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.


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 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.


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
O76062

UPID:
ERG24_HUMAN

ALTERNATIVE NAMES:
3-beta-hydroxysterol Delta (14)-reductase; Another new gene 1 protein; C-14 sterol reductase; Putative sterol reductase SR-1; Sterol C14-reductase; Transmembrane 7 superfamily member 2

ALTERNATIVE UPACC:
O76062; A8K4H0; O95982; Q8IY06; Q96E64; Q96GZ1

BACKGROUND:
The enzyme Delta(14)-sterol reductase TM7SF2, also referred to as C-14 sterol reductase, is integral to the cholesterol biosynthesis pathway. By catalyzing the reduction of the C14-unsaturated bond in lanosterol, it facilitates a critical step in the production of cholesterol, a fundamental component of cell membranes and precursor for steroid hormones.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Delta(14)-sterol reductase TM7SF2 offers a pathway to novel therapeutic avenues. Given its central role in cholesterol synthesis, targeting this enzyme could lead to innovative treatments for managing cholesterol levels and preventing diseases associated with cholesterol dysregulation.

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