Drug discovery FAQs: workflows for answering multidomain drug discovery questions

Abstract

Modern data-driven drug discovery requires integrated resources to support decision-making and enable new discoveries. The Open PHACTS Discovery Platform (http://dev.openphacts.org) was built to address this requirement by focusing on drug discovery questions that are of high priority to the pharmaceutical industry. Although complex, most of these frequently asked questions (FAQs) revolve around the combination of data concerning compounds, targets, pathways and diseases. Computational drug discovery using workflow tools and the integrated resources of Open PHACTS can deliver answers to most of these questions. Here, we report on a selection of workflows used for solving these use cases and discuss some of the research challenges. The workflows are accessible online from myExperiment (http://www.myexperiment.org) and are available for reuse by the scientific community.

Strategies for the discovery, identification and validation of milk protein-derived bioactive peptides

“…Pharmacological Concepts Triple Store (Open PHACTS) Discovery Platform 131 (http://www.openphacts.org) has combined several publicly available databases for drugs, 132 targets, pathways and diseases (for review, see: Chichester et al, 2015). Similarly, for dietary 133 peptides, several publicly available databases (e.g., BIOPEP, PepBank, etc.)…”

Reporting biological assay screening results for maximum impact

“…These data dictionaries are used to identify and validate incorporated target, compound, and bioactivity nomenclature data. As a platform, Open PHACTS supports various workflows (24–25) involving chemicals, targets, pathways, and diseases. This data integration of bioactivity information provides links between chemicals and targets.…”

Empowering pharmacoinformatics by linked life science data

“…Additionally, public–private initiatives facilitate close collaborations between academia and industry, giving access to proprietary data in order to develop and test novel computational methods on them. Thus, academic CADD is increasingly looking into topics which benefit from the unprecedented access to data, such as phenotypic annotations, in silico tools to facilitate drug repurposing, translational and precision medicine and provides computational solutions there, such as tailored workflows [11–13]. In this contribution we seek to demonstrate how all these developments influenced our (the Pharmacoinformatics Research Group at the Department of Pharmaceutical Chemistry, University of Vienna) way of approaching challenging research questions (Fig.…”