AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Endothelin-converting enzyme 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P0DPD6

UPID:

ECE2_HUMAN

Alternative names:

-

Alternative UPACC:

P0DPD6; A5PLK8; O60344; Q6NTG7; Q6UW36; Q8NFD7; Q96NX3; Q96NX4; Q9BRZ8

Background:

Endothelin-converting enzyme 2 (ECE-2) plays a pivotal role in cardiovascular physiology by converting big endothelin-1 to endothelin-1. Beyond its cardiovascular implications, ECE-2 is instrumental in processing a variety of neuroendocrine peptides, such as neurotensin, angiotensin I, substance P, and peptides derived from proenkephalin and prodynorphin. Its potential involvement in amyloid-beta processing suggests a broader biological significance, hinting at a role in neurodegenerative processes.

Therapeutic significance:

Understanding the role of Endothelin-converting enzyme 2 could open doors to potential therapeutic strategies. Its involvement in the processing of critical peptides and potential role in amyloid-beta processing positions ECE-2 as a target of interest in developing treatments for cardiovascular diseases and possibly neurodegenerative disorders.

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