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

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


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


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 top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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
Receptor.AI
 
UPACC
P35916

UPID:
VGFR3_HUMAN

ALTERNATIVE NAMES:
Fms-like tyrosine kinase 4; Tyrosine-protein kinase receptor FLT4

ALTERNATIVE UPACC:
P35916; A8K6L4; B5A926; Q16067; Q86W07; Q86W08

BACKGROUND:
The protein Vascular endothelial growth factor receptor 3, with alternative names Fms-like tyrosine kinase 4 and Tyrosine-protein kinase receptor FLT4, is crucial for the development of the vascular network. It mediates key signaling pathways, including MAPK and AKT1, and is involved in angiogenic sprouting and lymphangiogenesis.

THERAPEUTIC SIGNIFICANCE:
FLT4's involvement in conditions such as capillary infantile hemangioma and multiple types of congenital heart defects underscores its therapeutic potential. Targeting FLT4 could offer new avenues for treating these diseases, making it a significant focus for medical research and drug development.

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