Focused On-demand Library for Advanced glycosylation end product-specific receptor

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 our partner 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Receptor for advanced glycosylation end products

Alternative UPACC:

Q15109; A2BFI7; A6NKF0; A7Y2U9; B0V176; Q15279; Q3L1R4; Q3L1R5; Q3L1R6; Q3L1R7; Q3L1R8; Q3L1S0; Q86SN1; Q9H2X7; Q9Y3R3; V5R6A3


The Advanced glycosylation end product-specific receptor (RAGE) is a cell surface receptor that recognizes a variety of endogenous ligands. These include advanced glycation end products, S100 proteins, and HMGB1, among others. RAGE plays a pivotal role in sensing stress signals and mediating inflammatory responses by activating NF-kappa-B, leading to the production of pro-inflammatory cytokines.

Therapeutic significance:

Given its central role in inflammation and stress response, targeting RAGE could offer novel therapeutic avenues in treating diseases characterized by chronic inflammation, such as diabetes, neurodegenerative disorders, and cancers. Understanding the role of RAGE could open doors to potential therapeutic strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.