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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

This includes comprehensive molecular simulations of the receptor in its native membrane environment, paired with ensemble virtual screening that factors in its conformational mobility. In cases involving dimeric or oligomeric receptors, the entire functional complex is modelled, pinpointing potential binding pockets on and between the subunits to capture the full range of 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
O75899

UPID:
GABR2_HUMAN

ALTERNATIVE NAMES:
G-protein coupled receptor 51; HG20

ALTERNATIVE UPACC:
O75899; O75974; O75975; Q5VXZ2; Q8WX04; Q9P1R2; Q9UNR1; Q9UNS9

BACKGROUND:
The Gamma-aminobutyric acid type B receptor subunit 2, known alternatively as G-protein coupled receptor 51 or HG20, is integral to the GABAergic system's inhibitory function. This protein, in partnership with GABBR1, forms a receptor essential for neurotransmission, affecting adenylate cyclase activity, phospholipase A2 stimulation, and the modulation of ion channels.

THERAPEUTIC SIGNIFICANCE:
The association of Gamma-aminobutyric acid type B receptor subunit 2 with severe neurological conditions underscores its therapeutic importance. Targeting GABBR2 could lead to innovative treatments for diseases such as Neurodevelopmental disorder with poor language and loss of hand skills, and Developmental and epileptic encephalopathy 59, offering hope for affected individuals.

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