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   R & D

In this section

    R & D

    Domain Therapeutics addresses unmet needs in GPCR drug discovery

    • Identifying allosteric modulators presenting better efficacy
    • Selecting biased ligands presenting better safety profile
    • Addressing orphan and historically intractable GPCRs
    • Increasing the success rate of High Throughput Screening (HTS) campaigns

    Domain has positioned two dedicated technologies on the drug discovery process to address these unmet needs

    DTect-AllTM

    This platform, developed by the groups of Professor Marcel Hibert and Dr. Jean-Luc Galzi at the University of Strasbourg, is aimed at selecting in a library of hundreds of thousand of compounds any ligand interacting with the GPCR of interest without considering at this stage the functional activity of the selected ligands. An HTS campaign run with DTect-AllTM results in a sub-library of GPCR-interacting ligands. The size of the sub-library is compatible with a broad functional characterization. Learn more

    Domain’s activities with DTect-AllTM are to:

    • Develop HTS FRET-based assays
    • Run HTS campaigns either on Domain’s internal library or on partner compound collection
    • Confirm the specificity of binding of the GPCR-interacting ligands


    BioSens-AllTM

    This platform, developed by a consortium of researchers from Quebec, Canada (Pr Michel Bouvier, Pr Graciela Pineyro and Dr Christian Le Gouill at the University of Montreal, Pr Terry Hebert and Pr Stéphane Laporte at McGill University, and Pr Richard Leduc at Sherbrooke University), is aimed at defining the functional signature of GPCR-interacting ligands selected by DTect-AllTM. Multiple pathways can be activated by a single GPCR and each activated pathway may result in a different biological response – efficacy, toxicity, tolerance, receptor desensitization. The discovery of more efficient and safer GPCR drugs requires an extensive characterization of GPCR ligands on these signaling pathways. BioSens-AllTM identify every cluster of compounds presenting common signaling signatures in the sub-library of GPCR-interacting ligands. Representatives of each cluster are further characterized on in vitro native systems to determine which profile is worth considering for a medicinal chemistry optimization program. Learn more

    Domain’s activities with BioSens-AllTM are to:

    • Characterize GPCR-interacting ligands, selected with DTect-AllTM, on multiple functional signaling pathways in parallel (18 pathways)
    • Cluster the functionally active ligands according to their signaling signatures

    Hit-to-lead and lead optimization phases

    Domain Therapeutics leverages the knowledge and expertise of its R&D team to conduct:

    • Medicinal chemistry optimization
    • In vitro pharmacology (targeted GPCR and off-target)

    Domain Therapeutics also applies the same technologies that have been used during the HTS and functional characterization.
    DTect-AllTM and BioSens-AllTM are positioned to support the medicinal chemistry and pharmacology efforts. Newly synthesized compounds are tested on the platforms to monitor their binding on the targeted GPCR and signaling signatures. Domain Therapeutics has conducted multiple projects from validated hits to preclinical candidates by using a network of CROs and academic partners for:

    • Native in vitro/in vivo systems (for validation of signaling signatures)
    • In vivo models (for the specified indication)
    • Early-ADME Tox package

    The benefit of combining DTect-AllTM and BioSens-AllTM technologies

    DTect-AllTM and BioSens-AllTM can be used synergistically to efficiently discover biased allosteric modulators for challenging GPCRs. DTect-AllTM is used on an engineered GPCR (e.g. modified to screen on allosteric modulator regions) as a filtering step to reduce the number of compounds to be tested for functional characterization. The subset of selected ligands is then widely characterized on the wild-type GPCR using BioSens-AllTM to define clusters of ligands sharing the same signaling signature. Members of these clusters can be further characterized to select biased allosteric modulators offering the safest and most efficient profile. Then, such biased allosteric modulators are tested in native physiological systems to deliver fully validated hits ready to enter hit-to-lead optimization process.