Focused On-demand Library for Endoplasmic reticulum aminopeptidase 2

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted 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.

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.

partner

Reaxense

upacc

Q6P179

UPID:

ERAP2_HUMAN

Alternative names:

Leukocyte-derived arginine aminopeptidase

Alternative UPACC:

Q6P179; Q7Z5K1; Q8TD32; Q8WVJ4; Q9HBX2

Background:

Endoplasmic reticulum aminopeptidase 2, also known as leukocyte-derived arginine aminopeptidase, plays a pivotal role in peptide trimming. This process is crucial for generating HLA class I-binding peptides, fitting longer precursor peptides to the required length for presentation on MHC class I molecules. It preferentially hydrolyzes basic residues Arg and Lys.

Therapeutic significance:

Understanding the role of Endoplasmic reticulum aminopeptidase 2 could open doors to potential therapeutic strategies. Its central role in peptide trimming, essential for immune response, highlights its potential as a target in designing novel immunotherapies.