The 3rd alpha-release (v3.0) of the Guide to IMMUNOPHARMACOLOGY was released on 30th January 2017. This blog post summarises some of the main features of the release and other developments as we moved toward our first public, beta-release in Spring 2017
An early synopsis of the project can be found in this blog post. You can also review our previous technical blogs on GtoImmPdb.
Development Progress
Alpha-Release v3.0
No major changes have been made to the portal in this release. There are some minor edits to the help and tutorial to reflect other changes. We expect to be bale to implement links from the disease portal in the next release.
Figure 1: Alpha-release v3.0 portal
As a reminder, the portal provides a starting-point for accessing data in GtoImmuPdb, tailored to the requirements of users with a specific interest in immunopharmacology. It accesses the same database as GtoPdb, but provides specific immuno-focussed views of the data, which can be toggle on and off.
Ligand Summary Pages
The ligand summary pages have been modified to create a specific immunopharmacology tab which contains all immunopharmacology related data for that ligand.
Figure 2: Ligand summary page for ABT-737, showing immunopharmacology tab
The immunopharmacology tab displays ligand specific comments related to immunopharmacology as well as the newly included disease association data.
The inclusion of both these type of data has required extensions to the database schema. Firstly, extending of ligand tables to house the immunopharmacology comments. Secondly, adding in a series of new tables to house disease to ligand and disease to target associations, plus any references related to these associations.
Disease Associations
For the disease associations, as well as extending the database schema, we have extended the submission tool to aid capturing this data and providing a way for curators to edit and update these associations in the database.
As for the data itself, we are utilising a mixture of disease resources – OMIM, Orphanet and the Disease Ontology, to provide a controlled vocabulary against which we can annotate, and as a way by which we can cross-reference our disease associations to other resources. Basically this is so we can be as sure as possible that what we are calling and describing a disease as, is conforming to other understood and accepted descriptions of that disease or condition.
The GtoPdb database contains over 2,000 disease terms (including synonyms), 1,400 of which are currently curated as being associated with a target protein. Of these, there are about 270 association to roughly 80 distinct immuno targets. Our curators will be checking these association and ensuring that the ones of highest relevance to immunopharmacology will be recorded in GtoImmuPdb.
Displaying diease
Figure 2 shows the display of a ligand to disease association and figure 3 below shows how the data on target to disease association is being surfaced on the detailed target pages. This is a example on our test database and is not real data, but illustrates the intended style of display.
As well as listing the disease names and synonyms, we also provide the external references (X-Refs) to other disease resources as a useful cross-pointer. In addition curator comments and references are displayed.
Figure 3: Example of proposed display of disease to target association data on detailed view page in GtoImmuPdb.
Immuno Process Data
We have made some minor adjustments to the capturing to process association data from the Gene Ontology (GO). We have been obtaining the GO annotations from UniProt – so that we can restrict the data to targets cross-referenced in GtoPdb (human with quantitative interactions). Previously we’d also been restricting by those protein targets annotated to either immune system or inflammatory processes. This step has been removed, as we can check this against our own GO process tables (captured from the original OBO file). This usefully avoids any latency that could exist between GO updates and UniProt updates.
Searching Disease Data
Extensions have also been made to the search mechanisms to incorporate any immuno disease to ligand or target associations and their synonyms, descriptions and comments.
This project is supported by a 3-year grant awarded to Professor Jamie Davies at the University of Edinburgh by the Wellcome Trust (WT).
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