Focused On-demand Libraries - Receptor.AI 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 Reaxense.


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 for enzymes.


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
P52790

UPID:
HXK3_HUMAN

ALTERNATIVE NAMES:
Hexokinase type III; Hexokinase-C

ALTERNATIVE UPACC:
P52790; Q8N1E7

BACKGROUND:
Hexokinase-3, identified by its alternative names Hexokinase type III and Hexokinase-C, is essential for the phosphorylation of hexoses such as D-glucose and D-fructose to their 6-phosphate forms. This enzyme is a key player in the first step of glycolysis, facilitating the conversion of glucose to D-glucose 6-phosphate, a precursor for energy production and metabolic pathways.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Hexokinase-3 offers a promising avenue for the development of novel therapeutic approaches. Given its crucial role in the glycolytic pathway, targeting Hexokinase-3 could provide insights into treating conditions associated with impaired glucose metabolism.

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