What do we do?
At the Proteome Informatics Group (PIG) we are involved in software and database development for the benefit of the proteomics and the glycomics communities. These resources are made available through the ExPASy server. Software tools support experimental mass spectrometry data analysis, mainly for the detection of posttranslational modifications. Databases store knowledge of carbohydrates attached to proteins as well as protein-carbohydrate interactions.
In living organisms, the size of glycan (or sugar, or carbohydrate) molecules varies significantly according, for instance, to the availability of enzymes that synthesize them. Irrespective of their size, the recognition of glycans by other molecules – mainly proteins – is usually limited to a substructure. One of the challenges of glycobiology is to establish which part of a full glycan binds to other molecules, for example surface proteins. Exploring specific substructures can be useful to predict this binding potential. GlyS3 is a new tool that matches a glycan molecule fragment to large collections of full glycan structures as, for instance, those contained in UniCarbKB or GlycomeDB. The implementation of GlyS3 takes advantage of the latest developments in web semantics, and the tool was integrated into SugarBindDB – a database that collects information on glycan recognition by pathogens.
Over the past years, the group’s production has reached a critical mass warranting the creation of a dedicated tab on the ExPASy server where databases and tools useful for glycomics and glycoproteomics studies are now gathered. These resources are now centraliszed to improve usability as well as to enhance their interconnections. Besides SIB resources, the ExPASy glycomics tab will preferentially host tools that reveal the links between glycans and proteins, or the effect glycosylation has on cellular processes.
Main publications 2015
- Alocci D et al. Graph Database vs RDF Triple Store: A Comparison on Glycan Substructure Search, PLOS ONE 2015;10(12):e0144578.
- Bilbao A et al. Ranking fragment ions based on outlier detection for improved label-free quantification in Data-Independent Acquisition LC-MS/MS, J Prot Research 2015;14(11):4581-93.
- Horlacher O et al. MzJava: an open source mass spectrometry library, J Proteomics 2015;129:63-70.