The Flare Python API provides comprehensive access to Flare's scientific capabilities, enabling users to optimize their work processes through custom workflows, task automation, and the integration of Python modules and controls. To assist newcomers to Python™, Cresset has developed and consistently updates the Flare Python Cookbook.
Containing a compilation of readily applicable 'recipes', the cookbook presents simplified code snippets, each designed to execute a specific task directly from the Flare graphical user interface (GUI). Medicinal and computational chemists can leverage these recipes individually or in combination, crafting intricate workflows to suit their needs.
In the most recent release of Flare Python Cookbook V3, the newly introduced recipes empower users to refine ligand profiling by assessing synthetic accessibility score (SAS) and quantitatively estimating drug-likeness (QED). Furthermore, they enhance result organization and communication by incorporating visual aids that link images to ligands. These recipes also elevate structure-activity prediction capabilities by leveraging Quantum Mechanics (QM) based descriptors like chemical hardness, electronegativity, and global electrophilicity index. This update marks a significant step toward expediting the drug design process and streamlining molecule triage for chemists.