Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
Receptor.AI
 
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:
The Alpha-2-macroglobulin-like protein 1, with alternative names including C3 and PZP-like alpha-2-macroglobulin domain-containing protein 9, is pivotal in protease inhibition. It employs a 'trapping' mechanism to inhibit proteinases, crucial for its role in the immune response and tissue remodeling. This protein targets various proteinases, including chymotrypsin and papain, by a conformational change mechanism, reducing their activity against high molecular weight substrates.

THERAPEUTIC SIGNIFICANCE:
Alpha-2-macroglobulin-like protein 1's inhibitory activity on extracellular proteases links it to otitis media, marked by earache and vertigo. The exploration of Alpha-2-macroglobulin-like protein 1's function offers promising avenues for developing treatments for diseases associated with protease dysregulation.

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