AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Retinol dehydrogenase 5

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 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.

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 top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening 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.

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.

partner

Reaxense

upacc

Q92781

UPID:

RDH5_HUMAN

Alternative names:

11-cis retinol dehydrogenase; 9-cis retinol dehydrogenase; Short chain dehydrogenase/reductase family 9C member 5

Alternative UPACC:

Q92781; O00179; Q8TAI2

Background:

Retinol dehydrogenase 5, also known as 11-cis retinol dehydrogenase, plays a pivotal role in the visual cycle. It catalyzes the oxidation of cis-isomers of retinol, including 11-cis-, 9-cis-, and 13-cis-retinol, crucial for vision. This enzyme operates in an NAD-dependent manner and is significant in the retinal pigment epithelium cells for 11-cis retinol oxidation.

Therapeutic significance:

Retinol dehydrogenase 5 is linked to Fundus albipunctatus, a retinal disease characterized by night blindness and white dots on the fundus. Understanding the role of Retinol dehydrogenase 5 could open doors to potential therapeutic strategies for this and related visual impairments.

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