QioMed uses an iterative bio-computational, first principles modeling process to (a) determine target protein structures and binding sites, and (b) to discover, design and develop appropriate ligands and lead compounds for those targets.

QioMed’s technologies are applicable across all protein drug targets and enable determination of tertiary structures of GPCRs without reliance on experimental structural data. Our technology and approach have been proven in our own work and in collaborations with large pharmaceutical companies. QioMed can address a wide range of targets and therapeutic areas on its own or in collaboration with partners.

For GPCRs, a class of transmembrane proteins that includes the targets of ~40% of current drugs, QM’s technology has successfully determined the structure and drug binding site for the:

a) muscarinic acetylcholine M1 receptor,
b) chemokine CCR1/CCR5 receptors,
c) prostaglandin DP receptor,
d) serotonin 5HT2b/2c receptors,
e) adenosine A2a/A3 receptors,
f) histamine H3 receptor,
g) TAS2R38 taste receptor, and
h) cannabinoid CB1 receptor.

QioMed’s protein target structures and ligands have proven their value as the basis for discovery and design of lead compounds.

Structural information from nuclear magnetic resonance spectroscopy (NMR) and X-ray analysis, where available, provides only a snapshot of one conformation of a protein or part of a protein. These methods do not provide any dynamic information or any ability to explore protein dynamics as the molecule changes conformations, changes from inactive to active state, or interacts with ligands or other proteins. X-ray and NMR structural information provides only initial information that helps in the construction of QioMed’s computational models.

In the general case, QioMed uses sequence information and, if available, structural data to build highly precise, atomic level models of target proteins, binding sites, and ligands. These models allow us to explore a protein’s dynamics, including its conformational changes and the dynamics of its interactions with ligands and other proteins. Other computational approaches, including homology modeling, do not offer the precision and sensitivity required for protein structure and ligand binding analyses that are fundamental to drug discovery and design. First principles modeling is not homology modeling.



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