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 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.


Our high-tech, dedicated method is applied to construct targeted 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.


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
Q8IVV7

UPID:
GID4_HUMAN

ALTERNATIVE NAMES:
Vacuolar import and degradation protein 24 homolog

ALTERNATIVE UPACC:
Q8IVV7; Q8TEB5; Q9BW50

BACKGROUND:
The Glucose-induced degradation protein 4 homolog, known alternatively as Vacuolar import and degradation protein 24 homolog, is integral to the ubiquitin-proteasome system. It selectively interacts with ubiquitin from UBE2H, targeting the transcription factor HBP1 for degradation. Its binding affinity is highest for peptides with a specific Pro/N-degron, underscoring its role in protein turnover.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Glucose-induced degradation protein 4 homolog offers a promising avenue for drug discovery. By elucidating its role in the selective degradation of proteins, researchers can identify novel therapeutic targets for diseases where protein homeostasis is disrupted.

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