A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19

Alzbeta Tuerkova; Barbara Zdrazil

doi:10.1186/s13321-020-00474-z

A ligand-based computational drug repurposing pipeline using KNIME and Programmatic Data Access: case studies for rare diseases and COVID-19

J Cheminform. 2020 Nov 25:12:71. doi: 10.1186/s13321-020-00474-z. eCollection 2020.

Authors

Alzbeta Tuerkova¹, Barbara Zdrazil¹

Affiliation

¹ Department of Pharmaceutical Chemistry, Division of Drug Design and Medicinal Chemistry, University of Vienna, Althanstraße 14, 1090 Vienna, Austria.

Abstract

Biomedical information mining is increasingly recognized as a promising technique to accelerate drug discovery and development. Especially, integrative approaches which mine data from several (open) data sources have become more attractive with the increasing possibilities to programmatically access data through Application Programming Interfaces (APIs). The use of open data in conjunction with free, platform-independent analytic tools provides the additional advantage of flexibility, re-usability, and transparency. Here, we present a strategy for performing ligand-based in silico drug repurposing with the analytics platform KNIME. We demonstrate the usefulness of the developed workflow on the basis of two different use cases: a rare disease (here: Glucose Transporter Type 1 (GLUT-1) deficiency), and a new disease (here: COVID 19). The workflow includes a targeted download of data through web services, data curation, detection of enriched structural patterns, as well as substructure searches in DrugBank and a recently deposited data set of antiviral drugs provided by Chemical Abstracts Service. Developed workflows, tutorials with detailed step-by-step instructions, and the information gained by the analysis of data for GLUT-1 deficiency syndrome and COVID-19 are made freely available to the scientific community. The provided framework can be reused by researchers for other in silico drug repurposing projects, and it should serve as a valuable teaching resource for conveying integrative data mining strategies.

Keywords: Application programming interface; COVID-19; ChEMBL; Data access; Data integration; Data mining; Drug repurposing; DrugBank; GLUT-1 deficiency syndrome; Guide-to-pharmacology; KNIME workflow; Open targets platform; PDB; PubChem; Rare disease; SARS-CoV-2; Substructure search; UniProtKB.