Focused On-demand Library for Tumor necrosis factor-inducible gene 6 protein

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 utilise our cutting-edge, exclusive workflow to develop focused 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.

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.







Alternative names:

Hyaluronate-binding protein; TNF-stimulated gene 6 protein; Tumor necrosis factor alpha-induced protein 6

Alternative UPACC:

P98066; Q53TI7; Q8WWI9


The Tumor necrosis factor-inducible gene 6 protein, also known as Hyaluronate-binding protein or TNF-stimulated gene 6 protein, plays a pivotal role in extracellular matrix organization and tissue remodeling. It is crucial in the transfer and modification of heavy chains in the inter-alpha-inhibitor complex to hyaluronan, influencing antiprotease functions, oocyte fertilization, and leukocyte rolling. Its ability to modulate chemokine interactions and limit neutrophil recruitment highlights its regulatory role in inflammation.

Therapeutic significance:

Understanding the role of Tumor necrosis factor-inducible gene 6 protein could open doors to potential therapeutic strategies. Its involvement in key physiological processes such as tissue remodeling, inflammation regulation, and bone remodeling positions it as a target for therapeutic intervention in related disorders.

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.