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.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
P43626

UPID:
KI2L1_HUMAN

ALTERNATIVE NAMES:
CD158 antigen-like family member A; Natural killer-associated transcript 1; p58 natural killer cell receptor clones CL-42/47.11; p58.1 MHC class-I-specific NK receptor

ALTERNATIVE UPACC:
P43626; O43470; Q32WE6; Q6IST4

BACKGROUND:
The protein Killer cell immunoglobulin-like receptor 2DL1, also known as CD158 antigen-like family member A, plays a significant role in immune surveillance. It acts as a receptor on NK cells for certain HLA-C alleles, inhibiting NK cell activity to prevent cell lysis. This regulation is essential for maintaining the balance between immune defense and tolerance, highlighting the protein's critical function in immune system modulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Killer cell immunoglobulin-like receptor 2DL1 offers a promising pathway to novel therapeutic approaches. Given its regulatory role in NK cell activity, targeting KIR2DL1 could lead to breakthroughs in treatments for conditions where modulating the immune response is beneficial, including various cancers and autoimmune disorders.

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