. Along the way, with a combination of experiment and theoretical interpretation, a mechanism was elucidated for the thrombin-induced conversion of fibrinogen to a fibrin blood clot and for the oxidative-folding pathways of ribonuclease A. Before the atomic structure of a protein molecule was determined by x-ray diffraction or nuclear magnetic resonance spectroscopy, experimental studies of the fundamental interactions underlying protein structure led to several distance constraints which motivated the theoretical approach to determine protein structure, and culminated in the Empirical Conformational Energy Program for Peptides (ECEPP), an all-atom force field, with which the structures of fibrous collagen-like proteins and the 46-residue globular staphylococcal protein A were determined. To undertake the study of larger globular proteins, a physics-based coarse-grained UNited-RESidue (UNRES) force field was developed, and applied to the protein-folding problem in terms of structure, thermodynamics, dynamics, and folding pathways. Initially, single-chain and, ultimately, multiple-chain proteins were examined, and the methodology was extended to protein-protein interactions and to nucleic acids and to protein-nucleic acid interactions. The ultimate results led to an understanding of a variety of biological processes underlying natural and disease phenomena.

Characterization of the interaction of interleukin-8 with hyaluronan, chondroitin sulfate, dermatan sulfate and their sulfated derivatives by spectroscopy and molecular modeling.

PubMed

Pichert, Annelie; Samsonov, Sergey A; Theisgen, Stephan; Thomas, Lars; Baumann, Lars; Schiller, Jürgen; Beck-Sickinger, Annette G; Huster, Daniel; Pisabarro, M Teresa

2012-01-01

The interactions between glycosaminoglycans (GAGs), important components of the extracellular matrix, and proteins such as growth factors and chemokines play critical roles in cellular regulation processes. Therefore, the design of GAG derivatives for the development of innovative materials with bio-like properties in terms of their interaction with regulatory proteins is of great interest for tissue engineering and regenerative medicine. Previous work on the chemokine interleukin-8 (IL-8) has focused on its interaction with heparin and heparan sulfate, which regulate chemokine function. However, the extracellular matrix contains other GAGs, such as hyaluronic acid (HA), dermatan sulfate (DS) and chondroitin sulfate (CS), which have so far not been characterized in terms of their distinct molecular recognition properties towards IL-8 in relation to their length and sulfation patterns. NMR and molecular modeling have been in great part the methods of choice to study the structural and recognition properties of GAGs and their protein complexes. However, separately these methods have challenges to cope with the high degree of similarity and flexibility that GAGs exhibit. In this work, we combine fluorescence spectroscopy, NMR experiments, docking and molecular dynamics simulations to study the configurational and recognition properties of IL-8 towards a series of HA and CS derivatives and DS. We analyze the effects of GAG length and sulfation patterns in binding strength and specificity, and the influence of GAG binding on IL-8 dimer formation. Our results highlight the importance of combining experimental and theoretical approaches to obtain a better understanding of the molecular recognition properties of GAG-protein systems.

Allele-specific Characterization of Alanine: Glyoxylate Aminotransferase Variants Associated with Primary Hyperoxaluria

PubMed Central

Lage, Melissa D.; Pittman, Adrianne M. C.; Roncador, Alessandro; Cellini, Barbara; Tucker, Chandra L.

2014-01-01

Primary Hyperoxaluria Type 1 (PH1) is a rare autosomal recessive kidney stone disease caused by deficiency of the peroxisomal enzyme alanine: glyoxylate aminotransferase (AGT), which is involved in glyoxylate detoxification. Over 75 different missense mutations in AGT have been found associated with PH1. While some of the mutations have been found to affect enzyme activity, stability, and/or localization, approximately half of these mutations are completely uncharacterized. In this study, we sought to systematically characterize AGT missense mutations associated with PH1. To facilitate analysis, we used two high-throughput yeast-based assays: one that assesses AGT specific activity, and one that assesses protein stability. Approximately 30% of PH1-associated missense mutations are found in conjunction with a minor allele polymorphic variant, which can interact to elicit complex effects on protein stability and trafficking. To better understand this allele interaction, we functionally characterized each of 34 mutants on both the major (wild-type) and minor allele backgrounds, identifying mutations that synergize with the minor allele. We classify these mutants into four distinct categories depending on activity/stability results in the different alleles. Twelve mutants were found to display reduced activity in combination with the minor allele, compared with the major allele background. When mapped on the AGT dimer structure, these mutants reveal localized regions of the protein that appear particularly sensitive to interactions with the minor allele variant. While the majority of the deleterious effects on activity in the minor allele can be attributed to synergistic interaction affecting protein stability, we identify one mutation, E274D, that appears to specifically affect activity when in combination with the minor allele. PMID:24718375

The protein interactome of collapsin response mediator protein-2 (CRMP2/DPYSL2) reveals novel partner proteins in brain tissue.

PubMed

Martins-de-Souza, Daniel; Cassoli, Juliana S; Nascimento, Juliana M; Hensley, Kenneth; Guest, Paul C; Pinzon-Velasco, Andres M; Turck, Christoph W

2015-10-01

Collapsin response mediator protein-2 (CRMP2) is a CNS protein involved in neuronal development, axonal and neuronal growth, cell migration, and protein trafficking. Recent studies have linked perturbations in CRMP2 function to neurodegenerative disorders such as Alzheimer's disease, neuropathic pain, and Batten disease, and to psychiatric disorders such as schizophrenia. Like most proteins, CRMP2 functions though interactions with a molecular network of proteins and other molecules. Here, we have attempted to identify additional proteins of the CRMP2 interactome to provide further leads about its roles in neurological functions. We used a combined co-immunoprecipitation and shotgun proteomic approach in order to identify CRMP2 protein partners. We identified 78 CRMP2 protein partners not previously reported in public protein interaction databases. These were involved in seven biological processes, which included cell signaling, growth, metabolism, trafficking, and immune function, according to Gene Ontology classifications. Furthermore, 32 different molecular functions were found to be associated with these proteins, such as RNA binding, ribosomal functions, transporter activity, receptor activity, serine/threonine phosphatase activity, cell adhesion, cytoskeletal protein binding and catalytic activity. In silico pathway interactome construction revealed a highly connected network with the most overrepresented functions corresponding to semaphorin interactions, along with axon guidance and WNT5A signaling. Taken together, these findings suggest that the CRMP2 pathway is critical for regulating neuronal and synaptic architecture. Further studies along these lines might uncover novel biomarkers and drug targets for use in drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Examining Gene-Environment Interactions in Comorbid Depressive and Disruptive Behavior Disorders using a Bayesian Approach

PubMed Central

Adrian, Molly; Kiff, Cara; Glazner, Chris; Kohen, Ruth; Tracy, Julia Helen; Zhou, Chuan; McCauley, Elizabeth; Stoep, Ann Vander

2015-01-01

Objective The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition. Method Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children. Results One main effects, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene x environment and one signification gene x gene interaction emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene x gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems. Conclusions Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5, SERTxOPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status. PMID:26228411

Role of intercellular communications in breast cancer multicellular tumor spheroids after chemotherapy.

PubMed

Oktem, G; Bilir, A; Ayla, S; Yavasoglu, A; Goksel, G; Saydam, G; Uysal, A

2006-01-01

Tumor heterogeneity is an important feature that is especially involved in tumor aggressiveness. Multicellular tumor spheroids (MTS) may provide some benefits in different steps for investigation of the aggregation, organization, differentiation, and network formation of tumor cells in 3D space. This model offers a unique opportunity for improvements in the capability of a current strategy to detect the effect of an appropriate anticancer agent. The aim of this study was to investigate the cellular interactions and morphological changes following chemotherapy in a 3D breast cancer spheroid model. Distribution of the gap junction protein "connexin-43" and the tight junction protein "occludin" was investigated by immunohistochemistry. Cellular interactions were examined by using transmission and scanning electron microscopies as well as light microscopy with Giemsa staining after treating cells with doxorubicin, docetaxel, and doxorubicin/docetaxel combination. Statistical analyses showed significant changes and various alterations that were observed in all groups; however, the most prominent effect was detected in the doxorubicin/docetaxel combination group. Distinct composition as a vessel-like structure and a pseudoglandular pattern of control spheroids were detected in drug-administered groups. Immunohistochemical results were consistent with the ultrastructural changes. In conclusion, doxorubicin/docetaxel combination may be more effective than the single drug usage as shown in a 3D model. The MTS model has been found to be an appropriate and reliable method for the detection of the changes in the expression of cellular junction proteins as well as other cellular proteins occurring after chemotherapy. The MTS model can be used to validate the effects of various combinations or new chemotherapeutic agents as well as documentation of possible mechanisms of new drugs.

DNA Origami Reorganizes upon Interaction with Graphite: Implications for High-Resolution DNA Directed Protein Patterning

PubMed Central

Rahman, Masudur; Neff, David; Green, Nathaniel; Norton, Michael L.

2016-01-01

Although there is a long history of the study of the interaction of DNA with carbon surfaces, limited information exists regarding the interaction of complex DNA-based nanostructures with the important material graphite, which is closely related to graphene. In view of the capacity of DNA to direct the assembly of proteins and optical and electronic nanoparticles, the potential for combining DNA-based materials with graphite, which is an ultra-flat, conductive carbon substrate, requires evaluation. A series of imaging studies utilizing Atomic Force Microscopy has been applied in order to provide a unified picture of this important interaction of structured DNA and graphite. For the test structure examined, we observe a rapid destabilization of the complex DNA origami structure, consistent with a strong interaction of single-stranded DNA with the carbon surface. This destabilizing interaction can be obscured by an intentional or unintentional primary intervening layer of single-stranded DNA. Because the interaction of origami with graphite is not completely dissociative, and because the frustrated, expanded structure is relatively stable over time in solution, it is demonstrated that organized structures of pairs of the model protein streptavidin can be produced on carbon surfaces using DNA origami as the directing material. PMID:28335324

Protein social behavior makes a stronger signal for partner identification than surface geometry

PubMed Central

Laine, Elodie

2016-01-01

ABSTRACT Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico‐chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross‐docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S‐index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface‐based (ranking) score to discriminate partners from non‐interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137–154. © 2016 Wiley Periodicals, Inc. PMID:27802579

SBION: A Program for Analyses of Salt-Bridges from Multiple Structure Files.

PubMed

Gupta, Parth Sarthi Sen; Mondal, Sudipta; Mondal, Buddhadev; Islam, Rifat Nawaz Ul; Banerjee, Shyamashree; Bandyopadhyay, Amal K

2014-01-01

Salt-bridge and network salt-bridge are specific electrostatic interactions that contribute to the overall stability of proteins. In hierarchical protein folding model, these interactions play crucial role in nucleation process. The advent and growth of protein structure database and its availability in public domain made an urgent need for context dependent rapid analysis of salt-bridges. While these analyses on single protein is cumbersome and time-consuming, batch analyses need efficient software for rapid topological scan of a large number of protein for extracting details on (i) fraction of salt-bridge residues (acidic and basic). (ii) Chain specific intra-molecular salt-bridges, (iii) inter-molecular salt-bridges (protein-protein interactions) in all possible binary combinations (iv) network salt-bridges and (v) secondary structure distribution of salt-bridge residues. To the best of our knowledge, such efficient software is not available in public domain. At this juncture, we have developed a program i.e. SBION which can perform all the above mentioned computations for any number of protein with any number of chain at any given distance of ion-pair. It is highly efficient, fast, error-free and user friendly. Finally we would say that our SBION indeed possesses potential for applications in the field of structural and comparative bioinformatics studies. SBION is freely available for non-commercial/academic institutions on formal request to the corresponding author (akbanerjee@biotech.buruniv.ac.in).

Computational investigation of the HIV-1 Rev multimerization using molecular dynamics simulations and binding free energy calculations.

PubMed

Venken, Tom; Daelemans, Dirk; De Maeyer, Marc; Voet, Arnout

2012-06-01

The HIV Rev protein mediates the nuclear export of viral mRNA, and is thereby essential for the production of late viral proteins in the replication cycle. Rev forms a large organized multimeric protein-protein complex for proper functioning. Recently, the three-dimensional structures of a Rev dimer and tetramer have been resolved and provide the basis for a thorough structural analysis of the binding interaction. Here, molecular dynamics (MD) and binding free energy calculations were performed to elucidate the forces thriving dimerization and higher order multimerization of the Rev protein. It is found that despite the structural differences between each crystal structure, both display a similar behavior according to our calculations. Our analysis based on a molecular mechanics-generalized Born surface area (MM/GBSA) and a configurational entropy approach demonstrates that the higher order multimerization site is much weaker than the dimerization site. In addition, a quantitative hot spot analysis combined with a mutational analysis reveals the most contributing amino acid residues for protein interactions in agreement with experimental results. Additional residues were found in each interface, which are important for the protein interaction. The investigation of the thermodynamics of the Rev multimerization interactions performed here could be a further step in the development of novel antiretrovirals using structure based drug design. Moreover, the variability of the angle between each Rev monomer as measured during the MD simulations suggests a role of the Rev protein in allowing flexibility of the arginine rich domain (ARM) to accommodate RNA binding. Copyright © 2012 Wiley Periodicals, Inc.

Interactions in Undersaturated and Supersaturated Lysozyme Solutions: Static and Dynamic Light Scattering Results

NASA Technical Reports Server (NTRS)

Muschol, Martin; Rosenberger, Franz

1995-01-01

We have performed multiangle static and dynamic light scattering studies of lysozyme solutions at pH=4.7. The Rayleigh ratio R(sub g) and the collective diffusion coefficient D(sub c) were determined as function of both protein concentration c(sub p) and salt concentration c(sub s) with two different salts. At low salt concentrations, the scattering ratio K(sub c)(sub p)/R(sub theta) and diffusivity increased with protein concentration above the values for a monomeric, ideal solution. With increasing salt concentration this trend was eventually reversed. The hydrodynamic interactions of lysozyme in solution, extracted from the combination of static and dynamic scattering data, decreased significantly with increasing salt concentration. These observations reflect changes in protein interactions, in response to increased salt screening, from net repulsion to net attraction. Both salts had the same qualitative effect, but the quantitative behavior did not scale with the ionic strength of the solution. This indicates the presence of salt specific effects. At low protein concentrations, the slopes of K(sub c)(sub p)/R(sub theta) and D(sub c) vs c(sub p) were obtained. The dependence of the slopes on ionic strength was modeled using a DLVO potential for colloidal interactions of two spheres, with the net protein charge Z(sub e) and Hamaker constant A(sub H) as fitting parameters. The model reproduces the observed variations with ionic strength quite well. Independent fits to the static and dynamic data, however, led to different values of the fitting parameters. These and other shortcomings suggest that colloidal interaction models alone are insufficient to explain protein interactions in solutions.

Fundamentals of Nanoscale Polymer–Protein Interactions and Potential Contributions to Solid-State Nanobioarrays

PubMed Central

2015-01-01

Protein adsorption onto polymer surfaces is a very complex, ubiquitous, and integrated process, impacting essential areas of food processing and packaging, health devices, diagnostic tools, and medical products. The nature of protein–surface interactions is becoming much more complicated with continuous efforts toward miniaturization, especially for the development of highly compact protein detection and diagnostic devices. A large body of literature reports on protein adsorption from the perspective of ensemble-averaged behavior on macroscopic, chemically homogeneous, polymeric surfaces. However, protein–surface interactions governing the nanoscale size regime may not be effectively inferred from their macroscopic and microscopic characteristics. Recently, research efforts have been made to produce periodically arranged, nanoscopic protein patterns on diblock copolymer surfaces solely through self-assembly. Intriguing protein adsorption phenomena are directly probed on the individual biomolecule level for a fundamental understanding of protein adsorption on nanoscale surfaces exhibiting varying degrees of chemical heterogeneity. Insight gained from protein assembly on diblock copolymers can be effectively used to control the surface density, conformation, orientation, and biofunctionality of prebound proteins in highly miniaturized applications, now approaching the nanoscale. This feature article will highlight recent experimental and theoretical advances made on these fronts while focusing on single-biomolecule-level investigations of protein adsorption behavior combined with surface chemical heterogeneity on the length scale commensurate with a single protein. This article will also address advantages and challenges of the self-assembly-driven patterning technology used to produce protein nanoarrays and its implications for ultrahigh density, functional, and quantifiable protein detection in a highly miniaturized format. PMID:24456577

Alcohol-Binding Sites in Distinct Brain Proteins: The Quest for Atomic Level Resolution

PubMed Central

Howard, Rebecca J.; Slesinger, Paul A.; Davies, Daryl L.; Das, Joydip; Trudell, James R.; Harris, R. Adron

2011-01-01

Defining the sites of action of ethanol on brain proteins is a major prerequisite to understanding the molecular pharmacology of this drug. The main barrier to reaching an atomic-level understanding of alcohol action is the low potency of alcohols, ethanol in particular, which is a reflection of transient, low-affinity interactions with their targets. These mechanisms are difficult or impossible to study with traditional techniques such as radioligand binding or spectroscopy. However, there has been considerable recent progress in combining X-ray crystallography, structural modeling, and site-directed mutagenesis to define the sites and mechanisms of action of ethanol and related alcohols on key brain proteins. We review such insights for several diverse classes of proteins including inwardly rectifying potassium, transient receptor potential, and neurotransmit-ter-gated ion channels, as well as protein kinase C epsilon. Some common themes are beginning to emerge from these proteins, including hydrogen bonding of the hydroxyl group and van der Waals interactions of the methylene groups of ethanol with specific amino acid residues. The resulting binding energy is proposed to facilitate or stabilize low-energy state transitions in the bound proteins, allowing ethanol to act as a “molecular lubricant” for protein function. We discuss evidence for characteristic, discrete alcohol-binding sites on protein targets, as well as evidence that binding to some proteins is better characterized by an interaction region that can accommodate multiple molecules of ethanol. PMID:21676006

In non-transformed cells Bak activates upon loss of anti-apoptotic Bcl-XL and Mcl-1 but in the absence of active BH3-only proteins.

PubMed

Senft, D; Weber, A; Saathoff, F; Berking, C; Heppt, M V; Kammerbauer, C; Rothenfusser, S; Kellner, S; Kurgyis, Z; Besch, R; Häcker, G

2015-11-26

Mitochondrial apoptosis is controlled by proteins of the B-cell lymphoma 2 (Bcl-2) family. Pro-apoptotic members of this family, known as BH3-only proteins, initiate activation of the effectors Bcl-2-associated X protein (Bax) and Bcl-2 homologous antagonist/killer (Bak), which is counteracted by anti-apoptotic family members. How the interactions of Bcl-2 proteins regulate cell death is still not entirely clear. Here, we show that in the absence of extrinsic apoptotic stimuli Bak activates without detectable contribution from BH3-only proteins, and cell survival depends on anti-apoptotic Bcl-2 molecules. All anti-apoptotic Bcl-2 proteins were targeted via RNA interference alone or in combinations of two in primary human fibroblasts. Simultaneous targeting of B-cell lymphoma-extra large and myeloid cell leukemia sequence 1 led to apoptosis in several cell types. Apoptosis depended on Bak whereas Bax was dispensable. Activator BH3-only proteins were not required for apoptosis induction as apoptosis was unaltered in the absence of all BH3-only proteins known to activate Bax or Bak directly, Bcl-2-interacting mediator of cell death, BH3-interacting domain death agonist and p53-upregulated modulator of apoptosis. These findings argue for auto-activation of Bak in the absence of anti-apoptotic Bcl-2 proteins and provide evidence of profound differences in the activation of Bax and Bak.

Influence of surface features of hydroxyapatite on the adsorption of proteins relevant to bone regeneration.

PubMed

Fernández-Montes Moraleda, Belén; San Román, Julio; Rodríguez-Lorenzo, Luís M

2013-08-01

Protein-surface interaction may determine the success or failure of an implanted device. Not much attention have been paid to the specific surface parametes of hydroxyapatite (OHAp) that modulates and determines the formation and potential activity of the layer of proteins that is first formed when the material get in contact with the host tissue. the influence of specific surface area (SSA), crystallite size (CS) and particle size (PS) of OHAp on the adsorption of proteins relevant for bone regeneration is evaluated in this article. OHAp have been prepared by a wet chemical reaction of Ca(OH)2 with H3PO4. One set of reactions included poly acrylic acid in the reactant solution to modify the properties of the powder. Fibrinogen (Fg) Fraction I, type I: from Human plasma, (67% Protein), and Fibronectin (Fn) from Human plasma were selected to perform the adsorption experiments. The analysis of protein adsorption was carried out by UV/Vis spectrometry. A lower SSA and a different aspect ratio are obtained when the acrylic acid is included in the reaction badge. The deconvolution of the amide I band on the Raman spectra of free and adsorbed proteins reveals that the interaction apatite-protein happens through the carboxylate groups of the proteins. The combined analysis of CS, SSA and PS should be considered on the design of OHAp materials intended to interact with proteins. Copyright © 2013 Wiley Periodicals, Inc.

Structural evidence for solvent-stabilisation by aspartic acid as a mechanism for halophilic protein stability in high salt concentrations.

PubMed

Lenton, Samuel; Walsh, Danielle L; Rhys, Natasha H; Soper, Alan K; Dougan, Lorna

2016-07-21

Halophilic organisms have adapted to survive in high salt environments, where mesophilic organisms would perish. One of the biggest challenges faced by halophilic proteins is the ability to maintain both the structure and function at molar concentrations of salt. A distinct adaptation of halophilic proteins, compared to mesophilic homologues, is the abundance of aspartic acid on the protein surface. Mutagenesis and crystallographic studies of halophilic proteins suggest an important role for solvent interactions with the surface aspartic acid residues. This interaction, between the regions of the acidic protein surface and the solvent, is thought to maintain a hydration layer around the protein at molar salt concentrations thereby allowing halophilic proteins to retain their functional state. Here we present neutron diffraction data of the monomeric zwitterionic form of aspartic acid solutions at physiological pH in 0.25 M and 2.5 M concentration of potassium chloride, to mimic mesophilic and halophilic-like environmental conditions. We have used isotopic substitution in combination with empirical potential structure refinement to extract atomic-scale information from the data. Our study provides structural insights that support the hypothesis that carboxyl groups on acidic residues bind water more tightly under high salt conditions, in support of the residue-ion interaction model of halophilic protein stabilisation. Furthermore our data show that in the presence of high salt the self-association between the zwitterionic form of aspartic acid molecules is reduced, suggesting a possible mechanism through which protein aggregation is prevented.

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

Comprehensive peptidomimetic libraries targeting protein-protein interactions.

PubMed

Whitby, Landon R; Boger, Dale L

2012-10-16

Transient protein-protein interactions (PPIs) are essential components in cellular signaling pathways as well as in important processes such as viral infection, replication, and immune suppression. The unknown or uncharacterized PPIs involved in such interaction networks often represent compelling therapeutic targets for drug discovery. To date, however, the main strategies for discovery of small molecule modulators of PPIs are typically limited to structurally characterized targets. Recent developments in molecular scaffolds that mimic the side chain display of peptide secondary structures have yielded effective designs, but few screening libraries of such mimetics are available to interrogate PPI targets. We initiated a program to prepare a comprehensive small molecule library designed to mimic the three major recognition motifs that mediate PPIs (α-helix, β-turn, and β-strand). Three libraries would be built around templates designed to mimic each such secondary structure and substituted with all triplet combinations of groups representing the 20 natural amino acid side chains. When combined, the three libraries would contain a member capable of mimicking the key interaction and recognition residues of most targetable PPIs. In this Account, we summarize the results of the design, synthesis, and validation of an 8000 member α-helix mimetic library and a 4200 member β-turn mimetic library. We expect that the screening of these libraries will not only provide lead structures against α-helix- or β-turn-mediated protein-protein or peptide-receptor interactions, even if the nature of the interaction is unknown, but also yield key insights into the recognition motif (α-helix or β-turn) and identify the key residues mediating the interaction. Consistent with this expectation, the screening of the libraries against p53/MDM2 and HIV-1 gp41 (α-helix mimetic library) or the opioid receptors (β-turn mimetic library) led to the discovery of library members expected to mimic the known endogenous ligands. These efforts led to the discovery of high-affinity α-helix mimetics (K(i) = 0.7 μM) against HIV-1 gp41 as well as high-affinity and selective β-turn mimetics (K(i) = 80 nM) against the κ-opioid receptor. The results suggest that the use of such comprehensive libraries of peptide secondary structure mimetics, built around effective molecular scaffolds, constitutes a powerful method of interrogating PPIs. These structures provide small molecule modulators of PPI networks for therapeutic target validation, lead compound discovery, and the identification of modulators of biological processes for further study.

Combined x-ray crystallography and computational modeling approach to investigate the Hsp90 C-terminal peptide binding to FKBP51.

PubMed

Kumar, Rajnish; Moche, Martin; Winblad, Bengt; Pavlov, Pavel F

2017-10-27

FK506 binding protein of 51 kDa (FKBP51) is a heat shock protein 90 (Hsp90) co-chaperone involved in the regulation of steroid hormone receptors activity. It is known for its role in various regulatory pathways implicated in mood and stress-related disorders, cancer, obesity, Alzheimer's disease and corticosteroid resistant asthma. It consists of two FKBP12 like active peptidyl prolyl isomerase (PPIase) domains (an active FK1 and inactive FK2 domain) and one tetratricopeptide repeat (TPR) domain that mediates interaction with Hsp90 via its C-terminal MEEVD peptide. Here, we report a combined x-ray crystallography and molecular dynamics study to reveal the binding mechanism of Hsp90 MEEVD peptide to the TPR domain of FKBP51. The results demonstrated that the Hsp90 C-terminal peptide binds to the TPR domain of FKBP51 with the help of di-carboxylate clamp involving Lys272, Glu273, Lys352, Asn322, and Lys329 which are conserved throughout several di-carboxylate clamp TPR proteins. Interestingly, the results from molecular dynamics study are also in agreement to the complex structure where all the contacts between these two partners were consistent throughout the simulation period. In a nutshell, our findings provide new opportunity to engage this important protein-protein interaction target by small molecules designed by structure based drug design strategy.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Popeye domain containing protein family--A novel class of cAMP effectors with important functions in multiple tissues.

PubMed

Schindler, Roland F R; Brand, Thomas

2016-01-01

Popeye domain containing (Popdc) proteins are a unique family, which combine several different properties and functions in a surprisingly complex fashion. They are expressed in multiple tissues and cell types, present in several subcellular compartments, interact with different classes of proteins, and are associated with a variety of physiological and pathophysiological processes. Moreover, Popdc proteins bind the second messenger cAMP with high affinity and it is thought that they act as a novel class of cAMP effector proteins. Here, we will review the most important findings about the Popdc family, which accumulated since its discovery about 15 years ago. We will be focussing on Popdc protein interaction and function in striated muscle tissue. However, as a full picture only emerges if all aspects are taken into account, we will also describe what is currently known about the role of Popdc proteins in epithelial cells and in various types of cancer, and discuss these findings with regard to their relevance for cardiac and skeletal muscle. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Probing the binding interaction of a phenazinium dye with serum transport proteins: a combined fluorometric and circular dichroism study.

PubMed

Bose, Debosreeta; Sarkar, Deboleena; Chattopadhyay, Nitin

2010-01-01

In the present investigation, an attempt has been made to study the interaction of phenosafranin (PSF), a cationic phenazinium dye with the transport proteins, bovine serum albumin (BSA) and human serum albumin (HSA), employing steady-state and time-resolved fluorometric and circular dichroism (CD) techniques. The photophysical properties of the dye are altered on binding with the serum proteins. An explicit study with respect to the modification of the fluorescence and fluorescence anisotropy upon binding, effect of denaturant, fluorescence lifetime and CD measurements reveal that the dye binds to both BSA and HSA with almost the same affinity. Far-UV CD spectra indicate a decrease in the percentage of alpha-helicity only for BSA upon binding with the probe. Near-UV CD responses indicate an alteration in the tertiary structure of both the transport proteins because of binding.

mRNA interactome capture in mammalian cells.

PubMed

Kastelic, Nicolai; Landthaler, Markus

2017-08-15

Throughout their entire life cycle, mRNAs are associated with RNA-binding proteins (RBPs), forming ribonucleoprotein (RNP) complexes with highly dynamic compositions. Their interplay is one key to control gene regulatory mechanisms from mRNA synthesis to decay. To assay the global scope of RNA-protein interactions, we and others have published a method combining crosslinking with highly stringent oligo(dT) affinity purification to enrich proteins associated with polyadenylated RNA (poly(A)+ RNA). Identification of the poly(A)+ RNA-bound proteome (also: mRNA interactome capture) has by now been applied to a diversity of cell lines and model organisms, uncovering comprehensive repertoires of RBPs and hundreds of novel RBP candidates. In addition to determining the RBP catalog in a given biological system, mRNA interactome capture allows the examination of changes in protein-mRNA interactions in response to internal and external stimuli, altered cellular programs and disease. Copyright © 2017. Published by Elsevier Inc.

Protein bio-corona: critical issue in immune nanotoxicology.

PubMed

Neagu, Monica; Piperigkou, Zoi; Karamanou, Konstantina; Engin, Ayse Basak; Docea, Anca Oana; Constantin, Carolina; Negrei, Carolina; Nikitovic, Dragana; Tsatsakis, Aristidis

2017-03-01

With the expansion of the nanomedicine field, the knowledge focusing on the behavior of nanoparticles in the biological milieu has rapidly escalated. Upon introduction to a complex biological system, nanomaterials dynamically interact with all the encountered biomolecules and form the protein "bio-corona." The decoration with these surface biomolecules endows nanoparticles with new properties. The present review will address updates of the protein bio-corona characteristics as influenced by nanoparticle's physicochemical properties and by the particularities of the encountered biological milieu. Undeniably, bio-corona generation influences the efficacy of the nanodrug and guides the actions of innate and adaptive immunity. Exploiting the dynamic process of protein bio-corona development in combination with the new engineered horizons of drugs linked to nanoparticles could lead to innovative functional nanotherapies. Therefore, bio-medical nanotechnologies should focus on the interactions of nanoparticles with the immune system for both safety and efficacy reasons.

Electrophoretic Mobility Shift Assay (EMSA) for Detecting Protein-Nucleic Acid Interactions

PubMed Central

Hellman, Lance M.; Fried, Michael G.

2009-01-01

The gel electrophoresis mobility shift assay (EMSA) is used to detect protein complexes with nucleic acids. It is the core technology underlying a wide range of qualitative and quantitative analyses for the characterization of interacting systems. In the classical assay, solutions of protein and nucleic acid are combined and the resulting mixtures are subjected to electrophoresis under native conditions through polyacrylamide or agarose gel. After electrophoresis, the distribution of species containing nucleic acid is determined, usually by autoradiography of 32P-labeled nucleic acid. In general, protein-nucleic acid complexes migrate more slowly than the corresponding free nucleic acid. In this article, we identify the most important factors that determine the stabilities and electrophoretic mobilities of complexes under assay conditions. A representative protocol is provided and commonly used variants are discussed. Expected outcomes are briefly described. References to extensions of the method and a troubleshooting guide are provided. PMID:17703195

The Pro-Apoptotic BH3-Only Protein Bim Interacts with Components of the Translocase of the Outer Mitochondrial Membrane (TOM)

PubMed Central

Frank, Daniel O.; Dengjel, Jörn; Wilfling, Florian; Kozjak-Pavlovic, Vera; Häcker, Georg; Weber, Arnim

2015-01-01

The pro-apoptotic Bcl-2-family protein Bim belongs to the BH3-only proteins known as initiators of apoptosis. Recent data show that Bim is constitutively inserted in the outer mitochondrial membrane via a C-terminal transmembrane anchor from where it can activate the effector of cytochrome c-release, Bax. To identify regulators of Bim-activity, we conducted a search for proteins interacting with Bim at mitochondria. We found an interaction of Bim with Tom70, Tom20 and more weakly with Tom40, all components of the Translocase of the Outer Membrane (TOM). In vitro import assays performed on tryptically digested yeast mitochondria showed reduced Bim insertion into the outer mitochondrial membrane (OMM) indicating that protein receptors may be involved in the import process. However, RNAi against components of TOM (Tom40, Tom70, Tom22 or Tom20) by siRNA, individually or in combination, did not consistently change the amount of Bim on HeLa mitochondria, either at steady state or upon de novo-induction. In support of this, the individual or combined knock-downs of TOM receptors also failed to alter the susceptibility of HeLa cells to Bim-induced apoptosis. In isolated yeast mitochondria, lack of Tom70 or the TOM-components Tom20 or Tom22 alone did not affect the import of Bim into the outer mitochondrial membrane. In yeast, expression of Bim can sensitize the cells to Bax-dependent killing. This sensitization was unaffected by the absence of Tom70 or by an experimental reduction in Tom40. Although thus the physiological role of the Bim-TOM-interaction remains unclear, TOM complex components do not seem to be essential for Bim insertion into the OMM. Nevertheless, this association should be noted and considered when the regulation of Bim in other cells and situations is investigated. PMID:25875815

The pro-apoptotic BH3-only protein Bim interacts with components of the translocase of the outer mitochondrial membrane (TOM).

PubMed

Frank, Daniel O; Dengjel, Jörn; Wilfling, Florian; Kozjak-Pavlovic, Vera; Häcker, Georg; Weber, Arnim

2015-01-01

The pro-apoptotic Bcl-2-family protein Bim belongs to the BH3-only proteins known as initiators of apoptosis. Recent data show that Bim is constitutively inserted in the outer mitochondrial membrane via a C-terminal transmembrane anchor from where it can activate the effector of cytochrome c-release, Bax. To identify regulators of Bim-activity, we conducted a search for proteins interacting with Bim at mitochondria. We found an interaction of Bim with Tom70, Tom20 and more weakly with Tom40, all components of the Translocase of the Outer Membrane (TOM). In vitro import assays performed on tryptically digested yeast mitochondria showed reduced Bim insertion into the outer mitochondrial membrane (OMM) indicating that protein receptors may be involved in the import process. However, RNAi against components of TOM (Tom40, Tom70, Tom22 or Tom20) by siRNA, individually or in combination, did not consistently change the amount of Bim on HeLa mitochondria, either at steady state or upon de novo-induction. In support of this, the individual or combined knock-downs of TOM receptors also failed to alter the susceptibility of HeLa cells to Bim-induced apoptosis. In isolated yeast mitochondria, lack of Tom70 or the TOM-components Tom20 or Tom22 alone did not affect the import of Bim into the outer mitochondrial membrane. In yeast, expression of Bim can sensitize the cells to Bax-dependent killing. This sensitization was unaffected by the absence of Tom70 or by an experimental reduction in Tom40. Although thus the physiological role of the Bim-TOM-interaction remains unclear, TOM complex components do not seem to be essential for Bim insertion into the OMM. Nevertheless, this association should be noted and considered when the regulation of Bim in other cells and situations is investigated.