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

Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

PARTNER
Receptor.AI
 
UPACC
Q9GZZ9

UPID:
UBA5_HUMAN

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

ALTERNATIVE UPACC:
Q9GZZ9; A6NJL3; D3DNC8; Q96ST1

BACKGROUND:
The enzyme Ubiquitin-like modifier-activating enzyme 5, also known as UFM1-activating enzyme, ThiFP1, and Ubiquitin-activating enzyme E1 domain-containing protein 1, is essential for the ufmylation pathway. It activates UFM1, a ubiquitin-like molecule, preparing it for conjugation to substrates. This process is vital for maintaining cellular homeostasis, particularly in response to endoplasmic reticulum stress, through mechanisms like reticulophagy.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Ubiquitin-like modifier-activating enzyme 5 could open doors to potential therapeutic strategies. Its involvement in diseases such as Developmental and epileptic encephalopathy 44 and Spinocerebellar ataxia, autosomal recessive, 24, underscores its significance in neurodevelopmental integrity and offers a promising target for drug discovery efforts aimed at these genetic disorders.

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