Using ChEMBL web services for building applications and data processing workflows relevant to drug discovery

ABSTRACT

Introduction: ChEMBL is a manually curated database of bioactivity data on small drug-like molecules, used by drug discovery scientists. Among many access methods, a REST API provides programmatic access, allowing the remote retrieval of ChEMBL data and its integration into other applications. This approach allows scientists to move from a world where they go to the ChEMBL web site to search for relevant data, to one where ChEMBL data can be simply integrated into their everyday tools and work environment.

Areas covered: This review highlights some of the audiences who may benefit from using the ChEMBL API, and the goals they can address, through the description of several use cases. The examples cover a team communication tool (Slack), a data analytics platform (KNIME), batch job management software (Luigi) and Rich Internet Applications.

Expert opinion: The advent of web technologies, cloud computing and micro services oriented architectures have made REST APIs an essential ingredient of modern software development models.

The widespread availability of tools consuming RESTful resources have made them useful for many groups of users. The ChEMBL API is a valuable resource of drug discovery bioactivity data for professional chemists, chemistry students, data scientists, scientific and web developers.

KEYWORDS:

• API
• ChEMBL
• KNIME
• Luigi
• pipeline
• Python
• REST
• service
• Slack
• workflow

Article highlights

• ChEMBL API is free and open solution providing programmatic access to ChEMBL data.

• The API can be easily integrated with Slack to help chemists to collaborate.

• KNIME users can utilize the API for data mining and creating prototype workflows.

• ChEMBL web services can be a good foundation for well-designed chemistry web applications.

• Various API methods can be combined together to create a flexible data processing pipelines in production environments supporting micro services architecture.

• Professional chemists, chemistry students, data scientists, scientific developers and web designers can all benefit from using the API.

This box summarizes key points contained in the article.

Acknowledgments

The authors would like to thank Greg Landrum for his original idea of resolving chemical entities inside Slack and George Papadatos for his enthusiasm and dedication in evangelizing the KNIME platform.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Additional information

Funding

This work was supported by Strategic Awards from the Wellcome Trust (grants no. WT086151/Z/08/Z, WT104104/Z/14/Z) and the Member States of the European Molecular Biology Laboratory (EMBL)