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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


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
O14625

UPID:
CXL11_HUMAN

ALTERNATIVE NAMES:
Beta-R1; H174; Interferon gamma-inducible protein 9; Interferon-inducible T-cell alpha chemoattractant; Small-inducible cytokine B11

ALTERNATIVE UPACC:
O14625; Q53YA3; Q92840

BACKGROUND:
The protein C-X-C motif chemokine 11, also referred to as Interferon-inducible T-cell alpha chemoattractant, plays a crucial role in the chemotaxis of activated T-cells and not neutrophils or monocytes. Its ability to induce calcium release in T-cells and its binding affinity to CXCR3 underscore its importance in immune system functions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of C-X-C motif chemokine 11 reveals its potential in developing therapeutic strategies. Given its role in CNS diseases and skin immune responses through T-cell recruitment, it stands as a key target for innovative treatments.

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