Focused On-demand Library for Ephrin type-B receptor 1

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening 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 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.







Alternative names:

ELK; EPH tyrosine kinase 2; EPH-like kinase 6; Neuronally-expressed EPH-related tyrosine kinase; Tyrosine-protein kinase receptor EPH-2

Alternative UPACC:

P54762; A8K593; B3KTB2; B5A969; O43569; O95142; O95143; Q0VG87


Ephrin type-B receptor 1, known by alternative names such as ELK, EPH tyrosine kinase 2, and Tyrosine-protein kinase receptor EPH-2, plays a pivotal role in nervous system development, particularly in axon guidance and synapse formation. It binds with ephrin-B ligands to initiate bidirectional signaling crucial for cell migration, adhesion, and targeted cell migration. This receptor is instrumental in the development and maturation of dendritic spines, contributing significantly to the neural network's complexity.

Therapeutic significance:

Understanding the role of Ephrin type-B receptor 1 could open doors to potential therapeutic strategies. Its involvement in nervous system development and cell migration positions it as a key target for addressing neurological disorders and promoting neural regeneration.

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