AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin-fold modifier-conjugating enzyme 1

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

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

Q9Y3C8

UPID:

UFC1_HUMAN

Alternative names:

-

Alternative UPACC:

Q9Y3C8; A8K9R1; D3DVF9; Q549X0; Q5VTX1; Q9BS96; Q9P009

Background:

Ubiquitin-fold modifier-conjugating enzyme 1 plays a pivotal role in the process of ufmylation, a post-translational modification involving the ubiquitin-like modifier UFM1. This enzyme acts as an E2 conjugating enzyme, accepting UFM1 from the E1 enzyme UBA5, and is crucial for the maintenance of cellular homeostasis, particularly in response to endoplasmic reticulum stress.

Therapeutic significance:

The enzyme's involvement in neurodevelopmental disorder with spasticity and poor growth highlights its potential as a target for therapeutic intervention. Understanding the role of Ubiquitin-fold modifier-conjugating enzyme 1 could open doors to potential therapeutic strategies, offering hope for patients suffering from this debilitating condition.

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