Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We employ our advanced, specialised process to create targeted libraries for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P10912

UPID:
GHR_HUMAN

ALTERNATIVE NAMES:
Somatotropin receptor

ALTERNATIVE UPACC:
P10912; Q9HCX2

BACKGROUND:
Growth Hormone Receptor (GHR), identified by its alternative name Somatotropin receptor, is crucial for postnatal body growth regulation. It interacts with growth hormone from the pituitary gland, triggering the JAK2/STAT5 pathway. GHR's isoform 2 and its soluble form, GHBP, regulate GH signaling by modulating GHBP production and acting as a negative inhibitor.

THERAPEUTIC SIGNIFICANCE:
Involvement of GHR in diseases such as Laron syndrome and partial growth hormone insensitivity highlights its significance. These conditions, characterized by growth impairment and short stature, are linked to GHR gene variants. Targeting GHR could offer novel therapeutic approaches for these growth disorders.

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