Focused On-demand Library for SRSF protein kinase 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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.







Alternative names:

Muscle-specific serine kinase 1; Serine/arginine-rich protein-specific kinase 3; Serine/threonine-protein kinase 23

Alternative UPACC:

Q9UPE1; Q13583; Q4F970; Q562F5; Q9UM62


SRSF protein kinase 3, also known as Muscle-specific serine kinase 1 and Serine/threonine-protein kinase 23, plays a pivotal role in phosphorylating substrates at serine residues within arginine/serine-rich domains. This kinase's activity is crucial for the phosphorylation of the SR splicing factor SRSF1 and the lamin-B receptor, contributing significantly to cellular processes in vitro. Its necessity for normal muscle development underscores its biological importance.

Therapeutic significance:

Understanding the role of SRSF protein kinase 3 could open doors to potential therapeutic strategies, particularly in muscle development disorders. Its specific kinase activity offers a promising target for drug discovery, aiming to modulate its function for therapeutic benefits.

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