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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9NRM0

UPID:
GTR9_HUMAN

ALTERNATIVE NAMES:
Glucose transporter type 9; Urate transporter

ALTERNATIVE UPACC:
Q9NRM0; Q0VGC4; Q4W5D1; Q8WV30; Q96P00

BACKGROUND:
The Solute carrier family 2, facilitated glucose transporter member 9, known alternatively as Glucose transporter type 9 and Urate transporter, is crucial for urate handling in the kidneys. It transports urate much more efficiently than glucose, and has limited activity for fructose and adenine transport. This protein does not facilitate the transport of galactose.

THERAPEUTIC SIGNIFICANCE:
Mutations affecting SLC2A9 are responsible for Hypouricemia renal 2, characterized by reduced uric acid reabsorption and increased urinary urate excretion. This genetic condition can lead to severe renal issues, including acute and chronic renal failure, and kidney stones. Targeting SLC2A9 function offers a promising avenue for therapeutic intervention in these renal disorders.

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