AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Sulfhydryl oxidase 2

Available from Reaxense
Predicted by Alphafold

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 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 our associate Reaxense.

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 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.

partner

Reaxense

upacc

Q6ZRP7

UPID:

QSOX2_HUMAN

Alternative names:

Neuroblastoma-derived sulfhydryl oxidase; Quiescin Q6-like protein 1

Alternative UPACC:

Q6ZRP7; A2CEE0; A6NLB0; Q5TB37; Q7Z7B6; Q86VV7; Q8N3G2

Background:

Sulfhydryl oxidase 2, also known as Neuroblastoma-derived sulfhydryl oxidase and Quiescin Q6-like protein 1, plays a crucial role in the oxidation of sulfhydryl groups to disulfides, facilitating the formation of disulfide bonds in secreted proteins. This enzymatic activity is essential for protein structure and function, contributing to the stabilization of proteins outside the cell.

Therapeutic significance:

Understanding the role of Sulfhydryl oxidase 2 could open doors to potential therapeutic strategies. Its involvement in disulfide bond formation suggests a pivotal role in protein maturation and secretion, processes that are critical in numerous physiological and pathological contexts.

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