AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Macrophage metalloelastase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our partner 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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

Reaxense

upacc

P39900

UPID:

MMP12_HUMAN

Alternative names:

Macrophage elastase; Matrix metalloproteinase-12

Alternative UPACC:

P39900; B2R9X8; B7ZLF6; Q2M1L9

Background:

Macrophage metalloelastase, also known as Matrix metalloproteinase-12, plays a pivotal role in tissue injury and remodeling. It exhibits significant elastolytic activity, efficiently breaking down elastin. This enzyme demonstrates a preference for leucine at the P1' site and favors aromatic or hydrophobic residues at the P1 site, with a particular affinity for small hydrophobic residues, especially alanine, at the P3.

Therapeutic significance:

Understanding the role of Macrophage metalloelastase could open doors to potential therapeutic strategies. Its involvement in tissue remodeling and injury repair mechanisms highlights its importance in pathological conditions, suggesting that targeting this enzyme could offer novel approaches for treating diseases associated with tissue damage and inflammation.

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