Focused On-demand Library for RAF proto-oncogene serine/threonine-protein kinase

Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


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 screening 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.


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.

PARTNER
Receptor.AI
 
UPACC
P04049

UPID:
RAF1_HUMAN

ALTERNATIVE NAMES:
Proto-oncogene c-RAF; Raf-1

ALTERNATIVE UPACC:
P04049; B0LPH8; B2R5N3; Q15278; Q9UC20

BACKGROUND:
RAF proto-oncogene serine/threonine-protein kinase, known as c-RAF or Raf-1, is integral to cellular decision-making. It serves as a regulatory nexus for the MAPK/ERK signaling pathway, affecting cell proliferation, apoptosis, and oncogenic transformation. By phosphorylating key molecules like BAD/Bcl2 and adenylyl cyclases, it modulates apoptosis, cellular activation, and heart muscle function.

THERAPEUTIC SIGNIFICANCE:
The protein's association with diseases such as Noonan syndrome 5, LEOPARD syndrome 2, and cardiomyopathy underscores its therapeutic potential. Targeting the RAF proto-oncogene could offer new avenues for treating these disorders, which manifest in heart abnormalities, growth retardation, and increased leukemia risk, thereby opening doors to potential therapeutic strategies.

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