AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Glyoxylate reductase/hydroxypyruvate reductase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

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

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9UBQ7

UPID:

GRHPR_HUMAN

Alternative names:

-

Alternative UPACC:

Q9UBQ7; Q5T945; Q9H3E9; Q9H636; Q9UKX1

Background:

The Glyoxylate reductase/hydroxypyruvate reductase, encoded by the gene with the accession number Q9UBQ7, plays a crucial role in metabolic processes. It exhibits hydroxy-pyruvate reductase, glyoxylate reductase, and D-glycerate dehydrogenase enzymatic activities, facilitating the conversion of hydroxypyruvate to D-glycerate, glyoxylate to glycolate, and the oxidation of D-glycerate to hydroxypyruvate.

Therapeutic significance:

Linked to Hyperoxaluria primary 2, a disorder marked by elevated urinary excretion of oxalate and L-glycerate leading to severe renal complications, the protein's dysfunction underscores its therapeutic potential. Targeting its enzymatic pathways could offer novel treatment avenues for managing and potentially reversing the disease's progression.

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