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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q13554

UPID:
KCC2B_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q13554; A4D2K0; A4D2K1; A4D2K2; A4D2K3; A4D2K4; A4D2K5; A4D2K6; O95437; O95438; O95599; Q9UGH7; Q9UGH8; Q9UGH9; Q9UNX0; Q9UNX7; Q9UP00; Q9Y5N4; Q9Y6F4

BACKGROUND:
The Calcium/calmodulin-dependent protein kinase type II subunit beta is integral to neuronal architecture and plasticity, influencing dendritic tree arborization, remodeling, and neuron migration. It also modulates skeletal muscle response to exercise, impacting Ca(2+) transport and release. Its role extends to the JAK-STAT signaling pathway through phosphorylation of STAT1 in response to IFN-gamma, illustrating its broad biological significance.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Intellectual developmental disorder, autosomal dominant 54, the therapeutic potential of targeting Calcium/calmodulin-dependent protein kinase type II subunit beta is immense. Exploring its functions and mechanisms could lead to groundbreaking therapeutic strategies for neurological disorders, emphasizing the importance of continued research in this area.

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