AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fibroblast growth factor receptor 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, 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.

Our high-tech, dedicated method is applied to construct targeted 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 stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

P21802

UPID:

FGFR2_HUMAN

Alternative names:

K-sam; Keratinocyte growth factor receptor

Alternative UPACC:

P21802; B4DFC2; E7EVR6; E9PCR0; P18443; Q01742; Q12922; Q14300; Q14301; Q14302; Q14303; Q14304; Q14305; Q14672; Q14718; Q14719; Q1KHY5; Q86YI4; Q8IXC7; Q96KL9; Q96KM0; Q96KM1; Q96KM2; Q9NZU2; Q9NZU3; Q9UD01; Q9UD02; Q9UIH3; Q9UIH4; Q9UIH5; Q9UIH6; Q9UIH7; Q9UIH8; Q9UM87; Q9UMC6; Q9UNS7; Q9UQH7; Q9UQH8; Q9UQH9; Q9UQI0

Background:

Fibroblast growth factor receptor 2 (FGFR2), also known as Keratinocyte growth factor receptor and K-sam, is pivotal in cell proliferation, differentiation, migration, apoptosis, and embryonic development. It orchestrates osteogenesis, lung morphogenesis, and skin development by engaging in signaling cascades upon ligand binding, influencing cellular outcomes through pathways like MAPK and AKT1.

Therapeutic significance:

FGFR2's mutations are linked to various craniosynostosis syndromes, including Crouzon, Jackson-Weiss, and Apert syndromes, highlighting its critical role in skeletal development. Understanding FGFR2's function could unveil novel therapeutic avenues for these genetic disorders, offering hope for targeted treatments.

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