AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Killer cell immunoglobulin-like receptor 2DS4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We utilise our cutting-edge, exclusive workflow to develop focused 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 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

Reaxense

upacc

P43632

UPID:

KI2S4_HUMAN

Alternative names:

CD158 antigen-like family member I; Natural killer-associated transcript 8; P58 natural killer cell receptor clones CL-39/CL-17

Alternative UPACC:

P43632; Q6H2G7

Background:

Killer cell immunoglobulin-like receptor 2DS4 (KIR2DS4) 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 I, Natural killer-associated transcript 8, and P58 natural killer cell receptor clones CL-39/CL-17, KIR2DS4 is integral to the immune response.

Therapeutic significance:

Understanding the role of Killer cell immunoglobulin-like receptor 2DS4 could open doors to potential therapeutic strategies. Its unique position in the immune system as a modulator of NK cell activity highlights its potential as a target for immunotherapy, offering new avenues for treating diseases where NK cell regulation is crucial.

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