CiteULike: marcius's library [621 articles]

Automated de novo prediction of native-like RNA tertiary structures

Rhiju Das — 2007-08-31T15:18:20-00:00

PNAS (28 August 2007), 0703836104.

Edited by Ignacio Tinoco, Jr., University of California, Berkeley, CA, and approved July 10, 2007 (received for review April 25, 2007)RNA tertiary structure prediction has been based almost entirely on base-pairing constraints derived from phylogenetic covariation analysis. We describe here a complementary approach, inspired by the Rosetta low-resolution protein structure prediction method, that seeks the lowest energy tertiary structure for a given RNA sequence without using evolutionary information. In a benchmark test of 20 RNA sequences with known structure and lengths of approx30 nt, the new method reproduces better than 90% of WatsonCrick base pairs, comparable with the accuracy of secondary structure prediction methods. In more than half the cases, at least one of the top five models agrees with the native structure to better than 4 A rmsd over the backbone. Most importantly, the method recapitulates more than one-third of non-WatsonCrick base pairs seen in the native structures. Tandem stacks of "sheared" base pairs, base triplets, and pseudoknots are among the noncanonical features reproduced in the models. In the cases in which none of the top five models were native-like, higher energy conformations similar to the native structures are still sampled frequently but not assigned low energies. These results suggest that modest improvements in the energy function, together with the incorporation of information from phylogenetic covariance, may allow confident and accurate structure prediction for larger and more complex RNA chains. 10.1073/pnas.0703836104

RNA Maps Reveal New RNA Classes and a Possible Function for Pervasive Transcription

Philipp Kapranov — 2007-05-27T00:42:53-00:00

Science (17 May 2007), 1138341.

Significant fractions of eukaryotic genomes give rise to RNA, much of which is unannotated and has reduced protein-coding potential. The genomic origins and the relations of human nuclear and cytosolic polyadenylated RNAs longer than 200 nucleotides and whole-cell RNAs less than 200 nt are investigated in this genome-wide study. Subcellular addresses for nucleotides present in detected RNAs were assigned, and their potential processing into short RNAs was investigated. Taken together, these observations suggest a role for some unannotated RNAs as primary transcripts for the production of short RNAs. Three novel potentially functional classes of RNAs have been identified, two of which are syntenically conserved and correlate with the expression state of protein-coding genes. These data support a highly interleaved organization of the human transcriptome. 10.1126/science.1138341

RNA structure: experimental analysis.

Brice Felden — 2007-06-11T16:45:18-00:00

Curr Opin Microbiol (24 May 2007)

Among all of the biological macromolecules, the functional versatility of RNAs is unique including encoding or transferring genetic information and performing catalysis. These biological functions are highly dependent upon RNA folding and structure. Since the discovery of catalytic RNAs in the early 1980s, a recent breakthrough came from the identification of a wealth of micro RNAs, small interfering RNAs and regulatory RNAs, all involved in modulation of gene expression. The structure of these novel RNAs, either free or in complex with specific ligands, can be analyzed using various experimental strategies, including X-ray crystallography, cryo-electron microscopy, nuclear magnetic resonance spectroscopy, structure-specific probes, with some that can be used in living cells, RNA engineering, thermal denaturation and mass spectrometry. Among these, X-ray crystallography has recently enabled determination of the structures of several large and complex RNAs, as well as of ribonucleoprotein complexes. The database of RNA structure has grown tremendously since the recent crystal structure analyses of the prokaryotic ribosome and its subunits. These methods are now widely applied to a variety of biologically relevant RNAs.

RNA conformational classes.

B Schneider — 2007-06-11T16:56:41-00:00

Nucleic Acids Res, Vol. 32, No. 5. (2004), pp. 1666-1677.

RNA exhibits a large diversity of conformations. Three thousand nucleotides of 23S and 5S ribosomal RNA from a structure of the large ribosomal subunit were analyzed in order to classify their conformations. Fourier averaging of the six 3D distributions of torsion angles and analyses of the resulting pseudo electron maps, followed by clustering of the preferred combinations of torsion angles were performed on this dataset. Eighteen non-A-type conformations and 14 A-RNA related conformations were discovered and their torsion angles were determined; their Cartesian coordinates are available.

Evolutionary rates vary among rRNA structural elements

S Smit — 2007-06-12T01:37:54-00:00

Nucl. Acids Res., Vol. 35, No. 10. (11 May 2007), pp. 3339-3354.

Understanding patterns of rRNA evolution is critical for a number of fields, including structure prediction and phylogeny. The standard model of RNA evolution is that compensatory mutations in stems make up the bulk of the changes between homologous sequences, while unpaired regions are relatively homogeneous. We show that considerable heterogeneity exists in the relative rates of evolution of different secondary structure categories (stems, loops, bulges, etc.) within the rRNA, and that in eukaryotes, loops actually evolve much faster than stems. Both rates of evolution and abundance of different structural categories vary with distance from functionally important parts of the ribosome such as the tRNA path and the peptidyl transferase center. For example, fast-evolving residues are mainly found at the surface; stems are enriched at the subunit interface, and junctions near the peptidyl transferase center. However, different secondary structure categories evolve at different rates even when these effects are accounted for. The results demonstrate that relative rates and patterns of evolution are lineage specific, suggesting that phylogenetically and structurally specific models will improve evolutionary and structural predictions. 10.1093/nar/gkm101

RNAbor: a web server for RNA structural neighbors.

Eva Freyhult — 2007-06-02T12:13:31-00:00

Nucleic Acids Res (25 May 2007)

RNAbor provides a new tool for researchers in the biological and related sciences to explore important aspects of RNA secondary structure and folding pathways. RNAbor computes statistics concerning delta-neighbors of a given input RNA sequence and structure (the structure can, for example, be the minimum free energy (MFE) structure). A delta-neighbor is a structure that differs from the input structure by exactly delta base pairs, that is, it can be obtained from the input structure by adding and/or removing exactly delta base pairs. For each distance delta RNAbor computes the density of delta-neighbors, the number of delta-neighbors, and the MFE structure, or MFE (delta) structure, among all delta-neighbors. RNAbor can be used to study possible folding pathways, to determine alternate low-energy structures, to predict potential nucleation sites and to explore structural neighbors of an intermediate, biologically active structure. The web server is available at http://bioinformatics.bc.edu/clotelab/RNAbor.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

Sebastien Moretti — 2007-06-02T12:14:58-00:00

Nucleic Acids Res (25 May 2007)

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

RNA Sampler: A new sampling based algorithm for common RNA secondary structure prediction and structural alignment.

Xing Xu — 2007-06-02T13:26:58-00:00

Bioinformatics (30 May 2007)

MOTIVATION: Non-coding RNA genes and RNA structural regulatory motifs play important roles in gene regulation and other cellular functions. They are often characterized by specific secondary structures that are critical to their functions and are often conserved in phylogenetically or functionally related sequences. Predicting common RNA secondary structures in multiple unaligned sequences remains a challenge in bioinformatics research. Methods and RESULTS: We present a new sampling based algorithm to predict common RNA secondary structures in multiple unaligned sequences. Our algorithm finds the common structures between two sequences by probabilistically sampling aligned stems based on stem conservation calculated from intrasequence base pairing probabilities and intersequence base alignment probabilities. It iteratively updates these probabilities based on sampled structures and subsequently recalculates stem conservation using the updated probabilities. The iterative process terminates upon convergence of the sampled structures. We extend the algorithm to multiple sequences by a consistency-based method, which iteratively incorporates and reinforces consistent structure information from pairwise comparisons into consensus structures. The algorithm has no limitation on predicting pseudoknots. In extensive testing on real sequence data, our algorithm outperformed other leading RNA structure prediction methods in both sensitivity and specificity with a reasonably fast speed. It also generated better structural alignments than other programs in sequences of a wide range of identities, which more accurately represent the RNA secondary structure conservations. AVAILABILITY: The algorithm is implemented in a C program, RNA Sampler, which is available at http://ural.wustl.edu/software.html SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

On the relationship between sequence and structure similarities in proteomics

K Evgeny — 2007-04-09T23:47:21-00:00

Bioinformatics, Vol. 23, No. 6. (15 March 2007), pp. 717-723.

Deleterious SNP prediction: be mindful of your training data!

Care — 2007-04-09T23:47:22-00:00

Bioinformatics, Vol. 23, No. 6. (15 March 2007), pp. 664-672.

Multiple structural alignment and clustering of RNA sequences.

Elfar Torarinsson — 2007-03-01T11:27:32-00:00

Bioinformatics (25 February 2007)

MOTIVATION: An apparent paradox in computational RNA structure prediction is that many methods, in advance, require a multiple alignment of a set of related sequences, when searching for a common structure between them. However, such a multiple alignment is hard to obtain even for few sequences with low sequence similarity without simultaneously folding and aligning them. Furthermore, it is of interest to conduct a multiple alignment of RNA sequence candidates found from searching as few as two genomic sequences. RESULTS: Here, based on the PMcomp program, we present a global multiple alignment program, foldalignM, which performs especially well on few sequences with low sequence similarity, and is comparable in performance with state of the art programs in general. In addition, it can cluster sequences based on sequence and structure similarity and output a multiple alignment for each cluster. Furthermore, preliminary results with local datasets indicate that the program is useful for post processing foldalign pairwise scans. AVAILABILITY: The program foldalignM is implemented in JAVA and is, along with some accompanying PERL scripts, available at http://foldalign.ku.dk/

Key biology databases go wiki

Jim Giles — 2007-02-14T19:39:33-00:00

Nature, Vol. 445, No. 7129. (14 February 2007), pp. 691-691.

Modeling the Evolution of Protein Domain Architectures Using Maximum Parsimony

Jessica Fong — 2007-01-25T03:25:14-00:00

Journal of Molecular Biology, Vol. 366, No. 1. (9 February 2007), pp. 307-315.

Domains are basic evolutionary units of proteins and most proteins have more than one domain. Advances in domain modeling and collection are making it possible to annotate a large fraction of known protein sequences by a linear ordering of their domains, yielding their architecture. Protein domain architectures link evolutionarily related proteins and underscore their shared functions. Here, we attempt to better understand this association by identifying the evolutionary pathways by which extant architectures may have evolved. We propose a model of evolution in which architectures arise through rearrangements of inferred precursor architectures and acquisition of new domains. These pathways are ranked using a parsimony principle, whereby scenarios requiring the fewest number of independent recombination events, namely fission and fusion operations, are assumed to be more likely. Using a data set of domain architectures present in 159 proteomes that represent all three major branches of the tree of life allows us to estimate the history of over 85% of all architectures in the sequence database. We find that the distribution of rearrangement classes is robust with respect to alternative parsimony rules for inferring the presence of precursor architectures in ancestral species. Analyzing the most parsimonious pathways, we find 87% of architectures to gain complexity over time through simple changes, among which fusion events account for 5.6 times as many architectures as fission. Our results may be used to compute domain architecture similarities, for example, based on the number of historical recombination events separating them. Domain architecture "neighbors" identified in this way may lead to new insights about the evolution of protein function.

Structural proteomics: from the molecule to the system

Lucia Banci — 2007-01-04T23:07:41-00:00

Nature Structural & Molecular Biology, Vol. 14, No. 1., pp. 3-4.

A combinatorial approach to create artificial homing endonucleases cleaving chosen sequences

J Smith — 2006-12-22T14:19:49-00:00

Nucleic Acids Research, Vol. 34, No. 22. (December 2006), pp. e149-e149.

Sequence comparison by sequence harmony identifies subtype-specific functional sites

W Pirovano — 2006-12-22T14:19:37-00:00

Nucleic Acids Research, Vol. 34, No. 22. (December 2006), pp. 6540-6548.

The interaction networks of structured RNAs

A Lescoute — 2006-12-22T14:19:34-00:00

Nucleic Acids Research, Vol. 34, No. 22. (December 2006), pp. 6587-6604.

RNAs everywhere: genome-wide annotation of structured RNAs.

Rolf Backofen — 2006-12-16T16:08:14-00:00

J Exp Zoolog B Mol Dev Evol (14 December 2006)

Starting with the discovery of microRNAs and the advent of genome-wide transcriptomics, non-protein-coding transcripts have moved from a fringe topic to a central field research in molecular biology. In this contribution we review the state of the art of "computational RNomics", i.e., the bioinformatics approaches to genome-wide RNA annotation. Instead of rehashing results from recently published surveys in detail, we focus here on the open problem in the field, namely (functional) annotation of the plethora of putative RNAs. A series of exploratory studies are used to provide non-trivial examples for the discussion of some of the difficulties. J. Exp. Zool. (Mol. Dev. Evol.) 308B, 2007. (c) 2006 Wiley-Liss, Inc.

Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation

Letunic — 2006-12-25T11:16:04-00:00

Bioinformatics, Vol. 23, No. 1. (1 January 2007), pp. 127-128.

SCOR: a Structural Classification of RNA database.

PS Klosterman — 2006-12-20T19:39:03-00:00

Nucleic Acids Res, Vol. 30, No. 1. (1 January 2002), pp. 392-394.

The Structural Classification of RNA (SCOR) database provides a survey of the three-dimensional motifs contained in 259 NMR and X-ray RNA structures. In one classification, the structures are grouped according to function. The RNA motifs, including internal and external loops, are also organized in a hierarchical classification. The 259 database entries contain 223 internal and 203 external loops; 52 entries consist of fully complementary duplexes. A classification of the well-characterized tertiary interactions found in the larger RNA structures is also included along with examples. The SCOR database is accessible at http://scor.lbl.gov.

RNA structure: the long and the short of it.

SR Holbrook — 2006-11-29T12:03:32-00:00

Curr Opin Struct Biol, Vol. 15, No. 3. (June 2005), pp. 302-308.

The database of RNA structure has grown tremendously since the crystal structure analyses of ribosomal subunits in 2000-2001. During the past year, the trend toward determining the structure of large, complex biological RNAs has accelerated, with the analysis of three intact group I introns, A- and B-type ribonuclease P RNAs, a riboswitch-substrate complex and other structures. The growing database of RNA structures, coupled with efforts directed at the standardization of nomenclature and classification of motifs, has resulted in the identification and characterization of numerous RNA secondary and tertiary structure motifs. Because a large proportion of RNA structure can now be shown to be composed of these recurring structural motifs, a view of RNA as a modular structure built from a combination of these building blocks and tertiary linkers is beginning to emerge. At the same time, however, more detailed analysis of water, metal, ligand and protein binding to RNA is revealing the effect of these moieties on folding and structure formation. The balance between the views of RNA structure either as strictly a construct of preformed building blocks linked in a limited number of ways or as a flexible polymer assuming a global fold influenced by its environment will be the focus of current and future RNA structural biology.

Discovering disease-genes by topological features in human protein-protein interaction network

J Xu — 2006-11-16T06:24:43-00:00

Bioinformatics, Vol. 22, No. 22. (15 November 2006), pp. 2800-2805.

Synthetic biology--putting engineering into biology

Matthias Heinemann — 2006-11-05T23:02:33-00:00

Bioinformatics, Vol. 22, No. 22. (15 November 2006), pp. 2790-2799.

Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis--synthetic biology's system fabrication process--supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds. Contact: panke@ipe.mavt.ethz.ch 10.1093/bioinformatics/btl469

TimeTree: a public knowledge-base of divergence times among organisms

Hedges — 2006-11-23T09:23:13-00:00

Bioinformatics, Vol. 22, No. 23. (1 December 2006), pp. 2971-2972.

A protein interaction network for pluripotency of embryonic stem cells

Jianlong Wang — 2006-11-09T05:19:06-00:00

Nature

Variability and memory of protein levels in human cells

Alex Sigal — 2006-11-19T21:34:19-00:00

Nature (19 November 2006)

An RNA folding algorithm including pseudoknots based on dynamic weighted matching.

H Liu — 2006-11-16T13:01:13-00:00

Comput Biol Chem, Vol. 30, No. 1. (February 2006), pp. 72-76.

On the basis of maximum weighted matching (MWM) algorithm, we introduced a dynamic weight related with stem length and used a recursive algorithm to predict RNA secondary structures by searching the stem structure with maximum weight summation step-by-step. This algorithm not only avoids the complicated free energy calculation, but also it could attain higher prediction accuracy. Moreover, our algorithm can predict most types of potential pseudoknots in the RNA structure.

ProteinRNA interactions: exploring binding patterns with a three-dimensional superposition analysis of high resolution structures

N Morozova — 2006-11-16T06:24:45-00:00

Bioinformatics, Vol. 22, No. 22. (15 November 2006), pp. 2746-2752.

Mining frequent stem patterns from unaligned RNA sequences.

Michiaki Hamada — 2006-08-16T16:10:32-00:00

Bioinformatics (14 August 2006)

MOTIVATION: In detection of non-coding RNAs, it is often necessary to identify the secondary structure motifs from a set of putative RNA sequences. Most of the existing algorithms aim to provide the best motif or few good motifs, but biologists often need to inspect all the possible motifs thoroughly. RESULTS: Our method RNAmine employs a graph theoretic representation of RNA sequences, and detects all the possible motifs exhaustively using a graph mining algorithm. The motif detection problem boils down to finding frequently appearing patterns in a set of directed and labeled graphs. In the tasks of common secondary structure prediction and local motif detection from long sequences, our method performed favorably both in accuracy and in efficiency with the state-of-the-art methods such as CMFinder. AVAILABILITY: The software is available on request. SUPPLEMENTARY INFORMATION: Visit the following URL for supplementary information, software availability and the information about the web server. http://www.ncrna.org/RNAMINE/.

Spatial localization of ligand binding sites from electron current density surfaces calculated from NMR chemical shift perturbations.

MA McCoy — 2006-10-30T10:39:35-00:00

J Am Chem Soc, Vol. 124, No. 39. (2 October 2002), pp. 11758-11763.

Rapid, accurate structure determination of protein-ligand complexes is an essential component in structure-based drug design. We have developed a method that uses NMR protein chemical shift perturbations to spatially localize a ligand when it is complexed with a protein. Chemical shift perturbations on the protein arise primarily from the close proximity of electron current density from the ligand. In our approach the location of the center of the electron current density for a ligand aromatic ring was approximated by a point-dipole, and dot densities were used to represent ligand positions that are allowed by the experimental data. The dot density is increased in the region of space that is consistent for the most data. A surface can be formed in regions of the highest dot density that correlates to the center of the ligand aromatic ring. These surfaces allow for the rapid evaluation of ligand binding, which is demonstrated on a model system and on real data from HCV NS3 protease and HCV NS3 helicase, where the location of ligand binding can be compared to that obtained from difference electron density from X-ray crystallography.

Three-dimensional comparative modeling of RNA.

C Zwieb — 2006-10-27T20:31:05-00:00

Nucleic Acids Symp Ser, No. 36. (1997), pp. 69-71.

Comparative sequence analysis and ERNA-3D software were used to model the three-dimensional structure of the small domain of signal recognition particle RNA. RNA secondary structures were established by allowing only phylogenetically-supported base pairs. The folding of the RNA molecules was constrained further to include a well-supported pseudoknot. Helical sections were oriented coaxially where a continuous helical stack was formed in the RNA of another species. Finally, RNA helices were placed at distances that preserved the connectivity of the molecule with the smallest number of single-stranded nucleotide residues as identified from the aligned sequences. We show that the comparative three-dimensional structure modeling approach is an extremely powerful tool as it requires only a critical number of carefully aligned sequences.

From The Cover: Global mapping of the protein structure space and application in structure-based inference of protein function

Jingtong Hou — 2006-09-21T10:06:51-00:00

PNAS, Vol. 102, No. 10. (8 March 2005), pp. 3651-3656.

We have constructed a map of the "protein structure space" by using the pairwise structural similarity scores calculated for all nonredundant protein structures determined experimentally. As expected, proteins with similar structures clustered together in the map and the overall distribution of structural classes of this map followed closely that of the map of the "protein fold space" we have reported previously. Consequently, proteins sharing similar molecular functions also were found to colocalize in the protein structure space map, pointing toward a previously undescribed scheme for structure-based functional inference for remote homologues based on the proximity in the map of the protein structure space. We found that this scheme consistently outperformed other predictions made by using either the raw scores or normalized Z-scores of pairwise DALI structure alignment. 10.1073/pnas.0409772102

Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection

D Chivian — 2006-10-25T08:37:58-00:00

Nucleic Acids Research, Vol. 34, No. 17. (October 2006), pp. e112-e112.

RNA structures and folding: from conventional to new issues in structure predictions.

P Schuster — 2006-10-23T15:01:42-00:00

Curr Opin Struct Biol, Vol. 7, No. 2. (April 1997), pp. 229-235.

Prediction and modeling of RNA structures has become an indispensable tool of biological research disciplines. Currently, reliable predictions require massive input of experimental data. Structure-forming elements are conventional base pairs, as well as a rapidly increasing repertoire of novel structural motifs. New developments extend structural analysis beyond the one-sequence/one-structure paradigm and allow questions that are relevant to molecular evolution to be answered.

Protein–Protein Interactions More Conserved within Species than across Species

Sven Mika — 2006-07-25T13:29:09-00:00

PLoS Computational Biology, Vol. 2, No. 7. (1 July 2006), e79.

Experimental high-throughput studies of protein–protein interactions are beginning to provide enough data for comprehensive computational studies. Today, about ten large data sets, each with thousands of interacting pairs, coarsely sample the interactions in fly, human, worm, and yeast. Another about 55,000 pairs of interacting proteins have been identified by more careful, detailed biochemical experiments. Most interactions are experimentally observed in prokaryotes and simple eukaryotes; very few interactions are observed in higher eukaryotes such as mammals. It is commonly assumed that pathways in mammals can be inferred through homology to model organisms, e.g. the experimental observation that two yeast proteins interact is transferred to infer that the two corresponding proteins in human also interact. Two pairs for which the interaction is conserved are often described as interologs. The goal of this investigation was a large-scale comprehensive analysis of such inferences, i.e. of the evolutionary conservation of interologs. Here, we introduced a novel score for measuring the overlap between protein–protein interaction data sets. This measure appeared to reflect the overall quality of the data and was the basis for our two surprising results from our large-scale analysis. Firstly, homology-based inferences of physical protein–protein interactions appeared far less successful than expected. In fact, such inferences were accurate only for extremely high levels of sequence similarity. Secondly, and most surprisingly, the identification of interacting partners through sequence similarity was significantly more reliable for protein pairs within the same organism than for pairs between species. Our analysis underlined that the discrepancies between different datasets are large, even when using the same type of experiment on the same organism. This reality considerably constrains the power of homology-based transfer of interactions. In particular, the experimental probing of interactions in distant model organisms has to be undertaken with some caution. More comprehensive images of protein–protein networks will require the combination of many high-throughput methods, including in silico inferences and predictions. http://www.rostlab.org/results/2006/ppi_homology/

Structural Modeling of Protein Interactions by Analogy: Application to PSD-95

Dmitry Korkin — 2006-10-22T11:12:15-00:00

PLoS Computational Biology, Vol. preprint, No. 2006. (1 October 2006)

We describe comparative patch analysis for modeling the structures of multi-domain proteins and protein complexes, and apply it to the PSD-95 protein. Comparative patch analysis is a hybrid of comparative modeling based on a template complex and protein docking, with a greater applicability than comparative modeling and a higher accuracy than docking. It relies on structurally defined interactions of each of the complex components, or their homologs, with any other protein, irrespective of its fold. For each component, its known binding modes with other proteins of any fold are collected and expanded by the known binding modes of its homologs. These modes are then used to restrain conventional molecular docking, resulting in a set of binary domain complexes that are subsequently ranked by geometric complementarity and a statistical potential. The method is evaluated by predicting 20 binary complexes of known structure. It is able to correctly identify the binding mode in 70% of the benchmark complexes compared to 30% for protein docking. We applied comparative patch analysis to model the complex of the third PDZ domain and the SH3-GK domains in the PSD-95 protein, whose structure is unknown. In the first predicted configuration of the domains, PDZ interacts with SH3 leaving both the GMP-binding site of GK and the C-terminus binding cleft of PDZ accessible, while in the second configuration PDZ interacts with GK, burying both binding sites. We suggest that the two alternate configurations correspond to the different functional forms of PSD-95 and provide a possible structural description for the experimentally observed cooperative folding transitions in PSD-95 and its homologs. More generally, we expect that comparative patch analysis will provide useful spatial restraints for the structural characterization of an increasing number of binary and higher order protein complexes.

The Many Faces of Protein–Protein Interactions: A Compendium of Interface Geometry

Wan Kim — 2006-10-22T11:11:31-00:00

PLoS Computational Biology, Vol. 2, No. 9. (1 September 2006), e124.

A systematic classification of protein–protein interfaces is a valuable resource for understanding the principles of molecular recognition and for modelling protein complexes. Here, we present a classification of domain interfaces according to their geometry. Our new algorithm uses a hybrid approach of both sequential and structural features. The accuracy is evaluated on a hand-curated dataset of 416 interfaces. Our hybrid procedure achieves 83% precision and 95% recall, which improves the earlier sequence-based method by 5% on both terms. We classify virtually all domain interfaces of known structure, which results in nearly 6,000 distinct types of interfaces. In 40% of the cases, the interacting domain families associate in multiple orientations, suggesting that all the possible binding orientations need to be explored for modelling multidomain proteins and protein complexes. In general, hub proteins are shown to use distinct surface regions (multiple faces) for interactions with different partners. Our classification provides a convenient framework to query genuine gene fusion, which conserves binding orientation in both fused and separate forms. The result suggests that the binding orientations are not conserved in at least one-third of the gene fusion cases detected by a conventional sequence similarity search. We show that any evolutionary analysis on interfaces can be skewed by multiple binding orientations and multiple interaction partners. The taxonomic distribution of interface types suggests that ancient interfaces common to the three major kingdoms of life are enriched by symmetric homodimers. The classification results are online at http://www.scoppi.org.

Localization of protein-binding sites within families of proteins.

D Korkin — 2006-10-22T11:10:51-00:00

Protein Sci, Vol. 14, No. 9. (September 2005), pp. 2350-2360.

We address the question of whether or not the positions of protein-binding sites on homologous protein structures are conserved irrespective of the identities of their binding partners. First, for each domain family in the Structural Classification of Proteins (SCOP), protein-binding sites are extracted from our comprehensive database of structurally defined binary domain interactions (PIBASE). Second, the binding sites within each family are superposed using a structural alignment of its members. Finally, the degree of localization of binding sites within each family is quantified by comparing it with localization expected by chance. We found that 72% of the 1847 SCOP domain families in PIBASE have binding sites with localization values greater than expected by chance. Moreover, 554 (30%) of these families have localizations that are statistically significant (i.e., more than four standard deviations away from the mean expected by chance). In contrast, only 144 (8%) families have significantly low localization. The absence of a significant correlation of the binding site localization with the average sequence and structural conservations in a family suggests that localization can be helpful for describing the functional diversity of protein-protein interactions, complementing measures of sequence and structural conservation. Consideration of the binding site localization may also result in spatial restraints for the modeling of protein assembly structures.

NMR spectroscopy of RNA.

B Fürtig — 2006-10-22T11:10:15-00:00

Chembiochem, Vol. 4, No. 10. (6 October 2003), pp. 936-962.

NMR spectroscopy is a powerful tool for studying proteins and nucleic acids in solution. This is illustrated by the fact that nearly half of all current RNA structures were determined by using NMR techniques. Information about the structure, dynamics, and interactions with other RNA molecules, proteins, ions, and small ligands can be obtained for RNA molecules up to 100 nucleotides. This review provides insight into the resonance assignment methods that are the first and crucial step of all NMR studies, into the determination of base-pair geometry, into the examination of local and global RNA conformation, and into the detection of interaction sites of RNA. Examples of NMR investigations of RNA are given by using several different RNA molecules to illustrate the information content obtainable by NMR spectroscopy and the applicability of NMR techniques to a wide range of biologically interesting RNA molecules.

Mapping protein-protein interactions in solution by NMR spectroscopy.

ER Zuiderweg — 2005-04-19T11:51:36-00:00

Biochemistry, Vol. 41, No. 1. (8 January 2002), pp. 1-7.

NMR is very well suited to the study of especially weak protein-protein interactions, as no crystallization is required. The available NMR methods to this end are reviewed and illustrated with applications from the recent biochemical literature: intermolecular NOEs, cross-saturation, chemical shift perturbation, dynamics and exchange perturbation, paramagnetic methods, and dipolar orientation. Most of these methods are now routinely applied for complexes with total molecular mass of 60 kDa and can likely be applied to systems up to 1000 kDa. A substantial fraction of complexes studied show distinct effects of induced fit affecting structural and dynamical properties beyond the contact interface.

Use of 19F NMR spectroscopy to screen chemical libraries for ligands that bind to proteins.

T Tengel — 2006-10-22T11:09:15-00:00

Org Biomol Chem, Vol. 2, No. 5. (7 March 2004), pp. 725-731.

Identification of compounds from chemical libraries that bind to macromolecules by use of NMR spectroscopy has gained increasing importance during recent years. A simple methodology based on (19)F NMR spectroscopy for the screening of ligands that bind to proteins, which also provides qualitative information about relative binding strengths and the presence of multiple binding sites, is presented here. A library of fluorinated compounds was assembled and investigated for binding to the two bacterial chaperones PapD and FimC, and also to human serum albumin (HSA). It was found that library members which are bound to a target protein could be identified directly from line broadening and/or induced chemical shifts in a single, one-dimensional (19)F NMR spectrum. The results obtained for binding to PapD using (19)F NMR spectroscopy agreed well with independent studies based on surface plasmon resonance, providing support for the versatility and accuracy of the technique. When the library was titrated to a solution of PapD chemical shift and linewidth changes were observed with increasing ligand concentration, which indicated the presence of several binding sites on PapD and enabled the assessment of relative binding strengths for the different ligands. Screening by (19)F NMR spectroscopy should thus be a valuable addition to existing NMR techniques for evaluation of chemical libraries in bioorganic and medicinal chemistry.

A multi-model approach to nucleic acid-based drug development.

I Gautherot — 2006-10-22T11:08:45-00:00

BioDrugs, Vol. 18, No. 1. (2004), pp. 37-50.

With the advent of functional genomics and the shift of interest towards sequence-based therapeutics, the past decades have witnessed intense research efforts on nucleic acid-mediated gene regulation technologies. Today, RNA interference is emerging as a groundbreaking discovery, holding promise for development of genetic modulators of unprecedented potency. Twenty-five years after the discovery of antisense RNA and ribozymes, gene control therapeutics are still facing developmental difficulties, with only one US FDA-approved antisense drug currently available in the clinic. Limited predictability of target site selection models is recognized as one major stumbling block that is shared by all of the so-called complementary technologies, slowing the progress towards a commercial product. Currently employed in vitro systems for target site selection include RNAse H-based mapping, antisense oligonucleotide microarrays, and functional screening approaches using libraries of catalysts with randomized target-binding arms to identify optimal ribozyme/DNAzyme cleavage sites. Individually, each strategy has its drawbacks from a drug development perspective. Utilization of message-modulating sequences as therapeutic agents requires that their action on a given target transcript meets criteria of potency and selectivity in the natural physiological environment. In addition to sequence-dependent characteristics, other factors will influence annealing reactions and duplex stability, as well as nucleic acid-mediated catalysis. Parallel consideration of physiological selection systems thus appears essential for screening for nucleic acid compounds proposed for therapeutic applications. Cellular message-targeting studies face issues relating to efficient nucleic acid delivery and appropriate analysis of response. For reliability and simplicity, prokaryotic systems can provide a rapid and cost-effective means of studying message targeting under pseudo-cellular conditions, but such approaches also have limitations. To streamline nucleic acid drug discovery, we propose a multi-model strategy integrating high-throughput-adapted bacterial screening, followed by reporter-based and/or natural cellular models and potentially also in vitro assays for characterization of the most promising candidate sequences, before final in vivo testing.

Studies of protein-ligand interactions by NMR.

J Clarkson — 2006-10-22T11:08:24-00:00

Biochem Soc Trans, Vol. 31, No. Pt 5. (October 2003), pp. 1006-1009.

Solution-state NMR has become an accepted method for studying the structure of small proteins in solution. This has resulted in over 3000 NMR-based co-ordinate sets being deposited in the Protein Databank. It is becoming increasingly apparent, however, that NMR is also a very powerful tool for accessing interactions between macromolecules and various ligands. These interactions can be assessed at a wide variety of levels, e.g. qualitative screening of libraries of pharmaceuticals and 'chemical shift mapping'. Dissociation constants can sometimes be obtained in such cases. Another example would be the complete three-dimensional structure determination of a protein-ligand complex. Here we briefly describe a few of the principles involved and illustrate the method with recent examples.

Protein-protein interaction analysis by nuclear magnetic resonance spectroscopy.

G Gao — 2006-10-22T11:07:48-00:00

Methods Mol Biol, Vol. 261 (2004), pp. 79-92.

Nuclear magnetic resonance (NMR) is a powerful technique to study protein-protein interactions in solution. Various methods have been developed and applied successfully for locating binding sites on proteins. The application of NMR chemical-shift perturbation to map the protein-protein interfaces is described in this chapter, providing a practical guideline that can be followed to carry out the experiments.

1H MR spectroscopy of the brain: absolute quantification of metabolites.

JF Jansen — 2006-10-22T11:06:44-00:00

Radiology, Vol. 240, No. 2. (August 2006), pp. 318-332.

Hydrogen 1 (1H) magnetic resonance (MR) spectroscopy enables noninvasive in vivo quantification of metabolite concentrations in the brain. Currently, metabolite concentrations are most often presented as ratios (eg, relative to creatine) rather than as absolute concentrations. Despite the success of this approach, it has recently been suggested that relative quantification may introduce substantial errors and can lead to misinterpretation of spectral data and to erroneous metabolite values. The present review discusses relevant methods to obtain absolute metabolite concentrations with a clinical MR system by using single-voxel spectroscopy or chemical shift imaging. Important methodological aspects in an absolute quantification strategy are addressed, including radiofrequency coil properties, calibration procedures, spectral fitting methods, cerebrospinal fluid content correction, macromolecule suppression, and spectral editing. Techniques to obtain absolute concentrations are now available and can be successfully applied in clinical practice. Although the present review is focused on 1H MR spectroscopy of the brain, a large part of the methodology described can be applied to other tissues as well.

Virtual drug discovery and development for neglected diseases through public-private partnerships.

S Nwaka — 2006-10-21T14:23:37-00:00

Nat Rev Drug Discov, Vol. 2, No. 11. (November 2003), pp. 919-928.

Antimalarial drug discovery: efficacy models for compound screening.

DA Fidock — 2006-10-21T14:22:56-00:00

Nat Rev Drug Discov, Vol. 3, No. 6. (June 2004), pp. 509-520.

Drug discovery and beyond: the role of public-private partnerships in improving access to new malaria medicines

Solomon Nwaka — 2005-09-03T14:49:08-00:00

Transactions of the Royal Society of Tropical Medicine and Hygiene, Vol. 99, No. Supplement 1. (2005), pp. 20-29.

SummaryTraditional pharmaceutical research and development (R&D) strategy has failed to address the desperate need for new antimalarial drugs. The populations affected are too poor to attract commercially-driven R&D. Over the last few years, a new model, the public-private partnership for product development, has radically changed the antimalarial R&D landscape. The partnerships bring together academic and industry expertise with funding from governmental, philanthropic and charitable sources. The Medicines for Malaria Venture, a not-for-profit foundation based in Geneva, aims to develop new antimalarials for developing countries through public-private partnership. It is currently managing a portfolio of around 20 projects at various stages of development. However, as in all drug R&D, some of these projects will fail. The portfolio approach helps to maximize the chances of success, but there are obvious challenges, including financial and managerial ones. Proactive management of the two vital interfaces in the drug supply chain is important for success. Upstream, basic research must be aligned with translational research in order to ensure a continuous supply of leads into the development pipeline. Meanwhile, downstream, drug discovery and development must be aligned with access to ensure optimal health impact. All stages require partnership, sustainable financing and the engagement of disease-endemic countries. The recent G8 report on Africa has lent support to mechanisms aimed at improving health and achieving the Millenium Development Goals.

Evaluation of library ranking efficacy in virtual screening.

M Kontoyianni — 2005-05-10T15:15:33-00:00

J Comput Chem, Vol. 26, No. 1. (15 January 2005), pp. 11-22.

We present the results of a comprehensive study in which we explored how the docking procedure affects the performance of a virtual screening approach. We used four docking engines and applied 10 scoring functions to the top-ranked docking solutions of seeded databases against six target proteins. The scores of the experimental poses were placed within the total set to assess whether the scoring function required an accurate pose to provide the appropriate rank for the seeded compounds. This method allows a direct comparison of library ranking efficacy. Our results indicate that the LigandFit/Ligscore1 and LigandFit/GOLD docking/scoring combinations, and to a lesser degree FlexX/FlexX, Glide/Ligscore1, DOCK/PMF (Tripos implementation), LigandFit1/Ligscore2 and LigandFit/PMF (Tripos implementation) were able to retrieve the highest number of actives at a 10% fraction of the database when all targets were looked upon collectively. We also show that the scoring functions rank the observed binding modes higher than the inaccurate poses provided that the experimental poses are available. This finding stresses the discriminatory ability of the scoring algorithms, when better poses are available, and suggests that the number of false positives can be lowered with conformers closer to bioactive ones.

Protemot: prediction of protein binding sites with automatically extracted geometrical templates.

DT Chang — 2006-10-21T13:24:09-00:00

Nucleic Acids Res, Vol. 34, No. Web Server issue. (1 July 2006)

Geometrical analysis of protein tertiary substructures has been an effective approach employed to predict protein binding sites. This article presents the Protemot web server that carries out prediction of protein binding sites based on the structural templates automatically extracted from the crystal structures of protein-ligand complexes in the PDB (Protein Data Bank). The automatic extraction mechanism is essential for creating and maintaining a comprehensive template library that timely accommodates to the new release of PDB as the number of entries continues to grow rapidly. The design of Protemot is also distinctive by the mechanism employed to expedite the analysis process that matches the tertiary substructures on the contour of the query protein with the templates in the library. This expediting mechanism is essential for providing reasonable response time to the user as the number of entries in the template library continues to grow rapidly due to rapid growth of the number of entries in PDB. This article also reports the experiments conducted to evaluate the prediction power delivered by the Protemot web server. Experimental results show that Protemot can deliver a superior prediction power than a web server based on a manually curated template library with insufficient quantity of entries. Availability: http://protemot.csie.ntu.edu.tw/step1.cgi http://bioinfo.mc.ntu.edu.tw/protemot/step1.cgi.