Focused On-demand Library for Retinol dehydrogenase 12

Details

Focused On-demand Libraries - Receptor.AI 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 Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


 

Fig. 1. The screening 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
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:
The enzyme Retinol dehydrogenase 12, known for its alternative names All-trans and 9-cis retinol dehydrogenase, plays a pivotal role in the visual cycle. It is responsible for the oxidation of retinaldehydes to retinoic acids, crucial for vision. RDH12's activity extends to detoxifying harmful aldehydes from lipid peroxidation, highlighting its protective role in photoreceptor cells against oxidative stress.

THERAPEUTIC SIGNIFICANCE:
Linked to debilitating conditions like Leber congenital amaurosis 13 and Retinitis pigmentosa 53, RDH12's dysfunction underscores its therapeutic significance. Targeting RDH12's pathway offers a promising avenue for developing treatments aimed at restoring vision or halting the progression of these retinal dystrophies. The exploration of RDH12's function and its role in disease mechanisms is a critical step towards innovative therapeutic solutions.

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