Focused On-demand Libraries - Receptor.AI 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.


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 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 screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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
P20138

UPID:
CD33_HUMAN

ALTERNATIVE NAMES:
Sialic acid-binding Ig-like lectin 3; gp67

ALTERNATIVE UPACC:
P20138; B4E3P8; C9JEN7; F8WAL2; Q8TD24

BACKGROUND:
The protein Myeloid cell surface antigen CD33, with alternative names Sialic acid-binding Ig-like lectin 3 and gp67, functions significantly in cell-cell interaction and immune cell regulation. It has a high affinity for alpha-2,3- and alpha-2,6-linked sialic acid-bearing glycans. The phosphorylation of CD33's ITIMs upon ligand binding activates PTPN6/SHP-1 and PTPN11/SHP-2, leading to the regulation of immune responses through signal transduction pathways.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Myeloid cell surface antigen CD33 paves the way for innovative therapeutic approaches.

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