Focused On-demand Library for Serine/threonine-protein kinase SIK2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 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.

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

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:

Qin-induced kinase; Salt-inducible kinase 2; Serine/threonine-protein kinase SNF1-like kinase 2

Alternative UPACC:

Q9H0K1; A8K5B8; B0YJ94; O94878; Q17RV0; Q6AZE2; Q76N03; Q8NCV7; Q96CZ8


Serine/threonine-protein kinase SIK2, also known as Qin-induced kinase and Salt-inducible kinase 2, is a pivotal enzyme in various biological processes including fatty acid oxidation, autophagy, immune response, and glucose metabolism. It modulates insulin signal transduction by phosphorylating IRS1 in adipocytes and regulates DNA-binding ability of transcription factors such as PPARA or MLXIPL by phosphorylating EP300. Additionally, SIK2 plays a crucial role in thymic T-cell development.

Therapeutic significance:

Understanding the role of Serine/threonine-protein kinase SIK2 could open doors to potential therapeutic strategies.

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