AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for 3-keto-steroid reductase/17-beta-hydroxysteroid dehydrogenase 7

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our associate 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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

P56937

UPID:

DHB7_HUMAN

Alternative names:

17-beta-hydroxysteroid dehydrogenase 7; 3-keto-steroid reductase; Dihydrotestosterone oxidoreductase; Estradiol 17-beta-dehydrogenase 7; Short chain dehydrogenase/reductase family 37C member 1

Alternative UPACC:

P56937; Q5T246; Q7Z4V9; Q8WWS2; Q9UF00

Background:

The 3-keto-steroid reductase/17-beta-hydroxysteroid dehydrogenase 7, known for its roles in steroid-hormone metabolism and cholesterol biosynthesis, is a bifunctional enzyme. It regulates the potency of estrogens and androgens by converting estrone to 17beta-estradiol, dihydrotestosterone to its inactive form, and progesterone to an inactive state. Additionally, it functions in cholesterol biosynthesis post-squalene as a 3-ketosteroid reductase.

Therapeutic significance:

Understanding the role of 3-keto-steroid reductase/17-beta-hydroxysteroid dehydrogenase 7 could open doors to potential therapeutic strategies.

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