MeDor: a metaserver for predicting protein disorder

Detecting remote sequence homology in disordered proteins: discovery of conserved motifs in the N-termini of Mononegavirales phosphoproteins

Paramyxovirinae are a large group of viruses that includes measles virus and parainfluenza viruses. The viral Phosphoprotein (P) plays a central role in viral replication. It is composed of a highly variable, disordered N-terminus and a conserved C-terminus. A second viral protein alternatively expressed, the V protein, also contains the N-terminus of P, fused to a zinc finger. We suspected that, despite their high variability, the N-termini of P/V might all be homologous; however, using standard approaches, we could previously identify sequence conservation only in some Paramyxovirinae. We now compared the N-termini using sensitive sequence similarity search programs, able to detect residual similarities unnoticeable by conventional approaches. We discovered that all Paramyxovirinae share a short sequence motif in their first 40 amino acids, which we called soyuz1. Despite its short length (11-16aa), several arguments allow us to conclude that soyuz1 probably evolved by homologous descent, unlike linear motifs. Conservation across such evolutionary distances suggests that soyuz1 plays a crucial role and experimental data suggest that it binds the viral nucleoprotein to prevent its illegitimate self-assembly. In some Paramyxovirinae, the N-terminus of P/V contains a second motif, soyuz2, which might play a role in blocking interferon signaling. Finally, we discovered that the P of related Mononegavirales contain similarly overlooked motifs in their N-termini, and that their C-termini share a previously unnoticed structural similarity suggesting a common origin. Our results suggest several testable hypotheses regarding the replication of Mononegavirales and suggest that disordered regions with little overall sequence similarity, common in viral and eukaryotic proteins, might contain currently overlooked motifs (intermediate in length between linear motifs and disordered domains) that could be detected simply by comparing orthologous proteins.

Inherent structural disorder and dimerisation of murine norovirus NS1-2 protein

Human noroviruses are highly infectious viruses that cause the majority of acute, non-bacterial epidemic gastroenteritis cases worldwide. The first open reading frame of the norovirus RNA genome encodes for a polyprotein that is cleaved by the viral protease into six non-structural proteins. The first non-structural protein, NS1-2, lacks any significant sequence similarity to other viral or cellular proteins and limited information is available about the function and biophysical characteristics of this protein. Bioinformatic analyses identified an inherently disordered region (residues 1–142) in the highly divergent N-terminal region of the norovirus NS1-2 protein. Expression and purification of the NS1-2 protein of Murine norovirus confirmed these predictions by identifying several features typical of an inherently disordered protein. These were a biased amino acid composition with enrichment in the disorder promoting residues serine and proline, a lack of predicted secondary structure, a hydrophilic nature, an aberrant electrophoretic migration, an increased Stokes radius similar to that predicted for a protein from the pre-molten globule family, a high sensitivity to thermolysin proteolysis and a circular dichroism spectrum typical of an inherently disordered protein. The purification of the NS1-2 protein also identified the presence of an NS1-2 dimer in Escherichia coli and transfected HEK293T cells. Inherent disorder provides significant advantages including structural flexibility and the ability to bind to numerous targets allowing a single protein to have multiple functions. These advantages combined with the potential functional advantages of multimerisation suggest a multi-functional role for the NS1-2 protein.

Independent structural domains in paramyxovirus polymerase protein

All enzymatic activities required for genomic replication and transcription of nonsegmented negative strand RNA viruses (or Mononegavirales) are believed to be concentrated in the viral polymerase (L) protein. However, our insight into the organization of these different enzymatic activities into a bioactive tertiary structure remains rudimentary. Fragments of Mononegavirales polymerases analyzed to date cannot restore bioactivity through trans-complementation, unlike the related L proteins of segmented NSVs. We investigated the domain organization of phylogenetically diverse Paramyxovirus L proteins derived from measles virus (MeV), Nipah virus (NiV), and respiratory syncytial virus (RSV). Through a comprehensive in silico and experimental analysis of domain intersections, we defined MeV L position 615 as an interdomain candidate in addition to the previously reported residue 1708. Only position 1708 of MeV and the homologous positions in NiV and RSV L also tolerated the insertion of epitope tags. Splitting of MeV L at residue 1708 created fragments that were unable to physically interact and trans-complement, but strikingly, these activities were reconstituted by the addition of dimerization tags to the fragments. Equivalently split fragments of NiV, RSV, and MeV L oligomerized with comparable efficiency in all homo- and heterotypic combinations, but only the homotypic pairs were able to trans-complement. These results demonstrate that synthesis as a single polypeptide is not required for the Mononegavirales polymerases to adopt a proper tertiary conformation. Paramyxovirus polymerases are composed of at least two truly independent folding domains that lack a traditional interface but require molecular compatibility for bioactivity. The functional probing of the L domain architecture through trans-complementation is anticipated to be applicable to all Mononegavirales polymerases.

Meta-structure correlation in protein space unveils different selection rules for folded and intrinsically disordered proteins

The number of existing protein sequences spans a very small fraction of sequence space. Natural proteins have overcome a strong negative selective pressure to avoid the formation of insoluble aggregates. Stably folded globular proteins and intrinsically disordered proteins (IDPs) use alternative solutions to the aggregation problem. While in globular proteins folding minimizes the access to aggregation prone regions, IDPs on average display large exposed contact areas. Here, we introduce the concept of average meta-structure correlation maps to analyze sequence space. Using this novel conceptual view we show that representative ensembles of folded and ID proteins show distinct characteristics and respond differently to sequence randomization. By studying the way evolutionary constraints act on IDPs to disable a negative function (aggregation) we might gain insight into the mechanisms by which function-enabling information is encoded in IDPs.

Uncertainty analysis in protein disorder prediction

A grand challenge in the proteomics and structural genomics era is the prediction of protein structure, including identification of those proteins that are partially or wholly unstructured. A number of predictors for identification of intrinsically disordered proteins (IDPs) have been developed over the last decade, but none can be taken as a fully reliable on its own. Using a single model for prediction is typically inadequate because prediction based on only the most accurate model ignores model uncertainty. In this paper, we present an empirical method to specify and measure uncertainty associated with disorder predictions. In particular, we analyze the uncertainty in the reference model itself and the uncertainty in data. This is achieved by training a set of models and developing several meta predictors on top of them. The best meta predictor achieved comparable or better results than any other single model, suggesting that incorporating different aspects of protein disorder prediction is important for the disorder prediction task. In addition, the best meta-predictor had more balanced sensitivity and specificity than any individual model. We also assessed the effects of changes in disorder prediction as a function of changes in the protein sequence. For collections of homologous sequences, we found that mutations caused many of the predicted disordered residues to be flipped to be predicted as ordered residues, while the reverse was observed much less frequently. These results suggest that disorder tendencies are more sensitive to allowed mutations than structure tendencies and the conservation of disorder is indeed less stable than conservation of structure.

AVAILABILITY

five meta-predictors and four single models developed for this study will be publicly freely accessible for non-commercial use.

Dividing to unveil protein microheterogeneities: traveling wave ion mobility study

Overexpression of a protein in a foreign host is often the only route toward an exhaustive characterization, especially when purification from the natural source(s) is hardly achievable. The key issue in these studies relies on quality control of the purified recombinant protein to precisely determining its identity as well as any undesirable microheterogeneities. While standard proteomics approaches preclude unbiased search for modifications, the optional technique of top-down tandem mass spectrometry (MSMS) requires the use of highly accurate and highly resolved experiments to reveal subtle sequence modifications. In the present study, the top-down MSMS approach combined with traveling wave ion mobility (TWIM) separation was evaluated for its ability to achieve high sequence coverage and to reveal subtle microheterogeneities that were hitherto only accessible with Fourier-transform ion cyclotron resonance-MS instruments. The power of this approach is herein illustrated in an in-depth analysis of both the wild type and K496C variant of the recombinant X domain (XD; aa's 459-507) of the measles virus phosphoprotein expressed in Escherichia coli . Using top-down MSMS combined with TWIM, we show that XD samples occasionally exhibit a microheterogeneity that could not be anticipated from the nucleotide sequence of the encoding constructs and that likely reflects a genetic drift, neutral or not, occurring during expression. In addition, a 1-oxyl-2,2,5,5-tetramethyl-δ3-pyrroline-3-methyl methanethiosulfonate nitroxide probe that was grafted onto the K496C XD variant was shown to undergo oxidation and/or protonation in the electrospray ionization source, leading to artifactual mass increases.

Expanding the proteome: disordered and alternatively folded proteins

Proteins provide much of the scaffolding for life, as well as undertaking a variety of essential catalytic reactions. These characteristic functions have led us to presuppose that proteins are in general functional only when well structured and correctly folded. As we begin to explore the repertoire of possible protein sequences inherent in the human and other genomes, two stark facts that belie this supposition become clear: firstly, the number of apparent open reading frames in the human genome is significantly smaller than appears to be necessary to code for all of the diverse proteins in higher organisms, and secondly that a significant proportion of the protein sequences that would be coded by the genome would not be expected to form stable three-dimensional (3D) structures. Clearly the genome must include coding for a multitude of alternative forms of proteins, some of which may be partly or fully disordered or incompletely structured in their functional states. At the same time as this likelihood was recognized, experimental studies also began to uncover examples of important protein molecules and domains that were incompletely structured or completely disordered in solution, yet remained perfectly functional. In the ensuing years, we have seen an explosion of experimental and genome-annotation studies that have mapped the extent of the intrinsic disorder phenomenon and explored the possible biological rationales for its widespread occurrence. Answers to the question 'why would a particular domain need to be unstructured?' are as varied as the systems where such domains are found. This review provides a survey of recent new directions in this field, and includes an evaluation of the role not only of intrinsically disordered proteins but also of partially structured and highly dynamic members of the disorder-order continuum.

In-silico prediction of disorder content using hybrid sequence representation

Background

Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge of the content of the intrinsic disorder in proteins is useful for a variety of studies including estimation of the abundance of disorder in protein families, classes, and complete proteomes, and for the analysis of disorder-related protein functions. The above investigations currently utilize the disorder content derived from the per-residue disorder predictions. We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based prediction of the disorder content.

Results

We hypothesize that sequence-level aggregation of input information may provide more accurate content prediction when compared with the content extracted from the local window-based residue-level disorder predictors. We propose a novel predictor, DisCon, that takes advantage of a small set of 29 custom-designed descriptors that aggregate and hybridize information concerning sequence, evolutionary profiles, and predicted secondary structure, solvent accessibility, flexibility, and annotation of globular domains. Using these descriptors and a ridge regression model, DisCon predicts the content with low, 0.05, mean squared error and high, 0.68, Pearson correlation. This is a statistically significant improvement over the content computed from outputs of ten modern disorder predictors on a test dataset with proteins that share low sequence identity with the training sequences. The proposed predictive model is analyzed to discuss factors related to the prediction of the disorder content.

Conclusions

DisCon is a high-quality alternative for high-throughput annotation of the disorder content. We also empirically demonstrate that the DisCon's predictions can be used to improve binary annotations of the disordered residues from the real-value disorder propensities generated by current residue-level disorder predictors. The web server that implements the DisCon is available at http://biomine.ece.ualberta.ca/DisCon/.

Mining the TRAF6/p62 interactome for a selective ubiquitination motif

A new approach is described here to predict ubiquitinated substrates of the E3 ubiquitin ligase, TRAF6, which takes into account its interaction with the scaffold protein SQSTM1/p62. A novel TRAF6 ubiquitination motif defined as [–(hydrophobic)–k–(hydrophobic)–x–x–(hydrophobic)– (polar)–(hydrophobic)–(polar)–(hydrophobic)] was identified and used to screen the TRAF6/p62 interactome composed of 155 proteins, that were either TRAF6 or p62 interactors, or a negative dataset, composed of 54 proteins with no known association to either TRAF6 or p62. NRIF (K19), TrkA (K485), TrkB (K811), TrkC (K602 and K815), NTRK2 (K828), NTRK3 (K829) and MBP (K169) were found to possess a perfect match for the amino acid consensus motif for TRAF6/p62 ubiquitination. Subsequent analyses revealed that this motif was biased to the C-terminal regions of the protein (nearly 50% the sites), and had preference for loops (~50%) and helices (~37%) over beta-strands (15% or less). In addition, the motif was observed to be in regions that were highly solvent accessible (nearly 90%). Our findings suggest that specific Lysines may be selected for ubiquitination based upon an embedded code defined by a specific amino acid motif with structural determinants. Collectively, our results reveal an unappreciated role for the scaffold protein in targeting ubiquitination. The findings described herein could be used to aid in identification of other E3/scaffold ubiquitination sites.

Proteins without 3D structure: definition, detection and beyond

MOTIVATION

Predictions, and experiments to a lesser extent, following the decoding of the human genome showed that a significant fraction of gene products do not have well-defined 3D structures. While the presence of structured domains traditionally suggested function, it was not clear what the absence of structure implied. These and many other findings initiated the extensive theoretical and experimental research into these types of proteins, commonly known as intrinsically disordered proteins (IDPs). Crucial to understanding IDPs is the evaluation of structural predictors based on different principles and trained on various datasets, which is currently the subject of active research. The view is emerging that structural disorder can be considered as a separate structural category and not simply as absence of secondary and/or tertiary structure. IDPs perform essential functions and their improper functioning is responsible for human diseases such as neurodegenerative disorders.

Picobirnaviruses encode a protein with repeats of the ExxRxNxxxE motif

Picobirnaviruses possess a bisegmented double-stranded RNA genome. While the segment 2 encodes the RNA-dependent RNA polymerase, the segment 1 displays two open reading frames (ORFs). ORF2 was recently shown to code the capsid precursor and ORF1 product has not been characterized. In this study, we show that the three ORF1 sequences available in databases and representing three phylogenetically distant picobirnaviruses (two from human and one from rabbit hosts) encode proteins of various sizes (106-224 residues and without proline and cysteine) harbouring a particular sequence motif (ExxRxNxxxE) repeated four to ten times, depending on the virus species. Several algorithms predicted the three proteins to be mainly unfolded in the domains containing the repeats. The glycine-rich 25-40 amino acid long C-terminal domains containing hydrophobic residues with a periodicity of 3-4 residues are predicted structurally different of the upstream domains containing the motif repetitions. The ExxRxNxxxE sequence was not previously identified as a short linear motif in eukaryotic and prokaryotic proteins. Its function remains elusive.

Virus-host protein interactions in RNA viruses

RNA viruses exhibit small-sized genomes that only encode a limited number of viral proteins, but still establish complex networks of interactions with host cell components. Here we summarize recent reports that aim at understanding general features of RNA virus infection networks at the protein level.

Practical application of bioinformatics by the multidisciplinary VIZIER consortium

This review focuses on bioinformatics technologies employed by the EU-sponsored multidisciplinary VIZIER consortium (Comparative Structural Genomics of Viral Enzymes Involved in Replication, FP6 PROJECT: 2004-511960, active from 1 November 2004 to 30 April 2009), to achieve its goals. From the management of the information flow of the project, to bioinformatics-mediated selection of RNA viruses and prediction of protein targets, to the analysis of 3D protein structures and antiviral compounds, these technologies provided a communication framework and integrated solutions for steady and timely advancement of the project. RNA viruses form a large class of major pathogens that affect humans and domestic animals. Such RNA viruses as HIV, Influenza virus and Hepatitis C virus are of prime medical concern today, but the identities of viruses that will threaten human population tomorrow are far from certain. To contain outbreaks of common or newly emerging infections, prototype drugs against viruses representing the Virus Universe must be developed. This concept was championed by the VIZIER project which brought together experts in diverse fields to produce a concerted and sustained effort for identifying and validating targets for antivirus therapy in dozens of RNA virus lineages.

Structural disorder within Henipavirus nucleoprotein and phosphoprotein: from predictions to experimental assessment

Henipaviruses are newly emerged viruses within the Paramyxoviridae family. Their negative-strand RNA genome is packaged by the nucleoprotein (N) within alpha-helical nucleocapsid that recruits the polymerase complex made of the L protein and the phosphoprotein (P). To date structural data on Henipaviruses are scarce, and their N and P proteins have never been characterized so far. Using both computational and experimental approaches we herein show that Henipaviruses N and P proteins possess large intrinsically disordered regions. By combining several disorder prediction methods, we show that the N-terminal domain of P (PNT) and the C-terminal domain of N (NTAIL) are both mostly disordered, although they contain short order-prone segments. We then report the cloning, the bacterial expression, purification and characterization of Henipavirus PNT and NTAIL domains. By combining gel filtration, dynamic light scattering, circular dichroism and nuclear magnetic resonance, we show that both NTAIL and PNT belong to the premolten globule sub-family within the class of intrinsically disordered proteins. This study is the first reported experimental characterization of Henipavirus P and N proteins. The evidence that their respective N-terminal and C-terminal domains are highly disordered under native conditions is expected to be invaluable for future structural studies by helping to delineate N and P protein domains amenable to crystallization. In addition, following previous hints establishing a relationship between structural disorder and protein interactivity, the present results suggest that Henipavirus PNT and NTAIL domains could be involved in manifold protein-protein interactions.

Understanding protein non-folding

This review describes the family of intrinsically disordered proteins, members of which fail to form rigid 3-D structures under physiological conditions, either along their entire lengths or only in localized regions. Instead, these intriguing proteins/regions exist as dynamic ensembles within which atom positions and backbone Ramachandran angles exhibit extreme temporal fluctuations without specific equilibrium values. Many of these intrinsically disordered proteins are known to carry out important biological functions which, in fact, depend on the absence of a specific 3-D structure. The existence of such proteins does not fit the prevailing structure-function paradigm, which states that a unique 3-D structure is a prerequisite to function. Thus, the protein structure-function paradigm has to be expanded to include intrinsically disordered proteins and alternative relationships among protein sequence, structure, and function. This shift in the paradigm represents a major breakthrough for biochemistry, biophysics and molecular biology, as it opens new levels of understanding with regard to the complex life of proteins. This review will try to answer the following questions: how were intrinsically disordered proteins discovered? Why don't these proteins fold? What is so special about intrinsic disorder? What are the functional advantages of disordered proteins/regions? What is the functional repertoire of these proteins? What are the relationships between intrinsically disordered proteins and human diseases?

Predictors of natively unfolded proteins: unanimous consensus score to detect a twilight zone between order and disorder in generic datasets

BACKGROUND

Natively unfolded proteins lack a well defined three dimensional structure but have important biological functions, suggesting a re-assignment of the structure-function paradigm. To assess that a given protein is natively unfolded requires laborious experimental investigations, then reliable sequence-only methods for predicting whether a sequence corresponds to a folded or to an unfolded protein are of interest in fundamental and applicative studies. Many proteins have amino acidic compositions compatible both with the folded and unfolded status, and belong to a twilight zone between order and disorder. This makes difficult a dichotomic classification of protein sequences into folded and natively unfolded ones. In this work we propose an operational method to identify proteins belonging to the twilight zone by combining into a consensus score good performing single predictors of folding.

RESULTS

In this methodological paper dichotomic folding indexes are considered: hydrophobicity-charge, mean packing, mean pairwise energy, Poodle-W and a new global index, that is called here gVSL2, based on the local disorder predictor VSL2. The performance of these indexes is evaluated on different datasets, in particular on a new dataset composed by 2369 folded and 81 natively unfolded proteins. Poodle-W, gVSL2 and mean pairwise energy have good performance and stability in all the datasets considered and are combined into a strictly unanimous combination score SSU, that leaves proteins unclassified when the consensus of all combined indexes is not reached. The unclassified proteins: i) belong to an overlap region in the vector space of amino acidic compositions occupied by both folded and unfolded proteins; ii) are composed by approximately the same number of order-promoting and disorder-promoting amino acids; iii) have a mean flexibility intermediate between that of folded and that of unfolded proteins.

CONCLUSIONS

Our results show that proteins unclassified by SSU belong to a twilight zone. Proteins left unclassified by the consensus score SSU have physical properties intermediate between those of folded and those of natively unfolded proteins and their structural properties and evolutionary history are worth to be investigated.

Parameterization of disorder predictors for large-scale applications requiring high specificity by using an extended benchmark dataset

BACKGROUND

Algorithms designed to predict protein disorder play an important role in structural and functional genomics, as disordered regions have been reported to participate in important cellular processes. Consequently, several methods with different underlying principles for disorder prediction have been independently developed by various groups. For assessing their usability in automated workflows, we are interested in identifying parameter settings and threshold selections, under which the performance of these predictors becomes directly comparable.

RESULTS

First, we derived a new benchmark set that accounts for different flavours of disorder complemented with a similar amount of order annotation derived for the same protein set. We show that, using the recommended default parameters, the programs tested are producing a wide range of predictions at different levels of specificity and sensitivity. We identify settings, in which the different predictors have the same false positive rate. We assess conditions when sets of predictors can be run together to derive consensus or complementary predictions. This is useful in the framework of proteome-wide applications where high specificity is required such as in our in-house sequence analysis pipeline and the ANNIE webserver.

CONCLUSIONS

This work identifies parameter settings and thresholds for a selection of disorder predictors to produce comparable results at a desired level of specificity over a newly derived benchmark dataset that accounts equally for ordered and disordered regions of different lengths.

Oligomeric structure of brain abundant proteins GAP-43 and BASP1

Brain abundant proteins GAP-43 and BASP1 participate in the regulation of actin cytoskeleton dynamics in neuronal axon terminals. The proposed mechanism suggests that the proteins sequester phosphatidylinositol-4,5-diphosphate (PIP(2)) in the inner leaflet of the plasma membrane. We found that model anionic phospholipid membranes in the form of liposomes induce rapid oligomerization of GAP-43 and BASP1 proteins. Multiply charged phosphoinositides produced the most potent effect. Anionic detergent sodium dodecyl sulfate (SDS) at submicellar concentration stimulated formation of similar oligomers in solution. BASP1, but not GAP-43, also formed oligomers at sufficiently high concentration in the absence of lipids and SDS. Electron microscopy study demonstrated that the oligomers have disk-shaped or annular structure of 10-30nm in diameter. BASP1 also formed higher aggregates of linear rod-like structure, with average length of about 100nm. In outward appearance, the oligomers and linear aggregates are reminiscent of oligomers and protofibrils of amyloid proteins. Both the synthetic N-terminal peptide GAP-43(1-40) and the brain-derived fragment GAP-43-3 preserved the ability to oligomerize under the action of acidic phospholipids and SDS. On the contrary, BASP1 fragment truncated by the short N-terminal myristoylated peptide was unable to form oligomers. GAP-43 and BASP1 oligomerization can be regulated by calmodulin, which disrupts the oligomers and displaces the proteins from the membrane. We suggest that in vivo, the role of membrane-bound GAP-43 and BASP1 oligomers consists in accumulation of PIP(2) in functional clusters, which become accessible for other PIP(2)-binding proteins after dissociation of the oligomers.

Computational resources for the prediction and analysis of native disorder in proteins

Proteomics attempts to characterise the gene products expressed in a cell or tissue via a range of biophysical techniques including crystallography and NMR and, more relevantly to this volume, chromatography and mass spectrometry. It is becoming increasingly clear that the native states of segments of many of the cellular proteins are not stable, folded structures, and much of the proteome is in an unfolded, disordered state. These proteins and their disordered segments have functionally interesting properties and provide novel challenges for the biophysical techniques that are used to study them. This chapter focuses on computational approaches to predicting such regions and analyzing the functions linked to them, and has implications for protein scientists who wish to study such properties as molecular recognition and post-translational modifications. We also discuss resources where the results of predictions have been collated, making them publicly available to the wider biological community.

Conformational disorder

In recent years it was shown that a large number of proteins are either fully or partially disordered. Intrinsically disordered proteins are ubiquitary proteins that fulfill essential biological functions while lacking a stable 3D structure. Despite the large abundance of disorder, disordered regions are still poorly detected. The identification of disordered regions facilitates the functional annotation of proteins and is instrumental in delineating boundaries of protein domains amenable to crystallization. This chapter focuses on the methods currently employed for predicting disorder and identifying regions involved in induced folding.

Rules governing selective protein carbonylation

Background

Carbonyl derivatives are mainly formed by direct metal-catalysed oxidation (MCO) attacks on the amino-acid side chains of proline, arginine, lysine and threonine residues. For reasons unknown, only some proteins are prone to carbonylation.

Methodology/Principal Findings

We used mass spectrometry analysis to identify carbonylated sites in: BSA that had undergone in vitro MCO, and 23 carbonylated proteins in Escherichia coli. The presence of a carbonylated site rendered the neighbouring carbonylatable site more prone to carbonylation. Most carbonylated sites were present within hot spots of carbonylation. These observations led us to suggest rules for identifying sites more prone to carbonylation. We used these rules to design an in silico model (available at http://www.lcb.cnrs-mrs.fr/CSPD/), allowing an effective and accurate prediction of sites and of proteins more prone to carbonylation in the E. coli proteome.

Conclusions/Significance

We observed that proteins evolve to either selectively maintain or lose predicted hot spots of carbonylation depending on their biological function. As our predictive model also allows efficient detection of carbonylated proteins in Bacillus subtilis, we believe that our model may be extended to direct MCO attacks in all organisms.

Modular organization of rabies virus phosphoprotein

A phosphoprotein (P) is found in all viruses of the Mononegavirales order. These proteins form homo-oligomers, fulfil similar roles in the replication cycles of the various viruses, but differ in their length and oligomerization state. Sequence alignments reveal no sequence similarity among proteins from viruses belonging to the same family. Sequence analysis and experimental data show that phosphoproteins from viruses of the Paramyxoviridae contain structured domains alternating with intrinsically disordered regions. Here, we used predictions of disorder of secondary structure, and an analysis of sequence conservation to predict the domain organization of the phosphoprotein from Sendai virus, vesicular stomatitis virus (VSV) and rabies virus (RV P). We devised a new procedure for combining the results from multiple prediction methods and locating the boundaries between disordered regions and structured domains. To validate the proposed modular organization predicted for RV P and to confirm that the putative structured domains correspond to autonomous folding units, we used two-hybrid and biochemical approaches to characterize the properties of several fragments of RV P. We found that both central and C-terminal domains can fold in isolation, that the central domain is the oligomerization domain, and that the C-terminal domain binds to nucleocapsids. Our results suggest a conserved organization of P proteins in the Rhabdoviridae family in concatenated functional domains resembling that of the P proteins in the Paramyxoviridae family.

Nucleocapsid structure and function

Measles virus belongs to the Paramyxoviridae family within the Mononegavirales order. Its nonsegmented, single-stranded, negative-sense RNA genome is encapsidated by the nucleoprotein (N) to form a helical nucleocapsid. This ribonucleoproteic complex is the substrate for both transcription and replication. The RNA-dependent RNA polymerase binds to the nucleocapsid template via its co-factor, the phosphoprotein (P). This chapter describes the main structural information available on the nucleoprotein, showing that it consists of a structured core (N(CORE)) and an intrinsically disordered C-terminal domain (N(TAIL)). We propose a model where the dynamic breaking and reforming of the interaction between N(TAIL) and P would allow the polymerase complex (L-P) to cartwheel on the nucleocapsid template. We also propose a model where the flexibility of the disordered N and P domains allows the formation of a tripartite complex (No-P-L) during replication, followed by the delivery of N monomers to the newly synthesized genomic RNA chain. Finally, the functional implications of structural disorder are also discussed in light of the ability of disordered regions to establish interactions with multiple partners, thus leading to multiple biological effects.

Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are synergistic components of translational medicine and personalized healthcare research

Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures given by: Dr. A. Keith Dunker (Indiana), Dr. Jun Liu (Harvard), Dr. Brian Athey (Michigan), Dr. Mark Borodovsky (Georgia Tech and President of ISIBM), Dr. Hamid Arabnia (Georgia and Vice-President of ISIBM), Dr. Ruzena Bajcsy (Berkeley and Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Chih-Ming Ho (UCLA and Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Andy Baxevanis (United States National Institutes of Health), Dr. Arif Ghafoor (Purdue), Dr. John Quackenbush (Harvard), Dr. Eric Jakobsson (UIUC), Dr. Vladimir Uversky (Indiana), Dr. Laura Elnitski (United States National Institutes of Health) and other world-class scientific leaders. The Harvard meeting was a large academic event 100% full-sponsored by IEEE financially and academically. After a rigorous peer-review process, the committee selected 27 high-quality research papers from 600 submissions. The committee is grateful for contributions from keynote speakers Dr. Russ Altman (IEEE BIBM conference keynote lecturer on combining simulation and machine learning to recognize function in 4D), Dr. Mary Qu Yang (IEEE BIBM workshop keynote lecturer on new initiatives of detecting microscopic disease using machine learning and molecular biology, http://ieeexplore.ieee.org/servlet/opac?punumber=4425386) and Dr. Jack Y. Yang (IEEE BIBM workshop keynote lecturer on data mining and knowledge discovery in translational medicine) from the first IEEE Computer Society BioInformatics and BioMedicine (IEEE BIBM) international conference and workshops, November 2-4, 2007, Silicon Valley, California, USA.