Focused On-demand Library for Vascular endothelial growth factor receptor 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.







Alternative names:

Fms-like tyrosine kinase 4; Tyrosine-protein kinase receptor FLT4

Alternative UPACC:

P35916; A8K6L4; B5A926; Q16067; Q86W07; Q86W08


Vascular endothelial growth factor receptor 3 (VEGFR-3), also known as Fms-like tyrosine kinase 4 (FLT4), plays a pivotal role in lymphangiogenesis and cardiovascular system development. It acts as a cell-surface receptor for VEGFC and VEGFD, promoting endothelial cell proliferation, survival, and migration. FLT4 signaling enhances VEGFC production, creating a feedback loop that amplifies its own signaling.

Therapeutic significance:

FLT4 is implicated in diseases such as Lymphatic malformation 1, characterized by lymphedema and hypoplasia of lymphatic vessels, and congenital heart defects. Understanding FLT4's role could lead to novel therapeutic strategies for these conditions, highlighting its importance in drug discovery.

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