Análise preliminar de um processo para identificação e alinhamento de seqüências homólogas para proteínas com estrutura resolvida.

O objetivo deste trabalho é apresentar e fazer uma avaliação preliminar de um processo alternativo, denominado Sequences Homologue to the Query (Structure-having) Sequence-SH2Q, para elaboração de alinhamentos múltiplos semelhantes à aqueles relatados no HSSP. O processo aqui apresentado baseia-se em programas de domínio público para busca em bases de dados de sequências -Blast (Altschul et al., 1990, 1997) e para alinhamento múltiplo de sequências -ClustalW (Thompson et al., 1994) O critério para avaliação do mesmo é o grau de similaridade entre as medidas de Entropia Relativa, quando comparadas com os mesmos valores relatados pelo HSSP.bitstream/CNPTIA/10041/1/comtec48.pdfAcesso em: 30 maio 2008

A series of PDB related databases for everyday needs

The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible, for each PDB entry. DSSP holds the secondary structure of the proteins. PDBREPORT holds reports on the structure quality and lists errors. HSSP holds a multiple sequence alignment for all proteins. The PDBFINDER holds easy to parse summaries of the PDB file content, augmented with essentials from the other systems. PDB_REDO holds re-refined, and often improved, copies of all structures solved by X-ray. WHY_NOT summarizes why certain files could not be produced. All these systems are updated weekly. The data sets can be used for the analysis of properties of protein structures in areas ranging from structural genomics, to cancer biology and protein design

STING Millennium: a web-based suite of programs for comprehensive and simultaneous analysis of protein structure and sequence.

Sting Millennium suite intrinsics. SMS organization. Sting Millennium Modes. Sting Millennium Modules. Millennium Features. Example of Sting Millennium Application.Na publicação: Paula R. Kuser

Prediction of Functional Sites in SCOP Domains using Dynamics Perturbation Analysis

Dynamics perturbation analysis (DPA) finds regions in a protein structure where proteins are "ticklish", i.e., where interactions cause a large change in protein dynamics. Previously, such regions were shown to predict the location of native binding sites in a docking test set, but the more general applicability of DPA to the prediction of functional sites in proteins was not shown. Here we describe the results of applying an accelerated algorithm, called Fast DPA, to predict functional sites in over 50,000 SCOP domains

Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces

Contains fulltext : 89590.pdf (publisher's version ) (Open Access)BACKGROUND: Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools. RESULTS: In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers. CONCLUSIONS: We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background

The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il

Improved prediction of critical residues for protein function based on network and phylogenetic analyses

BACKGROUND: Phylogenetic approaches are commonly used to predict which amino acid residues are critical to the function of a given protein. However, such approaches display inherent limitations, such as the requirement for identification of multiple homologues of the protein under consideration. Therefore, complementary or alternative approaches for the prediction of critical residues would be desirable. Network analyses have been used in the modelling of many complex biological systems, but only very recently have they been used to predict critical residues from a protein's three-dimensional structure. Here we compare a couple of phylogenetic approaches to several different network-based methods for the prediction of critical residues, and show that a combination of one phylogenetic method and one network-based method is superior to other methods previously employed. RESULTS: We associate a network with each member of a set of proteins for which the three-dimensional structure is known and the critical residues have been previously determined experimentally. We show that several network-based centrality measurements (connectivity, 2-connectivity, closeness centrality, betweenness and cluster coefficient) accurately detect residues critical for the protein's function. Phylogenetic approaches render predictions as reliable as the network-based measurements, although, interestingly, the two general approaches tend to predict different sets of critical residues. Hence we propose a hybrid method that is composed of one network-based calculation – the closeness centrality – and one phylogenetic approach – the Conseq server. This hybrid approach predicts critical residues more accurately than the other methods tested here. CONCLUSION: We show that network analysis can be used to improve the prediction of amino acids critical for protein function, when utilized in combination with phylogenetic approaches. It is proposed that such improvement is due to the complementary nature of these approaches: network-based methods tend to predict as critical those residues that are highly connected and internal (i.e., non-surface), although some surface residues are indeed identified as critical by network analyses; whereas residues chosen by phylogenetic approaches display a lower overall probability of being surface inaccessible