Focused On-demand Library for Apoptosis-resistant E3 ubiquitin protein ligase 1

Details

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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are 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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Receptor.AI
 
UPACC
O15033

UPID:
AREL1_HUMAN

ALTERNATIVE NAMES:
Apoptosis-resistant HECT-type E3 ubiquitin transferase 1

ALTERNATIVE UPACC:
O15033; B4E2C7; Q7LDY1; Q8IYY9

BACKGROUND:
The protein Apoptosis-resistant E3 ubiquitin protein ligase 1, with its alternative name Apoptosis-resistant HECT-type E3 ubiquitin transferase 1, is pivotal in the ubiquitin-proteasome system. It specializes in forming 'Lys-11'- or 'Lys-33'-linked polyubiquitin chains, favoring 'Lys-33' linkages. This protein facilitates the transfer of ubiquitin from E2 enzymes to specific substrates such as SEPTIN4, DIABLO/SMAC, and HTRA2, playing a key role in protein degradation and signaling.

THERAPEUTIC SIGNIFICANCE:
The exploration of Apoptosis-resistant E3 ubiquitin protein ligase 1's function offers promising avenues for drug discovery, particularly in managing pulmonary inflammation. Its role in ubiquitinating SOCS2 for proteasomal degradation underscores its potential in therapeutic interventions.

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