Focused On-demand Libraries - Receptor.AI 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.


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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

This process includes extensive molecular simulations of the receptor in its native membrane environment, along with ensemble virtual screening that accounts for its conformational mobility. In the case of dimeric or oligomeric receptors, the entire functional complex is modelled, identifying potential binding pockets on and between the subunits to encompass all possible mechanisms of action.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q86WV6

UPID:
STING_HUMAN

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

ALTERNATIVE UPACC:
Q86WV6; A8K3P6; B6EB35; D6RBX0; D6RE01; D6RID9

BACKGROUND:
Endoplasmic reticulum interferon stimulator, also known as STING, is crucial for initiating an innate immune response against microbial infections. By binding to cyclic dinucleotides produced by bacteria and DNA viruses, STING activates interferon production and autophagy. Its ability to distinguish between different types of cyclic dinucleotides allows for a nuanced immune response.

THERAPEUTIC SIGNIFICANCE:
Given its central role in mediating immune responses, STING is implicated in STING-associated vasculopathy with infantile onset, a disease characterized by systemic inflammation and severe skin lesions. Targeting STING pathways offers a promising avenue for developing treatments for this and potentially other autoimmune diseases.

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