Focused On-demand Library for Endoplasmic reticulum aminopeptidase 1

Available from Reaxense
Predicted by Alphafold

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.

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 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

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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.







Alternative names:

ARTS-1; Adipocyte-derived leucine aminopeptidase; Aminopeptidase PILS; Puromycin-insensitive leucyl-specific aminopeptidase; Type 1 tumor necrosis factor receptor shedding aminopeptidase regulator

Alternative UPACC:

Q9NZ08; O60278; Q6UWY6; Q8NEL4; Q8TAD0; Q9UHF8; Q9UKY2


Endoplasmic reticulum aminopeptidase 1 (ERAP1), known by alternative names such as ARTS-1 and Adipocyte-derived leucine aminopeptidase, plays a pivotal role in peptide trimming for HLA class I-binding peptides presentation. It specializes in processing substrates 9-16 residues long, favoring those with a hydrophobic C-terminus, and is crucial in regulating blood pressure via angiotensin II inactivation.

Therapeutic significance:

Understanding the role of Endoplasmic reticulum aminopeptidase 1 could open doors to potential therapeutic strategies, especially in the context of immune response modulation and hypertension management.

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