Focused On-demand Library for Tyrosine-protein kinase Fer

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

Our top-notch dedicated system is used to design specialised 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.

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.







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


Tyrosine-protein kinase Fer, known by alternative names such as Feline encephalitis virus-related kinase FER and Proto-oncogene c-Fer, plays a pivotal role in cellular processes including actin cytoskeleton regulation, cell adhesion, migration, and chemotaxis. It functions downstream of receptors like EGFR and PDGFRB, influencing cell proliferation, mitotic cycle regulation, and insulin signaling. Additionally, it contributes to synaptic organization and neuron-neuron transmission, highlighting its importance in neuronal health.

Therapeutic significance:

Understanding the role of Tyrosine-protein kinase Fer could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.