Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
Q9Y5S2

UPID:
MRCKB_HUMAN

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

ALTERNATIVE UPACC:
Q9Y5S2; A9JR72; Q2L7A5; Q86TJ1; Q9ULU5

BACKGROUND:
The Serine/threonine-protein kinase MRCK beta, known for its roles in cell migration and cytoskeleton reorganization, is a key downstream effector of CDC42. It regulates actin cytoskeletal reorganization by phosphorylating PPP1R12C and MYL9/MLC2. Its function in concert with FAM89B/LRAP25 in targeting LIMK1 to the lamellipodium is crucial for lamellipodial F-actin regulation.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Chilton-Okur-Chung neurodevelopmental syndrome, which involves developmental delay and intellectual disability, the study of Serine/threonine-protein kinase MRCK beta holds promise for developing targeted therapies. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry and drug discovery.

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