AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Prolyl hydroxylase EGLN2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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.

We utilise our cutting-edge, exclusive workflow to develop focused 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q96KS0

UPID:

EGLN2_HUMAN

Alternative names:

Egl nine homolog 2; Estrogen-induced tag 6; HPH-3; Hypoxia-inducible factor prolyl hydroxylase 1; Prolyl hydroxylase domain-containing protein 1

Alternative UPACC:

Q96KS0; A8K5S0; Q8WWY4; Q9BV14

Background:

Prolyl hydroxylase EGLN2, also known as Hypoxia-inducible factor prolyl hydroxylase 1, plays a pivotal role in oxygen sensing and cellular response to hypoxia. It hydroxylates proline residues in various proteins, including HIF1A and HIF2A, under normoxic conditions, leading to their degradation. This process is crucial for regulating hypoxia-inducible genes' expression, cell cycle, and apoptosis in cardiac and skeletal muscle.

Therapeutic significance:

Understanding the role of Prolyl hydroxylase EGLN2 could open doors to potential therapeutic strategies. Its involvement in oxygen sensing and the hypoxic response pathway presents opportunities for developing treatments for diseases related to hypoxia and oxidative stress.

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