AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cytokine receptor common subunit gamma

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

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

P31785

UPID:

IL2RG_HUMAN

Alternative names:

Interleukin-2 receptor subunit gamma; gammaC; p64

Alternative UPACC:

P31785; Q5FC12

Background:

The Cytokine receptor common subunit gamma, also known as Interleukin-2 receptor subunit gamma, gammaC, or p64, plays a pivotal role in immune response regulation. It serves as a common component for the receptors of various interleukins, notably in association with IL15RA, facilitating neutrophil phagocytosis stimulated by IL15.

Therapeutic significance:

This protein is crucial in the pathogenesis of severe combined immunodeficiency X-linked T-cell-negative/B-cell-positive/NK-cell-negative and X-linked combined immunodeficiency. These conditions underscore the protein's vital role in T-cell development and immune system functionality, presenting a promising target for therapeutic intervention.

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