Focused On-demand Library for Prostaglandin reductase 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our associate 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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.







Alternative names:

15-oxoprostaglandin 13-reductase; Dithiolethione-inducible gene 1 protein; Leukotriene B4 12-hydroxydehydrogenase; NAD(P)H-dependent alkenal/one oxidoreductase

Alternative UPACC:

Q14914; A8K0N2; B4DPK3; F5GY50; Q8IYQ0; Q9H1X6


Prostaglandin reductase 1, known by alternative names such as 15-oxoprostaglandin 13-reductase and Leukotriene B4 12-hydroxydehydrogenase, plays a pivotal role in the metabolic inactivation of eicosanoids, including prostaglandins and leukotrienes. This enzyme efficiently reduces the 13,14 double bond of 15-oxoPGs and oxidizes LTB4 into less active metabolites, thereby modulating inflammatory responses.

Therapeutic significance:

Understanding the role of Prostaglandin reductase 1 could open doors to potential therapeutic strategies. Its involvement in the regulation of inflammatory mediators highlights its potential as a target for developing treatments for inflammation-related conditions.

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