Focused On-demand Library for Amiloride-sensitive sodium channel subunit alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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.







Alternative names:

Alpha-NaCH; Epithelial Na(+) channel subunit alpha; Nonvoltage-gated sodium channel 1 subunit alpha; SCNEA

Alternative UPACC:

P37088; A5X2U9; B4E2Q5; C5HTZ0; O43271; Q6GSQ6; Q9UM64


The Amiloride-sensitive sodium channel subunit alpha, also known as Alpha-NaCH, SCNEA, and Nonvoltage-gated sodium channel 1 subunit alpha, plays a pivotal role in the regulation of sodium permeability across epithelial cells. This protein facilitates the electrodiffusion of sodium, crucial for maintaining electrolyte balance, blood pressure, airway surface liquid homeostasis, and taste perception. Its expression in kidney, colon, lung, and eccrine sweat glands underscores its integral function in sodium reabsorption and fluid balance.

Therapeutic significance:

Mutations in the Amiloride-sensitive sodium channel subunit alpha are linked to several diseases, including Pseudohypoaldosteronism 1B1, autosomal recessive, characterized by salt wasting and severe electrolyte imbalance. Additionally, it is associated with Bronchiectasis with or without elevated sweat chloride 2, and Liddle syndrome 3, highlighting its role in respiratory and blood pressure disorders. Understanding the molecular mechanisms of this channel could lead to targeted therapies for these conditions.

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