Focused On-demand Library for Gamma-aminobutyric acid receptor-associated protein-like 2

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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.







Alternative names:

GABA(A) receptor-associated protein-like 2; Ganglioside expression factor 2; General protein transport factor p16; Golgi-associated ATPase enhancer of 16 kDa; MAP1 light chain 3-related protein

Alternative UPACC:

P60520; O08765; Q6FG91; Q9DCP8; Q9UQF7


Gamma-aminobutyric acid receptor-associated protein-like 2 (GABARAPL2) plays a pivotal role in cellular processes, including intra-Golgi traffic and autophagy. By modulating NSF activity and SNAREs activation, GABARAPL2 ensures efficient intra-Golgi transport. Its involvement in autophagy and mitophagy is crucial for maintaining cellular energy balance and preventing excess ROS production. The protein is essential for autophagosome maturation, highlighting its significance in cellular homeostasis.

Therapeutic significance:

Understanding the role of Gamma-aminobutyric acid receptor-associated protein-like 2 could open doors to potential therapeutic strategies. Its critical function in autophagy and mitophagy, processes vital for cellular health and energy regulation, positions GABARAPL2 as a key target in developing treatments for diseases where these processes are dysregulated.

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