Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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.


Our top-notch dedicated system is used to design specialised 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
Q6UWP2

UPID:
DHR11_HUMAN

ALTERNATIVE NAMES:
17-beta-hydroxysteroid dehydrogenase; 3-beta-hydroxysteroid 3-dehydrogenase; Estradiol 17-beta-dehydrogenase; Short-chain dehydrogenase/reductase family 24C member 1

ALTERNATIVE UPACC:
Q6UWP2; A0A0U5BLD0; B2RDZ3; Q9BUC7; Q9H674

BACKGROUND:
The enzyme Dehydrogenase/reductase SDR family member 11, with alternative names such as Estradiol 17-beta-dehydrogenase, is integral to the conversion of steroids into their bioactive forms. It exhibits reductive activity towards a broad spectrum of substrates, highlighting its versatility in steroid hormone metabolism.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Dehydrogenase/reductase SDR family member 11 offers a promising avenue for developing novel therapeutic approaches. Its key role in hormone synthesis and metabolism positions it as a potential target in treating hormonal disorders.

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