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 beta-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.

FRankenstein becomes a cyborg: the automatic recombination and realignment of fold recognition models in CASP6.

In the course of CASP6, we generated models for all targets using a new version of the "FRankenstein's monster approach." Previously (in CASP5) we were able to build many very accurate full-atom models by selection and recombination of well-folded fragments obtained from crude fold recognition (FR) results, followed by optimization of the sequence-structure fit and assessment of alternative alignments on the structural level. This procedure was however very arduous, as most of the steps required extensive visual and manual input from the human modeler. Now, we have automated the most tedious steps, such as superposition of alternative models, extraction of best-scoring fragments, and construction of a hybrid "monster" structure, as well as generation of alternative alignments in the regions that remain poorly scored in the refined hybrid model. We have also included the ROSETTA method to construct those parts of the target for which no reasonable structures were generated by FR methods (such as long insertions and terminal extensions). The analysis of successes and failures of the current version of the FRankenstein approach in modeling of CASP6 targets reveals that the considerably streamlined and automated method performs almost as well as the initial, mostly manual version, which suggests that it may be a useful tool for accurate protein structure prediction even in the hands of nonexperts.

Probabilistic cross-link analysis and experiment planning for high-throughput elucidation of protein structure.

Emerging high-throughput techniques for the characterization of protein and protein-complex structures yield noisy data with sparse information content, placing a significant burden on computation to properly interpret the experimental data. One such technique uses cross-linking (chemical or by cysteine oxidation) to confirm or select among proposed structural models (e.g., from fold recognition, ab initio prediction, or docking) by testing the consistency between cross-linking data and model geometry. This paper develops a probabilistic framework for analyzing the information content in cross-linking experiments, accounting for anticipated experimental error. This framework supports a mechanism for planning experiments to optimize the information gained. We evaluate potential experiment plans using explicit trade-offs among key properties of practical importance: discriminability, coverage, balance, ambiguity, and cost. We devise a greedy algorithm that considers those properties and, from a large number of combinatorial possibilities, rapidly selects sets of experiments expected to discriminate pairs of models efficiently. In an application to residue-specific chemical cross-linking, we demonstrate the ability of our approach to plan experiments effectively involving combinations of cross-linkers and introduced mutations. We also describe an experiment plan for the bacteriophage lambda Tfa chaperone protein in which we plan dicysteine mutants for discriminating threading models by disulfide formation. Preliminary results from a subset of the planned experiments are consistent and demonstrate the practicality of planning. Our methods provide the experimenter with a valuable tool (available from the authors) for understanding and optimizing cross-linking experiments.

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

BACKGROUND: Combination 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. RESULTS: In 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. CONCLUSIONS: We 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.

A "FRankenstein's monster" approach to comparative modeling: merging the finest fragments of Fold-Recognition models and iterative model refinement aided by 3D structure evaluation.

We applied a new multi-step protocol to predict the structures of all targets during CASP5, regardless of their potential category. 1) We used diverse fold-recognition (FR) methods to generate initial target-template alignments, which were converted into preliminary full-atom models by comparative modeling. All preliminary models were evaluated (scored) by VERIFY3D to identify well- and poorly-folded fragments. 2) Preliminary models with similar 3D folds were superimposed, poorly-scoring regions were deleted and the "average model" structure was created by merging the remaining segments. All template structures reported by FR were superimposed and a composite multiple-structure template was created from the most conserved fragments. 3). The average model was superimposed onto the composite template and the structure-based target-template alignment was inferred. This alignment was used to build a new (intermediate) comparative model of the target, again scored with VERIFY3D. 4) For all poorly scoring regions series of alternative alignments were generated by progressively shifting the "unfit" sequence fragment in either direction. Here, we considered additional information, such as secondary structure, placement of insertions and deletions in loops, conservation of putative catalytic residues, and the necessity to obtain a compact, well-folded structure. For all alternative alignments, new models were built and evaluated. 5) All models were superimposed and the "FRankenstein's monster" (FR, fold recognition) model was built from best-scoring segments. The final model was obtained after limited energy minimization to remove steric clashes between sidechains from different fragments. The novelty of this approach is in the focus on "vertical" recombination of structure fragments, typical for the ab initio field, rather than "horizontal" sequence alignment typical for comparative modeling. We tested the usefulness of the "FRankenstein" approach for non-expert predictors: only the leader of our team had considerable experience in protein modeling - he registered as a separate group (020) and submitted models built only by himself. At the onset of CASP5, the other five members of the team (students) had very little or no experience with modeling. They followed the same protocol in a deliberately naïve way. In the fourth step they used solely the VERIFY3D criterion to compare their models and the leader's model (the latter regarded only as one of the many alternatives) and generated the hybrid or selected only one model for submission (group 517). In order to compare our protocol with the traditional "one target-one template-one alignment" approach, we submitted (as a separate group 242) models selected from those automatically generated by all CAFASP servers (i.e. obtained without any human intervention). Here, we compare the results obtained by the three "groups", describe successes and failures of the "FRankenstein" approach and discuss future developments of comparative modeling. The automatic version of our multi-step protocol is being developed as a meta-server; the prototype is freely available at http://genesilico.pl/meta/.

STRUCLA: a WWW meta-server for protein structure comparison and evolutionary classification.

MOTIVATION: Evolutionary relationships of proteins have long been derived from the alignment of protein sequences. But from the view of function, most restraints of evolutionary divergence operate at the level of tertiary structure. It has been demonstrated that quantitative measures of dissimilarity in families of structurally similar proteins can be applied to the construction of trees from a comparison of their three-dimensional structures. However, no convenient tool is publicly available to carry out such analyses. RESULTS: We developed STRUCLA (STRUcture CLAssification), a WWW tool for generation of trees based on evolutionary distances inferred from protein structures according to various methods. The server takes as an input a list of PDB files or the initial alignment of protein coordinates provided by the user (for instance exported from SWISS PDB VIEWER). The user specifies the distance cutoff and selects the distance measures. The server returns series of unrooted trees in the NEXUS format and corresponding distance matrices, as well as a consensus tree. The results can be used as an alternative and a complement to a fixed hierarchy of current protein structure databases. It can complement sequence-based phylogenetic analysis in the 'twilight zone of homology', where amino acid sequences are too diverged to provide reliable relationships.

GeneSilico protein structure prediction meta-server.

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

Characterization of the cofactor-binding site in the SPOUT-fold methyltransferases by computational docking of S-adenosylmethionine to three crystal structures.

BACKGROUND: There are several evolutionarily unrelated and structurally dissimilar superfamilies of S-adenosylmethionine (AdoMet)-dependent methyltransferases (MTases). A new superfamily (SPOUT) has been recently characterized on a sequence level and three structures of its members (1gz0, 1ipa, and 1k3r) have been solved. However, none of these structures include the cofactor or the substrate. Due to the strong evolutionary divergence and the paucity of experimental information, no confident predictions of protein-ligand and protein-substrate interactions could be made, which hampered the study of sequence-structure-function relationships in the SPOUT superfamily. RESULTS: We used the computational docking program AutoDock to identify the AdoMet-binding site on the surface of three MTase structures. We analyzed the sequence divergence in two distinct lineages of the SPOUT superfamily in the context of surface features and preferred cofactor binding mode to propose specific function for the conserved residues. CONCLUSION: Our docking analysis has confidently predicted the common AdoMet-binding site in three remotely related proteins structures. In the vicinity of the cofactor-binding site, subfamily-conserved grooves were identified on the protein surface, suggesting location of the target-binding/catalytic site. Functionally important residues were inferred and a general reaction mechanism, involving conformational change of a glycine-rich loop, was proposed.