AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Tyrosine-protein kinase Fgr

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P09769

UPID:

FGR_HUMAN

Alternative names:

Gardner-Rasheed feline sarcoma viral (v-fgr) oncogene homolog; Proto-oncogene c-Fgr; p55-Fgr; p58-Fgr; p58c-Fgr

Alternative UPACC:

P09769; D3DPL7; Q9UIQ3

Background:

Tyrosine-protein kinase Fgr, known by its aliases such as Gardner-Rasheed feline sarcoma viral (v-fgr) oncogene homolog and Proto-oncogene c-Fgr, plays a pivotal role in immune response regulation. It influences neutrophil, monocyte, macrophage, and mast cell functions, alongside cytoskeleton remodeling, phagocytosis, cell adhesion, and migration. Fgr acts downstream of various receptors, regulating actin cytoskeleton reorganization and cellular responses to external stimuli.

Therapeutic significance:

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

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