Focused On-demand Library for All-trans-retinol dehydrogenase [NAD(+)] ADH7

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 for enzymes.

 Fig. 1. The sreening 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.







Alternative names:

Alcohol dehydrogenase class 4 mu/sigma chain; Alcohol dehydrogenase class IV mu/sigma chain; Gastric alcohol dehydrogenase; Omega-hydroxydecanoate dehydrogenase ADH7; Retinol dehydrogenase

Alternative UPACC:

P40394; A2RRB6; A8MVN9; B2R760; B4DWV6; Q13713


All-trans-retinol dehydrogenase [NAD(+)] ADH7, also known as Alcohol dehydrogenase class 4 mu/sigma chain, plays a crucial role in the NAD-dependent oxidation of substances like all-trans-retinol and omega-hydroxy fatty acids. Its ability to catalyze both oxidative and reductive reactions positions it as a key player in retinoid metabolism and the detoxification of cytotoxic aldehydes.

Therapeutic significance:

Understanding the role of All-trans-retinol dehydrogenase [NAD(+)] ADH7 could open doors to potential therapeutic strategies. Its involvement in critical metabolic pathways suggests its potential as a target for interventions in metabolic disorders or conditions related to oxidative stress.

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