Focused On-demand Library for Delta(24)-sterol reductase

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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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

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.


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
Q15392

UPID:
DHC24_HUMAN

ALTERNATIVE NAMES:
24-dehydrocholesterol reductase; 3-beta-hydroxysterol Delta-24-reductase; Diminuto/dwarf1 homolog; Seladin-1

ALTERNATIVE UPACC:
Q15392; B7Z817; D3DQ51; Q9HBA8

BACKGROUND:
The enzyme Delta(24)-sterol reductase, known alternatively as Seladin-1, is integral to the cholesterol biosynthetic pathway, facilitating the conversion of sterol intermediates by reducing the delta-24 double bond. Beyond its primary function in cholesterol synthesis, Delta(24)-sterol reductase exhibits protective roles in cellular mechanisms, notably in reducing oxidative stress-induced apoptosis and in defense against amyloid-beta peptide toxicity.

THERAPEUTIC SIGNIFICANCE:
Linked to the rare condition desmosterolosis, which manifests through congenital anomalies and abnormal cholesterol precursor levels, Delta(24)-sterol reductase's genetic variants underscore its clinical relevance. The exploration of Delta(24)-sterol reductase's functions and its involvement in cholesterol metabolism and cellular protection mechanisms holds promise for novel therapeutic avenues in managing desmosterolosis and enhancing our understanding of cholesterol-related pathologies.

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.