AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Gamma-aminobutyric acid receptor subunit alpha-4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

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

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our top-notch dedicated system is used to design specialised libraries for receptors.

 Fig. 1. The sreening 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P48169

UPID:

GBRA4_HUMAN

Alternative names:

GABA(A) receptor subunit alpha-4

Alternative UPACC:

P48169; Q8IYR7

Background:

Gamma-aminobutyric acid receptor subunit alpha-4, known as GABA(A) receptor subunit alpha-4, plays a pivotal role in the brain's inhibitory signaling by binding GABA, the primary inhibitory neurotransmitter. This interaction opens a chloride channel, leading to neuronal inhibition, crucial for maintaining the balance of neural activity.

Therapeutic significance:

Understanding the role of Gamma-aminobutyric acid receptor subunit alpha-4 could open doors to potential therapeutic strategies. Its involvement in inhibitory neurotransmission positions it as a key target for modulating brain activity, offering avenues for the development of treatments for neurological conditions.

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