Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


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
Q9NPF7

UPID:
IL23A_HUMAN

ALTERNATIVE NAMES:
Interleukin-23 subunit p19

ALTERNATIVE UPACC:
Q9NPF7; Q6NZ80; Q6NZ82; Q9H2A5

BACKGROUND:
The Interleukin-23 subunit alpha, known alternatively as Interleukin-23 subunit p19, is integral to the immune response, associating with IL12B to form IL-23. This cytokine is released by cells such as dendritic cells and macrophages, initiating a cascade that activates JAK2, TYK2, and leads to the phosphorylation of STAT3 and STAT4. This activation promotes the production of cytokines like IL-17A, crucial for bacterial clearance and the support of T-helper 17 cells, a subset vital for immune defense.

THERAPEUTIC SIGNIFICANCE:
The exploration of Interleukin-23 subunit alpha's function offers a promising avenue for developing new treatments. Its critical role in immune system regulation and inflammation suggests potential for therapeutic intervention in diseases characterized by immune dysregulation.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.