Current Proteomics - Volume 3, Issue 4, 2006

Since protein phosphorylation was accepted to play a key role in cellular metabolism the investigation of this important posttranslational modification has gained ever-growing interest of researchers. However, until recently, technical challenges have made large scale studies on protein phosphorylation impossible. With dramatic improvements in both phosporylated peptides/proteins enrichment methods and in the selectivity and resolving power of mass spectrometry based techniques, the main challenges have been addressed and large scale protein phosphorylation studies are now being conducted. These technical advancements have also opened the door for the more accurate determination of actual protein phosphorylation sites. Consequently, another important aspect of this prominent signalling event can be investigated: proteins possess several phosphorylation sites and it is assumed that many of them have distinct regulatory function. While these processes are under thorough investigation in animals, protein phosphorylation in plants is still a developing field. This is particularly surprising in light of the enormous number of predicted protein kinases in the Arabidopsis thaliana genome exceeding apparently the complexity of animal systems. In this review, we illustrate the advantages and drawbacks of methods currently used for studying phosphorylation with an emphasis on phosphoprotein/peptide enrichment and mass spectrometry. We then describe how these methods can be used to reveal the biological importance of multisite protein phosphorylation in plants.

Since translation is a central process in all living organisms, the components of translational machinery containing aminoacyltRNA synthetases, initiation, elongation, and releasing factors and ribosomal proteins have been considered as housekeepers of the cells. While these components are necessary for translational control, many of them have been found also to be involved in the control of cell fate through the diverse functions that are seemingly unrelated to protein synthesis. Also, there are several lines of evidence, suggesting the association of eukaryotic translational components with cancer development although the exact underlying mechanisms still await further investigation. Here we address the involvement of the translational components in the cell transformation and malignant phenotypes and the relationship of the deregulation of translational control of a wide range of cancers to provide systematic view on the association of translational components with cancers.

Signal transduction through reversible protein phosphorylation plays a central role in cellular physiology in both normal and disease states, and mass spectrometry is well-suited to the task of identifying and cataloging protein phosphorylation sites. Recent advances in sample enrichment strategies, instrumentation, and software availability allow researchers to identify hundreds of phosphorylation sites in a single study. However, to take the next step toward translating these findings into clinical application, the biological relevance of the sites must be validated and clinical assays must be developed to monitor phospho-specific biomarkers.

Molecular dynamics (MD) simulation methods have been an effective source of generating biomolecular-level structural information in immunology, as feedback to understand basic science and to design new experiments, leading to the discovery of drugs and vaccines. Different soluble or surface-bound proteins secreted by immune cells exchange signals through the formation of specialized molecular complexes. Molecules involved in the complex formation are complement proteins, antibodies, T cell receptors, MHC encoded HLA molecules, endogenous peptide antigens, and pathogenic peptides. Understanding the molecular details of the complex formation is very important to systematic design of drugs and vaccines. Experimental data provide only macroscopic reasoning and in many cases fail to perceive subtle differences in behaviors of two apparently very similar systems. Formation of stable complexes depends on complementary residues in proteins and peptides and their matching conformations. Here we present a comprehensive review of applications of MD simulations in immunology. In addition, a short section on computational predictive methods to identify T cell epitopes has been included.

A surface plasmon resonance (SPR) biosensor technology has recently been applied biochemically and clinically to the study of immunologic recognition and the evaluation of binding parameters for various interactions between antibodies (Abs) and antigens (Ags) at liquid-solid interface. The simple interaction between hapten and Ab fragment, e.g., variable single-chain fragment and antigenbinding fragment, can be described sufficiently by a 1:1 stoichiometry in SPR. However, the determination of the binding constant of an anti-protein Ab is usually complicated by the multivalence of the protein Ag. The SPR-based method enables direct determination of binding constants for a variety of specific Ab-Ag interactions in real-time. It also allows estimation of the binding stoichiometry and binding ratio for low-, intermediate-, and high-affinity Ab-Ag interaction systems. The present review is designed to indicate the theoretical background of SPR-based biosensor technology as well as to present the great variety of measurement modes of interaction kinetics that can be performed with these techniques. Quantitative aspects of the Ab-Ag interaction kinetics are reviewed, focusing especially on mono- and multi-valent Ab-Ag interaction modes using a SPR biosensor. Four model binding systems developed recently for use with SPR biosenser are described with principles and examples: (i) one to one interaction mode, (ii) nonequivalent two-site interaction mode, (iii) multiple equivalent-site interaction mode and (iv) multisite interaction mode. This article closes with two descriptions of the determinations of the binding stoichiometry and maximum binding ratio of Ab-Ag interactions.