AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for E3 ubiquitin-protein ligase UBR1

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 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 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 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

Reaxense

upacc

Q8IWV7

UPID:

UBR1_HUMAN

Alternative names:

N-recognin-1; RING-type E3 ubiquitin transferase UBR1; Ubiquitin-protein ligase E3-alpha-1; Ubiquitin-protein ligase E3-alpha-I

Alternative UPACC:

Q8IWV7; O60708; O75492; Q14D45; Q68DN9; Q8IWY6; Q96JY4

Background:

E3 ubiquitin-protein ligase UBR1, also known as N-recognin-1, plays a pivotal role in the N-end rule pathway of protein degradation. It specifically recognizes proteins with destabilizing N-terminal residues, marking them for ubiquitination and subsequent degradation. This process is crucial for maintaining cellular homeostasis and regulating protein levels.

Therapeutic significance:

UBR1's dysfunction is directly linked to Johanson-Blizzard syndrome, characterized by pancreatic insufficiency and developmental anomalies. Understanding UBR1's mechanisms offers a pathway to novel treatments for this syndrome and insights into pancreatic health.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.