Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Receptor.AI
 
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:
The protein E3 ubiquitin-protein ligase UBR1, known for its roles in the N-end rule pathway, binds to specific N-terminal residues on proteins, targeting them for degradation. This activity is essential for protein quality control and cellular regulation.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in protein degradation and pancreatic function, UBR1 is a key player in Johanson-Blizzard syndrome. Exploring UBR1's function could lead to groundbreaking therapeutic strategies for managing this disorder and enhancing pancreatic health.

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