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.


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.


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.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
P35221

UPID:
CTNA1_HUMAN

ALTERNATIVE NAMES:
Alpha E-catenin; Cadherin-associated protein; Renal carcinoma antigen NY-REN-13

ALTERNATIVE UPACC:
P35221; Q12795; Q8N1C0

BACKGROUND:
Catenin alpha-1, identified as a critical component in cadherin-catenin adhesion complexes, mediates the linkage between cadherins and the actin cytoskeleton. Its role extends beyond cell adhesion, influencing actin filament assembly and inhibiting actin branching by competing with the Arp2/3 complex. Additionally, Catenin alpha-1 is instrumental in cell differentiation processes through its regulation of key signaling pathways.

THERAPEUTIC SIGNIFICANCE:
The association of Catenin alpha-1 with Macular dystrophy, patterned, 2, a genetic eye disease, highlights its therapeutic relevance. Exploring the functions of Catenin alpha-1 offers promising avenues for developing novel treatments for related disorders.

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