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.


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 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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening 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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P40189

UPID:
IL6RB_HUMAN

ALTERNATIVE NAMES:
CDw130; Interleukin-6 signal transducer; Membrane glycoprotein 130; Oncostatin-M receptor subunit alpha

ALTERNATIVE UPACC:
P40189; A0N0L4; Q5FC04; Q9UQ41

BACKGROUND:
The Interleukin-6 receptor subunit beta, known for its alternative names such as Membrane glycoprotein 130 and Oncostatin-M receptor subunit alpha, is a key player in initiating signal transmission for cytokines. It activates intracellular signaling pathways, leading to the phosphorylation of tyrosine residues and activation of STAT3, which regulates immune response and bone metabolism. Additionally, it blocks IL6 trans-signaling and inhibits acute phase response, highlighting its regulatory role in inflammation.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in diseases like Hyper-IgE recurrent infection syndrome and Immunodeficiency 94, the Interleukin-6 receptor subunit beta represents a significant target for drug discovery. Its involvement in immune response regulation and skeletal abnormalities presents a unique opportunity for developing treatments for these genetic disorders. The exploration of this protein's functions could pave the way for innovative therapeutic approaches.

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