Improving therapeutic properties of protein drugs through alteration of intracellular trafficking pathways

Although intracellular trafficking processes can play a central role in the physiological function of a protein, these same processes can also limit the benefit of the protein when it is taken out of its physiological context and used as a protein drug. Therefore, the properties of certain protein drugs may be improved by manipulating their trafficking pathways to suit their therapeutic function. A detailed consideration of the factors that govern how protein traffic is routed among different cellular destinations can be used to ascertain molecular design criteria for engineering a protein drug so as to alter its trafficking pathway in a beneficial manner. In this review, we summarize studies that have applied this approach to achieve the following three improvements in protein drug function: (1) half-life extension of the Fc fragment of IgG, (2) half-life extension of granulocyte colony-stimulating factor, and (3) increase in cellular association of transferrin.     

Distinguishing enzyme structures from non-enzymes without alignments

The ability to predict protein function from structure is becoming increasingly important as the number of structures resolved is growing more rapidly than our capacity to study function. Current methods for predicting protein function are mostly reliant on identifying a similar protein of known function. For proteins that are highly dissimilar or are only similar to proteins also lacking functional annotations, these methods fail. Here, we show that protein function can be predicted as enzymatic or not without resorting to alignments. We describe 1178 high-resolution proteins in a structurally non-redundant subset of the Protein Data Bank using simple features such as secondary-structure content, amino acid propensities, surface properties and ligands. The subset is split into two functional groupings, enzymes and non-enzymes. We use the support vector machine-learning algorithm to develop models that are capable of assigning the protein class. Validation of the method shows that the function can be predicted to an accuracy of 77% using 52 features to describe each protein. An adaptive search of possible subsets of features produces a simplified model based on 36 features that predicts at an accuracy of 80%. We compare the method to sequence-based methods that also avoid calculating alignments and predict a recently released set of unrelated proteins. The most useful features for distinguishing enzymes from non-enzymes are secondary-structure content, amino acid frequencies, number of disulphide bonds and size of the largest cleft. This method is applicable to any structure as it does not require the identification of sequence or structural similarity to a protein of known function.     

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.     

Protein meta-functional signatures from combining sequence, structure, evolution, and amino acid property information

Protein function is mediated by different amino acid residues, both their positions and types, in a protein sequence. Some amino acids are responsible for the stability or overall shape of the protein, playing an indirect role in protein function. Others play a functionally important role as part of active or binding sites of the protein. For a given protein sequence, the residues and their degree of functional importance can be thought of as a signature representing the function of the protein. We have developed a combination of knowledge- and biophysics-based function prediction approaches to elucidate the relationships between the structural and the functional roles of individual residues and positions. Such a meta-functional signature (MFS), which is a collection of continuous values representing the functional significance of each residue in a protein, may be used to study proteins of known function in greater detail and to aid in experimental characterization of proteins of unknown function. We demonstrate the superior performance of MFS in predicting protein functional sites and also present four real-world examples to apply MFS in a wide range of settings to elucidate protein sequence-structure-function relationships. Our results indicate that the MFS approach, which can combine multiple sources of information and also give biological interpretation to each component, greatly facilitates the understanding and characterization of protein function.     

Predicting enzyme class from protein structure without alignments

Methods for predicting protein function from structure are becoming more important as the rate at which structures are solved increases more rapidly than experimental knowledge. As a result, protein structures now frequently lack functional annotations. The majority of methods for predicting protein function are reliant upon identifying a similar protein and transferring its annotations to the query protein. This method fails when a similar protein cannot be identified, or when any similar proteins identified also lack reliable annotations. Here, we describe a method that can assign function from structure without the use of algorithms reliant upon alignments. Using simple attributes that can be calculated from any crystal structure, such as secondary structure content, amino acid propensities, surface properties and ligands, we describe each enzyme in a non-redundant set. The set is split according to Enzyme Classification (EC) number. We combine the predictions of one-class versus one-class support vector machine models to make overall assignments of EC number to an accuracy of 35% with the top-ranked prediction, rising to 60% accuracy with the top two ranks. In doing so we demonstrate the utility of simple structural attributes in protein function prediction and shed light on the link between structure and function. We apply our methods to predict the function of every currently unclassified protein in the Protein Data Bank.     

The calcium-binding domain of the stress protein SEP53 is required for survival in response to deoxycholic acid-mediated injury

Stress protein responses have evolved in part as a mechanism to protect cells from the toxic effects of environmental damaging agents. Oesophageal squamous epithelial cells have evolved an atypical stress response that results in the synthesis of a 53 kDa protein of undefined function named squamous epithelial-induced stress protein of 53 kDa (SEP53). Given the role of deoxycholic acid (DCA) as a potential damaging agent in squamous epithelium, we developed assays measuring the effects of DCA on SEP53-mediated responses to damage. To achieve this, we cloned the human SEP53 gene, developed a panel of monoclonal antibodies to the protein, and showed that SEP53 expression is predominantly confined to squamous epithelium. Clonogenic assays were used to show that SEP53 can function as a survival factor in mammalian cell lines, can attenuate DCA-induced apoptotic cell death, and can attenuate DCA-mediated increases in intracellular free calcium. Deletion of the highly conserved EF-hand calcium-binding domain in SEP53 neutralizes the colony survival activity of the protein, neutralizes the protective effects of SEP53 after DCA exposure, and permits calcium elevation in response to DCA challenge. These data indicate that the squamous cell-stress protein SEP53 can function as a modifier of the DCA-mediated calcium influx and identify a novel survival pathway whose study may shed light on mechanisms relating to squamous cell injury and associated cancer development.     

Phosphorylation-dephosphorylation differentially affects activities of splicing factor ASF/SF2.

SR proteins are a conserved family of splicing factors that function in both constitutive and activated splicing. We reported previously that phosphorylation of the SR protein ASF/SF2 enhances its interaction with the U1 snRNP-specific 70K protein and is required for the protein to function in splicing, while other studies have provided evidence that subsequent dephosphorylation can also be required for SR protein function, at least in constitutive splicing. We now show that the phosphorylation status of ASF/SF2 can differentially affect several properties of the protein. In keeping with a dynamic cycle of phosphorylation-dephosphorylation during splicing, ASF/SF2 phosphorylation was found to affect interaction with several putative protein targets in different ways: positively, negatively or not at all. Extending these results, we also show that, in contrast to constitutive splicing, dephosphorylation is not required for ASF/SF2 to function as a splicing activator. We discuss these results with respect to the differential protein-protein interactions that must occur during constitutive and activated splicing.     

Modification of proteins by isoketal-containing oxidized phospholipids

Oxidative stress frequently leads to altered function of membrane proteins. Isoketals are highly reactive products of the isoprostane pathway of free radical-induced lipid peroxidation that rapidly form covalent protein adducts and exhibit a remarkable proclivity to form protein cross links in vitro. Examination of isoketal adducts from an animal model of oxidative injury revealed that initial adducts were formed by isoketals esterified in phospholipids, representing a novel oxidative injury-associated modification of proteins by phospholipids. Maturation of adducts involved cleavage from phospholipids and conversion of adducts to a more stable chemical form that can be detected for extended periods. Because initial adducts were formed by phospholipid-esterified isoketals, the functional consequence of isoketal adduction was examined using a model membrane protein (a cardiac K(+) channel). These studies revealed that isoketal adduction profoundly altered protein function, inhibiting potassium current in a dose-dependent manner. These findings indicate that phospholipid-esterified isoketals rapidly adduct membrane proteins and that such modification can alter protein function, suggesting a generalized cellular mechanism for alteration of membrane function as a consequence of oxidative stress.     

S-Nitrosylation and uncompetitive/fast off-rate (UFO) drug therapy in neurodegenerative disorders of protein misfolding

Although activation of glutamate receptors is essential for normal brain function, excessive activity leads to a form of neurotoxicity known as excitotoxicity. Key mediators of excitotoxic damage include overactivation of N-methyl-D-aspartate (NMDA) receptors, resulting in excessive Ca(2+) influx with production of free radicals and other injurious pathways. Overproduction of free radical nitric oxide (NO) contributes to acute and chronic neurodegenerative disorders. NO can react with cysteine thiol groups to form S-nitrosothiols and thus change protein function. S-nitrosylation can result in neuroprotective or neurodestructive consequences depending on the protein involved. Many neurodegenerative diseases manifest conformational changes in proteins that result in misfolding and aggregation. Our recent studies have linked nitrosative stress to protein misfolding and neuronal cell death. Molecular chaperones - such as protein-disulfide isomerase, glucose-regulated protein 78, and heat-shock proteins - can provide neuroprotection by facilitating proper protein folding. Here, we review the effect of S-nitrosylation on protein function under excitotoxic conditions, and present evidence that NO contributes to degenerative conditions by S-nitrosylating-specific chaperones that would otherwise prevent accumulation of misfolded proteins and neuronal cell death. In contrast, we also review therapeutics that can abrogate excitotoxic damage by preventing excessive NMDA receptor activity, in part via S-nitrosylation of this receptor to curtail excessive activity.     

Toll-like receptor signalling in liver disease: ER stress the missing link?

Toll-like receptors induce a complex inflammatory response that can function to alert the body to infection, neutralize pathogens and repair damaged tissues. Toll-like receptors are expressed on kupffer, endothelial, dendritic, biliary epithelial, hepatic stellate cells, and hepatocytes in the liver. The endoplasmic reticulum (ER) is a central organelle of eukaryotic cells that exists as a place of lipid synthesis, protein folding and protein maturation. The ER is a major signal transduction organelle that senses and responds to changes in homeostasis. Conditions interfering with the function of the ER are collectively known as ER stress and can be induced by accumulation of unfolded protein aggregates or by excessive protein traffic as can occur during viral infection. The ability of ER stress to induce an inflammatory response is considered to play a role in disease pathogenesis. Importantly, ER stress is viewed as a contributor to the pathogenesis of liver diseases with evidence linking components of ER homeostasis as requirements for optimal Toll-like receptor function. In this context this review discusses the association of Toll-like receptors with ER stress. This is an emerging paradigm in the understanding of Toll-like receptor signalling which may have an underlying role in the pathogenesis of liver disease.     

Structure-based identification of a novel NTPase from Methanococcus jannaschii.

Almost half of the entire set of predicted genomic products from Methanococcus jannaschii are classified as functionally unknown hypothetical proteins. We present a structure-based identification of the biochemical function of a protein with an as yet unknown function from a M. jannaschii gene, Mj0226. The crystal structure of Mj0226 protein determined at 2.2 A resolution reveals that the protein is a homodimer and each monomer folds into an elongated alpha/beta structure of a new fold family. Comparisons of Mj0226 protein with protein structures in the database, however, indicate that one part of the protein is homologous to some of the nucleotide-binding proteins. Biochemical analysis shows that Mj0226 protein is a novel nucleotide triphosphatase that can efficiently hydrolyze nonstandard nucleotides such as XTP to XMP or ITP to IMP, but not the standard nucleotides, in the presence of Mg2+ or Mn2+ ions.     

Analytical ultracentrifugation in structural biology

Researchers in the field of structural biology, especially X-ray crystallography and protein nuclear magnetic resonance, are interested in knowing as much as possible about the state of their target protein in solution. Not only is this knowledge relevant to studies of biological function, it also facilitates determination of a protein structure using homogeneous monodisperse protein samples. A researcher faced with a new protein to study will have many questions even after that protein has been purified. Analytical ultracentrifugation (AUC) can provide all of this information readily from a small sample in a non-destructive way, without the need for labeling, enabling structure determination experiments without any wasting time and material on uncharacterized samples. In this article, I use examples to illustrate how AUC can contribute to protein structural analysis. Integrating information from a variety of biophysical experimental methods, such as X-ray crystallography, small angle X-ray scattering, electrospray ionization-mass spectrometry, AUC allows a more complete understanding of the structure and function of biomacromolecules.     

Molecular biologist's guide to proteomics.

The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that the final product of a gene is inherently more complex and closer to function than the gene itself. Shortfalls in the ability of bioinformatics to predict both the existence and function of genes have also illustrated the need for protein analysis. Moreover, only through the study of proteins can posttranslational modifications be determined, which can profoundly affect protein function. Proteomics has been enabled by the accumulation of both DNA and protein sequence databases, improvements in mass spectrometry, and the development of computer algorithms for database searching. In this review, we describe why proteomics is important, how it is conducted, and how it can be applied to complement other existing technologies. We conclude that currently, the most practical application of proteomics is the analysis of target proteins as opposed to entire proteomes. This type of proteomics, referred to as functional proteomics, is always driven by a specific biological question. In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages of a functional proteomics approach and provide examples of how different methodologies can be utilized to address a wide variety of biological problems.     

Molecular Biologist's Guide to Proteomics

The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that the final product of a gene is inherently more complex and closer to function than the gene itself. Shortfalls in the ability of bioinformatics to predict both the existence and function of genes have also illustrated the need for protein analysis. Moreover, only through the study of proteins can posttranslational modifications be determined, which can profoundly affect protein function. Proteomics has been enabled by the accumulation of both DNA and protein sequence databases, improvements in mass spectrometry, and the development of computer algorithms for database searching. In this review, we describe why proteomics is important, how it is conducted, and how it can be applied to complement other existing technologies. We conclude that currently, the most practical application of proteomics is the analysis of target proteins as opposed to entire proteomes. This type of proteomics, referred to as functional proteomics, is always driven by a specific biological question. In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages of a functional proteomics approach and provide examples of how different methodologies can be utilized to address a wide variety of biological problems.     

The DinI and RecX proteins are competing modulators of RecA function

The DinI and RecX proteins of Escherichia coli both modulate the function of RecA protein, but have very different effects. DinI protein stabilizes RecA filaments, preventing disassembly but permitting assembly. RecX protein blocks RecA filament extension, which can lead to net filament disassembly. We demonstrate that both proteins can interact with the RecA filament, and propose that each can replace the other. The DinI/RecX displacement reactions are slow, requiring multiple minutes even when a large excess of the challenging protein is present. The effects of RecX protein on RecA filaments are manifest at lower modulator concentrations than the effects of DinI protein. Together, the DinI and RecX proteins constitute a new regulatory network. The two proteins compete directly as mainly positive (DinI) and negative (RecX) modulators of RecA function.