AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable E3 ubiquitin-protein ligase IRF2BPL

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9H1B7

UPID:

I2BPL_HUMAN

Alternative names:

Enhanced at puberty protein 1; Interferon regulatory factor 2-binding protein-like

Alternative UPACC:

Q9H1B7; Q8NDQ2; Q96JG2; Q9H3I7

Background:

The Probable E3 ubiquitin-protein ligase IRF2BPL, also known as Enhanced at puberty protein 1 and Interferon regulatory factor 2-binding protein-like, plays a crucial role in the proteasome-mediated ubiquitin-dependent degradation of target proteins. It negatively regulates the Wnt signaling pathway by degrading CTNNB1, downstream of FOXF2, and is implicated in central nervous system development and neuronal maintenance. Additionally, it acts as a transcriptional regulator of genes controlling female reproductive function.

Therapeutic significance:

IRF2BPL is linked to a neurodevelopmental disorder characterized by developmental delay, hypotonia, ataxia, intellectual disability, seizures, and abnormal movements. Understanding the role of IRF2BPL could open doors to potential therapeutic strategies for this disorder.

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