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 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 Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


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
Receptor.AI
 
UPACC
Q9H0U3

UPID:
MAGT1_HUMAN

ALTERNATIVE NAMES:
Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit MAGT1; Implantation-associated protein

ALTERNATIVE UPACC:
Q9H0U3; B2RAR4; D3DTE3; Q53G00; Q6P577; Q8NBN6

BACKGROUND:
The Magnesium transporter protein 1, known for its alternative names Dolichyl-diphosphooligosaccharide--protein glycosyltransferase subunit MAGT1 and Implantation-associated protein, is integral to the N-glycosylation of proteins. It acts within the STT3B-containing OST complex, specifically required for glycosylation near cysteine residues and may play a role in magnesium transport.

THERAPEUTIC SIGNIFICANCE:
Given MAGT1's critical function in immunodeficiency and congenital disorders of glycosylation, targeting this protein could lead to innovative treatments for related diseases. Its multifaceted role in biological systems makes it an intriguing subject for scientific inquiry and drug development.

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