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 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.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
Q9C098

UPID:
DCLK3_HUMAN

ALTERNATIVE NAMES:
Doublecortin domain-containing protein 3C; Doublecortin-like and CAM kinase-like 3; Doublecortin-like kinase 3

ALTERNATIVE UPACC:
Q9C098

BACKGROUND:
The protein Serine/threonine-protein kinase DCLK3, with alternative names including Doublecortin domain-containing protein 3C, Doublecortin-like and CAM kinase-like 3, and Doublecortin-like kinase 3, is integral to the regulation of kinase activity and neuronal development. The presence of doublecortin domains indicates its significance in brain function and cellular communication.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Serine/threonine-protein kinase DCLK3 holds the key to unlocking new therapeutic avenues. As a critical component of neuronal signaling, targeting DCLK3 could lead to innovative treatments for diseases affecting the nervous system.

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