Focused On-demand Library for Interleukin-7 receptor subunit alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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.

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

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:


Alternative UPACC:

P16871; B2RCS6; B4DVT1; Q05CU8; Q6NSP4; Q6NWM0; Q6NWM1; Q6NWM2; Q6NWM3; Q6SV45; Q9UPC1


Interleukin-7 receptor subunit alpha (IL-7Rα), also known as CDw127, plays a pivotal role in the immune system by acting as a receptor for interleukin-7 and thymic stromal lymphopoietin (TSLP). These interactions are crucial for the development and function of T cells and B cells, highlighting its significance in maintaining immune homeostasis.

Therapeutic significance:

IL-7Rα's involvement in Immunodeficiency 104 and Multiple Sclerosis 3 underscores its therapeutic potential. For Immunodeficiency 104, characterized by severe immune dysfunction, targeting IL-7Rα could enhance immune responses. In Multiple Sclerosis 3, modulating IL-7Rα activity might offer a novel approach to mitigate autoimmune attacks on the central nervous system. Understanding the role of IL-7Rα could open doors to potential therapeutic strategies.

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