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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are 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

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.


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
Q9P1W8

UPID:
SIRPG_HUMAN

ALTERNATIVE NAMES:
CD172 antigen-like family member B; Signal-regulatory protein beta-2

ALTERNATIVE UPACC:
Q9P1W8; B1AKP6; Q5D051; Q5JV25; Q5MKL4; Q8WWA5; Q9NQK8

BACKGROUND:
The Signal-regulatory protein gamma, identified by alternative names such as CD172 antigen-like family member B and Signal-regulatory protein beta-2, is integral to the immune system's functionality. It acts as an immunoglobulin-like cell surface receptor that, upon interaction with CD47, mediates critical cell-cell adhesion processes. This engagement on T-cells by CD47 on antigen-presenting cells significantly boosts antigen-specific T-cell proliferation and aids in T-cell activation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Signal-regulatory protein gamma unveils potential pathways for therapeutic intervention. Its key role in mediating T-cell proliferation and activation positions it as a valuable target for enhancing immunotherapeutic approaches, aiming to regulate immune responses more effectively.

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