Focused On-demand Library for Serine/threonine-protein kinase 16

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.

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

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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:

Myristoylated and palmitoylated serine/threonine-protein kinase; Protein kinase PKL12; TGF-beta-stimulated factor 1; Tyrosine-protein kinase STK16; hPSK

Alternative UPACC:

O75716; A8K9H9; Q5U0F8; Q96KI2; Q9BUH4; Q9UEN3; Q9UP78


Serine/threonine-protein kinase 16, known by alternative names such as Myristoylated and palmitoylated serine/threonine-protein kinase, Protein kinase PKL12, TGF-beta-stimulated factor 1, and Tyrosine-protein kinase STK16, plays a pivotal role in cellular processes. It phosphorylates serine and threonine residues, impacting substrates like DRG1, ENO1, and EIF4EBP1. Its autophosphorylation ability and involvement in secretory vesicle trafficking, intracellular signaling, and TGF-beta signaling highlight its multifaceted role in cellular function.

Therapeutic significance:

Understanding the role of Serine/threonine-protein kinase 16 could open doors to potential therapeutic strategies.

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