AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for 17-beta-hydroxysteroid dehydrogenase 14

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.

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 our associate Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9BPX1

UPID:

DHB14_HUMAN

Alternative names:

17-beta-hydroxysteroid dehydrogenase DHRS10; Dehydrogenase/reductase SDR family member 10; Retinal short-chain dehydrogenase/reductase retSDR3; Short chain dehydrogenase/reductase family 47C member 1

Alternative UPACC:

Q9BPX1; Q9UKU3

Background:

17-beta-hydroxysteroid dehydrogenase 14, also known as DHRS10, plays a crucial role in steroid metabolism by converting oestradiol to oestrone. This enzyme, part of the short chain dehydrogenase/reductase family, exhibits NAD-dependent activity, highlighting its importance in biochemical pathways. Alternative names include Dehydrogenase/reductase SDR family member 10 and Retinal short-chain dehydrogenase/reductase retSDR3.

Therapeutic significance:

Understanding the role of 17-beta-hydroxysteroid dehydrogenase 14 could open doors to potential therapeutic strategies. Its involvement in steroid metabolism makes it a compelling target for drug discovery, aiming to modulate hormonal balances in diseases.

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