BioPharmics

Industry-leading 3D Macrocycle Modelling

BioPharmics offers a cutting-edge platform for 3D macrocycle modeling, significantly reducing synthesis requirements by up to 90%. It provides unmatched speed and accuracy, enabling seamless integration into hit-to-candidate workflows. This technology accelerates project timelines, lowers costs, and boosts success rates in macrocycle discovery.

Backed by Rigorous Science

BioPharmics is supported by over 40 peer-reviewed publications and is trusted by top pharmaceutical companies to tackle complex macrocycle challenges. Its advanced algorithms capture macrocycle flexibility with exceptional speed and precision, generating low-energy conformational ensembles that incorporate experimental data from NMR, X-ray, or cryo-EM.

Comprehensive Macrocycle Modelling Suite

The platform includes five specialized methodologies:

• ForceGen™: Generates complete conformational ensembles quickly, exploring molecular conformational space without relying on precalculated templates.
• xGen™: Refines conformational ensembles using X-ray electron density maps, producing accurate models of ligand binding.
• eSim™: Performs high-performance 3D virtual screening, analyzing molecular shape and charge to screen compounds efficiently.
• Surflex-Dock™: Automates bound ligand pose prediction, ranking compounds by affinity to prioritize synthesis and testing.
• QuanSA™: Predicts ligand-based binding affinity with high accuracy, offering a fast and broad applicability without needing a protein target structure.

Proven Science and Peer-reviewed Results

BioPharmics' capabilities are validated by scientific research, demonstrating significant advances in computational macrocycle design. Its methods, such as ForceGen and Surflex-Dock, have shown to predict binding poses accurately, outperforming other solutions. The platform also supports complex peptide macrocycle optimization by integrating NMR restraints with computational analysis, enabling effective prioritization of ligand poses and conformational strain.