Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


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
Receptor.AI
 
UPACC
P43629

UPID:
KI3L1_HUMAN

ALTERNATIVE NAMES:
CD158 antigen-like family member E; HLA-BW4-specific inhibitory NK cell receptor; Natural killer-associated transcript 3; p70 natural killer cell receptor clones CL-2/CL-11

ALTERNATIVE UPACC:
P43629; O43473; Q14946; Q16541

BACKGROUND:
Killer cell immunoglobulin-like receptor 3DL1, known alternatively as HLA-BW4-specific inhibitory NK cell receptor, is integral to immune regulation. It serves as a receptor on natural killer cells, engaging with the HLA Bw4 allele to inhibit NK cell-mediated lysis. This receptor's function is essential for maintaining immune homeostasis, preventing the unnecessary destruction of cells and contributing to the body's defense mechanisms.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Killer cell immunoglobulin-like receptor 3DL1 holds promise for the development of novel therapeutic interventions. Its critical role in immune regulation suggests that targeting this receptor could lead to innovative treatments that modulate the immune system's response to various pathological conditions, potentially improving outcomes in immune-related diseases.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.