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.


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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9HB71

UPID:
CYBP_HUMAN

ALTERNATIVE NAMES:
S100A6-binding protein; Siah-interacting protein

ALTERNATIVE UPACC:
Q9HB71; B2ZWH2; B3KSF1; O60666; Q5R370; Q5R371

BACKGROUND:
The Calcyclin-binding protein, known for its alternative names S100A6-binding protein and Siah-interacting protein, is implicated in the regulation of protein stability and degradation. It is essential for the calcium-dependent ubiquitination process, serving as a key component in ubiquitin E3 complexes. This protein is particularly involved in the degradation pathway of beta-catenin, a critical player in cellular adhesion and Wnt signaling pathway.

THERAPEUTIC SIGNIFICANCE:
Exploring the mechanisms by which Calcyclin-binding protein influences protein ubiquitination and degradation offers a promising avenue for therapeutic intervention. Its role in the controlled degradation of beta-catenin positions it as a potential target in diseases where beta-catenin is dysregulated.

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