AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable oxidoreductase PXDNL

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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

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.

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

A1KZ92

UPID:

PXDNL_HUMAN

Alternative names:

Cardiac peroxidase; Inactive peroxidasin-like protein; Polysomal ribonuclease 1; Vascular peroxidase 2

Alternative UPACC:

A1KZ92; B5ME43; B6CGZ3; H0YBM9; Q6ZMR2; Q96LH9

Background:

Probable oxidoreductase PXDNL, also known as Cardiac peroxidase, Inactive peroxidasin-like protein, and Vascular peroxidase 2, plays a crucial role in cellular processes. It functions as a probable oxidoreductase and is known to inhibit the peroxidase activity of PXDN. Additionally, it acts as an endonuclease, degrading specific target mRNAs, including albumin and beta-globin, during translation.

Therapeutic significance:

Understanding the role of Probable oxidoreductase PXDNL could open doors to potential therapeutic strategies.

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