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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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 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
Q14088

UPID:
RB33A_HUMAN

ALTERNATIVE NAMES:
Small GTP-binding protein S10

ALTERNATIVE UPACC:
Q14088; Q5JUZ6; Q92465

BACKGROUND:
The Ras-related protein Rab-33A, with its alternative name Small GTP-binding protein S10, is integral to the cellular machinery responsible for vesicle trafficking. As a member of the Ras superfamily, Rab-33A's activities are essential for the proper functioning of intracellular signaling and transport. The exploration of Rab-33A's functions is ongoing, highlighting its potential impact on cellular dynamics and disease mechanisms.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Ras-related protein Rab-33A holds promise for unveiling novel therapeutic targets. Given its central role in cellular processes, interventions designed to modulate Rab-33A's activity could lead to breakthroughs in the management of disorders associated with vesicle transport and intracellular communication.

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