OpenGrowth

OpenGrowth generates de novo ligands within protein active sites by connecting small organic fragments to produce molecules that statistically mirror drug-like structures from an input training database and improve synthetic accessibility and pharmacokinetic properties.

Key Features:

• De novo ligand design: Constructs novel ligands directly within protein active sites by fragment assembly.
• Fragment connection guided by training data: Connects small organic fragments using statistical patterns derived from an input training database of drug-like structures.
• Synthetic accessibility and pharmacokinetics: Generates molecules with enhanced synthetic accessibility and favorable pharmacokinetic properties compared to random growth methods.
• Protein flexibility consideration: Incorporates protein flexibility during the molecule growth process to tailor ligand design to dynamic active sites.
• Seed-initiated growth: Allows growth initiation from a seed structure to emulate R-group optimization strategies.
• Fragment-based workflows: Supports fragment-based drug discovery approaches by growing and connecting fragments in situ.
• Inhibitor design focus: Facilitates design choices advantageous for inhibitors aiming for high specificity and potency.

Scientific Applications:

• Active site ligand discovery: Design novel ligands tailored to protein active sites using fragment-based assembly.
• R-group optimization: Optimize substituents on a seed scaffold by growing R-groups in the context of the target protein.
• Fragment-based drug discovery: Assemble and evolve fragment hits into drug-like molecules guided by training-database statistics.
• Lead optimization for inhibitors: Generate candidate inhibitors with improved synthetic accessibility and pharmacokinetic profiles.

Methodology:

Molecule growth connects small organic fragments guided by statistical patterns from an input training database, considers protein flexibility during growth, and can be initiated from a seed structure to emulate R-group optimization or fragment-based drug discovery.