Sanoosa’s Technology Platform


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 is based on: 


  • 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.

The heart of our method: 

Multiple Fragment Molecular Dynamics MFMD

How MFMD works:   

Our “Multiple Fragment Molecular Dynamics” (MFMD) scan of a target binding pocket helps to answer whether compounds are well suited to a target, but also indicates ways on how to improve the compounds.

We probe the ligand binding pocket of a protein target using a larger number (200 to 400) of fragments randomly distributed around sites of interest of a protein.  During a molecular dynamics simulation where fragments only “see” the protein and not each other, the fragments move towards the protein and cluster close to their preferred positions in the protein.  The density of the clusters provides an indication of the “affinity” of the fragment at a location inside the binding pocket. Molecular mechanics gives us a rough estimate of the interaction energies between fragments and the protein.  We optimise the positions and atomic interactions of selected fragments using ab-inito quantum mechanical (QM) methods. Finally, we calculate a most accurate interaction energy between the fragments and the binding site.  


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.  


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.

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