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.


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


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We employ our advanced, specialised process to create targeted 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
Q5VT25

UPID:
MRCKA_HUMAN

ALTERNATIVE NAMES:
CDC42-binding protein kinase alpha; DMPK-like alpha; Myotonic dystrophy kinase-related CDC42-binding kinase alpha

ALTERNATIVE UPACC:
Q5VT25; O75039; Q59GZ1; Q5H9N9; Q5T797; Q5VT26; Q5VT27; Q86XX2; Q86XX3; Q99646

BACKGROUND:
The protein Serine/threonine-protein kinase MRCK alpha, identified by alternative names such as DMPK-like alpha, is integral to the modulation of lamellar actomyosin retrograde flow, essential for cell protrusion and migration. It functions as a downstream effector of CDC42, orchestrating the phosphorylation of LIMK1, LIMK2, and PPP1R12A, thereby playing a critical role in cellular architecture and motility.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Serine/threonine-protein kinase MRCK alpha unveils potential pathways for developing novel therapeutic interventions.

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