AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Killer cell immunoglobulin-like receptor 2DS2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 our partner 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 sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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

Reaxense

upacc

P43631

UPID:

KI2S2_HUMAN

Alternative names:

CD158 antigen-like family member J; NK receptor 183 ActI; Natural killer-associated transcript 5; p58 natural killer cell receptor clone CL-49

Alternative UPACC:

P43631; Q14955; Q6H2G9

Background:

Killer cell immunoglobulin-like receptor 2DS2 (KIR2DS2) serves as a receptor on natural killer (NK) cells for HLA-C alleles, playing a pivotal role in the regulation of NK cell activity. Known by alternative names such as CD158 antigen-like family member J and NK receptor 183 ActI, KIR2DS2 is integral in the immune response, distinguishing between healthy cells and those presenting abnormalities.

Therapeutic significance:

Understanding the role of Killer cell immunoglobulin-like receptor 2DS2 could open doors to potential therapeutic strategies. Its involvement in the activation of NK cells suggests its potential in enhancing immune responses against malignancies and viral infections.

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