Focused On-demand Libraries - Receptor.AI 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.


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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Receptor.AI
 
UPACC
Q9NRG1

UPID:
PRDC1_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q9NRG1; B7Z1Z3; Q53HA7; Q59EL9; Q5VV18; Q5VV20

BACKGROUND:
The Phosphoribosyltransferase domain-containing protein 1, with the unique identifier Q9NRG1, is characterized by its ability to bind key molecules such as GMP, IMP, and PRPP, despite demonstrating low phosphoribosyltransferase activity in laboratory settings. This suggests a specialized role in cellular functions, possibly influencing purine metabolism or the salvage of GMP, which are critical pathways in nucleotide synthesis and recycling.

THERAPEUTIC SIGNIFICANCE:
The exploration of Phosphoribosyltransferase domain-containing protein 1's function offers a promising avenue for the development of novel therapeutic approaches. Its specific molecular interactions provide a foundation for research aimed at uncovering new drug targets, potentially leading to breakthroughs in the treatment of diseases linked to purine metabolism and nucleotide synthesis disorders.

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