Focused On-demand Library for Glucosidase 2 subunit beta

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

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.







Alternative names:

80K-H protein; Glucosidase II subunit beta; Protein kinase C substrate 60.1 kDa protein heavy chain

Alternative UPACC:

P14314; A8K318; Q96BU9; Q96D06; Q9P0W9


Glucosidase 2 subunit beta, also known as the 80K-H protein, plays a pivotal role in the maturation of glycoproteins. This enzyme acts by removing the two innermost glucose residues from the oligosaccharide precursor, a crucial step for the proper folding and function of many proteins. Additionally, it is essential for the biogenesis and plasma membrane trafficking of PKD1/Polycystin-1, a protein implicated in the primary cilia's structure and function.

Therapeutic significance:

The association of Glucosidase 2 subunit beta with Polycystic liver disease 1 highlights its potential as a therapeutic target. Understanding the role of Glucosidase 2 subunit beta could open doors to potential therapeutic strategies, especially for treating liver and possibly kidney cysts, offering hope for patients suffering from these conditions.

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