Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


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


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
Q9NUY8

UPID:
TBC23_HUMAN

ALTERNATIVE NAMES:
HCV non-structural protein 4A-transactivated protein 1

ALTERNATIVE UPACC:
Q9NUY8; B9A6M5; Q8TCN8; Q8WUB7; Q96D90; Q9NV75

BACKGROUND:
TBC1 domain family member 23 plays a pivotal role in vesicular trafficking, endosome-to-Golgi transport, and brain development. It binds golgins and the WASH complex, aiding in vesicle capture and neurite outgrowth. Additionally, it acts as a general inhibitor of innate immunity signaling, highlighting its multifaceted biological functions.

THERAPEUTIC SIGNIFICANCE:
The protein's association with pontocerebellar hypoplasia 11, characterized by developmental delays and brain abnormalities, underscores its therapeutic potential. Exploring TBC1 domain family member 23's functions could lead to innovative treatments for this and possibly other neurological disorders.

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