Focused On-demand Library for Killer cell immunoglobulin-like receptor 2DL1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







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


Killer cell immunoglobulin-like receptor 2DL1 (KIR2DL1) serves as a critical receptor on natural killer (NK) cells, recognizing specific HLA-C alleles such as w4 and w6. By inhibiting NK cell activity, KIR2DL1 plays a pivotal role in modulating immune responses and preventing unintended cell lysis. Known by alternative names such as CD158 antigen-like family member A and p58 natural killer cell receptor, KIR2DL1's interaction with MHC class-I molecules underscores its importance in immune regulation.

Therapeutic significance:

Understanding the role of Killer cell immunoglobulin-like receptor 2DL1 could open doors to potential therapeutic strategies. Its ability to regulate NK cell activity positions it as a key target in developing treatments aimed at enhancing or suppressing immune responses, crucial for autoimmune diseases, cancer immunotherapy, and transplant rejection prevention.

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