AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Chitobiosyldiphosphodolichol beta-mannosyltransferase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Reaxense

upacc

Q9BT22

UPID:

ALG1_HUMAN

Alternative names:

Asparagine-linked glycosylation protein 1 homolog; Beta-1,4-mannosyltransferase; GDP-Man:GlcNAc2-PP-dolichol mannosyltransferase; GDP-mannose-dolichol diphosphochitobiose mannosyltransferase; Mannosyltransferase-1

Alternative UPACC:

Q9BT22; B4DP08; Q6UVZ9; Q8N5Y4; Q9P2Y2

Background:

Chitobiosyldiphosphodolichol beta-mannosyltransferase, also known as Asparagine-linked glycosylation protein 1 homolog, plays a pivotal role in the biosynthesis of glycoproteins. It catalyzes the addition of the first mannose moieties, essential for proper N-linked glycosylation, a process critical for protein folding and stability.

Therapeutic significance:

This protein's malfunction is linked to Congenital disorder of glycosylation 1K, a condition with a wide range of clinical features including nervous system defects and immunodeficiency. Targeting the protein's function could lead to novel treatments for this multisystem disorder.

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