Focused On-demand Libraries - Receptor.AI 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 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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q8N806

UPID:
UBR7_HUMAN

ALTERNATIVE NAMES:
N-recognin-7; RING-type E3 ubiquitin transferase UBR7

ALTERNATIVE UPACC:
Q8N806; Q86U21; Q86UA9; Q96BY0; Q9NVV6

BACKGROUND:
The protein UBR7, known alternatively as N-recognin-7 and RING-type E3 ubiquitin transferase, is integral to the N-end rule pathway of protein degradation. It identifies proteins with destabilizing N-terminal residues for ubiquitination and degradation, playing a key role in cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Given UBR7's link to Li-Campeau syndrome, characterized by developmental delays and various anomalies, its study offers promising avenues for therapeutic intervention. Understanding UBR7's function could lead to novel treatments for this and potentially other related disorders.

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