AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Potassium voltage-gated channel subfamily H member 7

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.

We utilise our cutting-edge, exclusive workflow to develop 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9NS40

UPID:

KCNH7_HUMAN

Alternative names:

Ether-a-go-go-related gene potassium channel 3; Voltage-gated potassium channel subunit Kv11.3

Alternative UPACC:

Q9NS40; Q53QU4; Q53TB7; Q53TP9; Q8IV15

Background:

The Potassium voltage-gated channel subfamily H member 7, also known as Ether-a-go-go-related gene potassium channel 3 and Voltage-gated potassium channel subunit Kv11.3, plays a crucial role in cellular excitability. As the pore-forming alpha subunit of voltage-gated potassium channels, its activity is essential for the proper functioning of cardiac and nervous tissues. Channel properties can be influenced by cAMP levels and the assembly of different subunits, highlighting its complex regulatory mechanisms.

Therapeutic significance:

Understanding the role of Potassium voltage-gated channel subfamily H member 7 could open doors to potential therapeutic strategies. Its pivotal function in regulating heart rhythm and neuronal excitability positions it as a key target for drug discovery efforts aimed at treating arrhythmias and neurological disorders.

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