Focused On-demand Library for Protein O-GlcNAcase

Focused On-demand Libraries - Receptor.AI 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 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

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 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
O60502

UPID:
OGA_HUMAN

ALTERNATIVE NAMES:
Beta-N-acetylglucosaminidase; Beta-N-acetylhexosaminidase; Beta-hexosaminidase; Meningioma-expressed antigen 5; N-acetyl-beta-D-glucosaminidase; N-acetyl-beta-glucosaminidase; Nuclear cytoplasmic O-GlcNAcase and acetyltransferase

ALTERNATIVE UPACC:
O60502; B7WPB9; D3DR79; E9PGF9; O75166; Q86WV0; Q8IV98; Q9BVA5; Q9HAR0

BACKGROUND:
The Protein O-GlcNAcase, with alternative names such as Beta-hexosaminidase and N-acetyl-beta-D-glucosaminidase, is pivotal in biochemical pathways, specifically in cleaving GlcNAc residues from O-glycosylated proteins. Its activity is characterized by the selective use of substrates like p-nitrophenyl-beta-GlcNAc, underscoring its critical enzymatic role. Notably, it does not exhibit histone acetyltransferase activity, emphasizing its specialized function.

THERAPEUTIC SIGNIFICANCE:
The exploration of Protein O-GlcNAcase's function offers a promising avenue for drug discovery. Its unique substrate specificity and role in modifying O-glycosylated proteins present it as an intriguing target for developing novel therapeutic agents, potentially addressing unmet medical needs.

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