AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Natural killer cells antigen CD94

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

We employ our advanced, specialised process to create targeted libraries for protein-protein interfaces.

 Fig. 1. The sreening workflow of Receptor.AI

It features thorough molecular simulations of the target protein, both isolated and in complex with key partner proteins, complemented by ensemble virtual screening that accounts for conformational mobility in the unbound and complex states. The tentative binding sites are explored on the protein-protein interaction interface and at remote allosteric locations, encompassing the entire spectrum of potential mechanisms of action.

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

Reaxense

upacc

Q13241

UPID:

KLRD1_HUMAN

Alternative names:

KP43; Killer cell lectin-like receptor subfamily D member 1; NK cell receptor

Alternative UPACC:

Q13241; O43321; O43773; Q9UBE3; Q9UEQ0

Background:

Natural killer cells antigen CD94, also known as KP43, plays a crucial role in immune surveillance. As a part of the immune receptor complex with KLRC1 or KLRC2, it recognizes HLA-E molecules carrying peptides from MHC class I molecules, facilitating self-nonself discrimination. This process is vital for the immune system's ability to detect and respond to unhealthy cells while sparing normal ones.

Therapeutic significance:

Understanding the role of Natural killer cells antigen CD94 could open doors to potential therapeutic strategies. Its involvement in immune regulation and self-tolerance mechanisms highlights its potential as a target for modulating immune responses in diseases.

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