AI-ACCELERATED DRUG DISCOVERY

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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner 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 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.

partner

Reaxense

upacc

P04049

UPID:

RAF1_HUMAN

Alternative names:

Proto-oncogene c-RAF; Raf-1

Alternative UPACC:

P04049; B0LPH8; B2R5N3; Q15278; Q9UC20

Background:

The RAF proto-oncogene serine/threonine-protein kinase, also known as Proto-oncogene c-RAF and Raf-1, plays a pivotal role in cell fate decisions. It acts as a crucial link between Ras GTPases and the MAPK/ERK cascade, influencing processes such as proliferation, differentiation, and survival. Its activation triggers a chain reaction leading to the phosphorylation of various targets, including BAD/Bcl2, adenylyl cyclases, and TNNT2, affecting cell death, activation, and cardiac function.

Therapeutic significance:

Given its involvement in Noonan syndrome 5, LEOPARD syndrome 2, and dilated cardiomyopathy 1NN, understanding the RAF proto-oncogene's role could pave the way for innovative treatments. These conditions, characterized by congenital heart defects, developmental delays, and risk of leukemia, highlight the protein's potential as a target for therapeutic intervention.

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