Focused On-demand Library for Stimulator of interferon genes 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 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

It includes extensive molecular simulations of the receptor in its native membrane environment and the ensemble virtual screening accounting for its conformational mobility. In the case of dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets are determined on and between the subunits to cover the whole spectrum of possible mechanisms of action.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

Endoplasmic reticulum interferon stimulator; Mediator of IRF3 activation; Transmembrane protein 173

Alternative UPACC:

Q86WV6; A8K3P6; B6EB35; D6RBX0; D6RE01; D6RID9


The Stimulator of interferon genes protein (STING), encoded by the gene with accession number Q86WV6, plays a pivotal role in the innate immune response. It acts as a sensor of cytosolic DNA from bacteria and viruses, promoting the production of type I interferon. STING recognizes cyclic dinucleotides, leading to a potent anti-viral state. Additionally, it has a direct role in autophagy, targeting cytosolic DNA or DNA viruses for degradation.

Therapeutic significance:

STING-associated vasculopathy, infantile-onset (SAVI) is a severe autoinflammatory disease linked to variants affecting the STING gene. Understanding the role of STING could open doors to potential therapeutic strategies for SAVI and other related inflammatory conditions.

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