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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised 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 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
Q4ADV7

UPID:
RIC1_HUMAN

ALTERNATIVE NAMES:
Connexin-43-interacting protein of 150 kDa; Protein RIC1 homolog; RAB6A-GEF complex partner protein 1

ALTERNATIVE UPACC:
Q4ADV7; B2RN24; B7ZM67; G5E932; Q4VXJ8; Q4VXJ9; Q76MT5; Q8N6E0; Q8TEH4; Q9H0A5; Q9H9S1

BACKGROUND:
Guanine nucleotide exchange factor subunit RIC1, identified by alternative names such as Connexin-43-interacting protein of 150 kDa, plays a significant role in cellular trafficking and development. It activates RAB6A, essential for vesicle fusion with the Golgi, and participates in mannose-6-phosphate receptor recycling. Its functions extend to GJA1 phosphorylation and localization, and it is vital for the transport and secretion of procollagen, influencing cartilage and craniofacial skeleton formation.

THERAPEUTIC SIGNIFICANCE:
The involvement of Guanine nucleotide exchange factor subunit RIC1 in crucial cellular and developmental processes suggests that insights into its functions could lead to innovative therapeutic approaches, especially for diseases like CATIFA syndrome, which is associated with gene variants.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.