Open PHACTS Research Articles

Explicit interaction information from WikiPathways in RDF facilitates drug discovery in the Open PHACTS Discovery Platform.

Open PHACTS is a pre-competitive project to answer scientific questions developed recently by the pharmaceutical industry. Having high quality biological interaction information in the Open PHACTS Discovery Platform is needed to answer multiple pathway related questions. To address this, updated WikiPathways data has been added to the platform. This data includes information about biological interactions, such as stimulation and inhibition. The platform's Application Programming Interface (API) was extended with appropriate calls to reference these interactions. These new methods of the Open PHACTS API are available now.

Explicit interaction information from WikiPathways in RDF facilitates drug discovery in the Open PHACTS Discovery Platform

Open PHACTS is a pre-competitive project to answer scientific questions developed recently by the pharmaceutical industry. Having high quality biological interaction information in the Open PHACTS Discovery Platform is needed to answer multiple pathway related questions. To address this, updated WikiPathways data has been added to the platform. This data includes information about biological interactions, such as stimulation and inhibition. The platform's Application Programming Interface (API) was extended with appropriate calls to reference these interactions. These new methods of the Open PHACTS API are available now.

Explicit interaction information from WikiPathways in RDF facilitates drug discovery in the Open PHACTS Discovery Platform

Open PHACTS is a pre-competitive project to answer scientific questions developed recently by the pharmaceutical industry. Having high quality biological interaction information in the Open PHACTS Discovery Platform is needed to answer multiple pathway related questions. To address this, updated WikiPathways data has been added to the platform. This data includes information about biological interactions, such as stimulation and inhibition. The platform's Application Programming Interface (API) was extended with appropriate calls to reference these interactions. These new methods of the Open PHACTS API are available now.

Accessing the Open PHACTS Discovery Platform with Workflow Tools.

The Open PHACTS Discovery Platform integrates several public databases, which can be of interest when annotating the results of a phenotypic screening campaign. Workflow tools provide easy-to-customize possibilities to access the platform. Here, we describe how to create such workflows for two different workflow tools (KNIME and Pipeline Pilot), including a protocol to annotate compounds (e.g., phenotypic screening hits) with compound classification, known protein targets, and classifications of the targets.

An automated tool for obtaining QSAR-ready series of compounds using semantic web technologies.

We describe an application (Collector) for obtaining series of compounds annotated with bioactivity data, ready to be used for the development of quantitative structure-activity relationships (QSAR) models. The tool extracts data from the 'Open Pharmacological Space' (OPS) developed by the Open PHACTS project, using as input a valid name of the biological target. Collector uses the OPS ontologies for expanding the query using all known target synonyms and extracts compounds with bioactivity data against the target from multiple sources. The extracted data can be filtered to retain only drug-like compounds and the bioactivities can be automatically summarised to assign a single value per compound, yielding data ready to be used for QSAR modeling. The data obtained is locally stored facilitating the traceability and auditability of the process. Collector was used successfully for the development of models for toxicity endpoints within the eTOX project. The software is available at http://phi.upf.edu/collector. The source code is located at https://github.com/phi-grib/Collector and is free for use under the GPL3 license. The web version is hosted at http://collector.upf.edu/. manuel.pastor@upf.edu. Supplementary data are available at Bioinformatics online.

Empowering pharmacoinformatics by linked life science data

With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models.

Knowledge Representation and Management: a Linked Data Perspective.

Biomedical research is increasingly becoming a data-intensive science in several areas, where prodigious amounts of data is being generated that has to be stored, integrated, shared and analyzed. In an effort to improve the accessibility of data and knowledge, the Linked Data initiative proposed a well-defined set of recommendations for exposing, sharing and integrating data, information and knowledge, using semantic web technologies. The main goal of this paper is to identify the current status and future trends of knowledge representation and management in Life and Health Sciences, mostly with regard to linked data technologies. We selected three prominent linked data studies, namely Bio2RDF, Open PHACTS and EBI RDF platform, and selected 14 studies published after 2014 (inclusive) that cited any of the three studies. We manually analyzed these 14 papers in relation to how they use linked data techniques. The analyses show a tendency to use linked data techniques in Life and Health Sciences, and even if some studies do not follow all of the recommendations, many of them already represent and manage their knowledge using RDF and biomedical ontologies. These insights from RDF and biomedical ontologies are having a strong impact on how knowledge is generated from biomedical data, by making data elements increasingly connected and by providing a better description of their semantics. As health institutes become more data centric, we believe that the adoption of linked data techniques will continue to grow and be an effective solution to knowledge representation and management.

The Open PHACTS Discovery Platform from a network biology perspective

The Open PHACTS Discovery Platform from a network biology perspective

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

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.

The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets.

BackgroundThere are presently hundreds of online databases hosting millions of chemical compounds and associated data. As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online. In order to help facilitate validation and standardization of chemical structure datasets from various sources we have delivered a freely available internet-based platform to the community for the processing of chemical compound datasets.ResultsThe chemical validation and standardization platform (CVSP) both validates and standardizes chemical structure representations according to sets of systematic rules. The chemical validation algorithms detect issues with submitted molecular representations using pre-defined or user-defined dictionary-based molecular patterns that are chemically suspicious or potentially requiring manual review. Each identified issue is assigned one of three levels of severity - Information, Warning, and Error – in order to conveniently inform the user of the need to browse and review subsets of their data. The validation process includes validation of atoms and bonds (e.g., making aware of query atoms and bonds), valences, and stereo. The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file. This platform has been applied to the analysis of a large number of data sets prepared for deposition to our ChemSpider database and in preparation of data for the Open PHACTS project. In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set. CVSP web site is located at http://cvsp.chemspider.com/.ConclusionA platform for the validation and standardization of chemical structure representations of various formats has been developed and made available to the community to assist and encourage the processing of chemical structure files to produce more homogeneous compound representations for exchange and interchange between online databases. While the CVSP platform is designed with flexibility inherent to the rules that can be used for processing the data we have produced a recommended rule set based on our own experiences with the large data sets such as DrugBank, ChEMBL, and data sets from ChemSpider.

The application of the open pharmacological concepts triple store (open PHACTS) to support drug discovery research.

Integration of open access, curated, high-quality information from multiple disciplines in the Life and Biomedical Sciences provides a holistic understanding of the domain. Additionally, the effective linking of diverse data sources can unearth hidden relationships and guide potential research strategies. However, given the lack of consistency between descriptors and identifiers used in different resources and the absence of a simple mechanism to link them, gathering and combining relevant, comprehensive information from diverse databases remains a challenge. The Open Pharmacological Concepts Triple Store (Open PHACTS) is an Innovative Medicines Initiative project that uses semantic web technology approaches to enable scientists to easily access and process data from multiple sources to solve real-world drug discovery problems. The project draws together sources of publicly-available pharmacological, physicochemical and biomolecular data, represents it in a stable infrastructure and provides well-defined information exploration and retrieval methods. Here, we highlight the utility of this platform in conjunction with workflow tools to solve pharmacological research questions that require interoperability between target, compound, and pathway data. Use cases presented herein cover 1) the comprehensive identification of chemical matter for a dopamine receptor drug discovery program 2) the identification of compounds active against all targets in the Epidermal growth factor receptor (ErbB) signaling pathway that have a relevance to disease and 3) the evaluation of established targets in the Vitamin D metabolism pathway to aid novel Vitamin D analogue design. The example workflows presented illustrate how the Open PHACTS Discovery Platform can be used to exploit existing knowledge and generate new hypotheses in the process of drug discovery.

Drug discovery FAQs: workflows for answering multidomain drug discovery questions

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.

API-centric Linked Data integration: The Open PHACTS Discovery Platform case study

Data integration is a key challenge faced in pharmacology where there are numerous heterogeneous databases spanning multiple domains (e.g. chemistry and biology). To address this challenge, the Open PHACTS consortium has developed the Open PHACTS Discovery Platform that leverages Linked Data to provide integrated access to pharmacology databases. Between its launch in April 2013 and March 2014, the platform has been accessed over 13.5 million times and has multiple applications that integrate with it. In this work, we discuss how Application Programming Interfaces can extend the classical Linked Data Application Architecture to facilitate data integration. Additionally, we show how the Open PHACTS Discovery Platform implements this extended architecture.

Exploiting Open Data: A New Era in Pharmacoinformatics

Within the last decade open data concepts has been gaining increasing interest in the area of drug discovery. With the launch of ChEMBL and PubChem, an enormous amount of bioactivity data was made easily accessible to the public domain. In addition, platforms that semantically integrate those data, such as the Open PHACTS Discovery Platform, permit querying across different domains of open life science data beyond the concept of ligand-target-pharmacology. However, most public databases are compiled from literature sources and are thus heterogeneous in their coverage. In addition, assay descriptions are not uniform and most often lack relevant information in the primary literature and, consequently, in databases. This raises the question how useful large public data sources are for deriving computational models. In this perspective, we highlight selected open-source initiatives and outline the possibilities and also the limitations when exploiting this huge amount of bioactivity data.

Accessing Open PHACTS: interactive exploration of compounds and targets from the semantic web

Pharmacological research is hampered by scattered data which have to be retrieved by varying methods and in different data formats. This heterogeneity increases research costs and limits throughput. Over the last two years, the Open PHACTS Discovery Platform [1] has been developed as a centralized repository, integrating pharmacological data from a variety of information resources and providing tools and services to query these integrated data in pharmacological research. Following an application-oriented approach, the Open PHACTS project started with the definition of potential use cases in the form of prioritized research questions [2], most of which can only be answered by accessing multiple data sources in the web. The development of the platform as well as the services has been guided by these questions. Here, we present the ChemBioNavigator (CBN) [3], a web application allowing to navigate the Open PHACTS chem-bio space with a focus on small molecules and their targets. CBN comprises of a large visualization area with different view modes and two information panels, allowing a deeper insight in information for compounds and targets. It allows interactive exploration of compound sets through sorting and subset selection as well as extending sets by substructure or similarity search. The relation between compounds and targets is defined by assay data from the Discovery Platform. Each compound and each target is annotated with information from multiple data sources which is provided together with the provenance for each data point. In this contribution we roughly outline the OpenPHACTS/CBN technology and present a number of high-priority research questions, highlight the advantages of exploiting the integrated data through the CBN's smart and intuitive interface.

Api-Centric Linked Data Integration: The Open Phacts Discovery Platform Case Study

Data integration is a key challenge faced in pharmacology where there are numerous heterogenous databases spanning multiple domains (e.g. chemistry and biology). To address this challenge, the Open PHACTS consortium has developed the Open PHACTS Discovery Platform that leverages Linked Data to provide integrated access to pharmacology databases. Between its launch in April 2013 and March 2014, the platform has been accessed over 13.5 million times and has multiple applications that integrate with it. In this work, we discuss how Application Programming Interfaces can extend the classical Linked Data Application Architecture to facilitate data integration. Additionally, we show how the Open PHACTS Discovery Platform implements this extended architecture.

Applying linked data approaches to pharmacology: Architectural decisions and implementation

The discovery of new medicines requires pharmacologists to interact with a number of information sources ranging from tabular data to scientific papers, and other specialized formats. In this application report, we describe a linked data platform for integrating multiple pharmacology datasets that form the basis for several drug discovery applications. The functionality offered by the platform has been drawn from a collection of prioritised drug discovery business questions created as part of the Open PHACTS project, a collaboration of research institutions and major pharmaceutical companies. We describe the architecture of the platform focusing on seven design decisions that drove its development with the aim of informing others developing similar software in this or other domains. The utility of the platform is demonstrated by the variety of drug discovery applications being built to access the integrated data.An alpha version of the OPS platform is currently available to the Open PHACTS consortium and a first public release will be made in late 2012, see http://www.openphacts.org/ for details.

Mobile applications driven by Open PHACTS semantic web technology

The Open PHACTS proiect is a large-scale public-private partnership funded under the European Innovative Medicines Initiative. The aim of the project is to create a stable infrastructure that combines diverse biomedical databases and enables scientists to answer complex questions of relevance to drug discovery and human health. The data integration is achieved through semantic web technologies, with data modeled in RDF and served through a high performance triple store. The main point of interaction with the system is an API, designed to be “developer friendly” by using familiar web technologies such as REST services and JSON. The vision is the Open PHACTS API becomes the foundation of an “application ecosystem”, enabling anyone to create applications targeting different use-cases within this domain. Here, we present two examples of the use of the Open PHACTS API to create mobile scientific applications. The ChemBioNavigator is a tool that allows researchers to analyze and triage sets of bioactive small molecules. Physiochemical properties are used to separate the molecules into different areas of a graph, upon which biological information from the Open PHACTS database is overlaid. This visualization allows users to understand the relationship between these data and select the molecules with the best overall combinations of these properties. The second example is the iPharm application which is designed to address a common situation where a researcher needs a high-level overview on a drug or target. The user simply opens up the application, enters a drug name and is presented with key clinical and molecular data summarizing the action of that drug. An important aspect of both applications is that while they are based on semantic technologies, the user interfaces are specifically designed to look like “normal” applications. We demonstrate the combination of semantic data with natural user interfaces provides a powerful mechanism to address scientific data navigation.

Open_PHACTS and NanoPublications

This tutorial is an introduction to the Open PHACTS platform and API tailored to the wide community of potential data providers, data consumers, and service providers. The tutorial will include an overview of the Open PHACTS architecture, data sources, and example applications followed by a hands-on session detailing the use of the API.