Focused On-demand Library for Protein phosphatase 1 regulatory subunit 3B

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

Hepatic glycogen-targeting protein phosphatase 1 regulatory subunit GL; Protein phosphatase 1 regulatory subunit 4; Protein phosphatase 1 subunit GL

Alternative UPACC:

Q86XI6; B3KTV3; Q9H812


Protein phosphatase 1 regulatory subunit 3B, also known as Hepatic glycogen-targeting protein phosphatase 1 regulatory subunit GL and Protein phosphatase 1 subunit GL, plays a pivotal role in glycogen metabolism. It acts as a glycogen-targeting subunit for phosphatase PP1, facilitating the interaction of PP1 with enzymes of the glycogen metabolism and regulating its activity. This protein limits glycogen breakdown by suppressing the rate at which PP1 dephosphorylates glycogen phosphorylase and enhances the rate at which it activates glycogen synthase.

Therapeutic significance:

Understanding the role of Protein phosphatase 1 regulatory subunit 3B could open doors to potential therapeutic strategies. Its significant impact on glycogen metabolism and insulin-stimulated glycogen synthesis highlights its potential as a target for therapeutic intervention in metabolic disorders.

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