BioPharmics

Overview of 3D Modelling Capabilities

This platform offers cutting-edge 3D modelling for both ligand-based and structure-based drug design. It enables the rapid and accurate generation of conformational ensembles, even for complex macrocycles, without needing protein structural data. The software supports virtual screening and predicts ligand poses and binding affinities efficiently.

3D Computational Modelling Features

• 3D Chemical Toolkit Operations: Generate fast and accurate conformers without templates, including chirality enumeration and heuristic protonation at physiological pH. Create large-scale conformer databases for virtual screening.
• Docking and Structure-Based Design: Automate protein preparation and alignment, achieve high enrichment, and predict accurate poses. Model conformational heterogeneity with real-space fitting of ligands into X-ray electron density.
• Ligand-Based Modelling: Screen millions of compounds with industry-leading enrichment and predict relative bound poses of diverse ligands using multiple-ligand alignment.
• Affinity Prediction: Utilize machine learning to predict ligand binding affinity and pose with scaffold-independent models.

Collaborative Research and Publications

The platform is backed by a range of peer-reviewed publications that detail the scientific principles and applications of the software. It addresses complex challenges like scaffold replacement while maintaining potency and stability.

Method Highlights

• ForceGen: A patented method for generating accurate conformers for macrocycles and novel compounds, using 3D physical manipulations to explore geometrical configurations.
• xGen: A real-space ligand refinement method that fits ligand X-ray density to produce accurate, low-strain models of ligand binding.
• Surflex-Dock: Provides automated docking with top-tier enrichment and pose prediction, supporting 3D structure-based design.
• eSim: Facilitates fast, reliable 3D ligand-based drug design and virtual screening, using molecular similarity from a protein's perspective.

These features collectively enhance the drug design process, offering robust and accurate solutions for molecular modelling and virtual screening.