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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening 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.


PARTNER
Receptor.AI
 
UPACC
P49888

UPID:
ST1E1_HUMAN

ALTERNATIVE NAMES:
EST-1; Estrogen sulfotransferase; Sulfotransferase, estrogen-preferring

ALTERNATIVE UPACC:
P49888; Q8N6X5

BACKGROUND:
The enzyme Sulfotransferase 1E1, alternatively named Estrogen sulfotransferase, is a key enzyme in estrogen metabolism, inactivating estrogens through sulfate conjugation. It exhibits a broad substrate specificity, sulfating various steroids and xenobiotics, albeit with varying efficiencies. Notably, it does not sulfonate cortisol, testosterone, and dopamine. Its activity extends to metabolites from gut bacteria, implicating it in the gut-brain axis through metabolic regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Sulfotransferase 1E1 offers a promising avenue for developing novel therapeutic approaches, particularly in managing estrogen-related disorders and modulating the gut microbiota-host metabolic axis.

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.