Focused On-demand Library for Kynurenine--oxoglutarate transaminase 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Cysteine-S-conjugate beta-lyase 2; Kynurenine aminotransferase 3; Kynurenine aminotransferase III; Kynurenine--glyoxylate transaminase; Kynurenine--oxoglutarate transaminase III

Alternative UPACC:

Q6YP21; B3KQ13; O95335; Q5JS27; Q5T9T7; Q5T9T8; Q6AI27; Q6ICW1; Q9BVY5


Kynurenine--oxoglutarate transaminase 3, also known as Kynurenine aminotransferase III, plays a crucial role in the tryptophan catabolic pathway by catalyzing the conversion of L-kynurenine to kynurenic acid (KA). This enzyme is a broad spectrum antagonist of ionotropic excitatory amino acid receptors, impacting neurotransmission and neurobiology significantly. Its activity extends to various amino acids, showcasing versatility in substrate specificity.

Therapeutic significance:

Understanding the role of Kynurenine--oxoglutarate transaminase 3 could open doors to potential therapeutic strategies. Its involvement in the tryptophan catabolic pathway and neurotransmitter regulation presents a promising target for addressing neurological disorders and enhancing neuroprotective strategies.

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