AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Alpha-2-macroglobulin-like protein 1

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.

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

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.

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

Reaxense

upacc

A8K2U0

UPID:

A2ML1_HUMAN

Alternative names:

C3 and PZP-like alpha-2-macroglobulin domain-containing protein 9

Alternative UPACC:

A8K2U0; B5MDD1; B7Z7V4; D3DUV3; F5H2Z2; Q2M224; Q6ZW52; Q6ZW53; Q8N1M4; Q96LQ8

Background:

Alpha-2-macroglobulin-like protein 1, also known as C3 and PZP-like alpha-2-macroglobulin domain-containing protein 9, plays a crucial role in the body's defense mechanism. It inhibits a wide range of proteinases through a unique 'trapping' mechanism, involving a bait region that undergoes a conformational change upon cleavage, entrapping the proteinase. This protein is particularly effective against chymotrypsin, papain, thermolysin, subtilisin A, and to a lesser extent, elastase.

Therapeutic significance:

Given its role in inhibiting extracellular proteases, Alpha-2-macroglobulin-like protein 1 is implicated in otitis media, a condition characterized by ear inflammation and hearing disturbances. Understanding the role of Alpha-2-macroglobulin-like protein 1 could open doors to potential therapeutic strategies for otitis media and other protease-related conditions.

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