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.


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.


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


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q9NSA3

UPID:
CNBP1_HUMAN

ALTERNATIVE NAMES:
Inhibitor of beta-catenin and Tcf-4

ALTERNATIVE UPACC:
Q9NSA3; Q5T4V2

BACKGROUND:
The Beta-catenin-interacting protein 1, alternatively named Inhibitor of beta-catenin and Tcf-4, is integral to regulating the Wnt signaling pathway. By inhibiting the interaction between CTNNB1 and TCF family members, it plays a crucial role in controlling cellular signaling and development.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Beta-catenin-interacting protein 1 offers a promising avenue for developing new therapeutic approaches. Given its regulatory role in the Wnt signaling pathway, targeting this protein could lead to innovative treatments for conditions associated with pathway dysregulation.

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