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.


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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds 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
Q9UF56

UPID:
FXL17_HUMAN

ALTERNATIVE NAMES:
F-box and leucine-rich repeat protein 17; F-box only protein 13

ALTERNATIVE UPACC:
Q9UF56; A1A4E3

BACKGROUND:
The F-box/LRR-repeat protein 17, identified by its ubiquitin ligase activity within the SCF(FBXL17) complex, is pivotal in maintaining cellular integrity through the targeted degradation of compromised BTB domain-containing proteins. By recognizing and binding to a unique degron on BTB dimers, it ensures the elimination of dysfunctional proteins, a process vital for the proper differentiation and survival of specific cell types. Its involvement in the hedgehog/smoothened signaling pathway, through the ubiquitination and subsequent degradation of SUFU, underscores its significance in cellular signaling and development.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of F-box/LRR-repeat protein 17 could open doors to potential therapeutic strategies.

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