Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Q14739

UPID:
LBR_HUMAN

ALTERNATIVE NAMES:
3-beta-hydroxysterol Delta (14)-reductase; C-14 sterol reductase; Integral nuclear envelope inner membrane protein; LMN2R; Lamin-B receptor; Sterol C14-reductase

ALTERNATIVE UPACC:
Q14739; B2R5P3; Q14740; Q53GU7; Q59FE6

BACKGROUND:
The protein Delta(14)-sterol reductase LBR, with alternative names such as Lamin-B receptor and Sterol C14-reductase, is integral to the cholesterol biosynthesis pathway and myeloid cell development. Its function extends to activating NADPH oxidases, essential for neutrophil differentiation, and maintaining cholesterol levels for membrane lipid raft formation.

THERAPEUTIC SIGNIFICANCE:
Given its association with various genetic disorders, including Pelger-Huet anomaly and Greenberg dysplasia, Delta(14)-sterol reductase LBR represents a significant target for drug discovery. Its role in cholesterol biosynthesis and nuclear envelope structure offers a unique opportunity for developing treatments aimed at correcting these fundamental cellular processes.

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