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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9ULC3

UPID:
RAB23_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q9ULC3; B2R9I5; Q68DJ6; Q8NI06; Q9P023

BACKGROUND:
The Ras-related protein Rab-23 is integral to the regulation of membrane trafficking within cells, including vesicle tethering, movement, and autophagosome formation. By modulating the activity of GLI transcription factors and interacting with SUFU, Rab-23 is crucial for cellular differentiation and immune responses against pathogens like S.aureus.

THERAPEUTIC SIGNIFICANCE:
Given its role in Carpenter syndrome 1, characterized by diverse physical and cognitive impairments due to gene mutations, Rab-23 represents a promising target for therapeutic intervention. Advancing our grasp of Rab-23's mechanisms could pave the way for novel treatments, potentially alleviating the complex symptoms associated with this rare condition.

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