Focused On-demand Library for Dihydropteridine reductase

Details

Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
P09417

UPID:
DHPR_HUMAN

ALTERNATIVE NAMES:
HDHPR; Quinoid dihydropteridine reductase; Short chain dehydrogenase/reductase family 33C member 1

ALTERNATIVE UPACC:
P09417; A8K158; B3KW71; Q53F52; Q9H3M5

BACKGROUND:
The enzyme dihydropteridine reductase, also referred to as Short chain dehydrogenase/reductase family 33C member 1, catalyzes a critical step in the phenylalanine metabolism pathway. This action is pivotal for the synthesis of key neurotransmitters, underscoring the enzyme's importance in neurochemical balance.

THERAPEUTIC SIGNIFICANCE:
The deficiency of tetrahydrobiopterin, caused by mutations in the dihydropteridine reductase gene, leads to Hyperphenylalaninemia, BH4-deficient, C. This condition underscores the enzyme's therapeutic significance, as it highlights the critical need for innovative treatments targeting the underlying genetic and biochemical pathways.

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