A visual chip-based coimmunoprecipitation technique for analysis of protein-protein interactions

Here we report a visual chip-based coimmunoprecipitation (vChip-coIP) platform for analysis of protein-protein interactions (PPIs) by combining advantages of an antibody microarray, traditional coIP, and a silver enhancement detection method. The chip was fabricated by spotting anti-Flag antibody on aldehyde-modified slides, and the resulting platform could assay immunoprecipitate from a small amount of crude cell lysates containing Flag-bait and Myc-prey. The interaction signals are visible using biotinylated anti-Myc antibody and colloidal gold-labeled streptavidin followed by a silver enhancement detection method. It is shown that vChip-coIP is a simple, cost-effective, and highly efficient platform for the comprehensive study of PPIs.     

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

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

Adaptive compressive learning for prediction of protein-protein interactions from primary sequence

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems.     

Information integration of protein-protein interactions as essential tools for immunomics

After a brief introduction to point out the necessity to advance for a global understanding of the macromolecular interactions occurring during the immune system development and responses, Section 2 will be devoted to analyse the current tools for an automatic location of information on these protein-protein interactions in the web. In the next section (Section 3), we will point out different action lines to improve these tools and, consequently, to increase the efficiency to establish (to understand) the "protein network skeleton" that controls our immune responses. Finally, we will briefly present our current strategy and work to advance towards this goal.     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.     

pc1 and psc1, zebrafish homologs of Drosophila Polycomb and Posterior sex combs,encode nuclear proteins capable of complex interactions

Drosophila Polycomb group proteins are thought to form multimeric nuclear complexes that are responsible for stable transmission of repressed states of gene expression during the proliferation of differentiating embryos. In this study, we cloned, sequenced, and characterized two Polycomb group homologs, designated pc1 and psc1, in zebrafish. Amino acid sequence analyses determined that pc1 is a structural homolog of Drosophila Polycomb and that psc1 is a homolog of Drosophila Posterior sex combs. Northern blots and whole-mount in situ hybridization revealed that pc1 and psc1 had overlapping expression patterns at successive stages of embryogenesis. Immunocytochemistry localized both Pc1 and Psc1 protein in blastomere nuclei. Pull-down assays and two-hybrid system deletion analyses showed that these proteins were capable of homotypic and heterotypic interactions and identified the regions required for these interactions. The evidence supports the idea that zebrafish Polycomb group proteins, like those of other species, form nuclear complexes with compositions that may vary in a spatio-temporal manner during development.     

A novel mammalian display system for the selection of protein-protein interactions by decoy receptor engagement

The emerging field of proteomics has created a need for new high-throughput methodologies for the analysis of gene products. An attractive approach is to develop systems that allow for clonal selection of interacting protein pairs from large molecular libraries. In this study, we have characterized a novel approach for identification and selection of protein-protein interactions, denoted SPIRE (selection of protein interactions by receptor engagement), which is based on a mammalian expression system. We have demonstrated proof of concept by creating a general plasma membrane bound decoy receptor, by displaying a protein or a peptide genetically fused to a trunctated version of the CD40 molecule. When this decoy receptor is engaged by a ligand to the displayed protein/peptide, the receptor expressing cell is rescued from apoptosis. To design a high-throughput system with a highly parallel capacity, we utilized the B cell line WEHI-231, as carrier of the decoy receptor. One specific peptide-displaying cell could be identified and amplified, based on a specific receptor engagement, in a background of 12 500 wild-type cells after four selections. This demonstrates that the approach may serve as a tool in post-genomic research for identifying protein-protein interactions, without prior knowledge of either component.     

Expression of proteins with dimethylarginines in Escherichia coli for protein-protein interaction studies

Protein arginine methylation often modulates protein-protein interactions. To isolate a sufficient quantity of proteins enriched in methyl arginine(s) from natural sources for biochemical studies is laborious and difficult. We describe here an expression system that produces recombinant proteins that are enriched in omega-N(G),N(G)-asymmetry dimethylarginines. A yeast type I arginine methyltransferase gene (HMT1) is put on a plasmid under the control of the Escherichia coli methionine aminopeptidase promoter for constitutive expression. The protein targeted for post-translational modification is put on the same plasmid behind a T7 promoter for inducible expression of His(6)-tagged proteins. Sbp1p and Stm1p were used as model proteins to examine this expression system. The 13 arginines within the arginine-glycine-rich motif of Sbp1p and the RGG sequence near the C terminus of Stm1p were methylated. Unexpectedly, the arginine residue on the thrombin cleavage site (LVPRGS) of the fusion proteins can also be methylated by Hmt1p. Sbp1p and Sbp1p/hmt1 were covalently attached to solid supports for the isolation of interacting proteins. The results indicate that arginine methylation on Sbp1p exerts both positive and negative effects on protein-protein interaction.     

iWRAP: An interface threading approach with application to prediction of cancer-related protein-protein interactions

Current homology modeling methods for predicting protein-protein interactions (PPIs) have difficulty in the “twilight zone” (< 40%) of sequence identities. Threading methods extend coverage further into the twilight zone by aligning primary sequences for a pair of proteins to a best-fit template complex to predict an entire three-dimensional structure. We introduce a threading approach, iWRAP, which focuses only on the protein interface. Our approach combines a novel linear programming formulation for interface alignment with a boosting classifier for interaction prediction. We demonstrate its efficacy on SCOPPI, a classification of PPIs in the Protein Databank, and on the entire yeast genome. iWRAP provides significantly improved prediction of PPIs and their interfaces in stringent cross-validation on SCOPPI. Furthermore, by combining our predictions with a full-complex threader, we achieve a coverage of 13% for the yeast PPIs, which is close to a 50% increase over previous methods at a higher sensitivity. As an application, we effectively combine iWRAP with genomic data to identify novel cancer-related genes involved in chromatin remodeling, nucleosome organization, and ribonuclear complex assembly. iWRAP is available at http://iwrap.csail.mit.edu.     

Discovery of novel Streptococcus pneumoniae antigens by screening a whole-genome lambda-display library

Streptococcus pneumoniae is a causative agent of otitis media, pneumonia, meningitis and sepsis in humans. For the development of effective vaccines able to prevent pneumococcal infection, characterization of bacterial antigens involved in host immune response is crucial. In order to identify pneumococcal proteins recognized by host antibody response, we created an S. pneumoniae D39 genome library, displayed on lambda bacteriophage. The screening of such a library, with sera either from infected individuals or mice immunized with the S. pneumoniae D39 strain, allowed identification of phage clones carrying S. pneumoniae B-cell epitopes. Epitope-containing fragments within the families of the histidine-triad proteins (PhtE, PhtD), the choline-binding proteins (PspA, CbpD) and zinc metalloproteinase B (ZmpB) were identified. Moreover, library screening also allowed the isolation of phage clones carrying three distinct antigenic regions of a hypothetical pneumococcal protein, encoded by the ORF spr0075 in the R6 strain genome sequence. In this work, Spr0075 is first identified as an expressed S. pneumoniae gene product, having an antigenic function during infection.     

Allowance for thermodynamic nonideality in the characterization of protein interactions by spectral techniques

Theory is developed for the characterization of protein interactions by spectral techniques, where the constraints of constant temperature and pressure demand that thermodynamic activity be defined on the molal concentration scale. The customary practice of defining the equilibrium constant (K) on a molar basis is accommodated by developing expressions to convert those experimental values (K_molar) to their thermodynamically more rigorous counterparts (K_molal). Such procedures are illustrated by reanalysis of published results for the effects of molecular crowding agents on the isomerisation of α-chymotrypsin and reversible complex formation between catalase and superoxide dismutase. Although those reanalyses have led to only minor refinements of the quantitative interpretation, it is clearly preferable to adopt thermodynamic rigor throughout future spectral studies by employing the molal concentration scale from the outset.     

Effects of protein-protein interactions on electron transfer: docking and electron transfer calculations for complexes between flavodoxin and c-type cytochromes

 Theoretical studies of protein-protein association and electron transfer were performed on the binary systems formed by Desulfovibrio vulgaris Hildenborough (D. v. H.) flavodoxin and D. v. H. cytochrome c ₅₅₃ and by flavodoxin and horse heart cytochrome c. Initial structures for the complexes were obtained by rigid-body docking and were refined by MD to allow for molecular flexibility. The structures thus obtained were analysed in terms of their relative stability through the calculation of excess energies. Electrostatic, van der Waals and solvation energy terms showed all to have significant contributions to the stability of complexes. In the best association solutions found for both cytochromes, these bind to different zones of flavodoxin. The binding site of flavodoxin observed for cytochrome c is in accordance with earlier works [27]. The various association modes found were characterised in terms of electron transfer using the Pathways model. For complexes between flavodoxin and horse heart cytochrome c, some correlation was observed between electron tunnelling coupling factors and conformation energy; the best conformation found for electron transfer corresponded also to the best one in terms of energy. For complexes between flavodoxin and cytochrome c ₅₅₃ this was not the case and a lower correlation was observed between electron tunnelling coupling factors and excess energies. These results are in accordance with the differences in the experimental dependence of electron transfer rates with ionic strength observed between these two cases. Received: 29 December 1998 / Accepted: 22 March 1999     

Integrative modeling of protein-protein interactions with pyDock for the new docking challenges

The seventh CAPRI edition imposed new challenges to the modeling of protein-protein complexes, such as multimeric oligomerization, protein-peptide, and protein-oligosaccharide interactions. Many of the proposed targets needed the efficient integration of rigid-body docking, template-based modeling, flexible optimization, multiparametric scoring, and experimental restraints. This was especially relevant for the multimolecular assemblies proposed in the CASP12-CAPRI37 and CASP13-CAPRI46 joint rounds, which were described and evaluated elsewhere. Focusing on the purely CAPRI targets of this edition (rounds 38-45), we have participated in all 17 assessed targets (considering heteromeric and homomeric interfaces in T125 as two separate targets) both as predictors and as scorers, by using integrative modeling based on our docking and scoring approaches: pyDock, IRaPPA, and LightDock. In the protein-protein and protein-peptide targets, we have also participated with our webserver (pyDockWeb). On these 17 CAPRI targets, we submitted acceptable models (or better) within our top 10 models for 10 targets as predictors, 13 targets as scorers, and 4 targets as servers. In summary, our participation in this CAPRI edition confirmed the capabilities of pyDock for the scoring of docking models, increasingly used within the context of integrative modeling of protein interactions and multimeric assemblies.     

MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading

In this postgenomic era, the ability to identify protein-protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein-protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z-score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI-BLAST using a (less) permissive E-value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein-protein interactions are made; 1138 of these 2865 interactions have counterparts in the Database of Interacting Proteins. In contrast, PSI-BLAST made 1781 predictions, and 1215 have counterparts in DIP. An estimation of the false-negative rate for yeast-predicted interactions has also been provided. Thus, a promising approach to help assist in the assignment of protein-protein interactions on a genomic scale has been developed.     

An improved protocol for primary culture of cardiomyocyte from neonatal mice

The primary culture of neonatal mice cardiomyocyte model enables researchers to study and understand the morphological, biochemical, and electrophysiological characteristics of the heart, besides being a valuable tool for pharmacological and toxicological studies. Because cardiomyocytes do not proliferate after birth, primary myocardial culture is recalcitrant. The present study describes an improved method for rapid isolation of cardiomyocytes from neonatal mice, as well as the maintenance and propagation of such cultures for the long term. Immunocytochemical and gene expression data also confirmed the presence of several cardiac markers in the beating cells during the long-term culture condition used in this protocol. The whole culture process can be effectively shortened by reducing the enzyme digestion period and the cardiomyocyte enrichment step. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

鸡法氏囊B淋巴细胞中与鸡传染性法氏囊病病毒VP2相互作用蛋白筛选

为了获得鸡法氏囊B淋巴细胞中与鸡传染性法氏囊病病毒 (IBDV) VP2相互作用的蛋白质,利用酵母双杂交系统,用IBDV VP2蛋白为诱饵蛋白,筛选鸡法氏囊B淋巴细胞cDNA表达文库。将表达文库质粒转化含IBDV VP2诱饵质粒的酵母感受态细胞,检测报告基因在相应的营养缺陷型培养基 (SD/-Leu/-Trp/-His) 上表达情况,进一步经β-半乳糖苷酶报告基因检测,筛选到16个阳性克隆。提取阳性克隆质粒,经测序分析获得5个原鸡基因序列,分别是：线粒体DNA、蛋白质O位N-乙酰葡萄糖胺糖基化转移酶、肿瘤     

An expression system for screening of proteins for glycan and protein interactions

Here we describe a versatile high-throughput expression system that permits genome-wide screening of type 1 membrane and secreted proteins for interactions with glycans and proteins using both cell-expressed and soluble forms of the expressed proteins. Based on Gateway cloning methodology, we have engineered a destination vector that directs expression of enhanced green fluorescent protein (EGFP)-tagged proteins at the cell surface via a glycosylphosphatidylinositol tail. The EGFP fusion proteins can then be cleaved with PreScission protease to release soluble forms of proteins that can be optionally biotinylated. We demonstrate the utility of this cloning and expression system for selected low-affinity membrane lectins from the siglec family of sialic acid-binding immunoglobulin-like lectins, for the glycosaminoglycan-binding proteins FGF-1 and BACE, and for the heterotypic adhesion molecules JAM-B and JAM-C. Cell-expressed proteins can be evaluated for glycan interactions using polyvalent soluble glycan probes and for protein interactions using either cells or soluble proteins. Following cleavage from the cell surface, proteins were complexed in solution and sufficient avidity was achieved to measure weak protein–glycan and weak protein–protein interactions using glycan arrays and surface plasmon resonance, respectively.