Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


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 use our state-of-the-art dedicated workflow for designing focused 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
P42263

UPID:
GRIA3_HUMAN

ALTERNATIVE NAMES:
AMPA-selective glutamate receptor 3; GluR-C; GluR-K3; Glutamate receptor ionotropic, AMPA 3

ALTERNATIVE UPACC:
P42263; D3DTF1; Q4VXD5; Q4VXD6; Q9HDA0; Q9HDA1; Q9HDA2; Q9P0H1

BACKGROUND:
The Glutamate receptor 3, alternatively named AMPA-selective glutamate receptor 3, GluR-C, GluR-K3, or Glutamate receptor ionotropic, AMPA 3, is integral for excitatory synaptic transmission in the central nervous system. It acts as a ligand-gated ion channel, responding to L-glutamate by undergoing a conformational change that opens the cation channel, facilitating the conversion of a chemical signal into an electrical impulse.

THERAPEUTIC SIGNIFICANCE:
Linked to Intellectual developmental disorder, X-linked, syndromic, Wu type, Glutamate receptor 3's involvement suggests its potential as a target for therapeutic intervention. Understanding its role could pave the way for innovative treatments for this and possibly other neurological disorders.

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