Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


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 use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening 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.


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
Q8N5Z0

UPID:
AADAT_HUMAN

ALTERNATIVE NAMES:
2-aminoadipate aminotransferase; 2-aminoadipate transaminase; Alpha-aminoadipate aminotransferase; Glycine transaminase AADAT; Kynurenine aminotransferase II; Kynurenine--glyoxylate transaminase AADAT; Kynurenine--oxoglutarate aminotransferase II; Kynurenine--oxoglutarate transaminase 2; Kynurenine--oxoglutarate transaminase II; Methionine--glyoxylate transaminase AADAT

ALTERNATIVE UPACC:
Q8N5Z0; B3KP84; Q9UL02

BACKGROUND:
The enzyme Kynurenine/alpha-aminoadipate aminotransferase, located in the mitochondria, is crucial for amino acid metabolism, showing activity towards a wide range of substrates. It functions by transferring amino groups from amino acids to oxo-acids, demonstrating a preference for 2-oxoglutarate and phenylpyruvate among others. This enzyme's activity is essential for the synthesis and degradation of amino acids, playing a significant role in the body's metabolic processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Kynurenine/alpha-aminoadipate aminotransferase is key to unlocking new therapeutic avenues. Given its central role in amino acid metabolism, targeting this enzyme could lead to innovative treatments for metabolic diseases, offering hope for interventions in conditions where amino acid balance is disrupted.

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