AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Glucocorticoid modulatory element-binding protein 2

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.

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.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

Q9UKD1

UPID:

GMEB2_HUMAN

Alternative names:

DNA-binding protein p79PIF; Parvovirus initiation factor p79

Alternative UPACC:

Q9UKD1; E1P5J3; Q5TDS0; Q9H431; Q9H4X7; Q9H4X8; Q9UF78; Q9ULF1

Background:

Glucocorticoid modulatory element-binding protein 2, also known as DNA-binding protein p79PIF and Parvovirus initiation factor p79, plays a pivotal role in cellular processes. It binds to glucocorticoid modulatory elements in the TAT promoter, enhancing sensitivity to glucocorticoids, and interacts with the transferrin receptor promoter. This protein is also an essential auxiliary factor for parvovirus replication.

Therapeutic significance:

Understanding the role of Glucocorticoid modulatory element-binding protein 2 could open doors to potential therapeutic strategies.

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