Focused On-demand Library for Estradiol 17-beta-dehydrogenase 11

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.


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 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.


Our high-tech, dedicated method is applied to construct targeted 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

PARTNER
Receptor.AI
 
UPACC
Q8NBQ5

UPID:
DHB11_HUMAN

ALTERNATIVE NAMES:
17-beta-hydroxysteroid dehydrogenase 11; 17-beta-hydroxysteroid dehydrogenase XI; Cutaneous T-cell lymphoma-associated antigen HD-CL-03; Dehydrogenase/reductase SDR family member 8; Retinal short-chain dehydrogenase/reductase 2; Short chain dehydrogenase/reductase family 16C member 2

ALTERNATIVE UPACC:
Q8NBQ5; Q96HF6; Q9UKU4

BACKGROUND:
The protein Estradiol 17-beta-dehydrogenase 11, with alternative names such as Dehydrogenase/reductase SDR family member 8, is pivotal in androgen metabolism. It specifically catalyzes the conversion of androstan-3-alpha,17-beta-diol to androsterone, suggesting a significant role in steroidogenesis. Although its activity is selective, not affecting DHEA or A-dione significantly, its slight activity toward testosterone highlights its potential impact on steroid synthesis regulation.

THERAPEUTIC SIGNIFICANCE:
The exploration of Estradiol 17-beta-dehydrogenase 11's function offers promising avenues for therapeutic intervention, particularly given its tumor-associated antigen status in cutaneous T-cell lymphoma and its role in steroid metabolism.

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