AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Aldo-keto reductase family 1 member B10

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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

Reaxense

upacc

O60218

UPID:

AK1BA_HUMAN

Alternative names:

ARL-1; Aldose reductase-like; Aldose reductase-related protein; Small intestine reductase

Alternative UPACC:

O60218; A4D1P1; O75890; Q6FHF3; Q8IWZ1

Background:

Aldo-keto reductase family 1 member B10 (AKR1B10) exhibits a broad substrate specificity, catalyzing the NADPH-dependent reduction of various carbonyl compounds to their corresponding alcohols. This enzyme is particularly effective against all-trans-retinal, 9-cis-retinal, and 13-cis-retinal, playing a pivotal role in detoxifying dietary and lipid-derived unsaturated carbonyls. Despite its enzymatic activity, AKR1B10 does not reduce glucose. Known alternatively as ARL-1, Aldose reductase-like, Aldose reductase-related protein, and Small intestine reductase, its multifaceted role underscores its biological significance.

Therapeutic significance:

Understanding the role of Aldo-keto reductase family 1 member B10 could open doors to potential therapeutic strategies.

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