bbSelect - An Open-Source Tool for Performing a 3D Pharmacophore-Driven Diverse Selection of R-Groups

Area of Science:

• Computational chemistry and cheminformatics
• Drug discovery and medicinal chemistry

Background:

• Hit-to-lead optimization involves exploring chemical space around a core scaffold to enhance target protein interactions.
• Systematic 3D placement of pharmacophore features is crucial for rational compound design, especially without available protein structures.

Purpose of the Study:

• To introduce bbSelect, an open-source computational tool for mapping pharmacophore feature placements in 3D Euclidean space.
• To facilitate diverse and systematic selection of R-groups for drug design, aiding hit-to-lead optimization.

Main Methods:

• bbSelect utilizes a library of R-groups and employs partitioning algorithms to select features.
• The tool maps pharmacophore feature placements in 3D space to a user-defined selection size.
• Evaluated against existing methods to demonstrate its selection capabilities.

Main Results:

• bbSelect demonstrated superior performance in generating diverse selections compared to established methods.
• Achieved high coverage of pharmacophore feature placements with significantly smaller subset sizes.
• Selections were made without introducing unnecessary complexity, providing clear visualizations and rationale.

Conclusions:

• bbSelect is an effective open-source tool for guiding hit-to-lead activities in drug discovery.
• It enables systematic and diverse exploration of chemical space for optimized compound design.
• The tool enhances understanding and interrogation of results for medicinal chemists.