AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serine/threonine-protein kinase MRCK beta

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our partner Reaxense.

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.

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

 Fig. 1. The sreening 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.

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

Reaxense

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:

Serine/threonine-protein kinase MRCK beta, also known as CDC42-binding protein kinase beta, plays a pivotal role in cytoskeleton reorganization and cell migration. It achieves this through phosphorylation of key proteins such as PPP1R12C and MYL9/MLC2, crucial for actin cytoskeletal reorganization. Additionally, it collaborates with MYO18A and LURAP1 to modulate lamellar actomyosin retrograde flow, essential for cell protrusion and migration.

Therapeutic significance:

The protein's involvement in Chilton-Okur-Chung neurodevelopmental syndrome, characterized by developmental delay and intellectual disability, underscores its therapeutic significance. Understanding the role of Serine/threonine-protein kinase MRCK beta could open doors to potential therapeutic strategies for this and related disorders.

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