AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Interleukin-37

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.

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 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.

Our high-tech, dedicated method is applied to construct targeted 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 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

Reaxense

upacc

Q9NZH6

UPID:

IL37_HUMAN

Alternative names:

FIL1 zeta; IL-1X; Interleukin-1 family member 7; Interleukin-1 homolog 4; Interleukin-1 zeta; Interleukin-1-related protein

Alternative UPACC:

Q9NZH6; B5BU97; Q56AP9; Q8TD04; Q8TD05; Q9HBF2; Q9HBF3; Q9UHA6

Background:

Interleukin-37, known by alternative names such as FIL1 zeta and IL-1X, plays a pivotal role in the immune system. It acts as a suppressor of innate inflammatory and immune responses, crucial for preventing excessive inflammation. This protein operates through both intracellular mechanisms with SMAD3 and extracellularly by binding to its receptor composed of IL18R1 and IL18RAP.

Therapeutic significance:

Given its role in modulating inflammation, Interleukin-37 is directly linked to Inflammatory bowel disease 31, autosomal recessive, characterized by chronic gastrointestinal inflammation. Understanding the role of Interleukin-37 could open doors to potential therapeutic strategies for treating inflammatory bowel diseases by targeting the pathways it influences.

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