Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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.


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
P05231

UPID:
IL6_HUMAN

ALTERNATIVE NAMES:
B-cell stimulatory factor 2; CTL differentiation factor; Hybridoma growth factor; Interferon beta-2

ALTERNATIVE UPACC:
P05231; Q9UCU2; Q9UCU3; Q9UCU4

BACKGROUND:
The cytokine Interleukin-6, with aliases such as Hybridoma growth factor and CTL differentiation factor, is integral to immune responses, regeneration processes, and metabolic regulation. It triggers 'classic', 'trans', and 'cluster signaling' by interacting with IL6R and IL6ST, influencing a wide range of cellular activities from acute phase response to glucose homeostasis.

THERAPEUTIC SIGNIFICANCE:
Given IL-6's critical role in systemic juvenile Rheumatoid arthritis and its capacity to induce severe extraarticular features, understanding its mechanisms opens doors to developing targeted therapies. Modulating IL-6 activity presents a promising avenue for alleviating symptoms and potentially reversing the progression of this and similar autoimmune diseases.

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