Open PHACTS computational protocols for in silico target validation of cellular phenotypic screens: knowing the knowns

Phenotypic screening is in a renaissance phase and is expected by many academic and industry leaders to accelerate the discovery of new drugs for new biology. Given that phenotypic screening is per definition target agnostic, the emphasis of in silico and in vitro follow-up work is on the exploration of possible molecular mechanisms and efficacy targets underlying the biological processes interrogated by the phenotypic screening experiments. Herein, we present six exemplar computational protocols for the interpretation of cellular phenotypic screens based on the integration of compound, target, pathway, and disease data established by the IMI Open PHACTS project. The protocols annotate phenotypic hit lists and allow follow-up experiments and mechanistic conclusions. The annotations included are from ChEMBL, ChEBI, GO, WikiPathways and DisGeNET. Also provided are protocols which select from the IUPHAR/BPS Guide to PHARMACOLOGY interaction file selective compounds to probe potential targets and a correlation robot which systematically aims to identify an overlap of active compounds in both the phenotypic as well as any kinase assay. The protocols are applied to a phenotypic pre-lamin A/C splicing assay selected from the ChEMBL database to illustrate the process. The computational protocols make use of the Open PHACTS API and data and are built within the Pipeline Pilot and KNIME workflow tools.

PRINTS and its automatic supplement, prePRINTS

The PRINTS database houses a collection of protein fingerprints. These may be used to assign uncharacterised sequences to known families and hence to infer tentative functions. The September 2002 release (version 36.0) includes 1800 fingerprints, encoding approximately 11 000 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. In addition to its continued steady growth, we report here the development of an automatic supplement, prePRINTS, designed to increase the coverage of the resource and reduce some of the manual burdens inherent in its maintenance. The databases are accessible for interrogation and searching at http://www.bioinf.man.ac.uk/dbbrowser/PRINTS/.

Deriving structural and functional insights from a ligand-based hierarchical classification of G protein-coupled receptors

G protein-coupled receptors (GPCRs) constitute the largest known family of cell-surface receptors. With hundreds of members populating the rhodopsin-like GPCR superfamily and many more awaiting discovery in the human genome, they are of interest to the pharmaceutical industry because of the opportunities they afford for yielding potentially lucrative drug targets. Typical sequence analysis strategies for identifying novel GPCRs tend to involve similarity searches using standard primary database search tools. This will reveal the most similar sequence, generally without offering any insight into its family or superfamily relationships. Conversely, searches of most 'pattern' or family databases are likely to identify the superfamily, but not the closest matching subtype. Here we describe a diagnostic resource that allows identification of GPCRs in a hierarchical fashion, based principally upon their ligand preference. This resource forms part of the PRINTS database, which now houses approximately 250 GPCR-specific fingerprints (http://www.bioinf.man.ac.uk/dbbrowser/gpcrPRINTS/). This collection of fingerprints is able to provide more sensitive diagnostic opportunities than have been realized by related approaches and is currently the only diagnostic tool for assigning GPCR subtypes. Mapping such fingerprints on to three-dimensional GPCR models offers powerful insights into the structural and functional determinants of subtype specificity.

PRINTS and PRINTS-S shed light on protein ancestry

The PRINTS database houses a collection of protein fingerprints. These may be used to make family and tentative functional assignments for uncharacterised sequences. The September 2001 release (version 32.0) includes 1600 fingerprints, encoding approximately 10 000 motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. In addition to its continued steady growth, we report here its use as a source of annotation in the InterPro resource, and the use of its relational cousin, PRINTS-S, to model relationships between families, including those beyond the reach of conventional sequence analysis approaches. The database is accessible for BLAST, fingerprint and text searches at http://www.bioinf.man.ac.uk/dbbrowser/PRINTS/.