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.


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


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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
P29320

UPID:
EPHA3_HUMAN

ALTERNATIVE NAMES:
EPH-like kinase 4; HEK; Tyrosine-protein kinase TYRO4; Tyrosine-protein kinase receptor ETK1

ALTERNATIVE UPACC:
P29320; Q9H2V3; Q9H2V4

BACKGROUND:
The Ephrin type-A receptor 3, alternatively named Tyrosine-protein kinase TYRO4, is integral to cell migration, adhesion, and cytoskeletal organization. It binds preferentially to EFNA5, playing a significant role in forward and reverse signaling pathways that are essential for developmental processes such as atrioventricular canal formation and neuron mapping in the retinotectum.

THERAPEUTIC SIGNIFICANCE:
The association of Ephrin type-A receptor 3 with colorectal cancer, through genetic alterations leading to adenocarcinoma, underscores its therapeutic potential. Exploring the receptor's function could lead to groundbreaking treatments for this and possibly other related diseases.

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