AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Mitochondrial potassium channel ATP-binding subunit

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.

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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9NUT2

UPID:

MITOS_HUMAN

Alternative names:

ATP-binding cassette sub-family B member 8, mitochondrial; Mitochondrial ATP-binding cassette 1; Mitochondrial sulfonylurea-receptor

Alternative UPACC:

Q9NUT2; A5D8W3; B2RBL8; B3KND2; B4DG02; G3XAP3; O95787; Q53GM0

Background:

The Mitochondrial potassium channel ATP-binding subunit, also known as ATP-binding cassette sub-family B member 8, plays a pivotal role in mitochondrial function. It forms a complex with CCDC51/MITOK, facilitating ATP-dependent potassium currents across the mitochondrial inner membrane. This protein is essential for mitochondrial iron transport and the maintenance of cardiac function by regulating mitochondrial iron export and the maturation of cytosolic iron sulfur cluster-containing enzymes.

Therapeutic significance:

Understanding the role of the Mitochondrial potassium channel ATP-binding subunit could open doors to potential therapeutic strategies, particularly in cardiac health by ensuring the proper function of mitochondria.

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