AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cytosol aminopeptidase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised 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.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

P28838

UPID:

AMPL_HUMAN

Alternative names:

Cysteinylglycine-S-conjugate dipeptidase; Leucine aminopeptidase 3; Leucyl aminopeptidase; Peptidase S; Proline aminopeptidase; Prolyl aminopeptidase

Alternative UPACC:

P28838; B3KMQ3; Q6IAM6; Q6P0L6; Q9UQE3

Background:

Cytosol aminopeptidase, known by alternative names such as Cysteinylglycine-S-conjugate dipeptidase and Leucine aminopeptidase 3, plays a crucial role in cellular processes. It is a cytosolic metallopeptidase that catalyzes the removal of N-terminal hydrophobic amino acids from peptides, requiring Zn(2+) ions for activity. Its function is modulated by cofactors, with Mn(2+) enhancing its specificity for Cys-Gly hydrolyzing activity. This enzyme is pivotal in glutathione metabolism and the degradation of glutathione S-conjugates, influencing cell redox status.

Therapeutic significance:

Understanding the role of Cytosol aminopeptidase could open doors to potential therapeutic strategies.

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