Focused On-demand Library for Delta(14)-sterol reductase LBR

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 our partner 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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







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


Delta(14)-sterol reductase LBR, also known as 3-beta-hydroxysterol Delta(14)-reductase, plays a pivotal role in cholesterol biosynthesis, critical for cell growth and functional maturation in myeloid cells. It catalyzes the reduction of the C14-unsaturated bond of lanosterol, leading to cholesterol production. Additionally, it anchors the lamina and heterochromatin to the inner nuclear membrane, influencing nuclear shape and chromatin organization.

Therapeutic significance:

LBR's involvement in diseases such as Pelger-Huet anomaly, Greenberg dysplasia, Reynolds syndrome, and Rhizomelic skeletal dysplasia highlights its clinical importance. Understanding the role of Delta(14)-sterol reductase LBR could open doors to potential therapeutic strategies for these conditions, especially in targeting abnormal cholesterol biosynthesis pathways and nuclear envelope integrity.

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