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

Area of Science:

• Computational chemistry
• cheminformatics
• bioinformatics
• drug discovery

Background:

• eScience technologies are crucial for managing heterogeneous protein-ligand interaction data.
• Effective data integration is needed to build models for designing safe and efficacious medicines.

Purpose of the Study:

• To present scientific KNIME tools and workflows for integrating chemical, pharmacological, and structural information.
• To enable various drug design strategies, including scaffold hopping and ligand repurposing.

Main Methods:

• Structure-based bioactivity data mapping
• Structure-based identification of scaffold replacement strategies
• Ligand-based target prediction
• Protein sequence-based binding site identification and ligand repurposing
• Structure-based pharmacophore comparison for ligand repurposing

Main Results:

• Demonstrated the integration of diverse data types using KNIME workflows.
• Enabled structure-based and ligand-based approaches for drug design and repurposing.
• Facilitated customized computer-aided drug discovery (CADD) workflows.

Conclusions:

• The presented KNIME tools and workflows effectively integrate heterogeneous data for drug discovery.
• The modular design and use of standards allow for reusability and customization of CADD workflows.
• These advancements support the design of efficacious and safe medicines.