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Results for “Protein-protein interactions”

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102 records · Page 6

Genes encoding calmodulin-binding proteins in the Arabidopsis genome

Analysis of the recently completed Arabidopsis genome sequence indicates that approximately 31% of the predicted genes could not be assigned to functional categories, as they do not show any sequence similarity with proteins of known function from other organisms. Calmodulin (CaM), a ubiquitous and multifunctional Ca(2+) sensor, interacts with a wide variety of cellular proteins and modulates their activity/function in regulating diverse cellular processes. However, the primary amino acid sequence of the CaM-binding domain in different CaM-binding proteins (CBPs) is not conserved. One way to identify most of the CBPs in the Arabidopsis genome is by protein-protein interaction-based screening of expression libraries with CaM. Here, using a mixture of radiolabeled CaM isoforms from Arabidopsis, we screened several expression libraries prepared from flower meristem, seedlings, or tissues treated with hormones, an elicitor, or a pathogen. Sequence analysis of 77 positive clones that interact with CaM in a Ca(2+)-dependent manner revealed 20 CBPs, including 14 previously unknown CBPs. In addition, by searching the Arabidopsis genome sequence with the newly identified and known plant or animal CBPs, we identified a total of 27 CBPs. Among these, 16 CBPs are represented by families with 2-20 members in each family. Gene expression analysis revealed that CBPs and CBP paralogs are expressed differentially. Our data suggest that Arabidopsis has a large number of CBPs including several plant-specific ones. Although CaM is highly conserved between plants and animals, only a few CBPs are common to both plants and animals. Analysis of Arabidopsis CBPs revealed the presence of a variety of interesting domains. Our analyses identified several hypothetical proteins in the Arabidopsis genome as CaM targets, suggesting their involvement in Ca(2+)-mediated signaling networks.

NASA Discipline Plant Biology↗

Palmitoylation of caveolin-1 in endothelial cells is post-translational but irreversible

Caveolin-1 is a palmitoylated protein involved in assembly of signaling molecules in plasma membrane subdomains termed caveolae and in intracellular cholesterol transport. Three cysteine residues in the C terminus of caveolin-1 are subject to palmitoylation, which is not necessary for caveolar targeting of caveolin-1. Protein palmitoylation is a post-translational and reversible modification that may be regulated and that in turn may regulate conformation, membrane association, protein-protein interactions, and intracellular localization of the target protein. We have undertaken a detailed analysis of [(3)H]palmitate incorporation into caveolin-1 in aortic endothelial cells. The linkage of palmitate to caveolin-1 was hydroxylamine-sensitive and thus presumably a thioester bond. However, contrary to expectations, palmitate incorporation was blocked completely by the protein synthesis inhibitors cycloheximide and puromycin. In parallel experiments to show specificity, palmitoylation of aortic endothelial cell-specific nitric-oxide synthase was unaffected by these reagents. Inhibitors of protein trafficking, brefeldin A and monensin, blocked caveolin-1 palmitoylation, indicating that the modification was not cotranslational but rather required caveolin-1 transport from the endoplasmic reticulum and Golgi to the plasma membrane. In addition, immunophilin chaperones that form complexes with caveolin-1, i.e. FK506-binding protein 52, cyclophilin A, and cyclophilin 40, were not necessary for caveolin-1 palmitoylation because agents that bind immunophilins did not inhibit palmitoylation. Pulse-chase experiments showed that caveolin-1 palmitoylation is essentially irreversible because the release of [(3)H]palmitate was not significant even after 24 h. These results show that [(3)H]palmitate incorporation is limited to newly synthesized caveolin-1, not because incorporation only occurs during synthesis but because the continuous presence of palmitate on caveolin-1 prevents subsequent repalmitoylation.

Non-NASA Center↗

A mutation in the Arabidopsis HYL1 gene encoding a dsRNA binding protein affects responses to abscisic acid, auxin, and cytokinin

Both physiological and genetic evidence indicate interconnections among plant responses to different hormones. We describe a pleiotropic recessive Arabidopsis transposon insertion mutation, designated hyponastic leaves (hyl1), that alters the plant's responses to several hormones. The mutant is characterized by shorter stature, delayed flowering, leaf hyponasty, reduced fertility, decreased rate of root growth, and an altered root gravitropic response. It also exhibits less sensitivity to auxin and cytokinin and hypersensitivity to abscisic acid (ABA). The auxin transport inhibitor 2,3,5-triiodobenzoic acid normalizes the mutant phenotype somewhat, whereas another auxin transport inhibitor, N-(1-naph-thyl)phthalamic acid, exacerbates the phenotype. The gene, designated HYL1, encodes a 419-amino acid protein that contains two double-stranded RNA (dsRNA) binding motifs, a nuclear localization motif, and a C-terminal repeat structure suggestive of a protein-protein interaction domain. We present evidence that the HYL1 gene is ABA-regulated and encodes a nuclear dsRNA binding protein. We hypothesize that the HYL1 protein is a regulatory protein functioning at the transcriptional or post-transcriptional level.

NASA Discipline Plant Biology↗

A pollen-specific novel calmodulin-binding protein with tetratricopeptide repeats

Calcium is essential for pollen germination and pollen tube growth. A large body of information has established a link between elevation of cytosolic Ca(2+) at the pollen tube tip and its growth. Since the action of Ca(2+) is primarily mediated by Ca(2+)-binding proteins such as calmodulin (CaM), identification of CaM-binding proteins in pollen should provide insights into the mechanisms by which Ca(2+) regulates pollen germination and tube growth. In this study, a CaM-binding protein from maize pollen (maize pollen calmodulin-binding protein, MPCBP) was isolated in a protein-protein interaction-based screening using (35)S-labeled CaM as a probe. MPCBP has a molecular mass of about 72 kDa and contains three tetratricopeptide repeats (TPR) suggesting that it is a member of the TPR family of proteins. MPCBP protein shares a high sequence identity with two hypothetical TPR-containing proteins from Arabidopsis. Using gel overlay assays and CaM-Sepharose binding, we show that the bacterially expressed MPCBP binds to bovine CaM and three CaM isoforms from Arabidopsis in a Ca(2+)-dependent manner. To map the CaM-binding domain several truncated versions of the MPCBP were expressed in bacteria and tested for their ability to bind CaM. Based on these studies, the CaM-binding domain was mapped to an 18-amino acid stretch between the first and second TPR regions. Gel and fluorescence shift assays performed with CaM and a CaM-binding synthetic peptide further confirmed MPCBP binding to CaM. Western, Northern, and reverse transcriptase-polymerase chain reaction analysis have shown that MPCBP expression is specific to pollen. MPCBP was detected in both soluble and microsomal proteins. Immunoblots showed the presence of MPCBP in mature and germinating pollen. Pollen-specific expression of MPCBP, its CaM-binding properties, and the presence of TPR motifs suggest a role for this protein in Ca(2+)-regulated events during pollen germination and growth.

NASA Discipline Plant Biology↗

CCAAT/enhancer-binding protein delta is a critical regulator of insulin-like growth factor-I gene transcription in osteoblasts

Insulin-like growth factor-I (IGF-I) plays a major role in promoting skeletal growth by stimulating bone cell replication and differentiation. Prostaglandin E2 and other agents that induce cAMP production enhance IGF-I gene transcription in cultured rat osteoblasts through a DNA element termed HS3D, located in the proximal part of the major rat IGF-I promoter. We previously determined that CCAAT/enhancer-binding protein delta (C/EBPdelta) is the key cAMP-stimulated regulator of IGF-I transcription in these cells and showed that it transactivates the rat IGF-I promoter through the HS3D site. We now have defined the physical-chemical properties and functional consequences of the interactions between C/EBPdelta and HS3D. C/EBPdelta, expressed in COS-7 cells or purified as a recombinant protein from Escherichia coli, bound to HS3D with an affinity at least equivalent to that of the albumin D-site, a known high affinity C/EBP binding sequence, and both DNA elements competed equally for C/EBPdelta. C/EBPdelta bound to HS3D as a dimer, with protein-DNA contact points located on guanine residues on both DNA strands within and just adjacent to the core C/EBP half-site, GCAAT, as determined by methylation interference footprinting. C/EBPdelta also formed protein-protein dimers in the absence of interactions with its DNA binding site, as indicated by results of glutaraldehyde cross-linking studies. As established by competition gel-mobility shift experiments, the conserved HS3D sequence from rat, human, and chicken also bound C/EBPdelta with similar affinity. We also found that prostaglandin E2-induced expression of reporter genes containing human IGF-I promoter 1 or four tandem copies of the human HS3D element fused to a minimal promoter and show that these effects were enhanced by a co-transfected C/EBPdelta expression plasmid. Taken together, our results provide evidence that C/EBPdelta is a critical activator of IGF-I gene transcription in osteoblasts and potentially in other cell types and species.

NASA Discipline Musculoskeletal↗

Expression and purification of recombinant polyomavirus VP2 protein and its interactions with polyomavirus proteins

Recombinant polyomavirus VP2 protein was expressed in Escherichia coli (RK1448), using the recombinant expression system pFPYV2. Recombinant VP2 was purified to near homogeneity by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, electroelution, and Extracti-Gel chromatography. Polyclonal serum to this protein which reacted specifically with recombinant VP2 as well as polyomavirus virion VP2 and VP3 on Western blots (immunoblots) was produced. Purified VP2 was used to establish an in vitro protein-protein interaction assay with polyomavirus structural proteins and purified recombinant VP1. Recombinant VP2 interacted with recombinant VP1, virion VP1, and the four virion histones. Recombinant VP1 coimmunoprecipitated with recombinant VP2 or truncated VP2 (delta C12VP2), which lacked the carboxy-terminal 12 amino acids. These experiments confirmed the interaction between VP1 and VP2 and revealed that the carboxyterminal 12 amino acids of VP2 and VP3 were not necessary for formation of this interaction. In vivo VP1-VP2 interaction study accomplished by cotransfection of COS-7 cells with VP2 and truncated VP1 (delta N11VP1) lacking the nuclear localization signal demonstrated that VP2 was capable of translocating delta N11VP1 into the nucleus. These studies suggest that complexes of VP1 and VP2 may be formed in the cytoplasm and cotransported to the nucleus for virion assembly to occur.

Non-NASA Center↗

Modelling protein functional domains in signal transduction using Maude

Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

Signal Transduction↗

Computational studies of Ras and PI3K

Until recently, experimental techniques in molecular cell biology have been the primary means to investigate biological risk upon space radiation. However, computational modeling provides an alternative theoretical approach, which utilizes various computational tools to simulate proteins, nucleotides, and their interactions. In this study, we are focused on using molecular mechanics (MM) and molecular dynamics (MD) to study the mechanism of protein-protein binding and to estimate the binding free energy between proteins. Ras is a key element in a variety of cell processes, and its activation of phosphoinositide 3-kinase (PI3K) is important for survival of transformed cells. Different computational approaches for this particular study are presented to calculate the solvation energies and binding free energies of H-Ras and PI3K. The goal of this study is to establish computational methods to investigate the roles of different proteins played in the cellular responses to space radiation, including modification of protein function through gene mutation, and to support the studies in molecular cell biology and theoretical kinetics models for our risk assessment project.

Ren, Lei↗

CryoEM Structures of the Nitrogenase Complex During Catalytic Turnover

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multi-electron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here we report the cryogenic electron microscopic interrogation of the nitrogenase complex under enzymatic turnover conditions, which has enabled the structural characterization of the nitrogenase reaction intermediates at high resolution for the first time. Our structures show that asymmetry governs all aspects of nitrogenase mechanism including ATP hydrolysis, protein-protein interactions, and catalysis. Furthermore, they reveal several previously unobserved, mechanistically relevant conformational changes near the catalytic iron-molybdenum cofactor that are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗

Structures of the Nitrogenase Complex Prepared Under Catalytic Turnover Conditions

The enzyme nitrogenase couples adenosine triphosphate (ATP) hydrolysis to the multielectron reduction of atmospheric dinitrogen into ammonia. Despite extensive research, the mechanistic details of ATP-dependent energy transduction and dinitrogen reduction by nitrogenase are not well understood, requiring new strategies to monitor its structural dynamics during catalytic action. Here, we report cryo–electron microscopy structures of the nitrogenase complex prepared under enzymatic turnover conditions. We observe that asymmetry governs all aspects of the nitrogenase mechanism, including ATP hydrolysis, protein-protein interactions, and catalysis. Conformational changes near the catalytic iron-molybdenum cofactor are correlated with the nucleotide-hydrolysis state of the enzyme.

Hannah L. Rutledge↗

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗