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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


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
Q15907

UPID:
RB11B_HUMAN

ALTERNATIVE NAMES:
GTP-binding protein YPT3

ALTERNATIVE UPACC:
Q15907; A5YM50; B2R7I4; B4DMK0; D6W671; Q2YDT2; Q5U0I1; Q6FHR0; Q6FI42; Q8NI07

BACKGROUND:
The small GTPase Rab-11B, known for its regulatory role in membrane trafficking, cycles between an active and inactive state to recruit downstream effectors for vesicle movement and fusion. It is crucial for the recycling of several transmembrane proteins, secretion processes, and intracellular transport mechanisms, including those involved in melanosome release and response to acidosis.

THERAPEUTIC SIGNIFICANCE:
Linked to a severe neurodevelopmental disorder with symptoms like epilepsy and hypotonia, Rab-11B's involvement in disease highlights its potential as a target for therapeutic intervention. Understanding the role of Rab-11B could open doors to potential therapeutic strategies, offering hope for treatments targeting the underlying genetic causes.

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