Focused On-demand Library for Junctional adhesion molecule C

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

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

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.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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.







Alternative names:

JAM-2; Junctional adhesion molecule 3

Alternative UPACC:

Q9BX67; B3KWG9; Q8WWL8; Q96FL1


Junctional adhesion molecule C (JAM-C), also known as JAM-2 and Junctional adhesion molecule 3, plays a pivotal role in various cellular processes. It mediates cell-cell interactions, regulates hematopoietic stem cell mobilization, and is crucial in leukocyte extravasation, spermatogenesis, and angiogenesis. Its interaction with receptors like JAM2 and ITGAM influences cell migration, leukocyte-platelet interactions, and vascular endothelial cell chemotaxis.

Therapeutic significance:

The involvement of JAM-C in hemorrhagic destruction of the brain with subependymal calcification and cataracts highlights its potential as a therapeutic target. Understanding the role of Junctional adhesion molecule C could open doors to potential therapeutic strategies for this severe syndrome, offering hope for interventions that could mitigate the profound developmental delays and neurologic complications associated with the disease.

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