AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Retinol dehydrogenase 16

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our high-tech, dedicated method is applied to construct targeted 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.

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

Reaxense

upacc

O75452

UPID:

RDH16_HUMAN

Alternative names:

Human epidermal retinol dehydrogenase; Microsomal NAD(+)-dependent retinol dehydrogenase 4; Short chain dehydrogenase/reductase family 9C member 8; Sterol/retinol dehydrogenase

Alternative UPACC:

O75452; Q9UNV2

Background:

Retinol dehydrogenase 16 (RDH16) is a pivotal enzyme in the metabolism of retinol, converting various forms of retinol into their corresponding aldehydes. It exhibits a preference for NAD and demonstrates higher activity with CRBP-bound retinol than with free retinol. RDH16 is also capable of oxidizing 3-alpha-hydroxysteroids, including the conversion of androstanediol and androsterone into dihydrotestosterone and androstanedione, showcasing its versatility in steroid metabolism.

Therapeutic significance:

Understanding the role of Retinol dehydrogenase 16 could open doors to potential therapeutic strategies. Its involvement in retinol and steroid metabolism positions it as a key target for modulating physiological processes related to vision, cellular growth, and hormone regulation.

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