Qsarna

Qsarna combines machine learning and molecular docking to streamline virtual screening workflows for drug design.

Key Features:

• Activity Prediction: Employs machine learning to predict compound activity.
• Molecular Docking: Integrates traditional molecular docking for pose examination.
• Fragment-based Generative Model: Enables exploration of novel chemical spaces with desired pharmacophoric features.
• Chemical Space Navigation: Allows users to explore chemical space for virtual screening.

Scientific Applications:

• Virtual Screening: Streamlines virtual screening workflows for drug discovery.
• Hit Identification: Identified three new hits for monoamine oxidase B with nanomolar potency confirmed by experimental assays.

Methodology:

Qsarna combines machine learning for activity prediction with traditional molecular docking, employing a fragment-based generative model for chemical space exploration.