ConSSeq: a web-based application for analysis of amino acid conservation based on HSSP database and within context of structure

Higa, R. H.; Montagner, A. J.; Togawa, Roberto Coiti; Kuser, Paula R.; Yamagishi, M. E. B.; Mancini, A. L.; Pappas, George J.; Miura, R. T.; Horita, L. G.; Neshich, Goran

doi:10.1093/bioinformatics/bth185

Cited by 8 publications

(8 citation statements)

References 7 publications

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“… Labels : Cα = Carbon alpha; LHA = Last heavy atom; MM = Main chain – Main chain; MS = Main chain – Side chain; SS = Side chain – Side chain; W = Water molecule; WW = 2x Water molecules.*A complete description of the listed physicochemical and structural attributes is given at http://www.cbi.cnptia.embrapa.br/SMS and in [10]–[13], [20].…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, our method still functions in scenarios in which no close homologue to a protein of interest is available and in which all other methods that rely on the use of “conservation” attributes would fail. Nevertheless, for a complete assessment of the suitability of the selected physicochemical and structural descriptors for classifying amino acid residues as interface residues and also of the importance of the contribution of sequence conservation attributes to the same classification, an additional IFR classifier was built that also includes the “ amino acid conservation ” attribute from STING database [20]. We show that all the clues necessary for IFR prediction may already be contained within the information in descriptors that are derived only from the protein structure.…”

Section: Introductionmentioning

confidence: 99%

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Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

et al. 2014

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Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html).

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

et al. 2014

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“…However, schemes such as identity or similarity matrices can instead use a consensus sequence or a different sequence found in the alignment as the reference sequence. Consensus sequences can be supplied as part of the input MSA, permitting import of consensus sequences from sources such as HSSP or STING [9,12,33,34], or they can be generated by homolmapper at runtime as needed. A summary of the available reference sequence choices for different scoring schemes is presented in Table 2.…”

Section: Implementation and Resultsmentioning

confidence: 99%

Flexible mapping of homology onto structure with Homolmapper

Rockwell

Lagarias

2007

BMC Bioinformatics

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Background: Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.

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“…Such a graphic presentation and the large amount of information presented are distinctive characteristics of STING components in comparison with other software packages (8,9). This diagram is intuitive and easily understood by a typical STING Report user; the details describing all parameters and the procedures to calculate them are available on online help and in our earlier publications (10,11). In addition, the legend pointer at the STING Report HTML page contains the graphical presentation of all parameter classes which are clickable and which leads a user to the information describing a parameter definition and the procedure applied to calculate it.…”

Section: The Sting Report Image and Table Areasmentioning

confidence: 99%

“…This is convenient if the focus of a user is already determined. The different components to be inserted in the resulting document are built by distinct modules of Gold STING, such as J PD (3), Contacts, Ramachandran Plot, ConSSeq (10), Scorpion and Formiga (11). STING Report coordinates the execution of these modules, by submitting to them the query that specifies the residue to be recovered and eventual conditions to calculate the parameters and generate the outputs.…”

Section: Selecting Document Components With Sting Reportmentioning

confidence: 99%

STING Report: convenient web-based application for graphic and tabular presentations of protein sequence, structure and function descriptors from the STING database

Neshich

Mancini

Yamagishi

et al. 2004

Nucleic Acids Research

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The Sting Report is a versatile web-based application for extraction and presentation of detailed information about any individual amino acid of a protein structure stored in the STING Database. The extracted information is presented as a series of GIF images and tables, containing the values of up to 125 sequence/structure/ function descriptors/parameters. The GIF images are generated by the Gold STING modules. The HTML page resulting from the STING Report query can be printed and, most importantly, it can be composed and visualized on a computer platform with an elementary configuration. Using the STING Report, a user can generate a collection of customized reports for amino acids of specific interest. Such a collection comes as an ideal match for a demand for the rapid and detailed consultation and documentation of data about structure/function. The inclusion of information generated with STING Report in a research report or even a textbook, allows for the increased density of its contents. STING Report is freely accessible within the Gold STING Suite at

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ConSSeq: a web-based application for analysis of amino acid conservation based on HSSP database and within context of structure

Abstract: http://sms.cbi.cnptia.embrapa.br/SMS/STINGm/consseq/, http://trantor.bioc.columbia.edu/SMS/STINGm/consseq/, http://mirrors.rcsb.org//SMS/STINGm/consseq/, http://www.es.embnet.org/SMS/STINGm/consseq/ and http://www.ar.embnet.org/SMS/STINGm/consseq/

Cited by 8 publications

References 7 publications

Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

Flexible mapping of homology onto structure with Homolmapper

STING Report: convenient web-based application for graphic and tabular presentations of protein sequence, structure and function descriptors from the STING database

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