Focused On-demand Library for Solute carrier family 2, facilitated glucose transporter member 9

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

Glucose transporter type 9; Urate transporter

Alternative UPACC:

Q9NRM0; Q0VGC4; Q4W5D1; Q8WV30; Q96P00


Solute carrier family 2, facilitated glucose transporter member 9 (SLC2A9), also known as Glucose transporter type 9 and Urate transporter, plays a pivotal role in urate reabsorption in proximal renal tubules. It exhibits a high-capacity for urate transport, significantly outpacing its glucose transport activity. Additionally, SLC2A9 has a minor role in transporting fructose and adenine, but not galactose or other nucleobases.

Therapeutic significance:

SLC2A9's dysfunction is linked to Hypouricemia renal 2, a disorder marked by impaired uric acid reabsorption leading to high urinary urate excretion. This condition can result in exercise-induced acute renal failure, chronic renal dysfunction, and nephrolithiasis. Understanding the role of SLC2A9 could open doors to potential therapeutic strategies for managing these renal complications.

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