Focused On-demand Library for Ubiquitin-like modifier-activating enzyme 5

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 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.

 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.







Alternative names:

ThiFP1; UFM1-activating enzyme; Ubiquitin-activating enzyme E1 domain-containing protein 1

Alternative UPACC:

Q9GZZ9; A6NJL3; D3DNC8; Q96ST1


Ubiquitin-like modifier-activating enzyme 5 (Ubiquitin-activating enzyme E1 domain-containing protein 1, ThiFP1, UFM1-activating enzyme) plays a pivotal role in the ufmylation process. This enzyme catalyzes the initial step by activating UFM1, a ubiquitin-like modifier, through an ATP-dependent mechanism. It facilitates the transfer of UFM1 to target proteins via the E2-like enzyme UFC1, crucial for cellular processes such as reticulophagy, especially under endoplasmic reticulum stress conditions.

Therapeutic significance:

Ubiquitin-like modifier-activating enzyme 5 is implicated in severe diseases such as Developmental and epileptic encephalopathy 44 and Spinocerebellar ataxia, autosomal recessive, 24. These conditions highlight the enzyme's critical role in neurological development and function, suggesting that targeting this protein could offer novel therapeutic avenues for these debilitating disorders.

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