Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q9H9C1

UPID:
SPE39_HUMAN

ALTERNATIVE NAMES:
VPS33B-interacting protein in apical-basolateral polarity regulator; VPS33B-interacting protein in polarity and apical restriction

ALTERNATIVE UPACC:
Q9H9C1; B4DPI6; O95434; Q9H7E1; Q9H9I9

BACKGROUND:
The protein known for its involvement in endosomal maturation, VPS33B-interacting protein, contributes to the apical RAB11A-dependent recycling pathway and lysosomal trafficking. It plays a role in maintaining apical-basolateral polarity and is implicated in spermatogenesis and E-cadherin regulation.

THERAPEUTIC SIGNIFICANCE:
Linked to the development of Arthrogryposis, renal dysfunction, and cholestasis syndrome 2, the study of this protein offers a promising avenue for therapeutic intervention. Understanding the role of Spermatogenesis-defective protein 39 homolog could open doors to potential therapeutic strategies.

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