Focused On-demand Library for Tyrosine-protein kinase Fer

Details

Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
P16591

UPID:
FER_HUMAN

ALTERNATIVE NAMES:
Feline encephalitis virus-related kinase FER; Fujinami poultry sarcoma/Feline sarcoma-related protein Fer; Proto-oncogene c-Fer; Tyrosine kinase 3; p94-Fer

ALTERNATIVE UPACC:
P16591; B2RCR4; B4DSQ2; H2FLB8

BACKGROUND:
The Tyrosine-protein kinase Fer, encoded by the gene P16591, is integral to various cellular mechanisms such as microtubule assembly, lamellipodia formation, and leukocyte recruitment. It activates pathways downstream of growth factor receptors, including NF-kappa-B activation and phosphatidylinositol 3-kinase signaling, playing roles in cell survival, proliferation, and immune responses. Its involvement in mast cell degranulation and response to bacterial lipopolysaccharide underscores its potential in immune regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the multifaceted functions of Tyrosine-protein kinase Fer unveils promising avenues for therapeutic intervention.

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