Focused On-demand Library for Discoidin domain-containing receptor 2

Details

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 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 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

PARTNER
Receptor.AI
 
UPACC
Q16832

UPID:
DDR2_HUMAN

ALTERNATIVE NAMES:
CD167 antigen-like family member B; Discoidin domain-containing receptor tyrosine kinase 2; Neurotrophic tyrosine kinase, receptor-related 3; Receptor protein-tyrosine kinase TKT; Tyrosine-protein kinase TYRO10

ALTERNATIVE UPACC:
Q16832; Q7Z730

BACKGROUND:
The protein Discoidin domain-containing receptor 2, known by several names including Tyrosine-protein kinase TYRO10 and CD167 antigen-like family member B, is a key player in regulating tissue remodeling. It influences osteoblast differentiation, chondrocyte maturation, and extracellular matrix remodeling through signaling pathways that activate RUNX2 and up-regulate collagenases MMP1, MMP2, and MMP13, facilitating cell migration and proliferation.

THERAPEUTIC SIGNIFICANCE:
Involvement of DDR2 in conditions like Spondyloepimetaphyseal dysplasia and Warburg-Cinotti syndrome highlights its therapeutic potential. By targeting DDR2's pathway, new treatments for these genetic disorders affecting bone structure and skin integrity could be developed, showcasing the protein's critical role in human health.

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