CiteULike: zwang's library [532 articles]

A protocol for constructing gene targeting vectors: generating knockout mice for the cadherin family and beyond

Sen Wu — 2008-07-04T02:34:58-00:00

Nat. Protocols, Vol. 3, No. 6. (May 2008), pp. 1056-1076.

Footprinting protein-DNA complexes using the hydroxyl radical

Swapan Jain — 2008-07-04T02:32:59-00:00

Nat. Protocols, Vol. 3, No. 6. (June 2008), pp. 1092-1100.

Protein networks in disease

Trey Ideker — 2008-04-01T18:31:26-00:00

Genome Res., Vol. 18, No. 4. (1 April 2008), pp. 644-652.

During a decade of proof-of-principle analysis in model organisms, protein networks have been used to further the study of molecular evolution, to gain insight into the robustness of cells to perturbation, and for assignment of new protein functions. Following these analyses, and with the recent rise of protein interaction measurements in mammals, protein networks are increasingly serving as tools to unravel the molecular basis of disease. We review promising applications of protein networks to disease in four major areas: identifying new disease genes; the study of their network properties; identifying disease-related subnetworks; and network-based disease classification. Applications in infectious disease, personalized medicine, and pharmacology are also forthcoming as the available protein network information improves in quality and coverage. 10.1101/gr.071852.107

A generative, probabilistic model of local protein structure

Wouter Boomsma — 2008-07-02T08:23:30-00:00

Proceedings of the National Academy of Sciences, Vol. 105, No. 26. (1 July 2008), pp. 8932-8937.

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state. Our method represents a significant theoretical and practical improvement over the widely used fragment assembly technique by avoiding the drawbacks associated with a discrete and nonprobabilistic approach. 10.1073/pnas.0801715105

Evolutionary plasticity of genetic interaction networks

Julia Tischler — 2008-03-27T15:08:54-00:00

Nat Genet, Vol. 40, No. 4. (April 2008), pp. 390-391.

Data and Theory Point to Mainly Additive Genetic Variance for Complex Traits

William Hill — 2008-07-01T10:00:17-00:00

PLoS Genet, Vol. 4, No. 2. (29 February 2008), e1000008.

The relative proportion of additive and non-additive variation for complex traits is important in evolutionary biology, medicine, and agriculture. We address a long-standing controversy and paradox about the contribution of non-additive genetic variation, namely that knowledge about biological pathways and gene networks imply that epistasis is important. Yet empirical data across a range of traits and species imply that most genetic variance is additive. We evaluate the evidence from empirical studies of genetic variance components and find that additive variance typically accounts for over half, and often close to 100%, of the total genetic variance. We present new theoretical results, based upon the distribution of allele frequencies under neutral and other population genetic models, that show why this is the case even if there are non-additive effects at the level of gene action. We conclude that interactions at the level of genes are not likely to generate much interaction at the level of variance.

Using multiple templates to improve quality of homology models in automated homology modeling

Per Larsson — 2008-07-01T07:50:15-00:00

Protein Sci, Vol. 17, No. 6. (1 June 2008), pp. 990-1002.

When researchers build high-quality models of protein structure from sequence homology, it is today common to use several alternative target-template alignments. Several methods can, at least in theory, utilize information from multiple templates, and many examples of improved model quality have been reported. However, to our knowledge, thus far no study has shown that automatic inclusion of multiple alignments is guaranteed to improve models without artifacts. Here, we have carried out a systematic investigation of the potential of multiple templates to improving homology model quality. We have used test sets consisting of targets from both recent CASP experiments and a larger reference set. In addition to Modeller and Nest, a new method (Pfrag) for multiple template-based modeling is used, based on the segment-matching algorithm from Levitt's SegMod program. Our results show that all programs can produce multi-template models better than any of the single-template models, but a large part of the improvement is simply due to extension of the models. Most of the remaining improved cases were produced by Modeller. The most important factor is the existence of high-quality single-sequence input alignments. Because of the existence of models that are worse than any of the top single-template models, the average model quality does not improve significantly. However, by ranking models with a model quality assessment program such as ProQ, the average quality is improved by [~]5% in the CASP7 test set. 10.1110/ps.073344908

Kinetic barriers and the role of topology in Protein and RNA folding.

Tobin Sosnick — 2008-07-01T07:50:31-00:00

Protein Sci (23 May 2008), ps.036319.108.

This review compares the folding behavior of proteins and RNAs. Topics covered include the role of topology in the determination of folding rates, major folding events including collapse, properties of denatured states, pathway heterogeneity, and the influence of the mode of initiation on the folding pathway. 10.1110/ps.036319.108

Plasmid-chromosome shuffling for non-deletion alleles in yeast

Zhiwei Huang — 2008-01-31T11:58:19-00:00

Nature Methods, Vol. 5, No. 2. (13 January 2008), pp. 167-169.

Predicting protein function from domain content

Kristoffer Forslund — 2008-07-01T00:57:43-00:00

Bioinformatics (30 June 2008), btn312.

Motivation: Computational assignment of protein function may be the single most vital application of bioinformatics in the post-genome era. These assignments are made based on various protein features, where one is the presence of identifiable domains. The relationship between protein domain content and function is important to investigate to understand how domain combinations encode complex functions. Results: Two different models are presented for how protein domain combinations yield specific functions: one rule-based and one probabilistic. We demonstrate how these are useful for Gene Ontology annotation transfer. The first is an intuitive generalization of the Pfam2GO mapping, and detects cases of strict functional implications of sets of domains. The second uses a probabilistic model to represent the relationship between domain content and annotation terms, and was found to be better suited for incomplete training sets. We implemented these models as predictors of Gene Ontology functional annotation terms. Both predictors were more accurate than conventional best BLAST-hit annotation transfer and more sensitive than a single-domain model on a large-scale dataset. We present a number of cases where combinations of Pfam-A protein domains predict functional terms that do not follow from the individual domains. Availability: Scripts and documentation are available for download at http://sonnhammer.sbc.su.se/multipfam2go_source_docs.tar Contact: Kristoffer.Forslund@sbc.su.se Supplementary Information: Table S1 10.1093/bioinformatics/btn312

Sequence Similarity Network Reveals Common Ancestry of Multidomain Proteins

Nan Song — 2008-06-18T13:54:41-00:00

PLoS Comput Biol, Vol. 4, No. 5. (16 May 2008), e1000063.

We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1) an extension of the traditional model of homology to include domain insertions; and 2) a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://www.neighborhoodcorrelation.org. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with identical domain architectures, we show that homology can be rationally defined for multidomain families with diverse architectures by considering the genomic context of the genes that encode them. Our study demonstrates the utility of mining network structure for evolutionary information, suggesting this is a fertile approach for investigating evolutionary processes in the post-genomic era.

Dynamics and Design Principles of a Basic Regulatory Architecture Controlling Metabolic Pathways

Chen-Shan Chin — 2008-06-17T20:37:14-00:00

PLoS Biology, Vol. 6, No. 6. (1 June 2008), e146.

The dynamic features of a genetic network's response to environmental fluctuations represent essential functional specifications and thus may constrain the possible choices of network architecture and kinetic parameters. To explore the connection between dynamics and network design, we have analyzed a general regulatory architecture that is commonly found in many metabolic pathways. Such architecture is characterized by a dual control mechanism, with end product feedback inhibition and transcriptional regulation mediated by an intermediate metabolite. As a case study, we measured with high temporal resolution the induction profiles of the enzymes in the leucine biosynthetic pathway in response to leucine depletion, using an automated system for monitoring protein expression levels in single cells. All the genes in the pathway are known to be coregulated by the same transcription factors, but we observed drastically different dynamic responses for enzymes upstream and immediately downstream of the key control point—the intermediate metabolite α-isopropylmalate (αIPM), which couples metabolic activity to transcriptional regulation. Analysis based on genetic perturbations suggests that the observed dynamics are due to differential regulation by the leucine branch-specific transcription factor Leu3, and that the downstream enzymes are strictly controlled and highly expressed only when αIPM is available. These observations allow us to build a simplified mathematical model that accounts for the observed dynamics and can correctly predict the pathway's response to new perturbations. Our model also suggests that transient dynamics and steady state can be separately tuned and that the high induction levels of the downstream enzymes are necessary for fast leucine recovery. It is likely that principles emerging from this work can reveal how gene regulation has evolved to optimize performance in other metabolic pathways with similar architecture.

Structural specificity in coiled-coil interactions

Gevorg Grigoryan — 2008-06-17T01:24:18-00:00

Current Opinion in Structural Biology, Vol. In Press, Corrected Proof

Coiled coils have a rich history in the field of protein design and engineering. Novel structures, such as the first seven-helix coiled coil, continue to provide surprises and insights. Large-scale datasets quantifying the influence of systematic mutations on coiled-coil stability are a valuable new asset to the area. Scoring methods based on sequence and/or structure can predict interaction preferences in coiled-coil-mediated bZIP transcription factor dimerization. Experimental and computational methods for dealing with the near-degeneracy of many coiled-coil structures appear promising for future design applications.

An in Vivo Map of the Yeast Protein Interactome

Kirill Tarassov — 2008-06-13T17:39:23-00:00

Science, Vol. 320, No. 5882. (13 June 2008), pp. 1465-1470.

Protein interactions regulate the systems-level behavior of cells; thus, deciphering the structure and dynamics of protein interaction networks in their cellular context is a central goal in biology. We have performed a genome-wide in vivo screen for protein-protein interactions in Saccharomyces cerevisiae by means of a protein-fragment complementation assay (PCA). We identified 2770 interactions among 1124 endogenously expressed proteins. Comparison with previous studies confirmed known interactions, but most were not known, revealing a previously unexplored subspace of the yeast protein interactome. The PCA detected structural and topological relationships between proteins, providing an 8-nanometer-resolution map of dynamically interacting complexes in vivo and extended networks that provide insights into fundamental cellular processes, including cell polarization and autophagy, pathways that are evolutionarily conserved and central to both development and human health. 10.1126/science.1153878

Coils in the membrane core are conserved and functionally important

Anni Kauko — 2008-05-05T23:43:32-00:00

Journal of Molecular Biology, Vol. In Press, Accepted Manuscript

A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and its Application to Influenza A Virus.

Sergei L Kosakovsky Pond — 2008-06-01T12:46:57-00:00

Molecular biology and evolution (29 May 2008)

We develop a model-based phylogenetic maximum likelihood test for evidence of preferential substitution towards a given residue at individual positions of a protein alignment - Directional Evolution of Protein Sequences (DEPS). DEPS can identify both the target residue and sites evolving towards it, help detect selective sweeps and frequency dependent selection - scenarios that confound most existing tests for selection, and achieves good power and accuracy on simulated data. We applied DEPS to alignments representing different genomic regions of Influenza A virus (IAV), sampled from avian hosts (H5N1 serotype) and human hosts (H3N2 serotype) and identified multiple directionally evolving sites in 5/8 genomic segments of H5N1 and H3N2 IAV. We propose a simple descriptive classification of directionally evolving sites into 5 groups based on the temporal distribution of residue frequencies, and document known functional correlates, such as immune escape or host adaptation.

Ensemble Non-negative Matrix Factorization Methods for Clustering Protein-Protein Interactions

Derek Greene — 2008-06-27T02:43:10-00:00

Bioinformatics (12 June 2008), btn286.

Motivation: When working with large-scale protein interaction data, an important analysis task is the assignment of pairs of proteins to groups that correspond to higher order assemblies. Previously a common approach to this problem has been to apply standard hierarchical clustering methods to identify such a groups. Here we propose a new algorithm for aggregating a diverse collection of matrix factorizations to produce a more informative clustering, which takes the form of a "soft" hierarchy of clusters. Results: We apply the proposed Ensemble NMF algorithm to a high-quality assembly of binary protein interactions derived from two proteome-wide studies in yeast. Our experimental evaluation demonstrates that the algorithm lends itself to discovering small localized structures in this data, which correspond to known functional groupings of complexes. In addition, we show that the algorithm also supports the assignment of putative functions for previously uncharacterized proteins, for instance the protein YNR024W, which may be an uncharacterized component of the exosome. Contact: derek.greene@ucd.ie Supplementary information: http://mlg.ucd.ie/nmf 10.1093/bioinformatics/btn286

Protein model refinement using an optimized physics-based all-atom force field

Anna Jagielska — 2008-06-19T11:23:04-00:00

Proceedings of the National Academy of Sciences, Vol. 105, No. 24. (17 June 2008), pp. 8268-8273.

One of the greatest challenges in protein structure prediction is the refinement of low-resolution predicted models to high-resolution structures that are close to the native state. Although contemporary structure prediction methods can assemble the correct topology for a large fraction of protein domains, such approximate models are often not of the resolution required for many important applications, including studies of reaction mechanisms and virtual ligand screening. Thus, the development of a method that could bring those structures closer to the native state is of great importance. We recently optimized the relative weights of the components of the Amber ff03 potential on a large set of decoy structures to create a funnel-shaped energy landscape with the native structure at the global minimum. Such an energy function might be able to drive proteins toward their native structure. In this work, for a test set of 47 proteins, with 100 decoy structures per protein that have a range of structural similarities to the native state, we demonstrate that our optimized potential can drive protein models closer to their native structure. Comparing the lowest-energy structure from each trajectory with the starting decoy, structural improvement is seen for 70% of the models on average. The ability to do such systematic structural refinements by using a physics-based all-atom potential represents a promising approach to high-resolution structure prediction. 10.1073/pnas.0800054105

Progress and challenges in protein structure prediction

Yang Zhang — 2008-06-17T12:07:31-00:00

Current Opinion in Structural Biology, Vol. 18, No. 3. (June 2008), pp. 342-348.

Depending on whether similar structures are found in the PDB library, the protein structure prediction can be categorized into template-based modeling and free modeling. Although threading is an efficient tool to detect the structural analogs, the advancements in methodology development have come to a steady state. Encouraging progress is observed in structure refinement which aims at drawing template structures closer to the native; this has been mainly driven by the use of multiple structure templates and the development of hybrid knowledge-based and physics-based force fields. For free modeling, exciting examples have been witnessed in folding small proteins to atomic resolutions. However, predicting structures for proteins larger than 150 residues still remains a challenge, with bottlenecks from both force field and conformational search.

Assembly reflects evolution of protein complexes

Emmanuel Levy — 2008-06-19T16:48:31-00:00

Nature (18 June 2008)

The Leucine-Rich Repeat Domain of Internalin B Folds along a Polarized N-Terminal Pathway

Naomi Courtemanche — 2008-06-26T03:04:58-00:00

Structure, Vol. 16, No. 5. (7 May 2008), pp. 705-714.

Summary The leucine-rich repeat domain of Internalin B is composed of seven tandem leucine-rich repeats, which each contain a short [beta] strand connected to a 310 helix by a short turn, and an N-terminal [alpha]-helical capping motif. To determine whether folding proceeds along a single, discrete pathway or multiple, parallel pathways, and to map the structure of the transition state ensemble, we examined the effects of destabilizing substitutions of conserved residues in each repeat. We find that, despite the structural redundancy among the repeats, folding proceeds through an N-terminal transition state ensemble in which the extent of structure formation is biased toward repeats one and two and includes both local and interrepeat interactions. Our results suggest that the N-terminal capping motif serves to polarize the folding pathway by acting as a fast-growing nucleus onto which consecutive repeats fold in the transition state ensemble, and highlight the importance of sequence-specific interactions in pathway selection.

Phylogeny-Aware Gap Placement Prevents Errors in Sequence Alignment and Evolutionary Analysis

Ari Loytynoja — 2008-06-20T03:07:52-00:00

Science, Vol. 320, No. 5883. (20 June 2008), pp. 1632-1635.

Genetic sequence alignment is the basis of many evolutionary and comparative studies, and errors in alignments lead to errors in the interpretation of evolutionary information in genomes. Traditional multiple sequence alignment methods disregard the phylogenetic implications of gap patterns that they create and infer systematically biased alignments with excess deletions and substitutions, too few insertions, and implausible insertion-deletion-event histories. We present a method that prevents these systematic errors by recognizing insertions and deletions as distinct evolutionary events. We show theoretically and practically that this improves the quality of sequence alignments and downstream analyses over a wide range of realistic alignment problems. These results suggest that insertions and sequence turnover are more common than is currently thought and challenge the conventional picture of sequence evolution and mechanisms of functional and structural changes. 10.1126/science.1158395

Direct observation of fast protein conformational switching

Haruto Ishikawa — 2008-06-25T04:43:14-00:00

Proceedings of the National Academy of Sciences, Vol. 105, No. 25. (24 June 2008), pp. 8619-8624.

Folded proteins can exist in multiple conformational substates. Each substate reflects a local minimum on the free-energy landscape with a distinct structure. By using ultrafast 2D-IR vibrational echo chemical-exchange spectroscopy, conformational switching between two well defined substates of a myoglobin mutant is observed on the approx50-ps time scale. The conformational dynamics are directly measured through the growth of cross peaks in the 2D-IR spectra of CO bound to the heme active site. The conformational switching involves motion of the distal histidine/E helix that changes the location of the imidazole side group of the histidine. The exchange between substates changes the frequency of the CO, which is detected by the time dependence of the 2D-IR vibrational echo spectrum. These results demonstrate that interconversion between protein conformational substates can occur on very fast time scales. The implications for larger structural changes that occur on much longer time scales are discussed. 10.1073/pnas.0803764105

Inhibition of expression of virulence genes of Yersinia pestis in Escherichia coli by external guide sequences and RNase P

Jae-Hyeong Ko — 2008-06-25T03:43:51-00:00

RNA (20 June 2008), rna.1120508.

External guide sequences (EGSs) targeting virulence genes from Yersinia pestis were designed and tested in vitro and in vivo in Escherichia coli. Linear EGSs and M1 RNA-linked EGSs were designed for the yscN and yscS genes that are involved in type III secretion in Y. pestis. RNase P from E. coli cleaves the messages of yscN and yscS in vitro with the cognate EGSs, and the expression of the EGSs resulted in the reduction of the levels of these messages of the virulence genes when those genes were expressed in E. coli. 10.1261/rna.1120508

Chemistry & Biology -- Yoshikuni et al.

2008-06-22T08:48:26-00:00

Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences

Yanzhi Guo — 2008-04-14T01:37:18-00:00

Nucl. Acids Res. (4 April 2008), gkn159.

Compared to the available protein sequences of different organisms, the number of revealed proteinprotein interactions (PPIs) is still very limited. So many computational methods have been developed to facilitate the identification of novel PPIs. However, the methods only using the information of protein sequences are more universal than those that depend on some additional information or predictions about the proteins. In this article, a sequence-based method is proposed by combining a new feature representation using auto covariance (AC) and support vector machine (SVM). AC accounts for the interactions between residues a certain distance apart in the sequence, so this method adequately takes the neighbouring effect into account. When performed on the PPI data of yeast Saccharomyces cerevisiae, the method achieved a very promising prediction result. An independent data set of 11 474 yeast PPIs was used to evaluate this prediction model and the prediction accuracy is 88.09%. The performance of this method is superior to those of the existing sequence-based methods, so it can be a useful supplementary tool for future proteomics studies. The prediction software and all data sets used in this article are freely available at http://www.scucic.cn/Predict_PPI/index.htm. 10.1093/nar/gkn159

Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data

Roy Varshavsky — 2008-06-16T02:49:49-00:00

PLoS ONE, Vol. 3, No. 5. (21 May 2008), e2247.

Background: A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied. Methodology/Principal Findings: We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive), or glocal (global-local) algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU) and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree) based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available. Conclusions: Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can also provide insights in erroneous and missed annotations.

Improvisation in evolution of genes and genomes: whose structure is it anyway?

Boris E Shakhnovich — 2008-05-22T09:43:34-00:00

Current opinion in structural biology (17 May 2008)

Significant progress has been made in recent years in a variety of seemingly unrelated fields such as sequencing, protein structure prediction, and high-throughput transcriptomics and metabolomics. At the same time, new microscopic models have been developed that made it possible to analyze the evolution of genes and genomes from first principles. The results from these efforts enable, for the first time, a comprehensive insight into the evolution of complex systems and organisms on all scales - from sequences to organisms and populations. Every newly sequenced genome uncovers new genes, families, and folds. Where do these new genes come from? How do gene duplication and subsequent divergence of sequence and structure affect the fitness of the organism? What role does regulation play in the evolution of proteins and folds? Emerging synergism between data and modeling provides first robust answers to these questions.

Multiple protein sequence alignment

Jimin Pei — 2008-05-15T06:36:26-00:00

Current Opinion in Structural Biology, Vol. In Press, Corrected Proof

Multiple sequence alignments are essential in computational analysis of protein sequences and structures, with applications in structure modeling, functional site prediction, phylogenetic analysis and sequence database searching. Constructing accurate multiple alignments for divergent protein sequences remains a difficult computational task, and alignment speed becomes an issue for large sequence datasets. Here, I review methodologies and recent advances in the multiple protein sequence alignment field, with emphasis on the use of additional sequence and structural information to improve alignment quality.

Predicting novel RNA-RNA interactions.

Irmtraud M Meyer — 2008-06-03T10:32:03-00:00

Current opinion in structural biology (14 May 2008)

The purpose of this article is to give a brief, yet concise overview of the current computational methods for predicting novel RNA-RNA interactions, that is interactions whose characteristic features we do not yet know. We start by briefly reviewing experimentally confirmed examples of RNA-RNA interactions before introducing computational methods for predicting RNA-RNA interactions. We will focus primarily on the interactions between different RNA molecules, that is trans RNA-RNA interactions, and will only discuss methods for predicting RNA structure, that is cis-only RNA-RNA interactions, where this helps to gain a better understanding. We conclude by discussing the merits of the different approaches and provide an outlook on probably and desirable future developments in the field.

Implications from a Network-Based Topological Analysis of Ubiquitin Unfolding Simulations

Arun Krishnan — 2008-06-16T00:53:01-00:00

PLoS ONE, Vol. 3, No. 5. (14 May 2008), e2149.

Background: The architectural organization of protein structures has been the focus of intense research since it can hopefully lead to an understanding of how proteins fold. In earlier works we had attempted to identify the inherent structural organization in proteins through a study of protein topology. We obtained a modular partitioning of protein structures with the modules correlating well with experimental evidence of early folding units or “foldons”. Residues that connect different modules were shown to be those that were protected during the transition phase of folding. Methodology/Principal Findings: In this work, we follow the topological path of ubiquitin through molecular dynamics unfolding simulations. We observed that the use of recurrence quantification analysis (RQA) could lead to the identification of the transition state during unfolding. Additionally, our earlier contention that the modules uncovered through our graph partitioning approach correlated well with early folding units was vindicated through our simulations. Moreover, residues identified from native structure as connector hubs and which had been shown to be those that were protected during the transition phase of folding were indeed more stable (less flexible) well beyond the transition state. Further analysis of the topological pathway suggests that the all pairs shortest path in a protein is minimized during folding. Conclusions: We observed that treating a protein native structure as a network by having amino acid residues as nodes and the non-covalent interactions among them as links allows for the rationalization of many aspects of the folding process. The possibility to derive this information directly from 3D structure opens the way to the prediction of important residues in proteins, while the confirmation of the minimization of APSP for folding allows for the establishment of a potentially useful proxy for kinetic optimality in the validation of sequence-structure predictions.

GFP-based optimization scheme for the overexpression and purification of eukaryotic membrane proteins in Saccharomyces cerevisiae

David Drew — 2008-06-16T00:50:21-00:00

Nat. Protocols, Vol. 3, No. 5. (April 2008), pp. 784-798.

The prokaryotic tree of life: past, present...and future?

James Mcinerney — 2008-06-16T00:47:52-00:00

Trends in Ecology & Evolution, Vol. 23, No. 5. (May 2008), pp. 276-281.

No accepted phylogenetic scheme for prokaryotes emerged until the late 1970s. Prior to that, it was assumed that there was a phylogenetic tree uniting all prokaryotes, but no suitable data were available for its construction. For 20 years, through the 1980s and 1990s, rRNA phylogenies were the gold standard. However, beginning in the last decade, findings from genomic data have challenged this new consensus. Gene trees can conflict greatly, and strains of the same species can differ enormously in genome content. Horizontal gene transfer is now known to be a significant influence on genome evolution. The next decade is likely to resolve whether or not we retain the centuries-old metaphor of the tree for all of life.

Genomic analysis of estrogen cascade reveals histone variant H2A.Z associated with breast cancer progression

Sujun Hua — 2008-04-27T23:46:47-00:00

Mol Syst Biol, Vol. 4 (15 April 2008)

A map of human protein interactions derived from co-expression of human mRNAs and their orthologs

Arun Ramani — 2008-04-15T19:18:30-00:00

Mol Syst Biol, Vol. 4 (15 April 2008)

Mathematical modeling of pathogenicity of Cryptococcus neoformans

Jacqueline Garcia — 2008-06-13T11:17:05-00:00

Mol Syst Biol, Vol. 4 (15 April 2008)

A Bayesian Estimator of Protein-Protein Association Probabilities

JM Gilmore — 2008-06-03T03:00:58-00:00

Bioinformatics (22 May 2008), btn238.

Summary: The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. Availability: BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available from http://www.pnl.gov/statistics/BEPro3. Contact: ds.daly@pnl.gov Supplementary Information: A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download 10.1093/bioinformatics/btn238

Estimating dynamic models for gene regulation networks

Jiguo Cao — 2008-06-03T03:00:21-00:00

Bioinformatics (27 May 2008), btn246.

Motivation: Transcription regulation is a fundamental process in biology, and it is important to model the dynamic behavior of gene regulation networks. Many approaches have been proposed to specify the network structure. However, finding the network connectivity is not sufficient to understand the network dynamics. Instead, one needs to model the regulation reactions, usually with a set of ordinary differential equations (ODEs). Because some of the parameters involved in these ODEs are unknown, their values need to be inferred from the observed data. Results: In this article, we introduce the generalized profiling method to estimate ODE parameters in a gene regulation network from microarray gene expression data which can be rather noisy. Because numerically solving ODEs is computationally expensive, we apply the penalized smoothing technique, a fast and stable computational method to approximate ODE solutions. The ODE solutions with our parameter estimates fit the data well. A goodness-of-fit test of dynamic models is developed to identify gene regulation networks. Contact: jca76@sfu.ca, hongyu.zhao@yale.edu 10.1093/bioinformatics/btn246

Toward a Comprehensive Temperature-Sensitive Mutant Repository of the Essential Genes of Saccharomyces cerevisiae

Shay Ben-Aroya — 2008-06-02T06:16:08-00:00

Molecular Cell, Vol. 30, No. 2. (25 April 2008), pp. 248-258.

Summary The Saccharomyces cereivisiae gene deletion project revealed that approximately 20% of yeast genes are required for viability. The analysis of essential genes traditionally relies on conditional mutants, typically temperature-sensitive (ts) alleles. We developed a systematic approach (termed "diploid shuffle") useful for generating a ts allele for each essential gene in S. cerevisiae and for improved genetic manipulation of mutant alleles and gene constructs in general. Importantly, each ts allele resides at its normal genomic locus, flanked by specific cognate UPTAG and DNTAG bar codes. A subset of 250 ts mutants, including ts alleles for all uncharacterized essential genes and prioritized for genes with human counterparts, is now ready for distribution. The importance of this collection is demonstrated by biochemical and genetic screens that reveal essential genes involved in RNA processing and maintenance of chromosomal stability.

Evolution: A gene is born

Tanita Casci — 2008-05-17T12:26:02-00:00

Nature Reviews Genetics, Vol. 9, No. 6., pp. 415-415.

Estimating the size of the human interactome

Michael Stumpf — 2008-05-13T07:34:25-00:00

Proceedings of the National Academy of Sciences (12 May 2008), 0708078105.

After the completion of the human and other genome projects it emerged that the number of genes in organisms as diverse as fruit flies, nematodes, and humans does not reflect our perception of their relative complexity. Here, we provide reliable evidence that the size of protein interaction networks in different organisms appears to correlate much better with their apparent biological complexity. We develop a stable and powerful, yet simple, statistical procedure to estimate the size of the whole network from subnet data. This approach is then applied to a range of eukaryotic organisms for which extensive protein interaction data have been collected and we estimate the number of interactions in humans to be approx650,000. We find that the human interaction network is one order of magnitude bigger than the Drosophila melanogaster interactome and approx3 times bigger than in Caenorhabditis elegans. 10.1073/pnas.0708078105

An optimized split-ubiquitin cDNA-library screening system to identify novel interactors of the human Frizzled 1 receptor

Dietmar Dirnberger — 2008-05-14T11:09:51-00:00

Nucl. Acids Res., Vol. 36, No. 6. (1 April 2008), e37.

The yeast split-ubiquitin system has previously been shown to be suitable to detect protein interactions of membrane proteins and of transcription factors in vivo. Therefore, this technology complements the classical split-transcription factor based yeast two-hybrid system (Y2H). Success or failure of the Y2H depends primarily on the ability to avoid false-negative and false-positive hits that become a limiting factor for the value of the system, especially in large scale proteomic analyses. We provide here a systematic assessment of parameters to help improving the quality of split-ubiquitin cDNA-library screenings. We experimentally defined the optimal 5-fluoroorotic acid (5-FOA) concentration as a key parameter to increase the reproducibility of interactions and, at the same time, to keep non-specific background growth low. Furthermore, we show that the efficacy of the 5-FOA selection is modulated by the plating density of the yeast clones. Moreover, a reporter-specific class of false-positive hits was identified, and a simple phenotypic assay for efficient de-selection was developed. We demonstrate the application of this improved system to identify novel interacting proteins of the human Frizzled 1 receptor. We identified several novel interactors with components of the Wnt-Frizzled signalling pathways and discuss their potential roles as direct mediators of Frizzled receptor signalling. The present work is the first example of a split-ubiquitin interaction screen using an in-situ expressed receptor of the serpentine class, emphasizing the suitability of the described improvements in the screening protocol. 10.1093/nar/gkm1163

Network-based global inference of human disease genes

Xuebing Wu — 2008-05-06T20:36:46-00:00

Mol Syst Biol, Vol. 4 (6 May 2008)

Large-scale phosphorylation mapping reveals the extent of tyrosine phosphorylation in Arabidopsis

Naoyuki Sugiyama — 2008-05-06T22:38:46-00:00

Mol Syst Biol, Vol. 4 (6 May 2008)

Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction

SD Dunn — 2008-01-31T12:19:42-00:00

Bioinformatics, Vol. 24, No. 3. (1 February 2008), pp. 333-340.

Motivation: Compensating alterations during the evolution of protein families give rise to coevolving positions that contain important structural and functional information. However, a high background composed of random noise and phylogenetic components interferes with the identification of coevolving positions. Results: We have developed a rapid, simple and general method based on information theory that accurately estimates the level of background mutual information for each pair of positions in a given protein family. Removal of this background results in a metric, MIp, that correctly identifies substantially more coevolving positions in protein families than any existing method. A significant fraction of these positions coevolve strongly with one or only a few positions. The vast majority of such position pairs are in contact in representative structures. The identification of strongly coevolving position pairs can be used to impose significant structural limitations and should be an important additional constraint for ab initio protein folding. Availability: Alignments and program files can be found in the Supplementary Information. Contact: ggloor@uwo.ca Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btm604

Recent Progress and Future Directions in Protein-Protein Docking

2008-05-09T01:42:26-00:00

Design of protein function leaps by directed domain interface evolution

Jin Huang — 2008-04-30T19:38:26-00:00

Proceedings of the National Academy of Sciences (29 April 2008), 0801097105.

Most natural proteins performing sophisticated tasks contain multiple domains where an active site is located at the domain interface. Comparative structural analyses suggest that major leaps in protein function occur through gene recombination events that connect two or more protein domains to generate a new active site, frequently occurring at the newly created domain interface. However, such functional leaps by combination of unrelated domains have not been directly demonstrated. Here we show that highly specific and complex protein functions can be generated by joining a low-affinity peptide-binding domain with a functionally inert second domain and subsequently optimizing the domain interface. These directed evolution processes dramatically enhanced both affinity and specificity to a level unattainable with a single domain, corresponding to >500-fold and >2,000-fold increases of affinity and specificity, respectively. An x-ray crystal structure revealed that the resulting "affinity clamp" had clamshell architecture as designed, with large additional binding surface contributed by the second domain. The affinity clamps having a single-nanomolar dissociation constant outperformed a monoclonal antibody in immunochemical applications. This work establishes evolutionary paths from isolated domains with primitive function to multidomain proteins with sophisticated function and introduces a new protein-engineering concept that allows for the generation of highly functional affinity reagents to a predefined target. The prevalence and variety of natural interaction domains suggest that numerous new functions can be designed by using directed domain interface evolution. 10.1073/pnas.0801097105

3D structure of the influenza virus polymerase complex: Localization of subunit domains

Estela Area — 2008-05-09T01:37:57-00:00

Proceedings of the National Academy of Sciences, Vol. 101, No. 1. (6 January 2004), pp. 308-313.

The 3D structure of the influenza virus polymerase complex was determined by electron microscopy and image processing of recombinant ribonucleoproteins (RNPs). The RNPs were generated by in vivo amplification using cDNAs of the three polymerase subunits, the nucleoprotein, and a model virus-associated RNA containing 248 nt. The polymerase structure obtained is very compact, with no apparent boundaries among subunits. The position of specific regions of the PB1, PB2, and PA subunits was determined by 3D reconstruction of either RNP-mAb complexes or tagged RNPs. This structural model is available for the polymerase of a negative-stranded RNA virus and provides a general delineation of the complex and its interaction with the template-associated nucleoprotein monomers in the RNP. 10.1073/pnas.0307127101

Multiple Routes and Structural Heterogeneity in Protein Folding

Jayant Udgaonkar — 2008-05-08T08:58:52-00:00

Annual Review of Biophysics, Vol. 37, No. 1. (2008), pp. 489-510.

Experimental studies show that many proteins fold along sequential pathways defined by folding intermediates. An intermediate may not always be a single population of molecules but may consist of subpopulations that differ in their average structure. These subpopulations are likely to fold via independent pathways. Parallel folding and unfolding pathways appear to arise because of structural heterogeneity. For some proteins, the folding pathways can effectively switch either because different subpopulations of an intermediate get populated under different folding conditions, or because intermediates on otherwise hidden pathways get stabilized, leading to their utilization becoming discernible, or because mutations stabilize different substructures. Therefore, the same protein may fold via different pathways in different folding conditions. Multiple folding pathways make folding robust, and evolution is likely to have selected for this robustness to ensure that a protein will fold under the varying conditions prevalent in different cellular contexts.

Bimolecular Fluorescence Complementation (BiFC) Analysis as a Probe of Protein Interactions in Living Cells

Tom Kerppola — 2008-05-08T08:58:16-00:00

Annual Review of Biophysics, Vol. 37, No. 1. (2008), pp. 465-487.

Protein interactions are a fundamental mechanism for the generation of biological regulatory specificity. The study of protein interactions in living cells is of particular significance because the interactions that occur in a particular cell depend on the full complement of proteins present in the cell and the external stimuli that influence the cell. Bimolecular fluorescence complementation (BiFC) analysis enables direct visualization of protein interactions in living cells. The BiFC assay is based on the association between two nonfluorescent fragments of a fluorescent protein when they are brought in proximity to each other by an interaction between proteins fused to the fragments. Numerous protein interactions have been visualized using the BiFC assay in many different cell types and organisms. The BiFC assay is technically straightforward and can be performed using standard molecular biology and cell culture reagents and a regular fluorescence microscope or flow cytometer.