AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for 17-beta-hydroxysteroid dehydrogenase 13

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our partner 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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening 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

Reaxense

upacc

Q7Z5P4

UPID:

DHB13_HUMAN

Alternative names:

Hepatic retinol/retinal dehydrogenase; Short chain dehydrogenase/reductase family 16C member 3; Short-chain dehydrogenase/reductase 9

Alternative UPACC:

Q7Z5P4; A8K9R9; Q2M1L5; Q86W22; Q86W23

Background:

17-beta-hydroxysteroid dehydrogenase 13, also known as hepatic retinol/retinal dehydrogenase, plays a crucial role in hepatic lipid metabolism. It is capable of oxidizing a variety of lipid substrates, including 17beta-estradiol, retinol, retinal, and leukotriene B4. This protein is part of the short chain dehydrogenase/reductase family, highlighting its importance in metabolic processes.

Therapeutic significance:

Understanding the role of 17-beta-hydroxysteroid dehydrogenase 13 could open doors to potential therapeutic strategies. Its pivotal role in lipid metabolism makes it an intriguing target for addressing metabolic disorders.

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