Protein structural alignments and functional genomics

Structural genomics-the systematic solution of structures of the proteins of an organism-will increasingly often produce molecules of unknown function with no close relative of known function. Prediction of protein function from structure has thereby become a challenging problem of computational molecular biology. The strong conservation of active site conformations in homologous proteins suggests a method for identifying them. This depends on the relationship between size and goodness-of-fit of aligned substructures in homologous proteins. For all pairs of proteins studied, the root-mean-square deviation (RMSD) as a function of the number of residues aligned varies exponentially for large common substructures and linearly for small common substructures. The exponent of the dependence at large common substructures is well correlated with the RMSD of the core as originally calculated by Chothia and Lesk (EMBO J 1986;5:823-826), affording the possibility of reconciling different structural alignment procedures. In the region of small common substructures, reduced aligned subsets define active sites and can be used to suggest the locations of active sites in homologous proteins.     

A network module-based method for identifying cancer prognostic signatures

Discovering robust prognostic gene signatures as biomarkers using genomics data can be challenging. We have developed a simple but efficient method for discovering prognostic biomarkers in cancer gene expression data sets using modules derived from a highly reliable gene functional interaction network. When applied to breast cancer, we discover a novel 31-gene signature associated with patient survival. The signature replicates across 5 independent gene expression studies, and outperforms 48 published gene signatures. When applied to ovarian cancer, the algorithm identifies a 75-gene signature associated with patient survival. A Cytoscape plugin implementation of the signature discovery method is available at http://wiki.reactome.org/index.php/Reactome_FI_Cytoscape_Plugin     

Extracting multiple structural alignments from pairwise alignments: a comparison of a rigorous and a heuristic approach

MOTIVATION: Multiple structural alignments (MSTAs) provide position-specific information on the sequence variability allowed by protein folds. This information can be exploited to better understand the evolution of proteins and the physical chemistry of polypeptide folding. Most MSTA methods rely on a pre-computed library of pairwise alignments. This library will in general contain conflicting residue equivalences not all of which can be realized in the final MSTA. Hence to build a consistent MSTA, these methods have to select a conflict-free subset of equivalences. RESULTS: Using a dataset with 327 families from SCOP 1.63 we compare the ability of two different methods to select an optimal conflict-free subset of equivalences. One is an implementation of Reinert et al.'s integer linear programming formulation (ILP) of the maximum weight trace problem (Reinert et al., 1997, Proc. 1st Ann. Int. Conf. Comput. Mol. Biol. (RECOMB-97), ACM Press, New York). This ILP formulation is a rigorous approach but its complexity is difficult to predict. The other method is T-Coffee (Notredame et al., 2000) which uses a heuristic enhancement of the equivalence weights which allow it to use the speed and simplicity of the progressive alignment approach while still incorporating information of all alignments in each step of building the MSTA. We find that although the ILP formulation consistently selects a more optimal set of conflict-free equivalences, the differences are small and the quality of the resulting MSTAs are essentially the same for both methods. Given its speed and predictable complexity, our results show that T-Coffee is an attractive alternative for producing high-quality MSTAs.     

Gleaning structural and functional information from correlations in protein multiple sequence alignments

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CpG_MI: a novel approach for identifying functional CpG islands in mammalian genomes

CpG islands (CGIs) are CpG-rich regions compared to CpG-depleted bulk DNA of mammalian genomes and are generally regarded as the epigenetic regulatory regions in association with unmethylation, promoter activity and histone modifications. Accurate identification of CpG islands with epigenetic regulatory function in bulk genomes is of wide interest. Here, the common features of functional CGIs are identified using an average mutual information method to differentiate functional CGIs from the remaining CGIs. A new approach (CpG mutual information, CpG_MI) was further explored to identify functional CGIs based on the cumulative mutual information of physical distances between two neighboring CpGs. Compared to current approaches, CpG_MI achieved the highest prediction accuracy. This approach also identified new functional CGIs overlapping with gene promoter regions which were missed by other algorithms. Nearly all CGIs identified by CpG_MI overlapped with histone modification marks. CpG_MI could also be used to identify potential functional CGIs in other mammalian genomes, as the CpG dinucleotide contents and cumulative mutual information distributions are almost the same among six mammalian genomes in our analysis. It is a reliable quantitative tool for the identification of functional CGIs from bulk genomes and helps in understanding the relationships between genomic functional elements and epigenomic modifications.     

A novel data mining method to identify assay-specific signatures in functional genomic studies

Background:  

The highly dimensional data produced by functional genomic (FG) studies makes it difficult to visualize relationships between gene products and experimental conditions (i.e., assays). Although dimensionality reduction methods such as principal component analysis (PCA) have been very useful, their application to identify assay-specific signatures has been limited by the lack of appropriate methodologies. This article proposes a new and powerful PCA-based method for the identification of assay-specific gene signatures in FG studies.     

From analysis of protein structural alignments toward a novel approach to align protein sequences

Alignment of protein sequences is a key step in most computational methods for prediction of protein function and homology-based modeling of three-dimensional (3D)-structure. We investigated correspondence between "gold standard" alignments of 3D protein structures and the sequence alignments produced by the Smith-Waterman algorithm, currently the most sensitive method for pair-wise alignment of sequences. The results of this analysis enabled development of a novel method to align a pair of protein sequences. The comparison of the Smith-Waterman and structure alignments focused on their inner structure and especially on the continuous ungapped alignment segments, "islands" between gaps. Approximately one third of the islands in the gold standard alignments have negative or low positive score, and their recognition is below the sensitivity limit of the Smith-Waterman algorithm. From the alignment accuracy perspective, the time spent by the algorithm while working in these unalignable regions is unnecessary. We considered features of the standard similarity scoring function responsible for this phenomenon and suggested an alternative hierarchical algorithm, which explicitly addresses high scoring regions. This algorithm is considerably faster than the Smith-Waterman algorithm, whereas resulting alignments are in average of the same quality with respect to the gold standard. This finding shows that the decrease of alignment accuracy is not necessarily a price for the computational efficiency.     

Considerations in the identification of functional RNA structural elements in genomic alignments

Background  

Accurate identification of novel, functional noncoding (nc) RNA features in genome sequence has proven more difficult than for exons. Current algorithms identify and score potential RNA secondary structures on the basis of thermodynamic stability, conservation, and/or covariance in sequence alignments. Neither the algorithms nor the information gained from the individual inputs have been independently assessed. Furthermore, due to issues in modelling background signal, it has been difficult to gauge the precision of these algorithms on a genomic scale, in which even a seemingly small false-positive rate can result in a vast excess of false discoveries.     

A novel method for identifying hydrophobicity on fungal surfaces

Fungal surface hydrophobicity has many ecological functions and water contact angles measurement is a direct and simple approach for its characterization. The objective of this study was to evaluate if in-vitro growth conditions coupled with versatile image analysis allows for more accurate fungal contact angle measurements. Fungal cultures were grown on agar slide media and contact angles were measured utilizing a modified microscope and digital camera setup. Advanced imaging software was adopted for contact angle determination. Contact angles were observed in hydrophobic, hydrophilic and a newly created chronoamphiphilic class containing fungi taxa with changing surface hydrophobicity. Previous methods are unable to detect slight changes in hydrophobicity, which provide vital information of hydrophobicity expression patterns. Our method allows for easy and efficient characterization of hydrophobicity, minimizing disturbance to cultures and quantifying subtle variation in hydrophobicity.     

Screening and structural and functional investigation of a novel ferritin from Phascolosoma esculenta

Ferritins are primary iron storage proteins and play a crucial role in iron storage and detoxification. Yeast two‐hybrid method was employed to screen the cDNA library of Phascolosoma esculenta. Sequence of positive colony FER147 was analyzed. The higher similarity and conserved motifs for ferritin indicated that it belonged to a new member of ferritin family. The interaction between Ferritin and Fer147 was further confirmed through co‐immunoprecipitation. The pET‐28a‐FER147 prokaryotic expression vector was constructed. The expressed recombinant Fer147 was then isolated, purified, and refolded. When ferritins were treated by different heavy metals, several detection methods, including scanning electron microscopy (SEM), circular dichroism (CD), and inductively coupled plasma–mass spectrometry (ICP‐MS) were applied to examine the structures and functions of the new protein Fer147, recombinant P. esculenta ferritin (Rferritin), and natural horse‐spleen ferritin (Hferritin). SEM revealed that the three ferritin aggregates changed obviously after different heavy metals treatment, meanwhile, a little different in aggregates were detected when the ferritins were trapped by the same heavy metal. Hence, changes in aggregation structure of the three proteins are related to the nature of the different heavy metals and the interaction between the heavy metals and the three ferritins. CD data suggested that the secondary structure of the three ferritins hardly changed after different heavy metals were trapped. ICP–MS revealed that the ferritins exhibit different enrichment capacities for various heavy metals. In particular, the enrichment capacity of the recombinant Fer147 and Rferritin is much higher than that of hferritin.     

Identification and characterisation of a novel acylpeptide hydrolase from Sulfolobus solfataricus: structural and functional insights

A novel acylpeptide hydrolase, named APEH-3(Ss), was isolated from the hypertermophilic archaeon Sulfolobus solfataricus. APEH is a member of the prolyl oligopeptidase family which catalyzes the removal of acetylated amino acid residues from the N terminus of oligopeptides. The purified enzyme shows a homotrimeric structure, unique among the associate partners of the APEH cluster and, in contrast to the archaeal APEHs which show both exo/endo peptidase activities, it appears to be a "true" aminopeptidase as exemplified by its mammalian counterparts, with which it shares a similar substrate specificity. Furthermore, a comparative study on the regulation of apeh gene expression, revealed a significant but divergent alteration in the expression pattern of apeh-3(Ss) and apeh(Ss) (the gene encoding the previously identified APEH(Ss) from S. solfataricus), which is induced in response to various stressful growth conditions. Hence, both APEH enzymes can be defined as stress-regulated proteins which play a complementary role in enabling the survival of S. solfataricus cells under different conditions. These results provide new structural and functional insights into S. solfataricus APEH, offering a possible explanation for the multiplicity of this enzyme in Archaea.     

SimShift: identifying structural similarities from NMR chemical shifts

MOTIVATION: An important quantity that arises in NMR spectroscopy experiments is the chemical shift. The interpretation of these data is mostly done by human experts; to our knowledge there are no algorithms that predict protein structure from chemical shift sequences alone. One approach to facilitate this process could be to compare two such sequences, where the structure of one protein has already been resolved. Our claim is that similarity of chemical shifts thereby found implies structural similarity of the respective proteins. RESULTS: We present an algorithm to identify structural similarities of proteins by aligning their associated chemical shift sequences. To evaluate the correctness of our predictions, we propose a benchmark set of protein pairs that have high structural similarity, but low sequence similarity (because with high sequence similarity the structural similarities could easily be detected by a sequence alignment algorithm). We compare our results with those of HHsearch and SSEA and show that our method outperforms both in >50% of all cases.     

SEGID: identifying interesting segments in (multiple) sequence alignments

SUMMARY: SEGID is a tool for finding conserved regions (regions of high scores) for a given (multiple) sequence alignment. It takes a (multiple) sequence alignment as its input and converts the alignment into a sequence of numbers, where each number is the alignment score of a column. Three algorithms are used to identify regions of high scores. A graphical interface is provided to present those identified regions. AVAILABILITY: Free from http://www.cs.cityu.edu.hk/~lwang/segid/subject to copyright restrictions.     

APDB: a novel measure for benchmarking sequence alignment methods without reference alignments

MOTIVATION: We describe APDB, a novel measure for evaluating the quality of a protein sequence alignment, given two or more PDB structures. This evaluation does not require a reference alignment or a structure superposition. APDB is designed to efficiently and objectively benchmark multiple sequence alignment methods. RESULTS: Using existing collections of reference multiple sequence alignments and existing alignment methods, we show that APDB gives results that are consistent with those obtained using conventional evaluations. We also show that APDB is suitable for evaluating sequence alignments that are structurally equivalent. We conclude that APDB provides an alternative to more conventional methods used for benchmarking sequence alignment packages.     

ZRANB2: structural and functional insights into a novel splicing protein

ZRANB2 was identified originally in a differential display experiment on 2-day and 10-day primary cultures of rat juxtaglomerular cells. During prolonged culture it was found to undergo down-regulation in concert with renin, the archetypical constituent of these cells. ZRANB2 has two zinc fingers that form a novel fold and show striking homology to Ran-binding protein domains. Human ZRANB2 mRNA is alternatively spliced to give two variants with different 3' ends. ZRANB2 has homologues across a range of species, the N-terminal end being particularly conserved. ZRANB2 is present in the nucleus of human cells. It binds to mRNA, as well as the essential splicing factors U170K and U2AF(35) and the novel splicing component SFRS17A (formerly known as XE7). ZRANB2 is one of 20 genes up-regulated in grade III ovarian serous papillary carcinoma. Here, we review current knowledge surrounding ZRANB2.     

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets

Background

Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type (‘outlier genes’), a hallmark of potential oncogenes.

Methodology

A new statistical method (the gene tissue index, GTI) was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29) of these genes, and 17 of these 19 genes (90%) showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target.

Conclusions/Significance

Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is implemented in an R package (Text S1).     

Antibody-linked polymerase assay on protein blots: a novel method for identifying polymerases following SDS-polyacrylamide gel electrophoresis

We describe a method for correlating polymerase activity with a particular polypeptide band in an SDS-polyacrylamide gel which does not require renaturation of the SDS-denatured enzyme. The method involves the following steps: (i) transfer of proteins from an SDS-polyacrylamide gel onto nitrocellulose; (ii) incubation with excess antiserum raised against a partially purified polymerase preparation to link one Fab site of an antibody molecule to the denatured enzyme on the nitrocellulose; (iii) binding of native polymerase to the other Fab site of the antibody molecule in the immune complex to generate a specific polymerase 'sandwich'; (iv) assaying of the nitrocellulose filter for antibody-linked native polymerase activity using an appropriate template and a radioactive substrate followed by treatment with trichloroacetic acid to precipitate in situ the radioactive product. The essential feature of this method is that the use of both non-specific anti-polymerase serum and a partially purified enzyme preparation is sufficient to allow identification of a specific protein following SDS-polyacrylamide gel electrophoresis. This antibody-linked polymerase assay has been developed to identify a 130,000-dalton RNA-dependent RNA polymerase from cowpea leaves. Possible applications of this type of assay as a tool for identifying a wide variety of proteins are discussed.     

SAD--a normalized structural alignment database: improving sequence-structure alignments

MOTIVATION: We present a structural alignment database that is specifically targeted for use in derivation and optimization of sequence-structure alignment algorithms for homology modeling. We have paid attention to ensure that fold-space is properly sampled, that the structures involved in alignments are of significant resolution (better than 2.5 A) and the alignments are accurate and reliable. RESULTS: Alignments have been taken from the HOMSTRAD, BAliBASE and SCOP-based Gerstein databases along with alignments generated by a global structural alignment method described here. In order to discriminate between equivalent alignments from these different sources, we have developed a novel scoring function, Contact Alignment Quality score, which evaluates trial alignments by their statistical significance combined with their ability to reproduce conserved three-dimensional residue contacts. The resulting non-redundant, unbiased database contains 1927 alignments from across fold-space with high-resolution structures and a wide range of sequence identities. AVAILABILITY: The database can be interactively queried either over the web at http://abagyan.scripps.edu/lab/web/sad/show.cgi or by using MySQL, and is also available to download over the web.