Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q16667

UPID:
CDKN3_HUMAN

ALTERNATIVE NAMES:
CDK2-associated dual-specificity phosphatase; Cyclin-dependent kinase interactor 1; Cyclin-dependent kinase-interacting protein 2; Kinase-associated phosphatase

ALTERNATIVE UPACC:
Q16667; Q53ZU6; Q5U0M4; Q6P1N8; Q99585; Q9BPW7; Q9BY36; Q9C042; Q9C046; Q9C047; Q9C049; Q9C051; Q9C053

BACKGROUND:
Cyclin-dependent kinase inhibitor 3, known for its roles in cell cycle regulation, acts as a dual specificity phosphatase. It uniquely targets both phosphotyrosine and phosphoserine residues, playing a pivotal role in dephosphorylating CDK2, a key regulator of the cell cycle.

THERAPEUTIC SIGNIFICANCE:
The association of Cyclin-dependent kinase inhibitor 3 with hepatocellular carcinoma underscores its potential as a therapeutic target. Exploring its function further could unveil new avenues for treating this aggressive liver cancer, linked to various risk factors including viral hepatitis and aflatoxin exposure.

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