Sanoosa’s Technology Platform

Unique technology combined with process discipline


Our proprietary developed small molecule drug discovery & design platform generates rapidly new assets for targets that are considered intractable to the approaches taken by others.

Our proprietary computational design platform has been proven in commercial drug design, molecular modelling, development of lead compounds into drug candidates and antibody-binding epitope characterization. Our technology implements high-level quantum chemical methods for ligand docking and fragment-based drug design.


We design molecules that interact with protein surfaces, binding pockets and act as protein-protein interaction inhibitors. Our molecular designs reliably deliver the binding mode and mode-of action on protein surfaces and evaluate the “druggability” of target sites.

Our technology:

  • The consequent application of quantum mechanical methods throughout the design and modelling procedures.
  • Quantum Mechanical and Molecular Mechanical calculations of ligand binding energies.
  • Our own “Multiple Fragment Molecular Dynamics (MFMD)” method to explore the binding site with small fragments. 
  • Our own “Dynamic Score of Structural Stability” and “Clustering” – unique methods to analyse computational results.
  • Proficient application of AI/ML methods adds further precision to our compound design.

The heart of our method:

Multiple Fragment Molecular Dynamics MFMD

MFMD is based on the “MCSS” method we developed for computational design of protein-protein inhibitors and conventional target binding sites.  The origin of the method is published in: Zeng J. and Treutlein HR, A method for computational combinatorial peptide design of inhibitors of Ras. Protein Engineering 12, 457-468, 1999.

Our “Multiple Fragment Molecular Dynamics” (MFMD) scans of a target binding pocket not only tell us whether compounds are well suited to a target, but also indicate ways on how to improve the compounds.


Our outcomes speak for themselves. Using MFMD we have successfully predicted ligand binding modes and optimised inhibitors for numerous targets in collaborations with both members of academia and partners in the pharmaceutical industry. Click here for references to our published projects.

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