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.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q04864

UPID:
REL_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q04864; Q17RU2; Q2PNZ7; Q6LDY0

BACKGROUND:
The Proto-oncogene c-Rel, a key component of the NF-kappa-B signaling pathway, is implicated in critical biological functions such as cell differentiation and immune response. It forms part of a complex that controls transcription in nearly all cell types, influencing processes like tumorigenesis and apoptosis. The regulation of NF-kappa-B involves its interaction with I-kappa-B, which keeps it inactive in the cytoplasm until activation signals induce its release and nuclear translocation.

THERAPEUTIC SIGNIFICANCE:
Given its role in Immunodeficiency 92, characterized by significant immune system challenges from early life, understanding the function and regulation of c-Rel could lead to innovative treatments for immune deficiencies. Modulating c-Rel activity presents a promising avenue for therapeutic intervention.

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