AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Inositol oxygenase

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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 top-notch dedicated system is used to design specialised 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q9UGB7

UPID:

MIOX_HUMAN

Alternative names:

Aldehyde reductase-like 6; Kidney-specific protein 32; Myo-inositol oxygenase; Renal-specific oxidoreductase

Alternative UPACC:

Q9UGB7; Q05DJ6; Q5S8C9; Q9BZZ1; Q9UHB8

Background:

Inositol oxygenase, also known by alternative names such as Aldehyde reductase-like 6, Kidney-specific protein 32, Myo-inositol oxygenase, and Renal-specific oxidoreductase, plays a pivotal role in cellular metabolism. This enzyme is crucial for the conversion of myo-inositol into D-glucuronic acid, a process integral to the proper functioning of renal and other tissues.

Therapeutic significance:

Understanding the role of Inositol oxygenase could open doors to potential therapeutic strategies. Its critical function in cellular metabolism highlights its potential as a target for addressing metabolic disorders and renal diseases.

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