Recent developments in computational proteomics.

The mapping of the human genome was completed earlier this year and efforts are underway to understand the role of gene products (i.e. proteins) in biological pathways and human disease and to exploit their functional roles to derive protein therapeutics and protein-based drugs. A key component to the next revolution in the 'post-genomic' era will be the increasingly widespread use of protein structure in rational experimental design. Improvements in quality, availability and utility of large-scale 3D and 4D protein structural information are enabling a revolution in rational design, having particular impact on drug discovery and optimization. New computational methodologies now yield modeled structures that are, in many cases, quantitatively comparable with crystal structures, at a fraction of the cost.     

Recent developments in software for the automation of crystallographic macromolecular structure determination

The automation of macromolecular structure determination by X-ray crystallography has long been a goal for many researchers. Recently, there have been improvements in the underlying algorithms, some of which have been implemented in software packages that deal with multiple stages of the structure determination process. These first steps towards complete automation have made X-ray crystallography more efficient.     

NMR for structural proteomics of Thermotoga maritima: Screening and structure determination

This paper describes the NMR screening of 141 small (<15 kDa) recombinant Thermotoga maritima proteins for globular folding. The experimental data shows that approximately 25% of the screened proteins are folded under our screening conditions, which makes this procedure an important step for selecting those proteins that are suitable for structure determination. A comparison of screening based either on 1D 1H NMR with unlabeled proteins or on 2D [1H,15N]-COSY with uniformly 15N-labeled proteins is presented, and a comprehensive analysis of the 1D 1H NMR screening data is described. As an illustration of the utility of these methods to structural proteomics, the NMR structure determination of TM1492 (ribosomal protein L29) is presented. This 66-residue protein consists of a N-terminal 3(10)-helix and two long alpha-helices connected by a tight turn centered about glycine 35, where conserved leucine and isoleucine residues in the two alpha-helices form a small hydrophobic core.     

Recent developments in membrane-protein structural genomics

Recent work has identified the topology of almost all the inner membrane proteins in Escherichia coli, and advances in nuclear magnetic resonance spectroscopy now allow the determination of α-helical membrane protein structures at high resolution. Together these developments will help overcome the current limitations of high-throughput determination of membrane protein structures.     

Recent developments in chloroplast protein transport

Most proteins located in chloroplasts are encoded by nuclear genes, synthesized in the cytoplasm, and transported into the organelle. The study of protein uptake by chloroplasts has greatly expanded over the past few years. The increased activity in this field is due, in part, to the application of recombinant DNA methodology to the analysis of protein translocation. Added interest has also been gained by the realization that the transport mechanisms that mediate protein uptake by chloroplasts, mitochondria and the endoplasmic reticulum display certain characteristics in common. These include amino terminal sequences that target proteins to particular organelles, a transport process that is mechanistically independent from the events of translation, and an ATP-requiring transport step that is thought to involve partial unfolding of the protein to be translocated. In this review we examine recent studies on the binding of precursors to the chloroplast surface, the energy-dependent uptake of proteins into the stroma, and the targeting of proteins to the thylakoid lumen. These aspects of protein transport into chloroplasts are discussed in the context of recent studies on protein uptake by mitochondria.Abbrevlations CAT chloramphenicol acetyl transferase - CCCP carbonylcyanide m-chlorophenylhydrazone - DHFR dihydrofolate reductase - EPSP 5-enol-pyruvylshikimate-3-phosphate - ER endoplasmic reticulum - LHCP light harvesting chlorophyll a/b apoprotein - NPT neomycin phosphotransferase - oATP adenosine-2,3-dialdehyde-5-triphosphate - P-inorganic phosphate Rubisco ribulose-1,5-bisphosphate carboxylase/oxygenase - SSU small subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase - SRP signal recognition particle     

PIER: protein interface recognition for structural proteomics

Recent advances in structural proteomics call for development of fast and reliable automatic methods for prediction of functional surfaces of proteins with known three-dimensional structure, including binding sites for known and unknown protein partners as well as oligomerization interfaces. Despite significant progress the problem is still far from being solved. Most existing methods rely, at least partially, on evolutionary information from multiple sequence alignments projected on protein surface. The common drawback of such methods is their limited applicability to the proteins with a sparse set of sequential homologs, as well as inability to detect interfaces in evolutionary variable regions. In this study, the authors developed an improved method for predicting interfaces from a single protein structure, which is based on local statistical properties of the protein surface derived at the level of atomic groups. The proposed Protein IntErface Recognition (PIER) method achieved the overall precision of 60% at the recall threshold of 50% at the residue level on a diverse benchmark of 490 homodimeric, 62 heterodimeric, and 196 transient interfaces (compared with 25% precision at 50% recall expected from random residue function assignment). For 70% of proteins in the benchmark, the binding patch residues were successfully detected with precision exceeding 50% at 50% recall. The calculation only took seconds for an average 300-residue protein. The authors demonstrated that adding the evolutionary conservation signal only marginally influenced the overall prediction performance on the benchmark; moreover, for certain classes of proteins, using this signal actually resulted in a deteriorated prediction. Thorough benchmarking using other datasets from literature showed that PIER yielded improved performance as compared with several alignment-free or alignment-dependent predictions. The accuracy, efficiency, and dependence on structure alone make PIER a suitable tool for automated high-throughput annotation of protein structures emerging from structural proteomics projects.     

Recent developments and applications of electron transfer dissociation mass spectrometry in proteomics

Electron transfer dissociation (ETD) has been developed recently as an efficient ion fragmentation technique in mass spectrometry (MS), being presently considered a step forward in proteomics with real perspectives for improvement, upgrade and application. Available also on affordable ion trap mass spectrometers, ETD induces specific N–Cα bond cleavages of the peptide backbone with the preservation of the post-translational modifications and generation of product ions that are diagnostic for the modification site(s). In addition, in the last few years ETD contributed significantly to the development of top-down approaches which enable tandem MS of intact protein ions. The present review, covering the last 5 years highlights concisely the major achievements and the current applications of ETD fragmentation technique in proteomics. An ample part of the review is dedicated to ETD contribution in the elucidation of the most common posttranslational modifications, such as phosphorylation and glycosylation. Further, a brief section is devoted to top-down by ETD method applied to intact proteins. As the last few years have witnessed a major expansion of the microfluidics systems, a few considerations on ETD in combination with chip-based nanoelectrospray (nanoESI) as a platform for high throughput top-down proteomics are also presented.     

Recent developments in the analysis of protein complexes

Recent shotgun sequencing of filtered Sargasso Sea water samples has yielded data in astounding amount and diversity. Iron–sulfur proteins, which are ancient, diverse and ubiquitous, have been implemented here to further probe the sequence diversity of the Sargasso Sea database (SSDB). Sequence searches and comparisons confirm that the SSDB by and large equals in diversity the combined currently available databases. The data thus suggest that microbial diversity has so far been underestimated by orders of magnitude.     

Target selection of soluble protein complexes for structural proteomics studies

Background  

Protein expression in E. coli is the most commonly used system to produce protein for structural studies, because it is fast and inexpensive and can produce large quantity of proteins. However, when proteins from other species such as mammalian are produced in this system, problems of protein expression and solubility arise [1]. Structural genomics project are currently investigating proteomics pipelines that would produce sufficient quantities of recombinant proteins for structural studies of protein complexes. To investigate how the E. coli protein expression system could be used for this purpose, we purified apoptotic binary protein complexes formed between members of the Caspase Associated Recruitment Domain (CARD) family.     

Automated search of natively folded protein fragments for high-throughput structure determination in structural genomics

Structural genomic projects envision almost routine protein structure determinations, which are currently imaginable only for small proteins with molecular weights below 25,000 Da. For larger proteins, structural insight can be obtained by breaking them into small segments of amino acid sequences that can fold into native structures, even when isolated from the rest of the protein. Such segments are autonomously folding units (AFU) and have sizes suitable for fast structural analyses. Here, we propose to expand an intuitive procedure often employed for identifying biologically important domains to an automatic method for detecting putative folded protein fragments. The procedure is based on the recognition that large proteins can be regarded as a combination of independent domains conserved among diverse organisms. We thus have developed a program that reorganizes the output of BLAST searches and detects regions with a large number of similar sequences. To automate the detection process, it is reduced to a simple geometrical problem of recognizing rectangular shaped elevations in a graph that plots the number of similar sequences at each residue of a query sequence. We used our program to quantitatively corroborate the premise that segments with conserved sequences correspond to domains that fold into native structures. We applied our program to a test data set composed of 99 amino acid sequences containing 150 segments with structures listed in the Protein Data Bank, and thus known to fold into native structures. Overall, the fragments identified by our program have an almost 50% probability of forming a native structure, and comparable results are observed with sequences containing domain linkers classified in SCOP. Furthermore, we verified that our program identifies AFU in libraries from various organisms, and we found a significant number of AFU candidates for structural analysis, covering an estimated 5 to 20% of the genomic databases. Altogether, these results argue that methods based on sequence similarity can be useful for dissecting large proteins into small autonomously folding domains, and such methods may provide an efficient support to structural genomics projects.     

Utilization of protein intrinsic disorder knowledge in structural proteomics

Intrinsically disordered proteins (IDPs) and proteins with long disordered regions are highly abundant in various proteomes. Despite their lack of well-defined ordered structure, these proteins and regions are frequently involved in crucial biological processes. Although in recent years these proteins have attracted the attention of many researchers, IDPs represent a significant challenge for structural characterization since these proteins can impact many of the processes in the structure determination pipeline. Here we investigate the effects of IDPs on the structure determination process and the utility of disorder prediction in selecting and improving proteins for structural characterization. Examination of the extent of intrinsic disorder in existing crystal structures found that relatively few protein crystal structures contain extensive regions of intrinsic disorder. Although intrinsic disorder is not the only cause of crystallization failures and many structured proteins cannot be crystallized, filtering out highly disordered proteins from structure-determination target lists is still likely to be cost effective. Therefore it is desirable to avoid highly disordered proteins from structure-determination target lists and we show that disorder prediction can be applied effectively to enrich structure determination pipelines with proteins more likely to yield crystal structures. For structural investigation of specific proteins, disorder prediction can be used to improve targets for structure determination. Finally, a framework for considering intrinsic disorder in the structure determination pipeline is proposed.