Janusz M. Bujnicki

Pcons: A neural-network–based consensus predictor that improves fold recognition

During recent years many protein fold recognition methods have been developed, based on different algorithms and using various kinds of information. To examine the performance of these methods several evaluation experiments have been conducted. These include blind tests in CASP/CAFASP, large scale benchmarks, and long‐term, continuous assessment with newly solved protein structures. These studies confirm the expectation that for different targets different methods produce the best predictions, and the final prediction accuracy could be improved if the available methods were combined in a perfect manner. In this article a neural‐network‐based consensus predictor, Pcons, is presented that attempts this task. Pcons attempts to select the best model out of those produced by six prediction servers, each using different methods. Pcons translates the confidence scores reported by each server into uniformly scaled values corresponding to the expected accuracy of each model. The translated scores as well as the similarity between models produced by different servers is used in the final selection. According to the analysis based on two unrelated sets of newly solved proteins, Pcons outperforms any single server by generating ∼8%–10% more correct predictions. Furthermore, the specificity of Pcons is significantly higher than for any individual server. From analyzing different input data to Pcons it can be shown that the improvement is mainly attributable to measurement of the similarity between the different models. Pcons is freely accessible for the academic community through the protein structure‐prediction metaserver at http://bioinfo.pl/meta/.

Transcriptome Profile of Human Colorectal Adenomas

Colorectal cancers are believed to arise predominantly from adenomas. Although these precancerous lesions have been subjected to extensive clinical, pathologic, and molecular analyses, little is currently known about the global gene expression changes accompanying their formation. To characterize the molecular processes underlying the transformation of normal colonic epithelium, we compared the transcriptomes of 32 prospectively collected adenomas with those of normal mucosa from the same individuals. Important differences emerged not only between the expression profiles of normal and adenomatous tissues but also between those of small and large adenomas. A key feature of the transformation process was the remodeling of the Wnt pathway reflected in patent overexpression and underexpression of 78 known components of this signaling cascade. The expression of 19 Wnt targets was closely correlated with clear up-regulation of KIAA1199, whose function is currently unknown. In normal mucosa, KIAA1199 expression was confined to cells in the lower portion of intestinal crypts, where Wnt signaling is physiologically active, but it was markedly increased in all adenomas, where it was expressed in most of the epithelial cells, and in colon cancer cell lines, it was markedly reduced by inactivation of the β-catenin/T-cell factor(s) transcription complex, the pivotal mediator of Wnt signaling. Our transcriptomic profiles of normal colonic mucosa and colorectal adenomas shed new light on the early stages of colorectal tumorigenesis and identified KIAA1199 as a novel target of the Wnt signaling pathway and a putative marker of colorectal adenomatous transformation. (Mol Cancer Res 2007;5(12):1263–75)

IAPs contain an evolutionarily conserved ubiquitin-binding domain that regulates NF-kappaB as well as cell survival and oncogenesis.

The covalent attachment of ubiquitin to target proteins influences various cellular processes, including DNA repair, NF-κB signalling and cell survival. The most common mode of regulation by ubiquitin-conjugation involves specialized ubiquitin-binding proteins that bind to ubiquitylated proteins and link them to downstream biochemical processes. Unravelling how the ubiquitin-message is recognized is essential because aberrant ubiquitin-mediated signalling contributes to tumour formation. Recent evidence indicates that inhibitor of apoptosis (IAP) proteins are frequently overexpressed in cancer and their expression level is implicated in contributing to tumorigenesis, chemoresistance, disease progression and poor patient-survival. Here, we have identified an evolutionarily conserved ubiquitin-associated (UBA) domain in IAPs, which enables them to bind to Lys 63-linked polyubiquitin. We found that the UBA domain is essential for the oncogenic potential of cIAP1, to maintain endothelial cell survival and to protect cells from TNF-α-induced apoptosis. Moreover, the UBA domain is required for XIAP and cIAP2–MALT1 to activate NF-κB. Our data suggest that the UBA domain of cIAP2–MALT1 stimulates NF-κB signalling by binding to polyubiquitylated NEMO. Significantly, 98% of all cIAP2–MALT1 fusion proteins retain the UBA domain, suggesting that ubiquitin-binding contributes to the oncogenic potential of cIAP2–MALT1 in MALT lymphoma. Our data identify IAPs as ubiquitin-binding proteins that contribute to ubiquitin-mediated cell survival, NF-κB signalling and oncogenesis.

MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins

BackgroundIntrinsically unstructured proteins (IUPs) lack a well-defined three-dimensional structure. Some of them may assume a locally stable structure under specific conditions, e.g. upon interaction with another molecule, while others function in a permanently unstructured state. The discovery of IUPs challenged the traditional protein structure paradigm, which stated that a specific well-defined structure defines the function of the protein. As of December 2011, approximately 60 methods for computational prediction of protein disorder from sequence have been made publicly available. They are based on different approaches, such as utilizing evolutionary information, energy functions, and various statistical and machine learning methods.ResultsGiven the diversity of existing intrinsic disorder prediction methods, we decided to test whether it is possible to combine them into a more accurate meta-prediction method. We developed a method based on arbitrarily chosen 13 disorder predictors, in which the final consensus was weighted by the accuracy of the methods. We have also developed a disorder predictor GSmetaDisorder3D that used no third-party disorder predictors, but alignments to known protein structures, reported by the protein fold-recognition methods, to infer the potentially structured and unstructured regions. Following the success of our disorder predictors in the CASP8 benchmark, we combined them into a meta-meta predictor called GSmetaDisorderMD, which was the top scoring method in the subsequent CASP9 benchmark.ConclusionsA series of disorder predictors described in this article is available as a MetaDisorder web server at http://iimcb.genesilico.pl/metadisorder/. Results are presented both in an easily interpretable, interactive mode and in a simple text format suitable for machine processing.

RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

Phylogenomic identification of five new human homologs of the DNA repair enzyme AlkB

BackgroundCombination of biochemical and bioinformatic analyses led to the discovery of oxidative demethylation – a novel DNA repair mechanism catalyzed by the Escherichia coli AlkB protein and its two human homologs, hABH2 and hABH3. This discovery was based on the prediction made by Aravind and Koonin that AlkB is a member of the 2OG-Fe2+ oxygenase superfamily.ResultsIn this article, we report identification and sequence analysis of five human members of the (2OG-Fe2+) oxygenase superfamily designated here as hABH4 through hABH8. These experimentally uncharacterized and poorly annotated genes were not associated with the AlkB family in any database, but are predicted here to be phylogenetically and functionally related to the AlkB family (and specifically to the lineage that groups together hABH2 and hABH3) rather than to any other oxygenase family. Our analysis reveals the history of ABH gene duplications in the evolution of vertebrate genomes.ConclusionsWe hypothesize that hABH 4–8 could either be back-up enzymes for hABH1-3 or may code for novel DNA or RNA repair activities. For example, enzymes that can dealkylate N3-methylpurines or N7-methylpurines in DNA have not been described. Our analysis will guide experimental confirmation of these novel human putative DNA repair enzymes.

ModeRNA: a tool for comparative modeling of RNA 3D structure

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available.

ORFeus: detection of distant homology using sequence profiles and predicted secondary structure

ORFeus is a fully automated, sensitive protein sequence similarity search server available to the academic community via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/). The goal of the development of ORFeus was to increase the sensitivity of the detection of distantly related protein families. Predicted secondary structure information was added to the information about sequence conservation and variability, a technique known from hybrid threading approaches. The accuracy of the meta profiles created this way is compared with profiles containing only sequence information and with the standard approach of aligning a single sequence with a profile. Additionally, the alignment of meta profiles is more sensitive in detecting remote homology between protein families than if aligning two sequence-only profiles or if aligning a profile with a sequence. The specificity of the alignment score is improved in the lower specificity range compared with the robust sequence-only profiles.

LiveBench-1: continuous benchmarking of protein structure prediction servers.

We present a novel, continuous approach aimed at the large‐scale assessment of the performance of available fold‐recognition servers. Six popular servers were investigated: PDB‐Blast, FFAS, T98‐lib, GenTHREADER, 3D‐PSSM, and INBGU. The assessment was conducted using as prediction targets a large number of selected protein structures released from October 1999 to April 2000. A target was selected if its sequence showed no significant similarity to any of the proteins previously available in the structural database. Overall, the servers were able to produce structurally similar models for one‐half of the targets, but significantly accurate sequence‐structure alignments were produced for only one‐third of the targets. We further classified the targets into two sets: easy and hard. We found that all servers were able to find the correct answer for the vast majority of the easy targets if a structurally similar fold was present in the servers fold libraries. However, among the hard targets—where standard methods such as PSI‐BLAST fail—the most sensitive fold‐recognition servers were able to produce similar models for only 40% of the cases, half of which had a significantly accurate sequence‐structure alignment. Among the hard targets, the presence of updated libraries appeared to be less critical for the ranking. An “ideally combined consensus” prediction, where the results of all servers are considered, would increase the percentage of correct assignments by 50%. Each server had a number of cases with a correct assignment, where the assignments of all the other servers were wrong. This emphasizes the benefits of considering more than one server in difficult prediction tasks. The LiveBench program (http://BioInfo.PL/LiveBench) is being continued, and all interested developers are cordially invited to join.

Trm7p catalyses the formation of two 2′‐O‐methylriboses in yeast tRNA anticodon loop

The genome of Saccharomyces cerevisiae encodes three close homologues of the Escherichia coli 2′‐O‐rRNA methyltransferase FtsJ/RrmJ, designated Trm7p, Spb1p and Mrm2p. We present evidence that Trm7p methylates the 2′‐O‐ribose of nucleotides at positions 32 and 34 of the tRNA anticodon loop, both in vivo and in vitro. In a trm7Δ strain, which is viable but grows slowly, translation is impaired, thus indicating that these tRNA modifications could be important for translation efficiency. We discuss the emergence of a family of three 2′‐O‐RNA methyltransferases in Eukaryota and one in Prokaryota from a common ancestor. We propose that each eukaryotic enzyme is located in a different cell compartment, in which it would methylate a different RNA that can adopt a very similar secondary structure.