AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin-conjugating enzyme E2 Z

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 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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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

Q9H832

UPID:

UBE2Z_HUMAN

Alternative names:

E2 ubiquitin-conjugating enzyme Z; Uba6-specific E2 conjugating enzyme 1; Ubiquitin carrier protein Z; Ubiquitin-protein ligase Z

Alternative UPACC:

Q9H832; A6N8M6; A6NC60; Q7L354; Q8TCM4; Q9H893

Background:

Ubiquitin-conjugating enzyme E2 Z, also known as E2 ubiquitin-conjugating enzyme Z, Uba6-specific E2 conjugating enzyme 1, Ubiquitin carrier protein Z, and Ubiquitin-protein ligase Z, plays a pivotal role in protein ubiquitination. This enzyme catalyzes the covalent attachment of ubiquitin to other proteins, a process crucial for protein degradation, cell cycle regulation, and DNA repair. It is a specific substrate for UBA6, distinguishing it from other enzymes charged by UBE1, and is implicated in apoptosis regulation.

Therapeutic significance:

Understanding the role of Ubiquitin-conjugating enzyme E2 Z could open doors to potential therapeutic strategies.

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