Focused On-demand Library for Azurocidin

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.

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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

P20160

UPID:

CAP7_HUMAN

Alternative names:

Cationic antimicrobial protein CAP37; Heparin-binding protein

Alternative UPACC:

P20160; P80014; Q52LG4; Q9UCM1; Q9UCT5

Background:

Azurocidin, also known as Cationic antimicrobial protein CAP37 or Heparin-binding protein, is a crucial glycoprotein derived from neutrophil granules. It exhibits a strong affinity for negatively charged lipopolysaccharides unique to Gram-negative bacterial outer envelopes, explaining its specificity. Azurocidin's antibacterial activity is notably effective against P.aeruginosa, though it is inhibited by LPS from the same bacterium. Its role extends to chemotaxis, specifically attracting monocytes and fibroblasts, thereby playing a pivotal role in the inflammatory response.

Therapeutic significance:

Understanding the role of Azurocidin could open doors to potential therapeutic strategies, particularly in combating Gram-negative bacterial infections and modulating inflammatory responses.