AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Antiviral innate immune response receptor RIG-I

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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 employ our advanced, specialised process to create targeted libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

This includes comprehensive molecular simulations of the receptor in its native membrane environment, paired with ensemble virtual screening that factors in its conformational mobility. In cases involving dimeric or oligomeric receptors, the entire functional complex is modelled, pinpointing potential binding pockets on and between the subunits to capture the full range of 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.

partner

Reaxense

upacc

O95786

UPID:

RIGI_HUMAN

Alternative names:

ATP-dependent RNA helicase DDX58; DEAD box protein 58; RIG-I-like receptor 1; RNA sensor RIG-I; Retinoic acid-inducible gene 1 protein; Retinoic acid-inducible gene I protein

Alternative UPACC:

O95786; A2RU81; Q5HYE1; Q5VYT1; Q9NT04

Background:

The Antiviral innate immune response receptor RIG-I, also known as ATP-dependent RNA helicase DDX58, plays a pivotal role in the innate immune system. It detects viral RNAs in the cytoplasm, triggering a signaling cascade that results in the production of type I interferons and pro-inflammatory cytokines. This receptor's ability to sense both positive and negative strand RNA viruses, including influenza, hepatitis C, and SARS-CoV-2, underscores its critical function in antiviral defense.

Therapeutic significance:

RIG-I's involvement in Singleton-Merten syndrome 2, characterized by aortic calcification and skeletal abnormalities, highlights its potential as a therapeutic target. Understanding the role of RIG-I could open doors to potential therapeutic strategies for treating viral infections and associated immune 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.
No Spam. Cancel Anytime.