Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for protein-protein interfaces.


 

Fig. 1. The screening workflow of Receptor.AI

It includes extensive molecular simulations of the target alone and in complex with its most relevant partner proteins, followed by ensemble virtual screening that accounts for conformational mobility in free and bound forms. The tentative binding pockets are considered on the protein-protein interface itself and in remote allosteric locations in order to cover the whole spectrum of possible mechanisms of action.


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
P12830

UPID:
CADH1_HUMAN

ALTERNATIVE NAMES:
CAM 120/80; Epithelial cadherin; Uvomorulin

ALTERNATIVE UPACC:
P12830; A8K1U7; Q13799; Q14216; Q15855; Q16194; Q4PJ14; Q9UII8

BACKGROUND:
Cadherin-1, known for its aliases CAM 120/80 and Uvomorulin, is integral to cell adhesion and epithelial cell dynamics, including adhesion, mobility, and proliferation. It serves as a ligand for integrin alpha-E/beta-7, emphasizing its role in cellular interactions and tissue organization. Furthermore, Cadherin-1's involvement in non-amyloidogenic degradation pathways illustrates its broader implications in cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
The association of Cadherin-1 with various cancers, such as Diffuse gastric cancer, Endometrial cancer, Ovarian cancer, and specific breast cancer types, underscores its therapeutic relevance. Its genetic variants contribute to disease susceptibility, making it a critical focus for drug discovery efforts aimed at mitigating these malignancies. Exploring Cadherin-1's function offers promising avenues for developing targeted cancer therapies.

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