AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Gremlin-2

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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

Q9H772

UPID:

GREM2_HUMAN

Alternative names:

Cysteine knot superfamily 1, BMP antagonist 2; DAN domain family member 3; Protein related to DAN and cerberus

Alternative UPACC:

Q9H772; Q86UD9

Background:

Gremlin-2, also known as Cysteine knot superfamily 1, BMP antagonist 2, and DAN domain family member 3, plays a crucial role in modulating BMP2 and BMP4 signaling. This protein is instrumental in embryonic morphogenesis and the regulation of progesterone production in granulosa cells by antagonizing BMP4-induced effects.

Therapeutic significance:

Gremlin-2's involvement in selective tooth agenesis, specifically Tooth agenesis, selective, 9, highlights its potential as a target for therapeutic intervention. Understanding the role of Gremlin-2 could open doors to potential therapeutic strategies.

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