Focused On-demand Library for ERO1-like protein alpha

Focused On-demand Libraries - Receptor.AI 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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q96HE7

UPID:
ERO1A_HUMAN

ALTERNATIVE NAMES:
Endoplasmic oxidoreductin-1-like protein; Endoplasmic reticulum oxidoreductase alpha; Oxidoreductin-1-L-alpha

ALTERNATIVE UPACC:
Q96HE7; A8K9X4; A8MYW1; Q7LD45; Q9P1Q9; Q9UKV6

BACKGROUND:
The ERO1-like protein alpha, identified by its alternative names such as Endoplasmic reticulum oxidoreductase alpha, is pivotal in disulfide bond formation, crucial for protein folding in the endoplasmic reticulum. It assists in the reoxidation of P4HB/PDI for continuous disulfide bond formation, leading to reactive oxygen species production. This protein is vital for immunoglobulin folding, ER stress-induced apoptosis, and plays a role in the defense mechanism against V.cholerae infection.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of ERO1-like protein alpha offers a promising avenue for developing novel therapeutic approaches. Its critical role in protein folding, apoptosis, and response to cellular stress underscores its potential as a therapeutic target in diseases linked to protein misfolding, immune response, and cellular homeostasis.

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