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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are 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.


We use our state-of-the-art dedicated workflow for designing focused 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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q13237

UPID:
KGP2_HUMAN

ALTERNATIVE NAMES:
cGMP-dependent protein kinase II

ALTERNATIVE UPACC:
Q13237; B4DMX3; E7EPE6; O00125; O60916

BACKGROUND:
The enzyme cGMP-dependent protein kinase 2, alternatively known as cGMP-dependent protein kinase II, is a crucial regulator of bone growth and intestinal secretion. It activates CFTR for intestinal secretion, facilitates synaptic plasticity by phosphorylating GRIA1/GLUR1, and triggers the MAPK3/ERK1 and MAPK1/ERK2 pathways in osteoblasts under mechanical stress. Its role extends to the regulation of gene expression, highlighting its importance in cellular signaling and physiological regulation.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in diseases such as spondylometaphyseal dysplasia, Pagnamenta type, and acromesomelic dysplasia 4, cGMP-dependent protein kinase 2 represents a promising target for therapeutic intervention. The kinase's involvement in these genetic disorders, which affect bone structure and growth, suggests that modulating its activity could lead to innovative treatments for patients suffering from these conditions.

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