Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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
Receptor.AI
 
UPACC
Q9UHY7

UPID:
ENOPH_HUMAN

ALTERNATIVE NAMES:
2,3-diketo-5-methylthio-1-phosphopentane phosphatase; MASA homolog

ALTERNATIVE UPACC:
Q9UHY7; Q7Z4C5; Q9BVC2

BACKGROUND:
The enzyme Enolase-phosphatase E1, with alternative names such as 2,3-diketo-5-methylthio-1-phosphopentane phosphatase and MASA homolog, is a bifunctional entity in the methionine salvage pathway. It efficiently catalyzes the transformation of 2,3-diketo-5-methylthiopentyl-1-phosphate into a crucial intermediate, further leading to the production of acireductone. This process is vital for the synthesis of methionine, an essential amino acid, underscoring the enzyme's critical role in cellular health and metabolism.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Enolase-phosphatase E1 could open doors to potential therapeutic strategies.

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