Focused On-demand Library for Probable dolichyl pyrophosphate Glc1Man9GlcNAc2 alpha-1,3-glucosyltransferase

Details

Focused On-demand Libraries - Receptor.AI 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 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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q9BVK2

UPID:
ALG8_HUMAN

ALTERNATIVE NAMES:
Asparagine-linked glycosylation protein 8 homolog; Dol-P-Glc:Glc(1)Man(9)GlcNAc(2)-PP-dolichyl alpha-1,3-glucosyltransferase; Dolichyl-P-Glc:Glc1Man9GlcNAc2-PP-dolichyl glucosyltransferase

ALTERNATIVE UPACC:
Q9BVK2; A6NDW6; O60860

BACKGROUND:
Probable dolichyl pyrophosphate Glc1Man9GlcNAc2 alpha-1,3-glucosyltransferase, known alternatively as Dolichyl-P-Glc:Glc1Man9GlcNAc2-PP-dolichyl glucosyltransferase, is crucial for the synthesis of N-glycoproteins. By transferring glucose from dolichyl phosphate glucose onto the lipid-linked oligosaccharide precursor, it plays a key role in glycoprotein biosynthesis. This enzyme's function is vital for the development and maintenance of cell functions, as evidenced by its requirement for the proper functioning of PKD1/Polycystin-1.

THERAPEUTIC SIGNIFICANCE:
The enzyme's critical role in diseases such as congenital disorder of glycosylation 1H and polycystic liver disease 3 underscores the potential for developing targeted therapies. By elucidating the mechanisms by which Probable dolichyl pyrophosphate Glc1Man9GlcNAc2 alpha-1,3-glucosyltransferase functions, researchers can identify new therapeutic strategies for these complex diseases.

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