AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Rab3 GTPase-activating protein catalytic subunit

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast 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.

partner

Reaxense

upacc

Q15042

UPID:

RB3GP_HUMAN

Alternative names:

RAB3 GTPase-activating protein 130 kDa subunit; Rab3-GAP p130

Alternative UPACC:

Q15042; A6H8Z3; C9J837; Q659F5; Q8TBB4

Background:

The Rab3 GTPase-activating protein catalytic subunit, also known as RAB3GAP1, plays a pivotal role in neurotransmitter and hormone exocytosis regulation. It functions as a catalytic subunit within the Rab3GAP complex, facilitating the conversion of RAB3-GTP to RAB3-GDP and activating RAB18 at the ER membrane, crucial for maintaining proper ER structure and normal eye and brain development.

Therapeutic significance:

Mutations in RAB3GAP1 are linked to Warburg Micro syndrome 1 and Martsolf syndrome 2, rare disorders characterized by severe intellectual disability, eye abnormalities, and hypogonadism. Understanding the role of RAB3GAP1 could open doors to potential therapeutic strategies for these conditions.

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