AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serine/threonine-protein kinase 32C

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Q86UX6

UPID:

ST32C_HUMAN

Alternative names:

PKE; Yet another novel kinase 3

Alternative UPACC:

Q86UX6; Q5T0Q5; Q86UE1

Background:

Serine/threonine-protein kinase 32C, known by its alternative names PKE and Yet another novel kinase 3, represents a unique entity in the kinase family. This protein, encoded by the gene with the accession number Q86UX6, plays a pivotal role in phosphorylation, a critical process in cellular signaling and function. Its structure and enzymatic mechanisms, characteristic of serine/threonine-specific protein kinases, facilitate diverse biological processes.

Therapeutic significance:

Understanding the role of Serine/threonine-protein kinase 32C could open doors to potential therapeutic strategies. While direct links to specific diseases are yet to be established, its fundamental role in phosphorylation suggests its potential impact on disease mechanisms. Targeting such kinases could lead to novel treatments for conditions where signaling pathways are disrupted.

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