AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Bisphosphoglycerate mutase

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.

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 our partner Reaxense.

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.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Reaxense

upacc

P07738

UPID:

PMGE_HUMAN

Alternative names:

2,3-bisphosphoglycerate mutase, erythrocyte; 2,3-bisphosphoglycerate synthase; 2,3-diphosphoglycerate mutase; BPG-dependent PGAM

Alternative UPACC:

P07738; A4D1N9

Background:

Bisphosphoglycerate mutase, known for its pivotal role in regulating hemoglobin oxygen affinity, controls the levels of 2,3-bisphosphoglycerate (2,3-BPG). This enzyme not only facilitates oxygen release to tissues by modulating hemoglobin's oxygen-binding capacity but also exhibits mutase activity, crucial for erythrocyte function.

Therapeutic significance:

The enzyme's mutation leads to Erythrocytosis, familial, 8, characterized by hemolytic anemia and splenomegaly. Understanding the role of Bisphosphoglycerate mutase could open doors to potential therapeutic strategies for managing this autosomal recessive disorder.

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