3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery

Albert J. Kooistra, Márton Vass, Ross Mcguire, Rob Leurs, Iwan J.P. deEsch, Gert Vriend, Stefan Verhoeven*, Chris deGraaf

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

eScience technologies are needed to process the information available in many heterogeneous types of protein-ligand interaction data and to capture these data into models that enable the design of efficacious and safe medicines. Here we present scientific KNIME tools and workflows that enable the integration of chemical, pharmacological, and structural information for: i)structure-based bioactivity data mapping, ii)structure-based identification of scaffold replacement strategies for ligand design, iii)ligand-based target prediction, iv)protein sequence-based binding site identification and ligand repurposing, and v)structure-based pharmacophore comparison for ligand repurposing across protein families. The modular setup of the workflows and the use of well-established standards allows the re-use of these protocols and facilitates the design of customized computer-aided drug discovery workflows.

Original languageEnglish
Pages (from-to)614-626
Number of pages13
JournalChemMedChem
Volume13
Issue number6
DOIs
Publication statusAccepted/In press - 1 Jan 2017

Funding

The authors would like to thank Thomas E. Exner for discussion on the PLANTS nodes development, David E. Gloriam and Christian Munk for discussion on the GPCRdb nodes development, and Silicos-IT for making their tools open source. This research was supported financially by the Netherlands eScience Center (NLeSC)/NWO (Enabling Technologies project: 3D-e-Chem, grant 027.014.201) to C.d.G.. A.J.K., M.V., R.L., I.J.P.d.E., and C.d.G. participate in the GPCR Consortium (https://gpcrconsortium.org).

FundersFunder number
Netherlands eScience Center
Nederlandse Organisatie voor Wetenschappelijk Onderzoek027.014.201

    Keywords

    • Cheminformatics workflows
    • KNIME
    • Ligand design
    • Ligand repurposing
    • Target prediction

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