The Golgi complex: a hub of the secretory pathway

The Golgi complex plays a central role in protein secretion by regulating cargo sorting and trafficking. As these processes are of functional importance to cell polarity, motility, growth, and division, there is considerable interest in achieving a comprehensive understanding of Golgi complex biology. However, the unique stack structure of this organelle has been a major hurdle to our understanding of how proteins are secreted through the Golgi apparatus. Herein, we summarize available relevant research to gain an understanding of protein secretion via the Golgi complex. This includes the molecular mechanisms of intra-Golgi trafficking and cargo export in the trans-Golgi network. Moreover, we review recent insights on signaling pathways regulated by the Golgi complex and their physiological significance.     

Folding pathway of the b1 domain of protein G explored by multiscale modeling

The understanding of the folding mechanisms of single-domain proteins is an essential step in the understanding of protein folding in general. Recently, we developed a mesoscopic CA-CB side-chain protein model, which was successfully applied in protein structure prediction, studies of protein thermodynamics, and modeling of protein complexes. In this research, this model is employed in a detailed characterization of the folding process of a simple globular protein, the B1 domain of IgG-binding protein G (GB1). There is a vast body of experimental facts and theoretical findings for this protein. Performing unbiased, ab initio simulations, we demonstrated that the GB1 folding proceeds via the formation of an extended folding nucleus, followed by slow structure fine-tuning. Remarkably, a subset of native interactions drives the folding from the very beginning. The emerging comprehensive picture of GB1 folding perfectly matches and extends the previous experimental and theoretical studies.     

Systems for the detection and analysis of protein–protein interactions

The analysis of protein–protein interactions is important for developing a better understanding of the functional annotations of proteins that are involved in various biochemical reactions in vivo. The discovery that a protein with an unknown function binds to a protein with a known function could provide a significant clue to the cellular pathway concerning the unknown protein. Therefore, information on protein–protein interactions obtained by the comprehensive analysis of all gene products is available for the construction of interactive networks consisting of individual protein–protein interactions, which, in turn, permit elaborate biological phenomena to be understood. Systems for detecting protein–protein interactions in vitro and in vivo have been developed, and have been modified to compensate for limitations. Using these novel approaches, comprehensive and reliable information on protein–protein interactions can be determined. Systems that permit this to be achieved are described in this review.K. Kuroda, M. Kato and J. Mima contributed equally to this work.     

Proteomics strategies for protein identification

The information from genome sequencing provides new approaches for systems-wide understanding of protein networks and cellular function. DNA microarray technologies have advanced to the point where nearly complete monitoring of gene expression is feasible in several organisms. An equally important goal is to comprehensive survey cellular proteomes and profile protein changes under different cellular states. This presents a complex analytical problem, due to the chemical variability between proteins and peptides. Here, we discuss strategies to improve accuracy and sensitivity of peptide identification, distinguish represented protein isoforms, and quantify relative changes in protein abundance.     

Applying proteomics to signaling networks

The information from genome sequencing provides a new framework for a systems-wide understanding of protein networks and cellular function. Whereas microarray technologies provide information about global gene expression within cells, complementary proteomic strategies monitor expression of proteins and their posttranslational modifications. Improved technologies that have emerged for comprehensive and high-throughput protein analysis yield novel insights into cell regulation.     

The structural analysis of protein–protein interactions by NMR spectroscopy

A comprehensive understanding of protein–protein interactions is an important next step in our quest to understand how the information contained in a genome is put into action. Although a number of experimental techniques can report on the existence of a protein– protein interaction, very few can provide detailed structural information. NMR spectroscopy is one of these, and in recent years several complementary NMR approaches, including residual dipolar couplings and the use of paramagnetic effects, have been developed that can provide insight into the structure of protein–protein complexes. In this article, we review these approaches and comment on their strengths and weaknesses.     

Yeast-based functional genomics and proteomics technologies: the first 15 years and beyond

Yeast-based functional genomics and proteomics technologies developed over the past decade have contributed greatly to our understanding of bacterial, yeast, fly, worm, and human gene functions. In this review, we highlight some of these yeast-based functional genomic and proteomic technologies that are advancing the utility of yeast as a model organism in molecular biology and speculate on their future uses. Such technologies include use of the yeast deletion strain collection, large-scale determination of protein localization in vivo, synthetic genetic array analysis, variations of the yeast two-hybrid system, protein microarrays, and tandem affinity purification (TAP)-tagging approaches. The integration of these advances with established technologies is invaluable in the drive toward a comprehensive understanding of protein structure and function in the cellular milieu.     

GWYRE: A Resource for Mapping Variants onto Experimental and Modeled Structures of Human Protein Complexes

Rapid progress in structural modeling of proteins and their interactions is powered by advances in knowledge-based methodologies along with better understanding of physical principles of protein structure and function. The pool of structural data for modeling of proteins and protein–protein complexes is constantly increasing due to the rapid growth of protein interaction databases and Protein Data Bank. The GWYRE (Genome Wide PhYRE) project capitalizes on these developments by advancing and applying new powerful modeling methodologies to structural modeling of protein–protein interactions and genetic variation. The methods integrate knowledge-based tertiary structure prediction using Phyre2 and quaternary structure prediction using template-based docking by a full-structure alignment protocol to generate models for binary complexes. The predictions are incorporated in a comprehensive public resource for structural characterization of the human interactome and the location of human genetic variants. The GWYRE resource facilitates better understanding of principles of protein interaction and structure/function relationships. The resource is available at http://www.gwyre.org.     

Classification of protein folds

The diversity and complexity of bioinformatics tools currently available for protein sequence analysis can make it difficult to know where to begin when presented with a new sequence. In this article, we present a protocol outlining one approach to sequence analysis that should give as comprehensive a picture as possible as to the likely structure and function of a protein given the limits of available tools. We also provide worked examples showing how these tools can have an impact on the understanding of protein function prior to experimental studies.     

Quantitative Characterization of Local Protein Solvation To Predict Solvent Effects on Protein Structure

Characterization of solvent preferences of proteins is essential to the understanding of solvent effects on protein structure and stability. Although it is generally believed that solvent preferences at distinct loci of a protein surface may differ, quantitative characterization of local protein solvation has remained elusive. In this study, we show that local solvation preferences can be quantified over the entire protein surface from extended molecular dynamics simulations. By subjecting microsecond trajectories of two proteins (lysozyme and antibody fragment D1.3) in 4 M glycerol to rigorous statistical analyses, solvent preferences of individual protein residues are quantified by local preferential interaction coefficients. Local solvent preferences for glycerol vary widely from residue to residue and may change as a result of protein side-chain motions that are slower than the longest intrinsic solvation timescale of ～10 ns. Differences of local solvent preferences between distinct protein side-chain conformations predict solvent effects on local protein structure in good agreement with experiment. This study extends the application scope of preferential interaction theory and enables molecular understanding of solvent effects on protein structure through comprehensive characterization of local protein solvation.     

Intrinsic protein disorder in human pathways

We analyze human-specific KEGG pathways trying to understand the functional role of intrinsic disorder in proteins. Pathways provide a comprehensive picture of biological processes and allow better understanding of a protein's function within the specific context of its surroundings. Our study pinpoints a few specific pathways significantly enriched in disorder-containing proteins and identifies the role of these proteins within the framework of pathway relationships. Three major categories of relations are shown to be significantly enriched in disordered proteins: gene expression, protein binding and to a lesser degree, protein phosphorylation. Finally we find that relations involving protein activation and to some extent inhibition are characterized by low disorder content.     

Systems approach to explore components and interactions in the presynapse

The application of proteomic techniques to neuroscientific research provides an opportunity for a greater understanding of nervous system structure and function. As increasing amounts of neuroproteomic data become available, it is necessary to formulate methods to integrate these data in a meaningful way to obtain a more comprehensive picture of neuronal subcompartments. Furthermore, computational methods can be used to make biologically relevant predictions from large proteomic data sets. Here, we applied an integrated proteomics and systems biology approach to characterize the presynaptic (PRE) nerve terminal. For this, we carried out proteomic analyses of presynaptically enriched fractions, and generated a PRE literature‐based protein–protein interaction network. We combined these with other proteomic analyses to generate a core list of 117 PRE proteins, and used graph theory‐inspired algorithms to predict 92 additional components and a PRE complex containing 17 proteins. Some of these predictions were validated experimentally, indicating that the computational analyses can identify novel proteins and complexes in a subcellular compartment. We conclude that the combination of techniques (proteomics, data integration, and computational analyses) used in this study are useful in obtaining a comprehensive understanding of functional components, especially low‐abundance entities and/or interactions in the PRE nerve terminal.     

Overview of human endogenous retroviruses found in human genome assembly GRCh37/hg19

The late Nobel Laureate Sir Peter Medawar once memorably described viruses as ‘bad news wrapped in protein’. Virus assembly in HIV is a remarkably well coordinated process in which the virus achieves extracellular budding using primarily intracellular budding machinery and also the unusual phenomenon of export from the cell of an RNA. Recruitment of the ESCRT system by HIV is one of the best documented examples of the comprehensive way in which a virus hijacks a normal cellular process. This review is a summary of our current understanding of the budding process of HIV, from genomic RNA capture through budding and on to viral maturation, but centering on the proteins of the ESCRT pathway and highlighting some recent advances in our understanding of the cellular components involved and the complex interplay between the Gag protein and the genomic RNA.     

DIP: the database of interacting proteins

The Database of Interacting Proteins (DIP; http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. This database is intended to provide the scientific community with a comprehensive and integrated tool for browsing and efficiently extracting information about protein interactions and interaction networks in biological processes. Beyond cataloging details of protein-protein interactions, the DIP is useful for understanding protein function and protein-protein relationships, studying the properties of networks of interacting proteins, benchmarking predictions of protein-protein interactions, and studying the evolution of protein-protein interactions.     

A human protein-protein interaction network: a resource for annotating the proteome

Protein-protein interaction maps provide a valuable framework for a better understanding of the functional organization of the proteome. To detect interacting pairs of human proteins systematically, a protein matrix of 4456 baits and 5632 preys was screened by automated yeast two-hybrid (Y2H) interaction mating. We identified 3186 mostly novel interactions among 1705 proteins, resulting in a large, highly connected network. Independent pull-down and co-immunoprecipitation assays validated the overall quality of the Y2H interactions. Using topological and GO criteria, a scoring system was developed to define 911 high-confidence interactions among 401 proteins. Furthermore, the network was searched for interactions linking uncharacterized gene products and human disease proteins to regulatory cellular pathways. Two novel Axin-1 interactions were validated experimentally, characterizing ANP32A and CRMP1 as modulators of Wnt signaling. Systematic human protein interaction screens can lead to a more comprehensive understanding of protein function and cellular processes.     

Response to nickel in the proteome of the metal accumulator plant Brassica juncea

To gain a comprehensive understanding of the molecular mechanism of heavy metal accumulation in Brassica juncea, comparative proteomic approaches were used to analysis protein profiles in leaf tissues of 6-week-old B. juncea after exposure to 100 µM Ni. Proteomic analysis revealed that 61 protein spots showed 1.5-fold change in protein abundance after Ni exposure as compared to that of corresponding spots in control. Out of the 61 differentially expressed protein spots, 37 protein spots were ambiguously identified by matrix assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF MS). The majority of these identified proteins were found to be involved in sulphur metabolism, protection against oxidative stress, clearly indicated that heavy metal sequestration and antioxidant system were activated by Ni treatment. The induced expression of photosynthesis and ATP generation-related proteins were also observed in plants exposed to metals, suggesting the tolerance and accumulation is an energy-demanding process. The identification of these proteins in response to Ni can lead a deep understanding of heavy metal accumulation and tolerance in B. juncea.     

Tracking protein turnover and degradation by microscopy: photo-switchable versus time-encoded fluorescent proteins

Expanded fluorescent protein techniques employing photo-switchable and fluorescent timer proteins have become important tools in biological research. These tools allow researchers to address a major challenge in cell and developmental biology, namely obtaining kinetic information about the processes that determine the distribution and abundance of proteins in cells and tissues. This knowledge is often essential for the comprehensive understanding of a biological process, and/or required to determine the precise point of interference following an experimental perturbation.     

A Multiparametric Computational Algorithm for Comprehensive Assessment of Genetic Mutations in Mucopolysaccharidosis Type IIIA (Sanfilippo Syndrome)

Mucopolysaccharidosis type IIIA (MPS-IIIA, Sanfilippo syndrome) is a Lysosomal Storage Disease caused by cellular deficiency of N-sulfoglucosamine sulfohydrolase (SGSH). Given the large heterogeneity of genetic mutations responsible for the disease, a comprehensive understanding of the mechanisms by which these mutations affect enzyme function is needed to guide effective therapies. We developed a multiparametric computational algorithm to assess how patient genetic mutations in SGSH affect overall enzyme biogenesis, stability, and function. 107 patient mutations for the SGSH gene were obtained from the Human Gene Mutation Database representing all of the clinical mutations documented for Sanfilippo syndrome. We assessed each mutation individually using ten distinct parameters to give a comprehensive predictive score of the stability and misfolding capacity of the SGSH enzyme resulting from each of these mutations. The predictive score generated by our multiparametric algorithm yielded a standardized quantitative assessment of the severity of a given SGSH genetic mutation toward overall enzyme activity. Application of our algorithm has identified SGSH mutations in which enzymatic malfunction of the gene product is specifically due to impairments in protein folding. These scores provide an assessment of the degree to which a particular mutation could be treated using approaches such as chaperone therapies. Our multiparametric protein biogenesis algorithm advances a key understanding in the overall biochemical mechanism underlying Sanfilippo syndrome. Importantly, the design of our multiparametric algorithm can be tailored to many other diseases of genetic heterogeneity for which protein misfolding phenotypes may constitute a major component of disease manifestation.