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

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

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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