Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


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
P98172

UPID:
EFNB1_HUMAN

ALTERNATIVE NAMES:
EFL-3; ELK ligand; EPH-related receptor tyrosine kinase ligand 2

ALTERNATIVE UPACC:
P98172; D3DVU0

BACKGROUND:
The protein Ephrin-B1, with aliases such as EFL-3 and ELK ligand, serves as a crucial ligand for Eph receptors, playing a significant role in the development of various tissues by mediating cell-cell interactions. It exhibits high affinity for EPHB1/ELK and can also interact with EPHB2 and EPHB3, influencing axonal guidance and cellular arrangement.

THERAPEUTIC SIGNIFICANCE:
Given Ephrin-B1's critical function in developmental pathways and its association with Craniofrontonasal syndrome, research into this protein holds promise for uncovering novel therapeutic avenues. Understanding the role of Ephrin-B1 could open doors to potential therapeutic strategies.

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