AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Thioredoxin domain-containing protein 12

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

We use our state-of-the-art dedicated workflow for designing focused 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.

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

O95881

UPID:

TXD12_HUMAN

Alternative names:

Endoplasmic reticulum resident protein 18; Endoplasmic reticulum resident protein 19; Thioredoxin-like protein p19; hTLP19

Alternative UPACC:

O95881; B3KQS0; Q5T1T4; Q96H50

Background:

Thioredoxin domain-containing protein 12, known by alternative names such as Endoplasmic reticulum resident protein 18 and 19, Thioredoxin-like protein p19, and hTLP19, plays a crucial role as a protein-disulfide reductase in the endoplasmic reticulum. It promotes disulfide bond formation in client proteins through its thiol-disulfide oxidase activity, essential for protein folding and stability.

Therapeutic significance:

Understanding the role of Thioredoxin domain-containing protein 12 could open doors to potential therapeutic strategies. Its pivotal function in protein folding and stability highlights its importance in cellular homeostasis and disease prevention.

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