AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Retinol dehydrogenase 12

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Q96NR8

UPID:

RDH12_HUMAN

Alternative names:

All-trans and 9-cis retinol dehydrogenase; Short chain dehydrogenase/reductase family 7C member 2

Alternative UPACC:

Q96NR8; B2RDA2; Q8TAW6

Background:

Retinol dehydrogenase 12 (RDH12) functions as a retinoids dehydrogenase/reductase, primarily converting various forms of retinal, including 9-cis, 11-cis, and all-trans-retinal, with a preference for NADP. It exhibits activity towards lipid peroxidation products, playing a crucial role in detoxifying toxic aldehyde products in photoreceptor cells. Despite its weak activity towards 13-cis-retinol, RDH12's involvement in visual processes and cellular detoxification underscores its biological significance.

Therapeutic significance:

RDH12 is implicated in severe retinal dystrophies, such as Leber congenital amaurosis 13 and Retinitis pigmentosa 53, diseases characterized by early-onset vision loss and progressive retinal degeneration. Understanding the role of RDH12 could open doors to potential therapeutic strategies, offering hope for interventions that could mitigate or reverse the progression of these debilitating visual impairments.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.