Focused On-demand Library for Alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase A

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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


We employ our advanced, specialised process to create 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
Q09328

UPID:
MGT5A_HUMAN

ALTERNATIVE NAMES:
Alpha-mannoside beta-1,6-N-acetylglucosaminyltransferase V; GlcNAc-T V; Mannoside acetylglucosaminyltransferase 5; N-acetylglucosaminyl-transferase V

ALTERNATIVE UPACC:
Q09328; D3DP70

BACKGROUND:
The enzyme Alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase A, known as MGAT5, catalyzes critical steps in the synthesis of branched, complex-type N-glycans. These glycans, found on key receptors and adhesion molecules, are vital for activating signaling pathways, modulating the actin cytoskeleton, and facilitating cell migration and adhesion. MGAT5's role extends to promoting angiogenesis and influencing the inflammatory response, highlighting its importance in cellular functions and growth factor signaling.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Alpha-1,6-mannosylglycoprotein 6-beta-N-acetylglucosaminyltransferase A could open doors to potential therapeutic strategies.

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