AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Transient receptor potential cation channel subfamily M 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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

Q96QT4

UPID:

TRPM7_HUMAN

Alternative names:

Channel-kinase 1; Long transient receptor potential channel 7

Alternative UPACC:

Q96QT4; Q6ZMF5; Q86VJ4; Q8NBW2; Q9BXB2; Q9NXQ2

Background:

Transient receptor potential cation channel subfamily M member 7 (TRPM7) is a unique protein that functions as both an essential ion channel and a serine/threonine-protein kinase. It is permeable to divalent cations, notably calcium and magnesium, playing a pivotal role in magnesium ion homeostasis and the regulation of anoxic neuronal cell death. TRPM7's kinase activity is crucial for its channel function, and it is involved in adjusting plasma membrane divalent cation fluxes based on the cell's metabolic state.

Therapeutic significance:

TRPM7's involvement in neurodegenerative disorders, specifically the Amyotrophic lateral sclerosis-parkinsonism/dementia complex 1, highlights its potential as a therapeutic target. Understanding the role of TRPM7 could open doors to potential therapeutic strategies for these debilitating conditions.

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