Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We use our state-of-the-art dedicated workflow for designing focused 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
Q9NZN1

UPID:
IRPL1_HUMAN

ALTERNATIVE NAMES:
Oligophrenin-4; Three immunoglobulin domain-containing IL-1 receptor-related 2; X-linked interleukin-1 receptor accessory protein-like 1

ALTERNATIVE UPACC:
Q9NZN1; A0AVG4; Q9UJ53

BACKGROUND:
The protein Interleukin-1 receptor accessory protein-like 1, with alternative names such as Oligophrenin-4, is integral to synaptic differentiation and neuronal outgrowth. Its interaction with PTPRD during dendritic spine formation exemplifies its critical function in synaptic connectivity and plasticity.

THERAPEUTIC SIGNIFICANCE:
Given its association with Intellectual developmental disorder, X-linked 21, the study of Interleukin-1 receptor accessory protein-like 1 offers promising avenues for therapeutic intervention. Exploring its biological mechanisms could lead to groundbreaking treatments for neurodevelopmental disorders.

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