AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-1,2-mannosyltransferase ALG9

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 top-notch dedicated system is used to design specialised 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

Q9H6U8

UPID:

ALG9_HUMAN

Alternative names:

Asparagine-linked glycosylation protein 9 homolog; Disrupted in bipolar disorder protein 1; Dol-P-Man:Man(6)GlcNAc(2)-PP-Dol alpha-1,2-mannosyltransferase; Dol-P-Man:Man(8)GlcNAc(2)-PP-Dol alpha-1,2-mannosyltransferase

Alternative UPACC:

Q9H6U8; Q6ZMD5; Q7Z4R4; Q96GS7; Q96PB9; Q9H068

Background:

Alpha-1,2-mannosyltransferase ALG9, also known as Asparagine-linked glycosylation protein 9 homolog, plays a pivotal role in the biosynthesis of glycoproteins by catalyzing the transfer of mannose from Dol-P-Man to lipid-linked oligosaccharides. This enzyme is essential for proper cell function and development.

Therapeutic significance:

Mutations in ALG9 are linked to Congenital disorder of glycosylation 1L and Gillessen-Kaesbach-Nishimura syndrome, highlighting its critical role in human health. Understanding the function of ALG9 could lead to novel therapeutic strategies for these genetic disorders.

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