AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myelin-associated glycoprotein

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P20916

UPID:

MAG_HUMAN

Alternative names:

Siglec-4a

Alternative UPACC:

P20916; B7Z2E5; F5GYC0; Q15489; Q567S4

Background:

Myelin-associated glycoprotein (MAG), also known as Siglec-4a, plays a crucial role in the nervous system. It mediates interactions between myelinating cells and neurons, aiding in the maintenance of axon myelination and protecting motoneurons against apoptosis. MAG's interaction with neuronal sialic acid-containing gangliosides and glycoproteins RTN4R and RTN4RL2 is pivotal for its function.

Therapeutic significance:

MAG's involvement in Spastic paraplegia 75, a neurodegenerative disorder, highlights its therapeutic potential. Understanding MAG's role could lead to novel treatments for this condition, emphasizing the importance of research into its functions and disease associations.

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