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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
P14061

UPID:
DHB1_HUMAN

ALTERNATIVE NAMES:
20 alpha-hydroxysteroid dehydrogenase; E2DH; Estradiol 17-beta-dehydrogenase 1; Placental 17-beta-hydroxysteroid dehydrogenase; Short chain dehydrogenase/reductase family 28C member 1

ALTERNATIVE UPACC:
P14061; B3KXS1; Q2M2L8

BACKGROUND:
The enzyme 17-beta-hydroxysteroid dehydrogenase type 1, with alternative names such as E2DH and Estradiol 17-beta-dehydrogenase 1, is essential for the conversion of estrone to 17beta-estradiol, a potent estrogen. This process is crucial for maintaining estrogen balance and involves the preferential use of NADH.

THERAPEUTIC SIGNIFICANCE:
Exploring the enzymatic pathways of 17-beta-hydroxysteroid dehydrogenase type 1 offers a pathway to novel therapeutic interventions. Its involvement in synthesizing potent estrogens highlights its potential impact on diseases modulated by hormonal levels.

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