AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Killer cell immunoglobulin-like receptor 2DL3

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening 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.

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

P43628

UPID:

KI2L3_HUMAN

Alternative names:

CD158 antigen-like family member B2; KIR-023GB; Killer inhibitory receptor cl 2-3; NKAT2a; NKAT2b; Natural killer-associated transcript 2; p58 natural killer cell receptor clone CL-6; p58.2 MHC class-I-specific NK receptor

Alternative UPACC:

P43628; O43472; P78402; Q14944; Q14945; Q9UM51; Q9UQ70

Background:

Killer cell immunoglobulin-like receptor 2DL3 (KIR2DL3) functions as a receptor on natural killer (NK) cells for HLA-C alleles, including HLA-Cw1, HLA-Cw3, and HLA-Cw7. By inhibiting the activity of NK cells, KIR2DL3 plays a crucial role in preventing cell lysis. This protein is also known by several alternative names, such as CD158 antigen-like family member B2 and NKAT2a, highlighting its significance in immune regulation.

Therapeutic significance:

Understanding the role of Killer cell immunoglobulin-like receptor 2DL3 could open doors to potential therapeutic strategies. Its ability to regulate NK cell activity positions it as a key player in the immune response, offering pathways for interventions in diseases where NK cell function is pivotal.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.