Focused On-demand Library for Serine/threonine-protein kinase 40

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.

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.

Our top-notch dedicated system is used to design specialised 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

SINK-homologous serine/threonine-protein kinase; Sugen kinase 495

Alternative UPACC:

Q8N2I9; D3DPS8; Q5VTK8; Q5VTK9; Q6ZMN1; Q8N2J8; Q8N3I6; Q96HN6; Q96I44; Q9BSA3; Q9H7H6


Serine/threonine-protein kinase 40, also known by its alternative names SINK-homologous serine/threonine-protein kinase and Sugen kinase 495, plays a crucial role in cellular signaling pathways. This protein is identified by the unique identifier Q8N2I9 and is recognized for its potential regulatory function in inhibiting NF-kappa-B and p53-mediated gene transcription. These pathways are pivotal in controlling cell survival, proliferation, and apoptosis.

Therapeutic significance:

Understanding the role of Serine/threonine-protein kinase 40 could open doors to potential therapeutic strategies. Its involvement in key regulatory pathways suggests that modulation of its activity could have implications in treating diseases where NF-kappa-B and p53 pathways are dysregulated.

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