AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Putative E3 ubiquitin-protein ligase UBR7

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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

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

Q8N806

UPID:

UBR7_HUMAN

Alternative names:

N-recognin-7; RING-type E3 ubiquitin transferase UBR7

Alternative UPACC:

Q8N806; Q86U21; Q86UA9; Q96BY0; Q9NVV6

Background:

Putative E3 ubiquitin-protein ligase UBR7, also known as N-recognin-7 and RING-type E3 ubiquitin transferase UBR7, plays a pivotal role in the N-end rule pathway. This pathway is crucial for protein degradation, where UBR7 recognizes and binds to proteins with specific N-terminal residues, marking them for ubiquitination and subsequent degradation.

Therapeutic significance:

UBR7's involvement in Li-Campeau syndrome, a neurodevelopmental disorder with symptoms including intellectual disability and epilepsy, highlights its potential as a therapeutic target. Understanding the role of UBR7 could open doors to potential therapeutic strategies.

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