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Integrative visual analysis of protein sequence mutations.

Doncheva NT, Klein K, Morris JH, Wybrow M, Domingues FS, Albrecht M - BMC Proc (2014)

Bottom Line: An important aspect of studying the relationship between protein sequence, structure and function is the molecular characterization of the effect of protein mutations.The views are linked tightly and synchronized to reduce the cognitive load of the user when switching between them.We demonstrate the effectiveness of our approach and the developed software on the data provided for the BioVis 2013 data contest.

View Article: PubMed Central - HTML - PubMed

Affiliation: Max Planck Institute for Informatics, 66123 Saarb├╝cken, Germany ; University of California, San Francisco, 94143-2240 San Francisco, USA.

ABSTRACT

Background: An important aspect of studying the relationship between protein sequence, structure and function is the molecular characterization of the effect of protein mutations. To understand the functional impact of amino acid changes, the multiple biological properties of protein residues have to be considered together.

Results: Here, we present a novel visual approach for analyzing residue mutations. It combines different biological visualizations and integrates them with molecular data derived from external resources. To show various aspects of the biological information on different scales, our approach includes one-dimensional sequence views, three-dimensional protein structure views and two-dimensional views of residue interaction networks as well as aggregated views. The views are linked tightly and synchronized to reduce the cognitive load of the user when switching between them. In particular, the protein mutations are mapped onto the views together with further functional and structural information. We also assess the impact of individual amino acid changes by the detailed analysis and visualization of the involved residue interactions. We demonstrate the effectiveness of our approach and the developed software on the data provided for the BioVis 2013 data contest.

Conclusions: Our visual approach and software greatly facilitate the integrative and interactive analysis of protein mutations based on complementary visualizations. The different data views offered to the user are enriched with information about molecular properties of amino acid residues and further biological knowledge.

No MeSH data available.


General analysis workflow. The workflow consists of three parts: input, software and output. The input consists of biological data, which might be protein sequences, structures, RINs as well as additional annotations and biological knowledge retrieved from external sources and databases (shown as gray background for each view). The middle part of the workflow shows the interactions between the different tools and which tool is responsible for the presentation of which data. The output consists of the different views with data mapped onto them and sets of important residues that can be identified through visual exploratory analysis of the available data. The yellow and green boundaries indicate the default selection color used by the different tools.
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Figure 6: General analysis workflow. The workflow consists of three parts: input, software and output. The input consists of biological data, which might be protein sequences, structures, RINs as well as additional annotations and biological knowledge retrieved from external sources and databases (shown as gray background for each view). The middle part of the workflow shows the interactions between the different tools and which tool is responsible for the presentation of which data. The output consists of the different views with data mapped onto them and sets of important residues that can be identified through visual exploratory analysis of the available data. The yellow and green boundaries indicate the default selection color used by the different tools.

Mentions: A general analysis workflow is presented in Figure 6. Normally, the user starts with one or more experimentally determined protein structures and retrieves or generates RINs for them. In case only sequences are available, external tools for predicting the 3D structure could be used instead. External data such as evolutionary conservation and functional annotations need to be prepared in a format compatible with Cytoscape and the RIN specifications. Then the data is loaded by the user into Cytoscape and UCSF Chimera. Further views such as the secondary structure cartoon, the aggregated secondary structure network or the comparison network can be created from within Cytoscape. The sequences of the structures can be displayed and manipulated from within UCSF Chimera. Functional annotations and evolutionary conservation have to be imported manually into Cytoscape as node attributes of the RINs, while structural properties can be retrieved automatically from the protein structures currently opened in UCSF Chimera. These data can then be applied to create the visual cues and semi-automatically propagate them to the different views. Finally, by browsing and filtering the data in Cytoscape and UCSF Chimera, the user can identify relevant amino acids, in particular, mutated residues with a potentially strong effect on the protein function. Even if the visual analysis does not immediately reveal the functional consequences of mutations, our software will provide the user at least with very useful biological indications for the molecular analysis and further experiments.


Integrative visual analysis of protein sequence mutations.

Doncheva NT, Klein K, Morris JH, Wybrow M, Domingues FS, Albrecht M - BMC Proc (2014)

General analysis workflow. The workflow consists of three parts: input, software and output. The input consists of biological data, which might be protein sequences, structures, RINs as well as additional annotations and biological knowledge retrieved from external sources and databases (shown as gray background for each view). The middle part of the workflow shows the interactions between the different tools and which tool is responsible for the presentation of which data. The output consists of the different views with data mapped onto them and sets of important residues that can be identified through visual exploratory analysis of the available data. The yellow and green boundaries indicate the default selection color used by the different tools.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4155609&req=5

Figure 6: General analysis workflow. The workflow consists of three parts: input, software and output. The input consists of biological data, which might be protein sequences, structures, RINs as well as additional annotations and biological knowledge retrieved from external sources and databases (shown as gray background for each view). The middle part of the workflow shows the interactions between the different tools and which tool is responsible for the presentation of which data. The output consists of the different views with data mapped onto them and sets of important residues that can be identified through visual exploratory analysis of the available data. The yellow and green boundaries indicate the default selection color used by the different tools.
Mentions: A general analysis workflow is presented in Figure 6. Normally, the user starts with one or more experimentally determined protein structures and retrieves or generates RINs for them. In case only sequences are available, external tools for predicting the 3D structure could be used instead. External data such as evolutionary conservation and functional annotations need to be prepared in a format compatible with Cytoscape and the RIN specifications. Then the data is loaded by the user into Cytoscape and UCSF Chimera. Further views such as the secondary structure cartoon, the aggregated secondary structure network or the comparison network can be created from within Cytoscape. The sequences of the structures can be displayed and manipulated from within UCSF Chimera. Functional annotations and evolutionary conservation have to be imported manually into Cytoscape as node attributes of the RINs, while structural properties can be retrieved automatically from the protein structures currently opened in UCSF Chimera. These data can then be applied to create the visual cues and semi-automatically propagate them to the different views. Finally, by browsing and filtering the data in Cytoscape and UCSF Chimera, the user can identify relevant amino acids, in particular, mutated residues with a potentially strong effect on the protein function. Even if the visual analysis does not immediately reveal the functional consequences of mutations, our software will provide the user at least with very useful biological indications for the molecular analysis and further experiments.

Bottom Line: An important aspect of studying the relationship between protein sequence, structure and function is the molecular characterization of the effect of protein mutations.The views are linked tightly and synchronized to reduce the cognitive load of the user when switching between them.We demonstrate the effectiveness of our approach and the developed software on the data provided for the BioVis 2013 data contest.

View Article: PubMed Central - HTML - PubMed

Affiliation: Max Planck Institute for Informatics, 66123 Saarb├╝cken, Germany ; University of California, San Francisco, 94143-2240 San Francisco, USA.

ABSTRACT

Background: An important aspect of studying the relationship between protein sequence, structure and function is the molecular characterization of the effect of protein mutations. To understand the functional impact of amino acid changes, the multiple biological properties of protein residues have to be considered together.

Results: Here, we present a novel visual approach for analyzing residue mutations. It combines different biological visualizations and integrates them with molecular data derived from external resources. To show various aspects of the biological information on different scales, our approach includes one-dimensional sequence views, three-dimensional protein structure views and two-dimensional views of residue interaction networks as well as aggregated views. The views are linked tightly and synchronized to reduce the cognitive load of the user when switching between them. In particular, the protein mutations are mapped onto the views together with further functional and structural information. We also assess the impact of individual amino acid changes by the detailed analysis and visualization of the involved residue interactions. We demonstrate the effectiveness of our approach and the developed software on the data provided for the BioVis 2013 data contest.

Conclusions: Our visual approach and software greatly facilitate the integrative and interactive analysis of protein mutations based on complementary visualizations. The different data views offered to the user are enriched with information about molecular properties of amino acid residues and further biological knowledge.

No MeSH data available.