Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9H0K1

UPID:
SIK2_HUMAN

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

BACKGROUND:
The enzyme Serine/threonine-protein kinase SIK2, recognized by alternative names such as Qin-induced kinase and Salt-inducible kinase 2, orchestrates key roles in metabolic and immune pathways. It influences insulin signaling, CREB activity, and transcription factor DNA-binding through specific phosphorylation events. Its involvement extends to the inhibition of CREB-specific coactivators and histone acetyltransferase activity of EP300, highlighting its regulatory capacity in cellular metabolism and development.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Serine/threonine-protein kinase SIK2 unveils promising avenues for therapeutic intervention.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.