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SARConnect: A Tool to Interrogate the Connectivity Between Proteins, Chemical Structures and Activity Data

The access and use of large-scale structure-activity relationships (SAR) is increasing as the range of targets and availability of bioactive compound-to-protein mappings expands. However, effective exploitation requires merging and normalisation of activity data, mappings to target classifications a...

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Detalles Bibliográficos
Autores principales: Eriksson, Mats, Nilsson, Ingemar, Kogej, Thierry, Southan, Christopher, Johansson, Martin, Tyrchan, Christian, Muresan, Sorel, Blomberg, Niklas, Bjäreland, Marcus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: WILEY-VCH Verlag 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3535785/
https://www.ncbi.nlm.nih.gov/pubmed/23308082
http://dx.doi.org/10.1002/minf.201200030
Descripción
Sumario:The access and use of large-scale structure-activity relationships (SAR) is increasing as the range of targets and availability of bioactive compound-to-protein mappings expands. However, effective exploitation requires merging and normalisation of activity data, mappings to target classifications as well as visual display of chemical structure relationships. This work describes the development of the application “SARConnect” to address these issues. We discuss options for delivery and analysis of large-scale SAR data together with a set of use-cases to illustrate the design choices and utility. The main activity sources of ChEMBL,1 GOSTAR2 and AstraZeneca’s internal system IBIS, had already been integrated in Chemistry Connect.3 For target relationships we selected human UniProtKB/Swiss-Prot4 as our primary source of a heuristic target classification. Similarly, to explore chemical relationships we combined several methods for framework and scaffold analysis into a unified, hierarchical classification where ease of navigation was the primary goal. An application was built on TIBCO Spotfire to retrieve data for visual display. Consequently, users can explore relationships between target, activity and structure across internal, external and commercial sources that encompass approximately 3 million compounds, 2000 human proteins and 10 million activity values. Examples showing the utility of the application are given.