Focused On-demand Libraries - Receptor.AI 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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening 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.


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
Q9UPE1

UPID:
SRPK3_HUMAN

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

BACKGROUND:
The SRSF protein kinase 3, known for its specificity in phosphorylating serine residues in arginine/serine dipeptides, is essential for normal muscle development. It targets the SR splicing factor SRSF1 and the lamin-B receptor in vitro, highlighting its role in post-translational modifications and cellular structure maintenance.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of SRSF protein kinase 3 holds the potential to unlock new therapeutic avenues. Given its critical role in muscle development, targeting this kinase could lead to innovative treatments for related conditions, making it a focal point in drug discovery research.

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