AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Gamma-aminobutyric acid receptor subunit gamma-2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

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 utilise our cutting-edge, exclusive workflow to develop focused libraries for receptors.

 Fig. 1. The sreening 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P18507

UPID:

GBRG2_HUMAN

Alternative names:

GABA(A) receptor subunit gamma-2

Alternative UPACC:

P18507; F5HB82; Q6GRL6; Q6PCC3; Q9UDB3; Q9UN15

Background:

Gamma-aminobutyric acid receptor subunit gamma-2, also known as GABA(A) receptor subunit gamma-2, plays a pivotal role in the brain's inhibitory signaling by forming ligand-gated chloride channels. This protein is essential for the development of functional inhibitory GABAergic synapses, contributing to synaptic inhibition as a GABA-gated ion channel. Its interaction with different alpha and beta subunits influences the formation of synaptic contacts, highlighting its significance in neurodevelopment.

Therapeutic significance:

The protein's involvement in various epileptic conditions, including Developmental and epileptic encephalopathy 74, Epilepsy, childhood absence 2, Febrile seizures, familial, 8, and Generalized epilepsy with febrile seizures plus 3, underscores its therapeutic significance. Understanding the role of Gamma-aminobutyric acid receptor subunit gamma-2 could open doors to potential therapeutic strategies for these debilitating neurological disorders.

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