Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create 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
P80188

UPID:
NGAL_HUMAN

ALTERNATIVE NAMES:
25 kDa alpha-2-microglobulin-related subunit of MMP-9; Lipocalin-2; Oncogene 24p3; Siderocalin; p25

ALTERNATIVE UPACC:
P80188; A6NII8; B4DWV4; B7ZAA2; P30150; Q5SYV9; Q5SYW0; Q6FGL5; Q92683

BACKGROUND:
The protein Neutrophil gelatinase-associated lipocalin, with alternative names such as Lipocalin-2 and Siderocalin, is integral to various biological processes including apoptosis, innate immunity, and iron metabolism. It binds and transports iron within the cell, influencing iron availability through its interactions with the SLC22A17 receptor. This protein's ability to modulate iron levels plays a crucial role in cellular responses to stress and infection.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Neutrophil gelatinase-associated lipocalin offers promising avenues for therapeutic intervention. Its critical role in managing iron levels and immune defense positions it as a valuable target in developing treatments for diseases linked to iron imbalance and immune dysfunctions.

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