Focused On-demand Library for Triggering receptor expressed on myeloid cells 2

Details

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.


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.


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 top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

PARTNER
Receptor.AI
 
UPACC
Q9NZC2

UPID:
TREM2_HUMAN

ALTERNATIVE NAMES:
Triggering receptor expressed on monocytes 2

ALTERNATIVE UPACC:
Q9NZC2; Q8N5H8; Q8WYN6

BACKGROUND:
The protein Triggering receptor expressed on myeloid cells 2 (TREM2) serves as a receptor for various ligands, including amyloid-beta, lipoproteins, and phospholipids, enhancing their uptake by microglia. It is pivotal in microglial activation, proliferation, and phagocytosis, playing a significant role in the brain's response to injury and disease. TREM2 regulates several critical pathways, including Wnt/beta-catenin signaling, PI3K, NF-kappa-B, and MTOR, influencing microglial metabolism and the immune response.

THERAPEUTIC SIGNIFICANCE:
Given TREM2's crucial role in mediating immune responses and its association with neurodegenerative diseases, particularly Polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy 2, it represents a promising target for therapeutic intervention. Exploring TREM2's pathways and interactions could lead to breakthroughs in treating Alzheimer's disease and other neurodegenerative disorders.

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.