Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening 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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P49759

UPID:
CLK1_HUMAN

ALTERNATIVE NAMES:
CDC-like kinase 1

ALTERNATIVE UPACC:
P49759; B4DFW7; Q0P694; Q8N5V8

BACKGROUND:
The Dual specificity protein kinase CLK1, alternatively named CDC-like kinase 1, is a crucial enzyme in the regulation of RNA splicing. It achieves this by phosphorylating serine- and arginine-rich proteins within the spliceosomal complex. This kinase's activity on substrates such as SRSF1, SRSF3, and PTPN1 places it at the heart of cellular regulatory mechanisms that control gene expression post-transcriptionally.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Dual specificity protein kinase CLK1 offers a promising pathway to uncovering novel therapeutic approaches. Its key role in modulating the alternative splicing of critical genes suggests its potential as a target in developing treatments for diseases where splicing errors are implicated.

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.