Focused On-demand Library for Squalene monooxygenase

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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We employ our advanced, specialised process to create targeted 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.


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
Q14534

UPID:
ERG1_HUMAN

ALTERNATIVE NAMES:
Squalene epoxidase

ALTERNATIVE UPACC:
Q14534; Q9UEK6; Q9UNR6

BACKGROUND:
Squalene monooxygenase, identified by its alternative name Squalene epoxidase, is a key enzyme in the cholesterol synthesis pathway. By catalyzing the conversion of squalene into (S)-2,3-epoxysqualene, it serves as a rate-limiting step in the production of vital sterols, including cholesterol.

THERAPEUTIC SIGNIFICANCE:
The exploration of Squalene monooxygenase's function offers a promising avenue for the development of novel therapeutic approaches. Given its crucial role in sterol biosynthesis, targeting this enzyme could lead to breakthroughs in treating cholesterol-related conditions.

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