AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Dehydrogenase/reductase SDR family member 11

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.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

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:

Dehydrogenase/reductase SDR family member 11, also known as 17-beta-hydroxysteroid dehydrogenase, plays a crucial role in steroid metabolism. It catalyzes the conversion of key steroid hormones, including estrone and androstenes, into their more active forms. This enzyme is pivotal in the synthesis of estrogens and androgens, hormones essential for various physiological processes.

Therapeutic significance:

Understanding the role of Dehydrogenase/reductase SDR family member 11 could open doors to potential therapeutic strategies. Its involvement in the metabolic pathways of critical hormones suggests its potential as a target in disorders related to hormone imbalance.

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