Efficient identification of side-chain patterns using a multidimensional index tree

Convergent evolution often produces similar functional sites in nonhomologous proteins. The identification of these sites can make it possible to infer function from structure, to pinpoint the location of a functional site, to identify enzymes with similar enzymatic mechanisms, or to discover putative functional sites. In this article, a novel method is presented that (a) queries a database of protein structures for the occurrence of a given side chain pattern and (b) identifies interesting side-chain patterns in a given structure. For efficiency and to make a robust statistical evaluation of the significance of a similarity possible, patterns of three residues (or triads) are considered. Each triad is encoded as a high-dimensional vector and stored in an SR (Sphere/Rectangle) tree, an efficient multidimensional index tree. Identifying similar triads can then be reformulated as identifying neighboring vectors. The method deals with many features that otherwise complicate the identification of meaningful patterns: shifted backbone positions, conservative substitutions, various atom label ambiguities and mirror imaged geometries. The combined treatment of these features leads to the identification of previously unidentified patterns. In particular, the identification of mirror imaged side-chain patterns is unique to the here-described method. Interesting triads in a given structure can be identified by extracting all triads and comparing them with a database of triads involved in ligand binding. The approach was tested by an all-against-all comparison of unique representatives of all SCOP superfamilies. New findings include mirror imaged metal binding and active sites, and a putative active site in bacterial luciferase.     

A structural-informatics approach for mining beta-sheets: locating sheets in intermediate-resolution density maps

Here, we report a new computational method, called sheetminer, for mining beta-sheets in the density maps at intermediate resolutions of 6 to 10A. The method employs a multi-step ad hoc morphological analysis of density maps to identify the unique characteristics of beta-sheets. It was tested on density maps from 12 protein crystal structures that were artificially blurred to intermediate resolutions. There are a total of 35 independent beta-sheets with a wide distribution of morphology. The method successfully located 34 of them and missed only one. The method was also applied to an experimental 9A electron cryomicroscopic structure and an 8A X-ray density map. In both cases, the sheet-searching results were found to agree very well with known high-resolution crystal structures. Collectively, these results demonstrate clearly the robustness of sheetminer in locating the regions belonging to beta-sheets in the intermediate-resolution density maps. Furthermore, sheetminer is completely complementary to all other existing computational methods, including helixhunter and threading algorithms. Their combined usage has the potential to significantly enhance the computational modeling capacity for a much more complete interpretation of structural data at intermediate resolutions, from which extraction of functional information would be more effective. This is particularly important in the field of structural genomics, in which the fast screening approach may not always yield crystals that diffract to atomic resolution. An exciting future application of sheetminer is as a valuable tool for revealing the structures of amyloid fibrils that are rich in beta-motifs.     

Combining inference from evolution and geometric probability in protein structure evaluation

Starting from the hypothesis that evolutionarily important residues form a spatially limited cluster in a protein's native fold, we discuss the possibility of detecting a non-native structure based on the absence of such clustering. The relevant residues are determined using the Evolutionary Trace method. We propose a quantity to measure clustering of the selected residues on the structure and show that the exact values for its average and variance over several ensembles of interest can be found. This enables us to study the behavior of the associated z-scores. Since our approach rests on an analytic result, it proves to be general, customizable, and computationally fast. We find that clustering is indeed detectable in a large representative protein set. Furthermore, we show that non-native structures tend to achieve lower residue-clustering z-scores than those attained by the native folds. The most important conclusion that we draw from this work is that consistency between structural and evolutionary information, manifested in clustering of key residues, imposes powerful constraints on the conformational space of a protein.     

EBI databases and services

The EMBL Outstation-European Bioinformatics Institute (EBI) is a center for research and services in bioinformatics. It serves researchers in molecular biology, genetics, medicine, and agriculture from academia, and the agricultural, biotechnology, chemical, and pharmaceutical industries. The Institute manages and makes available databases of biological data including nucleic acid, protein sequences, and macromolecular structures. It provides to this community bioinformatics services relevant to molecular biology free of charge over the Internet. Some of these databases and services are described in this review. For more information, visit the EBI Web server at http://www.ebi.ac.uk/.     

Analysis and comparison of metabolic pathway databases

Enormous amounts of data result from genome sequencing projects and new experimental methods. Within this tremendous amount of genomic data 30-40 per cent of the genes being identified in an organism remain unknown in terms of their biological function. As a consequence of this lack of information the overall schema of all the biological functions occurring in a specific organism cannot be properly represented. To understand the functional properties of the genomic data more experimental data must be collected. A pathway database is an effort to handle the current knowledge of biochemical pathways and in addition can be used for interpretation of sequence data. Some of the existing pathway databases can be interpreted as detailed functional annotations of genomes because they are tightly integrated with genomic information. However, experimental data are often lacking in these databases. This paper summarises a list of pathway databases and some of their corresponding biological databases, and also focuses on information about the content and the structure of these databases, the organisation of the data and the reliability of stored information from a biological point of view. Moreover, information about the representation of the pathway data and tools to work with the data are given. Advantages and disadvantages of the analysed databases are pointed out, and an overview to biological scientists on how to use these pathway databases is given.     

On the parallelisation of bioinformatics applications

This paper surveys the computational strategies followed to parallelise the most used software in the bioinformatics arena. The studied algorithms are computationally expensive and their computational patterns range from regular, such as database-searching applications, to very irregularly structured patterns (phylogenetic trees). Fine- and coarse-grained parallel strategies are discussed for these very diverse sets of applications. This overview outlines computational issues related to parallelism, physical machine models, parallel programming approaches and scheduling strategies for a broad range of computer architectures. In particular, it deals with shared, distributed and shared/distributed memory architectures.     

Characterizing the metabolic phenotype: a phenotype phase plane analysis.

Genome-scale metabolic maps can be reconstructed from annotated genome sequence data, biochemical literature, bioinformatic analysis, and strain-specific information. Flux-balance analysis has been useful for qualitative and quantitative analysis of metabolic reconstructions. In the past, FBA has typically been performed in one growth condition at a time, thus giving a limited view of the metabolic capabilities of a metabolic network. We have broadened the use of FBA to map the optimal metabolic flux distribution onto a single plane, which is defined by the availability of two key substrates. A finite number of qualitatively distinct patterns of metabolic pathway utilization were identified in this plane, dividing it into discrete phases. The characteristics of these distinct phases are interpreted using ratios of shadow prices in the form of isoclines. The isoclines can be used to classify the state of the metabolic network. This methodology gives rise to a "phase plane" analysis of the metabolic genotype-phenotype relation relevant for a range of growth conditions. Phenotype phase planes (PhPPs) were generated for Escherichia coli growth on two carbon sources (acetate and glucose) at all levels of oxygenation, and the resulting optimal metabolic phenotypes were studied. Supplementary information can be downloaded from our website (http://epicurus.che.udel.edu).     

Pise: software for building bioinformatics webs

Pise is interface construction software for bioinformatics applications that run by command-line operations. It creates common, easy-to-use interfaces to these applications for the Web, or other uses. It is adaptable to new bioinformatics tools, and offers program chaining, Unix system batch and other controls, making it an attractive method for building and using your own bioinformatics web services.     

ATP synthases: insights into their motor functions from sequence and structural analyses

ATP synthases are motor complexes comprised of F₀ and F₁ parts that couple the proton gradient across the membrane to the synthesis of ATP by rotary catalysis. Although a great deal of information has been accumulated regarding the structure and function of ATP synthases, their motor functions are not fully understood. For this reason, we performed the alignments and analyses of the protein sequences comprising the core of the ATP synthase motor complex, and examined carefully the locations of the conserved residues in the subunit structures of ATP synthases. A summary of the findings from this bioinformatic study is as follows. First, we found that four conserved regions in the sequence of subunit are clustered into three patches in its structure. The interactions of these conserved patches with the and subunits are likely to be critical for energy coupling and catalytic activity of the ATP synthase. Second, we located a four-residue cluster at the N-terminal domain of mitochondrial OSCP or bacterial (or chloroplast) subunit which may be critical for the binding of these subunits to F₁. Third, from the localizations of conserved residues in the subunits comprising the rotors of ATP synthases, we suggest that the conserved interaction site at the interface of subunit c and (mitochondria) or (bacteria and chloroplasts) may be important for connecting the rotor of F₁ to the rotor of F₀. Finally, we found the sequence of mitochondrial subunit b to be highly conserved, significantly longer than bacterial subunit b, and to contain a shorter dimerization domain than that of the bacterial protein. It is suggested that the different properties of mitochondrial subunit b may be necessary for interaction with other proteins, e.g., the supernumerary subunits.     

Proteomics of chloroplast envelope membranes

Proteomics is a very powerful approach to link the information contained in sequenced genomes, like Arabidopsis, to the functional knowledge provided by studies of plant cell compartments, such as chloroplast envelope membranes. This review summarizes the present state of proteomic analyses of highly purified spinach and Arabidopsis envelope membranes. Methods targeted towards the hydrophobic core of the envelope allow identifying new proteins, and especially new transport systems. Common features were identified among the known and newly identified putative envelope inner membrane transporters and were used to mine the complete Arabidopsis genome to establish a virtual plastid envelope integral protein database. Arabidopsis envelope membrane proteins were extracted using different methods, that is, chloroform/methanol extraction, alkaline or saline treatments, in order to retrieve as many proteins as possible, from the most to the less hydrophobic ones. Mass spectrometry analyses lead to the identification of more than 100 proteins. More than 50% of the identified proteins have functions known or very likely to be associated with the chloroplast envelope. These proteins are (a) involved in ion and metabolite transport, (b) components of the protein import machinery and (c) involved in chloroplast lipid metabolism. Some soluble proteins, like proteases, proteins involved in carbon metabolism or in responses to oxidative stress, were associated with envelope membranes. Almost one third of the newly identified proteins have no known function. The present stage of the work demonstrates that a combination of different proteomics approaches together with bioinformatics and the use of different biological models indeed provide a better understanding of chloroplast envelope biochemical machinery at the molecular level.