Focused On-demand Libraries - Receptor.AI 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 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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
Q9H772

UPID:
GREM2_HUMAN

ALTERNATIVE NAMES:
Cysteine knot superfamily 1, BMP antagonist 2; DAN domain family member 3; Protein related to DAN and cerberus

ALTERNATIVE UPACC:
Q9H772; Q86UD9

BACKGROUND:
The protein Gremlin-2, known for its alternative names such as Protein related to DAN and cerberus, inhibits BMP2 and BMP4 activities, contributing significantly to embryonic development and cellular processes. Its function in antagonizing BMP4's suppression of progesterone underscores its importance in reproductive biology.

THERAPEUTIC SIGNIFICANCE:
Linked to Tooth agenesis, selective, 9, Gremlin-2's genetic variants suggest its therapeutic relevance. Exploring Gremlin-2's biological mechanisms offers promising avenues for developing novel treatments.

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.